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Li J, Jiang Z. Antibody drug conjugates in breast cancer in China: Highlights, challenges, and prospects. Cancer 2024; 130:1371-1377. [PMID: 37921976 DOI: 10.1002/cncr.35093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 10/03/2023] [Accepted: 10/10/2023] [Indexed: 11/05/2023]
Abstract
Antibody drug conjugates (ADCs) are novel drugs that exert specific cytotoxicity against tumor cells. China approved T-Dxd in May 2023, and their introduction has changed the nation's clinical practice. Although more than 700 ADCs are being investigated worldwide, the challenges that remain in antibody engineering, drug discovery, safety management, resistance, drug selection, and sequencing hinder the further promotion and application of ADCs. Experts in China have discussed the several critical concerns related to clinical practice since 2022. Here, the authors conducted a review of ADCs and then discussed several ADCs explored in China. This study proposes several solutions and strategies to maximize the potential benefit that ADCs can provide to patients with breast cancer.
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Affiliation(s)
- Jianbin Li
- Senior Department of Oncology, Fifth Medical Center of PLA General Hospital, Beijing, China
- Department of Medical Molecular Biology, Beijing Institute of Biotechnology, Academy of Military Medical Sciences, Beijing, China
| | - Zefei Jiang
- Senior Department of Oncology, Fifth Medical Center of PLA General Hospital, Beijing, China
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Li F, Li J, Yuan Y, Zhang H, Zhang S, Bian L, Wang T, Jiang Z. A real-world comparison of circulating tumor cells in breast cancer from China: Novel device, CTC counts and its overall survival. Heliyon 2024; 10:e29217. [PMID: 38623216 PMCID: PMC11016733 DOI: 10.1016/j.heliyon.2024.e29217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 04/02/2024] [Accepted: 04/02/2024] [Indexed: 04/17/2024] Open
Abstract
Background Both CellSearch and CellCollector have been accepted as the proper devices to capture CTC by domestic approval department. However, there is little article about the comparison between these two devices around the world. Herein, we conducted the real-world study to compare with these two devices and to re-verify the efficacy of CTC counts. Methods Patients who meet the following points should be included in the analysis. 1. Female, aged 18 years or older; 2. Eastern Cooperative Oncology Group (ECOG) score 0-2; 3. With at least one measurable tumor lesion; 4. Clear immunohistochemistry result; 5. Accept at least one CTC test. Patients were excluded in the analysis if they had a history of malignant tumors, incomplete follow-up information. Results 536 metastatic breast cancer patients who had been detected for CTC at least once by CellSearch or CellCollector were included in the analysis. CellCollector in vivo CTC detection technology has a higher detection rate than the CellSearch system (69.2% vs 57.4%, P = 0.009). However, the proportion of CTC≥5 detected by CellSearch was higher than CellCollector (37.4% vs 16.3%, P < 0.001). There was a statistically significant difference in overall survival of patients with CTC negative and CTC positive (mOS:49.8 months vs 26.9 months). After 4 weeks of treatment, when CTC decreased by more than 50%, there was a significant difference in survival between the two groups (40.1 months vs 25.8 months, HR = 0.588, 95% CI: 0.350-0.933). In addition, for HER2-positive patients, Patients with CTC HER2 positive had longer overall survival than patients with CTC HER2 negative (median OS: 26.7 months vs 17.3 month, HR = 0.528, 95% CI: 0.269-0.887). Conclusions Real-world data indicate that CTC is an independent prognostic factor, and CellCollector and CellSearch have their own advantages in CTC detection.
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Affiliation(s)
- Feng Li
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100071, People's Republic of China
| | - Jianbin Li
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100071, People's Republic of China
- Department of Medical Molecular Biology, Beijing Institute of Biotechnology, Academy of Military Medical Sciences, Beijing, 100850, People's Republic of China
| | - Yang Yuan
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100071, People's Republic of China
| | - Huiqiang Zhang
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100071, People's Republic of China
| | - Shaohua Zhang
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100071, People's Republic of China
| | - Li Bian
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100071, People's Republic of China
| | - Tao Wang
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100071, People's Republic of China
| | - Zefei Jiang
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100071, People's Republic of China
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3
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Rosenberg E, Andersen TI, Samajdar R, Petukhov A, Hoke JC, Abanin D, Bengtsson A, Drozdov IK, Erickson C, Klimov PV, Mi X, Morvan A, Neeley M, Neill C, Acharya R, Allen R, Anderson K, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bilmes A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Campero J, Chang HS, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Barba ADT, Demura S, Di Paolo A, Dunsworth A, Earle C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Garcia G, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Dau AG, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hill G, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Mandrà S, Martin O, Martin S, McClean JR, McEwen M, Meeks S, Miao KC, Mieszala A, Montazeri S, Movassagh R, Mruczkiewicz W, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Omonije S, Opremcak A, Potter R, Pryadko LP, Quintana C, Rhodes DM, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Sivak V, Skruzny J, Smith WC, Somma RD, Sterling G, Strain D, Szalay M, Thor D, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Khemani V, Gopalakrishnan S, Prosen T, Roushan P. Dynamics of magnetization at infinite temperature in a Heisenberg spin chain. Science 2024; 384:48-53. [PMID: 38574139 DOI: 10.1126/science.adi7877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 03/01/2024] [Indexed: 04/06/2024]
Abstract
Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.
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Affiliation(s)
- E Rosenberg
- Google Research, Mountain View, CA, USA
- Department of Physics, Cornell University, Ithaca, NY, USA
| | | | - R Samajdar
- Department of Physics, Princeton University, Princeton, NJ, USA
- Princeton Center for Theoretical Science, Princeton University, Princeton, NJ, USA
| | | | - J C Hoke
- Department of Physics, Stanford University, Stanford, CA, USA
| | - D Abanin
- Google Research, Mountain View, CA, USA
| | | | - I K Drozdov
- Google Research, Mountain View, CA, USA
- Department of Physics, University of Connecticut, Storrs, CT, USA
| | | | | | - X Mi
- Google Research, Mountain View, CA, USA
| | - A Morvan
- Google Research, Mountain View, CA, USA
| | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | - R Acharya
- Google Research, Mountain View, CA, USA
| | - R Allen
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - A Bilmes
- Google Research, Mountain View, CA, USA
| | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - J Campero
- Google Research, Mountain View, CA, USA
| | - H-S Chang
- Google Research, Mountain View, CA, USA
| | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | - C Earle
- Google Research, Mountain View, CA, USA
| | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - G Garcia
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | | | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | - G Hill
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- QSI, Faculty of Engineering & Information Technology, University of Technology Sydney, Ultimo, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | - S Mandrà
- Google Research, Mountain View, CA, USA
| | - O Martin
- Google Research, Mountain View, CA, USA
| | - S Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | - S Meeks
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | - S Omonije
- Google Research, Mountain View, CA, USA
| | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - V Sivak
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | | | - R D Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - D Thor
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | | | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | | | - V Khemani
- Department of Physics, Stanford University, Stanford, CA, USA
| | | | - T Prosen
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - P Roushan
- Google Research, Mountain View, CA, USA
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4
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Zhang S, Yin Y, Xiong H, Wang J, Liu H, Lu J, Zhang Q, Zhang L, Zhong J, Nie J, Lei K, Wang H, Yang S, Yao H, Wu H, Yu D, Ji X, Zhang H, Wu F, Xie W, Li W, Yao W, Zhong D, Sun H, Sun T, Guo Z, Wang R, Guo Y, Yu Z, Li D, Jin H, Song H, Chen X, Ma W, Hu Z, Liu D, Guo Y, Tang J, Jiang Z. Efficacy, Safety, and Population Pharmacokinetics of MW032 Compared With Denosumab for Solid Tumor-Related Bone Metastases: A Randomized, Double-Blind, Phase 3 Equivalence Trial. JAMA Oncol 2024; 10:448-455. [PMID: 38329745 PMCID: PMC10853867 DOI: 10.1001/jamaoncol.2023.6520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 09/27/2023] [Indexed: 02/09/2024]
Abstract
Importance The bioequivalence of denosumab biosimilar has yet to be studied in a 53-week, multicenter, large-scale, and head-to-head trial. A clinically effective biosimilar may help increase access to denosumab in patients with solid tumor-related bone metastases. Objectives To establish the biosimilarity of MW032 to denosumab in patients with solid tumor-related bone metastases based on a large-scale head-to-head study. Design, Setting, and Participants In this 53-week, randomized, double-blind, phase 3 equivalence trial, patients with solid tumors with bone metastasis were recruited from 46 clinical sites in China. Overall, 856 patients were screened and 708 eligible patients were randomly allocated to receive either MW032 or denosumab. Interventions Patients were randomly assigned (1:1) to receive MW032 or reference denosumab subcutaneously every 4 weeks until week 49. Main Outcomes and Measures The primary end point was percentage change from baseline to week 13 of natural logarithmic transformed urinary N-telopeptide/creatinine ratio (uNTx/uCr). Results Among the 701 evaluable patients (350 in the MW032 group and 351 in the denosumab group), the mean (range) age was 56.1 (22.0-86.0) years and 460 patients were women (65.6%). The mean change of uNTx/uCr from baseline to week 13 was -72.0% (95% CI, -73.5% to -70.4%) in the MW032 group and -72.7% (95% CI, -74.2% to -71.2%) in the denosumab group. These percent changes corresponded to mean logarithmic ratios of -1.27 and -1.30, or a difference of 0.02. The 90% CI for the difference (-0.04 to 0.09) was within the equivalence margin (-0.13 to 0.13); the mean changes of uNTx/uCr and bone-specific alkaline phosphatase (s-BALP) at each time point were also similar during 53 weeks. The differences of uNTx/uCr change were 0.015 (95% CI, -0.06 to 0.09), -0.02 (95% CI, -0.09 to 0.06), -0.05 (95% CI, -0.13 to 0.03) and 0.001 (95% CI, -0.10 to 0.10) at weeks 5, 25, 37, and 53, respectively. The differences of s-BALP change were -0.006 (95% CI, 0.06 to 0.05), 0.00 (95% CI, -0.07 to 0.07), -0.085 (95% CI, -0.18 to 0.01), -0.09 (95% CI, -0.20 to 0.02), and -0.13 (95% CI, -0.27 to 0.004) at weeks 5, 13, 25, 37 and 53, respectively. No significant differences were observed in the incidence of skeletal-related events (-1.4%; 95% CI, -5.8% to 3.0%) or time to first on-study skeletal-related events (unadjusted HR, 0.86; P = .53; multiplicity adjusted HR, 0.87; P = .55) in the 2 groups. Conclusions and Relevance MW032 and denosumab were biosimilar in efficacy, population pharmacokinetics, and safety profile. Availability of denosumab biosimilars may broaden the access to denosumab and reduce the drug burden for patients with advanced tumors. Trial Registration ClinicalTrials.gov Identifier: NCT04812509.
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Affiliation(s)
- Shaohua Zhang
- Senior Department of Oncology, the Fifth Medical Center of PLA General Hospital, Beijing, PR China
| | - Yongmei Yin
- Department of Oncology, The First Affiliated Hospital with Nanjing Medical University, Jiangsu Province Hospital, Jiangsu, PR China
| | - Hailin Xiong
- Huizhou Central People’s Hospital, Huizhou, PR China
| | | | - Hu Liu
- The First Affiliated Hospital of USTC/Anhui Provincial Cancer Hospital, Hefei, PR China
| | - Junguo Lu
- Nantong Tumor Hospital, Nantong, PR China
| | - Qingyuan Zhang
- Harbin Medical University Cancer Hospital, Harbin, PR China
| | - Longzhen Zhang
- The Affiliated Hospital of Xuzhou Medical University, Xuzhou, PR China
| | - Jincai Zhong
- The First Affiliated Hospital of Guangxi Medical University, Nanning, PR China
| | - Jianyun Nie
- Yunnan Cancer Hospital, The Third Affiliated Hospital of Kunming Medical University, Kunming, PR China
| | - Kaijian Lei
- The Second People’s Hospital of Yibin, Yibin, PR China
| | - Hong Wang
- Nanchang People’s Hospital, Nanchang, PR China
| | - Shu Yang
- The First Affiliated Hospital, The First Clinical Medicine School of Guangdong Pharmaceutical University, Guangzhou, PR China
| | - Herui Yao
- Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, PR China
| | | | - Ding Yu
- Hubei Cancer Hospital, Wuhan, PR China
| | - Xuening Ji
- Zhongshan Clinical Collage of Dalian University, Dalian, PR China
| | - Hua Zhang
- The First Affiliated Hospital of Xinjiang Medical University, Urumchi, PR China
| | - Fang Wu
- The First Affiliated Hospital of Nanchang University, Nanchang, PR China
| | - Weimin Xie
- Guangxi Medical University Cancer Hospital, Nanning, PR China
| | - Wei Li
- The First Bethune Hospital of Jilin University, Changchun, PR China
| | - Weirong Yao
- The Jiangxi Provincial People’s Hospital, Nanchang, PR China
| | - Diansheng Zhong
- Tianjin Medical University General Hospital, Tianjin, PR China
| | | | - Tao Sun
- Liaoning Cancer Hospital & Institute, Shenyang, PR China
| | | | - Rui Wang
- Anhui Chest Hospital, Hefei, PR China
| | - Yanzhen Guo
- The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, PR China
| | - Zhuang Yu
- The Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Dairong Li
- Chongqing University Cancer Hospital, Chongqing, PR China
| | | | - Haifeng Song
- Institute of Lifeomics, Academy of Military Medical Sciences, National Engineering Research Center for Protein Drugs, Beijing, PR China
| | - Xiaoyuan Chen
- Tsinghua Clinical Research Institute, School of Medicine, Tsinghua University, Beijing, PR China
| | - Wen Ma
- Mabwell (Shanghai) Bioscience Co, Ltd, Shanghai, PR China
| | - Zhitian Hu
- Mabwell (Shanghai) Bioscience Co, Ltd, Shanghai, PR China
| | - Datao Liu
- Mabwell (Shanghai) Bioscience Co, Ltd, Shanghai, PR China
| | - Yinhan Guo
- Mabwell (Shanghai) Bioscience Co, Ltd, Shanghai, PR China
| | - Jinhai Tang
- Department of Oncology, The First Affiliated Hospital with Nanjing Medical University, Jiangsu Province Hospital, Jiangsu, PR China
| | - Zefei Jiang
- Senior Department of Oncology, the Fifth Medical Center of PLA General Hospital, Beijing, PR China
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5
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Mi X, Michailidis AA, Shabani S, Miao KC, Klimov PV, Lloyd J, Rosenberg E, Acharya R, Aleiner I, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Chou C, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Erickson C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Malone FD, Martin O, McClean JR, McEwen M, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Roushan P, Smelyanskiy V, Abanin DA. Stable quantum-correlated many-body states through engineered dissipation. Science 2024; 383:1332-1337. [PMID: 38513021 DOI: 10.1126/science.adh9932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 02/13/2024] [Indexed: 03/23/2024]
Abstract
Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.
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Affiliation(s)
- X Mi
- Google Research, Mountain View, CA, USA
| | - A A Michailidis
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - S Shabani
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | - J Lloyd
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | | | - R Acharya
- Google Research, Mountain View, CA, USA
| | - I Aleiner
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | | | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - C Chou
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | - A G Dau
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | | | | | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | | | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- Centre for Quantum Software and Information (QSI), Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | | | - O Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | | | | | - A Morvan
- Google Research, Mountain View, CA, USA
| | | | | | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | | | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Google Research, Mountain View, CA, USA
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | - W C Smith
- Google Research, Mountain View, CA, USA
| | - R Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | - Z J Yao
- Google Research, Mountain View, CA, USA
| | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | - P Roushan
- Google Research, Mountain View, CA, USA
| | | | - D A Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
- Department of Physics, Princeton University, Princeton, NJ, USA
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6
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Jiang Z, Yang T, Xu L. Head-to-head comparison of prostate-specific membrane antigen positron emission tomography/computed tomography and multiparametric magnetic resonance imaging in the detection of biochemical recurrence of prostate cancer: a systematic review and meta-analysis. Clin Radiol 2024:S0009-9260(24)00130-2. [PMID: 38582633 DOI: 10.1016/j.crad.2024.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/30/2024] [Accepted: 02/05/2024] [Indexed: 04/08/2024]
Abstract
AIM Our main goal of this meta-analytical analysis was to evaluate the diagnostic effectiveness of prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT) against multiparametric magnetic resonance imaging (mpMRI) in the context of identifying biochemical recurrence in patients with prostate cancer (PCa). MATERIALS AND METHODS A thorough search covering articles published until March 2023 was carried out across major databases such as PubMed, Embase, and Web of Science. Studies examining the direct comparison of PSMA PET/CT and mpMRI in patients with PCa suffering biochemical recurrence were included in the inclusion criteria. Using the renowned Quality Assessment of Diagnostic Performance Studies-2 technique, each study's methodological rigor was assessed. RESULTS We analyzed data from six eligible studies involving 290 patients in total. The combined data showed that for PSMA PET/CT and mpMRI, respectively, the pooled overall detection rates for recurrent PCa after definitive treatment were 0.69 (95% confidence interval [CI]: 0.45-0.89) and 0.70 (95% CI: 0.44-0.91). The detection rates for local recurrence were specifically 0.52 (95% CI: 0.39-0.65) and 0.62 (95% CI: 0.31-0.89), while they were 0.50 (95% CI: 0.26-0.74) and 0.32 (95% CI: 0.18-0.48) for lymph node metastasis. Notably, there was no discernible difference between the two imaging modalities in terms of the overall detection rate (P = 0.95). The detection rates for local recurrence and lymph node metastasis did not differ statistically significantly (P = 0.55, 0.23). CONCLUSION The performance of PSMA PET/CT and mpMRI in identifying biochemical recurrence in PCa appears to be comparable. However, the meta-analysis' findings came from research with modest sample sizes. In this context, more extensive research should be conducted in the future.
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Affiliation(s)
- Z Jiang
- Medical School, Hunan University of Chinese Medicine, Changsha, Hunan, 410208, China.
| | - T Yang
- Medical School, Hunan University of Chinese Medicine, Changsha, Hunan, 410208, China
| | - L Xu
- Medical School, Hunan University of Chinese Medicine, Changsha, Hunan, 410208, China
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7
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Huang L, Pang D, Yang H, Li W, Wang S, Cui S, Liao N, Wang Y, Wang C, Chang YC, Wang HC, Kang SY, Seo JH, Shen K, Laohawiriyakamol S, Jiang Z, Wang H, Lamour F, Song G, Curran M, Duan C, Lysbet de Haas S, Restuccia E, Shao Z. Neoadjuvant-adjuvant pertuzumab in HER2-positive early breast cancer: final analysis of the randomized phase III PEONY trial. Nat Commun 2024; 15:2153. [PMID: 38461323 PMCID: PMC10925021 DOI: 10.1038/s41467-024-45591-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 01/29/2024] [Indexed: 03/11/2024] Open
Abstract
The randomized, multicenter, double-blind, placebo-controlled, phase III PEONY trial (NCT02586025) demonstrated significantly improved total pathologic complete response (primary endpoint) with dual HER2 blockade in HER2-positive early/locally advanced breast cancer, as previously reported. Here, we present the final, long-term efficacy (secondary endpoints: event-free survival, disease-free survival, overall survival) and safety analysis (62.9 months' median follow-up). Patients (female; n = 329; randomized 2:1) received neoadjuvant pertuzumab/placebo with trastuzumab and docetaxel, followed by adjuvant 5-fluorouracil, epirubicin, and cyclophosphamide, then pertuzumab/placebo with trastuzumab until disease recurrence or unacceptable toxicity, for up to 1 year. Five-year event-free survival estimates are 84.8% with pertuzumab and 73.7% with placebo (hazard ratio 0.53; 95% confidence interval 0.32-0.89); 5-year disease-free survival rates are 86.0% and 75.0%, respectively (hazard ratio 0.52; 95% confidence interval 0.30-0.88). Safety data are consistent with the known pertuzumab safety profile and generally comparable between arms, except for diarrhea. Limitations include the lack of ado-trastuzumab emtansine as an option for patients with residual disease and the descriptive nature of the secondary, long-term efficacy endpoints. PEONY confirms the positive benefit:risk ratio of neoadjuvant/adjuvant pertuzumab, trastuzumab, and docetaxel treatment in this patient population.
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Affiliation(s)
- Liang Huang
- Fudan University Shanghai Cancer Center, 200032, Shanghai, China
- Shanghai Medical College, Fudan University, 200032, Shanghai, China
| | - Da Pang
- Harbin Medical University Cancer Hospital, 150040, Harbin, China
| | - Hongjian Yang
- Cancer Hospital of The University of Chinese Academy of Sciences, 310022, Hangzhou, China
| | - Wei Li
- The First Hospital of Jilin University, 130012, Changchun, China
| | - Shusen Wang
- Sun Yat-sen University Cancer Center, 510060, Guangzhou, China
| | - Shude Cui
- Henan Cancer Hospital, 450003, Zhengzhou, China
| | - Ning Liao
- Guangdong General Hospital, 510060, Guangzhou, China
| | | | - Chuan Wang
- Fujian Medical University Union Hospital, 350001, Fuzhou, China
| | - Yuan-Ching Chang
- Department of General Surgery, Mackay Memorial Hospital, 104, Taipei City, Taiwan
| | - Hwei-Chung Wang
- Department of Surgery, China Medical University Hospital, 404, Taichung City, Taiwan
| | - Seok Yun Kang
- Ajou University School of Medicine, 206, Suwon, Republic of Korea
| | - Jae Hong Seo
- Korea University Guro Hospital, 08308, Seoul, Republic of Korea
| | - Kunwei Shen
- Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Zefei Jiang
- The Affiliated Hospital of Military Medical Sciences (The 307th Hospital of Chinese. People's Liberation Army), 100071, Beijing, China
| | - Haiyan Wang
- Roche Product Development, 201203, Shanghai, China
| | - François Lamour
- F. Hoffmann-La Roche Ltd, 4070, Basel, Switzerland
- Alentis Therapeutics AG, Allschwil, Switzerland
| | - Grace Song
- Hangzhou Tigermed Consulting Co., Ltd, 310053, Shanghai, China
| | | | - Chunzhe Duan
- Department of Translational Medicine Oncology, Roche (China) Holding Ltd, 201203, Shanghai, China
| | | | | | - Zhimin Shao
- Fudan University Shanghai Cancer Center, 200032, Shanghai, China.
- Shanghai Medical College, Fudan University, 200032, Shanghai, China.
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Su H, Xu Z, Bao MDL, Luo S, Liang JW, Pei W, Guan X, Liu Z, Jiang Z, Zhang MG, Zhao ZX, Jin WS, Zhou HT. [The clinical significance of lateral pelvic sentinel lymph node biopsy using indocyanine green fluorescence navigation in laparoscopic lateral pelvic lymph node dissection]. Zhonghua Zhong Liu Za Zhi 2024; 46:140-145. [PMID: 38418188 DOI: 10.3760/cma.j.cn112152-20231026-00265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/01/2024]
Abstract
Objectives: This study aims to explore the clinical significance of lateral pelvic sentinel lymph node biopsy (SLNB) using indocyanine green (ICG) fluorescence navigation in laparoscopic lateral pelvic lymph node dissection (LLND) and evaluate the accuracy and feasibility of this technique to predict the status of lateral pelvic lymph nodes (LPLNs). Methods: The clinical and pathological characteristics, surgical outcomes, lymph node findings and perioperative complications of 16 rectal cancer patients who underwent SLNB using ICG fluorescence navigation in laparoscopic LLND in the Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College during April 2017 and October 2022 were retrospectively collected and analyzed. The patients did not receive preoperative neoadjuvant radiotherapy and presented with LPLNs but without LPLN enlargement (MRI showed the maximum short axes of the LPLNs were ≥5 mm and <10 mm at first visit). Results: All 16 patients were successfully performed SLNB using ICG fluorescence navigation in laparoscopic LLND. Three patients underwent bilateral LLND and 13 patients underwent unilateral LLND. The lateral pelvic sentinel lymph nodes (SLNs) were clearly fluorescent before dissection in 14 patients and the detection rate of SLNs for these patients was 87.5%. Lateral pelvic SLN metastasis was diagnosed in 2 patients and negative results were found in 12 patients by frozen pathological examinations. Among the 14 patients in whom lateral pelvic SLNs were detected, the dissected lateral pelvic non-SLNs were all negative. All dissected LPLNs were negative in two patients without fluorescent lateral pelvic SLNs. The specificity, sensitivity, negative predictive value, and accuracy was 85.7%, 100%, 100%, and 100%, respectively. Conclusions: This study indicates that lateral pelvic SLNB using ICG fluorescence navigation shows promise as a safe and feasible procedure with good accuracy. This technique may replace preventive LLND for locally advanced lower rectal cancer.
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Affiliation(s)
- H Su
- Department of Gastrointestinal Surgery, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Z Xu
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - M D L Bao
- Department of Pancreatic and Gastric Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - S Luo
- Department of Gastrointestinal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - J W Liang
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - W Pei
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - X Guan
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - Z Liu
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - Z Jiang
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - M G Zhang
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - Z X Zhao
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - W S Jin
- Department of Anorectal Diseases, Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - H T Zhou
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
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9
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Fan C, Jiang Z, Teng C, Song X, Li L, Shen W, Jiang Q, Huang D, Lv Y, Du L, Wang G, Hu Y, Man S, Zhang Z, Gao N, Wang F, Shi T, Xin T. Efficacy and safety of intrathecal pemetrexed for TKI-failed leptomeningeal metastases from EGFR+ NSCLC: an expanded, single-arm, phase II clinical trial. ESMO Open 2024; 9:102384. [PMID: 38377785 DOI: 10.1016/j.esmoop.2024.102384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/06/2024] [Accepted: 01/19/2024] [Indexed: 02/22/2024] Open
Abstract
BACKGROUND This study aimed to evaluate the efficacy and safety of intrathecal pemetrexed (IP) for treating patients with leptomeningeal metastases (LM) from non-small-cell lung cancer (NSCLC) who progressed from epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) treatment in an expanded, prospective, single-arm, phase II clinical study (ChiCTR1800016615). PATIENTS AND METHODS Patients with confirmed NSCLC-LM who progressed from TKI received IP (50 mg, day 1/day 5 for 1 week, then every 3 weeks for four cycles, and then once monthly) until disease progression or intolerance. Objectives were to assess overall survival (OS), response rate, and safety. Measurable lesions were assessed by investigator according to RECIST version 1.1. LM were assessed according to the Response Assessment in Neuro-Oncology (RANO) criteria. RESULTS The study included 132 patients; 68% were female and median age was 52 years (31-74 years). The median OS was 12 months (95% confidence interval 10.4-13.6 months), RANO-assessed response rate was 80.3% (106/132), and the most common adverse event was myelosuppression (n = 42; 31.8%), which reversed after symptomatic treatment. The results of subgroup analysis showed that absence of brain parenchymal metastasis, good Eastern Cooperative Oncology Group score, good response to IP treatment, negative cytology after treatment, and patients without neck/back pain/difficult defecation had longer survival. Gender, age, previous intrathecal methotrexate/cytarabine, and whole-brain radiotherapy had no significant influence on OS. CONCLUSIONS This study further showed that IP is an effective and safe treatment method for the EGFR-TKI-failed NSCLC-LM, and should be recommended for these patients in clinical practice and guidelines.
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Affiliation(s)
- C Fan
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Z Jiang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - C Teng
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - X Song
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - L Li
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - W Shen
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Q Jiang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - D Huang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Y Lv
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - L Du
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - G Wang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Y Hu
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - S Man
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Z Zhang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - N Gao
- Department of Oncology, Heilongjiang Sengong General Hospital, Harbin, People's Republic of China
| | - F Wang
- Department of Oncology, Heilongjiang Sengong General Hospital, Harbin, People's Republic of China
| | - T Shi
- Department of Oncology, Heilongjiang Sengong General Hospital, Harbin, People's Republic of China
| | - T Xin
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin.
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Chen C, Xu J, Jiang Z, Wu GH, Zhang YQ, Zhao Y, Wu ZY. [Association between CD4 +T lymphocyte and body composition with physical frailty among elderly HIV-infected patients in Chongqing City]. Zhonghua Yu Fang Yi Xue Za Zhi 2024; 58:235-240. [PMID: 38387956 DOI: 10.3760/cma.j.cn112150-20230822-00115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Objective: To identify the association between CD4+T lymphocyte (CD4) counts and physical frailty among HIV-infected people aged 65 years and older, and evaluate whether this association will be modified by the indicators of body composition. Methods: From May to October 2022, 485 elderly HIV-infected patients receiving antiretroviral therapy (ART) were recruited from 7 antiviral treatment sites in Jiangjin District Center for Disease Control and Prevention, Chongqing. The data of basic characteristics (age and gender), living habits (smoking and drinking) and disease history (metabolic diseases, cardiovascular and cerebrovascular diseases, respiratory disease and malignant tumors) were collected through the face-to-face investigation with self-made questionnaires. Fried Frailty Scale was used to evaluate the status of physical frailty. Physical fitness (walking speed, grip strength, height, and weight) and body composition (skeletal muscle mass, body fat mass, and basal metabolic rate) were measured. The antiretroviral treatment data were obtained from the China AIDS Integrated Prevention and Treatment Data information management system. The prevalence of physical frailty was calculated among the HIV-infected patients. The potential effects of CD4 counts on physical frailty were explored by using multivariate logistic regression. Subgroup analyses were repeated in the logistic regression with muscle mass, body fat mass, and other indicators of body composition as subgroup variables to determine whether the association might be modified by body composition. Results: The age of 485 patients were (72±5) years old, of which 48.2% (234 cases) were>70 years old and 70.9% (344 cases) were male, and all of whom had initiated the ART treatment. The prevalence of physical frailty among these patients was 7.4% (36/485). Multivariate logistic regression showed that after adjusting for age, sex, smoking, drinking, body composition index, ART duration, viral load and the number of comorbidities, increased CD4 cell level was associated with decreased prevalent risk of physical frailty among elderly HIV-infected patients. For every increase of 5.0×107 CD4 cells/L, the prevalent risk of physical frailty decreased by 12% [OR (95%CI): 0.88 (0.76-1.01)]. Compared with the low CD4 cell level group, the risk of physical frailty in those with normal CD4 cell level decreased by 69% [OR (95%CI): 0.31 (0.10-0.92)]. Subgroup analysis of body composition indicators showed that the protective effect of normal CD4 cell level on physical frailty was more pronounced in the high skeletal muscle mass and high basal metabolic rate group (Pinteraction<0.05). Conclusion: The prevalence of physical frailty among elderly HIV-infected patients is relatively lower in Chongqing, and the CD4 cell level, skeletal muscle mass and basal metabolic rate are related to physical frailty.
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Affiliation(s)
- C Chen
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - J Xu
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Z Jiang
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - G H Wu
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
| | - Y Q Zhang
- Department of AIDS/STD Control and Prevention, Chongqing Jiangjin District Center for Disease Control and Prevention, Chongqing 402260, China
| | - Y Zhao
- Department of Treatment and Care, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Z Y Wu
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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Hao X, Jiang Z. Hot issues in triple-negative breast cancer. Cancer Biol Med 2024; 20:j.issn.2095-3941.2023.0294. [PMID: 38318879 PMCID: PMC10845930 DOI: 10.20892/j.issn.2095-3941.2023.0294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 09/06/2023] [Indexed: 02/07/2024] Open
Affiliation(s)
- Xiaopeng Hao
- Department of General Surgery, The First Medical Center of PLA General Hospital, Beijing 100036, China
| | - Zefei Jiang
- Department of Oncology Medicine, The Fifth Medical Center of PLA General Hospital, Beijing 100036, China
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Jiang Z, Ouyang Q, Sun T, Zhang Q, Teng Y, Cui J, Wang H, Yin Y, Wang X, Zhou X, Wang Y, Sun G, Wang J, Zhang L, Yang J, Qian J, Yan M, Liu X, Yi T, Cheng Y, Li M, Zang A, Wang S, Wang C, Wu X, Cheng J, Li H, Lin Y, Geng C, Gu K, Xie C, Xiong H, Wu X, Yang J, Li Q, Chen Y, Li F, Zhang A, Zhang Y, Wu Y, Nie J, Liu Q, Wang K, Mo X, Chen L, Pan Y, Fu P, Zhang H, Pang D, Sheng Y, Han Y, Wang H, Cang S, Luo X, Yu W, Deng R, Yang C, Keegan P. Toripalimab plus nab-paclitaxel in metastatic or recurrent triple-negative breast cancer: a randomized phase 3 trial. Nat Med 2024; 30:249-256. [PMID: 38191615 DOI: 10.1038/s41591-023-02677-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 11/01/2023] [Indexed: 01/10/2024]
Abstract
The combination of immune-checkpoint blockade with chemotherapy for the first-line treatment of advanced triple-negative breast cancer (TNBC) has generated mixed results. TORCHLIGHT is a randomized, double-blinded phase 3 trial evaluating the efficacy and safety of first-line toripalimab and nab-paclitaxel (nab-P) (n = 353; experimental arm) versus placebo and nab-P (n = 178; control arm) for the treatment of women with metastatic or recurrent TNBC. The primary end point was progression-free survival (PFS) assessed by a blinded independent central review in the PD-L1-positive and intention-to-treat populations. The secondary end points included overall survival and safety. Overall, 200 and 100 patients, in the toripalimab and placebo arm respectively had PD-L1-positive TNBC. At the prespecified interim analysis, a statistically significant improvement in PFS assessed by a blinded independent central review was demonstrated in the experimental arm in the PD-L1-positive population (median PFS 8.4 versus 5.6 months; hazard ratio (HR) = 0.65, 95% confidence interval (CI) 0.470-0.906, P = 0.0102). The median overall survival was 32.8 versus 19.5 months (HR = 0.62, 95% CI 0.414-0.914, P = 0.0148). Similar incidences of treatment-emergent adverse events (AEs) (99.2% versus 98.9%), grade ≥3 treatment-emergent AEs (56.4% versus 54.3%) and fatal AEs (0.6% versus 3.4%) occurred in the experimental and control arms. The addition of toripalimab to nab-P provided a significant improvement in PFS for PD-L1-positive patients with metastatic or recurrent TNBC with an acceptable safety profile. ClinicalTrial.gov identifier NCT03777579 .
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Affiliation(s)
- Zefei Jiang
- Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
| | - Quchang Ouyang
- Breast Internal Medicine Department, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Tao Sun
- Breast Medicine Ward Area I, Liaoning Cancer Hospital, Shenyang, China
| | - Qingyuan Zhang
- Department of Breast & Lymphoma, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yuee Teng
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Jiuwei Cui
- Oncology Center, Oncology Department, The First Hospital of Jilin University, Changchun, China
| | - Haibo Wang
- Breast Disease Center, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yongmei Yin
- Department of Oncology, Jiangsu Province Hospital, Nanjing, China
| | - Xiaojia Wang
- Department of Breast (Mammary Gland) Disease, Zhejiang Cancer Hospital, Hangzhou, China
| | - Xin Zhou
- The Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | | | - Gang Sun
- Breast Medicine Department, Xinjiang Medical University Affiliated Cancer Hospital, Urumqi, China
| | - Jingfen Wang
- Breast Medicine Department, Linyi Cancer Hospital, Linyi, China
| | - Lili Zhang
- Department of Oncology, Jiangsu Cancer Hospital, Nanjing, China
| | - Jin Yang
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jun Qian
- Department of Surgical Oncology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China
| | - Min Yan
- Breast Surgery, Henan Cancer Hospital, Zhengzhou, China
| | - Xinlan Liu
- Department of Medical Oncology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Tienan Yi
- Department of Oncology, Xiangyang Central Hospital, Xiangyang, China
| | - Ying Cheng
- Department of Medical Oncology, Jilin Cancer Hospital, Changchun, China
| | - Man Li
- Department of Medical Oncology, The Second Hospital of Dalian Medical University, Dalian, China
| | - Aimin Zang
- Department of Medical Oncology, Affiliated Hospital of Hebei University, Baoding, China
| | - Shusen Wang
- Internal Medicine Department, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Chuan Wang
- Breast Surgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xinhong Wu
- Galactophore Department, Hubei Cancer Hospital, Wuhuan, China
| | - Jing Cheng
- Galactophore Department, Union Hospital Tongji Medical College of Hust, Wuhan, China
| | - Hui Li
- Breast Surgery, Sichuan Cancer Hospital, Chengdu, China
| | - Ying Lin
- Breast Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Cuizhi Geng
- Department of Breast Cancer, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Kangsheng Gu
- Department of Medical Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Chunwei Xie
- Breast Surgery, Nanchang People's Hospital, Nanchang, China
| | - Huihua Xiong
- Department of Oncology, Tongji Hospital Tongji Medical College of Hust, Wuhan, China
| | - Xiaohong Wu
- Department of Oncology, Affiliated Hospital of Jiangnan University, Wuxi, China
| | - Junlan Yang
- Department of Medical Oncology, The First Medical Center of the General Hospital of the People's Liberation Army of China, Beijing, China
| | - Qingshan Li
- Department of Oncology, Affiliated Hospital of Chengde Medical University, Chengde, China
| | - Yiding Chen
- Breast Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fanfan Li
- Department of Oncology, The Second Affiliated Hospital of Anhui University, Hefei, China
| | - Anqin Zhang
- Breast Surgery Department, Guandong Maternal Hospital, Guandong Children's Hospital, Guangzhou, China
| | - Yongqiang Zhang
- Department of Medical Oncology, Beijing Hospital, Beijing, China
| | - Yudong Wu
- Breast Surgery, Jiangxi Cancer Hospital, Nanchang, China
| | - Jianyun Nie
- Third department of Breast surgery, Yunnan Cancer Hospital (The Third Affiliated Hospital of Kunming Medical University), Kuming, China
| | - Qiang Liu
- Breast Surgery Department, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Kun Wang
- Department of Breast Oncology, Guangdong Provincial People's Hospital, Guangzhou, China
| | - Xueli Mo
- Breast Disease Department, Peking University Shougang Hospital, Beijing, China
| | - Lilin Chen
- Department of Medical Oncology, The First Affiliated Hospital of Xiamen University, Xiamen, China
| | - Yueyin Pan
- Oncology Chemotherapy Department, First Affiliated Hospital of USTC (Anhui Provincial Hospital), Hefei, China
| | - Peifen Fu
- Breast Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Helong Zhang
- Department of Medical Oncology, The Second Affiliated Hospital of the Air Force Medical University of the People's Liberation Army Chinese People's Liberation Army, Xi'an, China
| | - Danmei Pang
- Breast Oncology Department, The First People's Hospital of Foshan, Foshan, China
| | - Yuan Sheng
- Thyroid and Breast Surgery Department, Changhai Hospital of Shanghai, Shanghai, China
| | - Yunwei Han
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Hongxia Wang
- Department of Oncology, Shanghai General Hospital, Shanghai, China
- Fudan University Shanghai Cancer Center, Shanghai, China
| | - Shundong Cang
- Department of Medical Oncology, Henan Provincial People's Hospital, Zhengzhou, China
| | | | - Wenbo Yu
- Shanghai Junshi Biosciences, Shanghai, China
| | - Rong Deng
- Shanghai Junshi Biosciences, Shanghai, China
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Zhang S, Li J, Xu R, Chen Q, Sun G, Lin Y, Cao Y, Chen Y, Geng C, Teng Y, Nie J, Li X, Xu G, Liu X, Jin F, Fan Z, Luo T, Liu H, Wang FS, Jiang Z. Safety of COVID-19 Vaccination in Patients With Breast Cancer: Cross-Sectional Study in China. JMIR Public Health Surveill 2023; 9:e46009. [PMID: 38060302 PMCID: PMC10739232 DOI: 10.2196/46009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 07/26/2023] [Accepted: 10/31/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND The widespread use of vaccines against the novel coronavirus disease (COVID-19) has become one of the most effective means to establish a population immune barrier. Patients with cancer are vulnerable to COVID-19 infection, adverse events, and high mortality, and should be the focus of epidemic prevention and treatment. However, real-world data on the safety of vaccines for patients with breast cancer are still scarce. OBJECTIVE This study aims to compare the safety of COVID-19 vaccines between patients vaccinated before or after being diagnosed with breast cancer. METHODS Patients with breast cancer who sought medical advice from October 2021 to December 2021 were screened. Those who received COVID-19 vaccines were enrolled in this study to analyze the safety of the vaccines. The primary outcome was patient-reported adverse events (AEs). All events after vaccine injection were retrospectively documented from the patients. RESULTS A total of 15,455 patients with breast cancer from 41 hospitals in 20 provinces in China were screened, and 5766 patients who received COVID-19 vaccines were enrolled. Of those enrolled, 45.1% (n=2599) of patients received vaccines before breast cancer diagnosis, 41.3% (n=2379) were vaccinated after diagnosis, and 13.6% (n=784) did not known the accurate date of vaccination or cancer diagnosis. Among the patients vaccinated after diagnosis, 85.4% (n=2032) were vaccinated 1 year after cancer diagnosis and 95.4% (n=2270) were vaccinated during early-stage cancer. Of all 5766 vaccinated patients, 93.9% (n=5415) received an inactivated vaccine, 3.7% (n=213) received a recombinant subunit vaccine, and 2.4% (n=138) received other vaccines, including adenovirus and mRNA vaccines. In the first injection of vaccines, 24.4% (n=10, 95% CI 11.2-37.5) of patients who received an adenovirus vaccine reported AEs, compared to only 12.5% (n=677, 95% CI 11.6-13.4) of those who received an inactivated vaccine. Patients with metastatic breast cancer reported the highest incidence of AEs (n=18, 16.5%, 95% CI 9.5-23.5). Following the second injection, patients who received an inactivated vaccine (n=464, 8.7%, 95% CI 8.0-9.5) and those who received a recombinant vaccine (n=25, 8.7%, 95% CI 5.5-12.0) reported the same incidence of AEs. No significant differences in patient-reported AEs were found between the healthy population and patients with breast cancer (16.4% vs 16.9%, respectively); the most common AEs were local pain (11.1% vs 9.1%, respectively), fatigue (5.5% vs 6.3%, respectively), and muscle soreness (2.3% vs 3.6%, respectively). The type of vaccine and time window of vaccination had little impact on patient-reported AEs. CONCLUSIONS Compared with patients vaccinated before breast cancer diagnosis, there were no significant differences in patient-reported AEs in the patients vaccinated after diagnosis. Thus, it is safe for patients with breast cancer, especially for those in the early stage, to receive COVID-19 vaccines. TRIAL REGISTRATION Chinese Clinical Trial Registry ChiCTR2200055509; https://tinyurl.com/33zzj882.
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Affiliation(s)
- Shaohua Zhang
- Fifth Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China
| | - Jianbin Li
- Fifth Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China
- Beijing Institute of Biotechnology, Academy of Military Medical Sciences, Beijing, China
| | - Ruonan Xu
- Fifth Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China
| | - Qianjun Chen
- Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangdong, China
| | - Gang Sun
- Cancer Hospital Affiliated to Xinjiang Medical University, Xinjiang, China
| | - Ying Lin
- The First Affiliated Hospital of Sun Yat-sen University, Guangdong, China
| | - Yali Cao
- Nanchang Third Hospital, Jiangxi, China
| | - Yiding Chen
- The Second Affiliated Hospital of Medical College of Zhejiang University, Zhejiang, China
| | - Cuizhi Geng
- Fourth Hospital of Hebei Medical University, Hebei, China
| | - Yuee Teng
- The First Hospital of China Medical University, Liaoning, China
| | | | | | | | - Xinlan Liu
- General Hospital of Ningxia Medical University, Ningxia, China
| | - Feng Jin
- The First Hospital of China Medical University, Liaoning, China
| | - Zhimin Fan
- The First Hospital of Jilin University, Jilin, China
| | - Ting Luo
- Sichuan Uniersity Huaxi Campus, Sichuan, China
| | - Hong Liu
- Tumor Hospital of Tianjin Medical University, Tianjin, China
| | - Fu-Sheng Wang
- Fifth Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China
| | - Zefei Jiang
- Fifth Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China
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Wu L, Ying J, Jiang Z, Zhang L, Cai Y, Zhou C, Xu Y, Lei S. Risk factors in ICU patients with initial acquisition of carbapenemase-resistant Klebsiella Pneumoniae. Int J Tuberc Lung Dis 2023; 27:899-905. [PMID: 38042974 DOI: 10.5588/ijtld.23.0043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2023] Open
Abstract
OBJECTIVE: To identify the risk factors associated with antimicrobial use on the initial acquisition of carbapenem-resistant Klebsiella pneumoniae (CRKP) in elderly intensive care unit (ICU) patients.METHODS: Respiratory secretion, blood, urine, anal swab and peritoneal drainage samples from all elderly patients with non-colonised CRKP who had been hospitalised from January 2021 to December 2022 were collected, and screened for CRKP colonisation using surveillance culture at the time of the first ICU admission and weekly thereafter in Zhejiang Provincial Hospital of Chinese Medicine, Zhejiang, China. Cumulative antibiotic variables included duration of antibiotic use, total amount of antimicrobials received in grams, total antibiotic consumption (defined daily dose) and the types of antimicrobial exposure. A time-dependent model based on Cox regression analysis was used to investigate the effect of each variable on the initial acquisition of CRKP infection or colonisation.RESULTS: Of 214 patients, 44 were infected or had CRKP colonies and death rate was 34.1%. males were the risk factor for acquiring CRKP in culture (HR 2.12, 95% CI 1.06-4.21; P = 0.033). It is notable that the hazard of acquiring CRKP increased by 9% with every single-point increase in the APACHE II score (HR 1.09, 95% CI 1.01-1.18; P = 0.025). The hazard of acquiring CRKP doubled when carbapenems were administered (HR 1.81, 95% CI 1.42-2.30; P < 0.001), In contrast, exposure to quinolone antimicrobials had a smaller effect on acquiring CRKP (HR 1.07; 95% CI 1.01-1.14; P = 0.024).CONCLUSION: This study found that male sex, APACHE II score and exposure to quinolones and carbapenems were independent risk factors for acquiring CRKP.
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Affiliation(s)
- L Wu
- Departments of Respiratory and Critical Care Medicine, and
| | - J Ying
- Departments of Obstetrics and Gynecology, The Affiliated Cangnan Hospital of Wenzhou Medical University, Cangnan, Zhejiang
| | - Z Jiang
- Department of Emergency Medicine, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou, Zhejiang
| | - L Zhang
- Departments of Respiratory and Critical Care Medicine, and
| | - Y Cai
- Departments of Respiratory and Critical Care Medicine, and
| | - C Zhou
- Departments of Respiratory and Critical Care Medicine, and
| | - Y Xu
- Department of Cardiology, Hangzhou Ninth People's Hospital, Hangzhou, Zhejiang
| | - S Lei
- Intensive Care Unit, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
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Jiang Z, Zhi N, Liu G, Sun X, Chen X, Ma D, Guo M, Wang S, Zhang H. Electroacupuncture for post-stroke urinary incontinence: a systematic review and meta-analysis with trial sequential analysis. Front Neurol 2023; 14:1282580. [PMID: 38046590 PMCID: PMC10693342 DOI: 10.3389/fneur.2023.1282580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 10/20/2023] [Indexed: 12/05/2023] Open
Abstract
Background The evidence for the effectiveness of electroacupuncture (EA) for post-stroke urinary incontinence (PSUI) patients remains unclear. Therefore, the purpose of this systematic review and meta-analysis was to assess the efficacy of EA for PSUI. Methods and analysis Eight English and Chinese databases were searched from their inception until 1 August 2023 to collect randomized controlled trials (RCTs) that investigated the effect of EA on PSUI. Two reviewers independently selected studies that met the eligibility criteria, extracted the necessary data, and assessed the risk of bias for included studies using Cochrane Handbook version 5.1.0. Meta-analysis was performed using Review Manager software (version 5.4.1). Publication bias detection was conducted using STATA (version 16.0). Sequential analysis was performed using TSA 0.9.5.10 Beta. The Grading of Recommendations Assessment, Development, and Evaluation System (GRADE) was used for assessing the certainty of evidence. Results We included 15 RCTs involving a total of 1,414 patients. The narrative analysis revealed that compared with sham EA, genuine EA exhibited greater efficacy in reducing occurrences of 24-h urinary incontinence while also enhancing maximum cystometric capacity (MCC). Moreover, this effect remained significant even during the 3-month follow-up period. Fourteen studies were encompassed within the quantitative analysis. In contrast to active interventions, EA did not yield an improvement in the responder rate (RR 1.53, 95% CI 0.61 to 3.80, p = 0.36). When compared with basic treatments, the combination of EA with them led to a reduction in 24-h urinary incontinence occurrences (MD -0.56, 95% CI -0.60 to -0.52, p < 0.00001), an improvement in MCC (MD 43.23, 95% CI 28.86 to 57.60, p < 0.00001), and a decrease in residual urine volume (RUV; MD -19.99, 95% CI -29.75 to -10.23, p < 0.0001). However, it did not lead to an increase in the responder rate (RR 1.39, 95% CI 0.88 to 2.20, p = 0.16). In comparison to basic treatments combined with active interventions, the amalgamation of EA and them led to an increase in the responder rate (RR 1.24, 95% CI 1.14 to 1.35, p < 0.00001), a reduction in 24-h urinary incontinence occurrences (MD -2.90, 95% CI -5.26 to -0.55, p = 0.02), a decrease in International Consultation on Incontinence Questionnaire-Short Form scores, and an improvement in both MCC (MD 42.11, 95% CI 23.26 to 60.96, p < 0.0001) and RUV (MD 42.11, 95% CI 23.26 to 60.96, p < 0.0001). Furthermore, all reported adverse effects associated with EA were mild. The trial sequential analysis suggested that a sufficient sample size was available to yield results. However, the level of evidence was predominantly assessed as low or very low. Conclusion Electroacupuncture improved post-stroke urinary incontinence with no serious adverse effects. Caution is warranted due to methodological issues, and more high-quality studies are required to confirm its efficacy and safety.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023449599, Identifier CRD42023449599.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Hong Zhang
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
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Kuai YX, Li M, Jiang Z, Chen J, Bai ZJ, Li XZ, Lu GP, Li YH. [Comparison of diagnostic criteria for acute kidney injury in critically ill children]. Zhonghua Er Ke Za Zhi 2023; 61:1011-1017. [PMID: 37899340 DOI: 10.3760/cma.j.cn112140-20230623-00418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
Objective: The kidney disease: improving global outcome (KDIGO) and pediatric reference change value optimized for acute kidney injury (pROCK) criteria were used to evaluate the incidence, stages and mortality of acute kidney injury (AKI). The differences between the 2 criteria were compared for exploring the value of pROCK criteria in diagnosing pediatric AKI and predicting adverse outcomes. Methods: In the multicenter prospective clinical cohort study, we collected general data and clinical data such as serum creatinine values from 1 120 children admitted to 4 PICUs of Children's Hospital of Soochow University, Children's Hospital of Fudan University, Anhui Provincial Children's Hospital, and Xuzhou Children's Hospital from September 2019 to February 2021. AKI was defined and staged according to the KDIGO and pROCK criteria. The incidence of AKI, the consistency of AKI definite diagnosis and stages, and the mortality in PICU were compared between the 2 groups. The chi-square test or Fisher's exact test was applied for comparison between 2 groups. The Cohen's Kappa and Weighted Kappa analyses were used for evaluating diagnostic consistency. The Cox regression analysis was used to evaluate the correlation between AKI and mortality. Results: A total of 1 120 critically ill children were included, with an age of 33 (10, 84) months. There are 668 boys and 452 girls. The incidence of AKI defined by the KDIGO guideline was higher than that defined by pROCK criteria (27.2%(305/1 120), 14.7%(165/1 120), χ2=52.78, P<0.001). The concordance rates of the 2 criteria for the diagnosis of AKI and AKI staging were 87.0% (κ=0.62) and 79.7% (κ=0.58), respectively. Totally 63 infants with AKI stage 1 defined by the KDIGO guideline were redefined as non-AKI by following the pROCK criteria. The PICU mortality rate of these infants was similar to patients without AKI defined by KDIGO guideline(P=0.761). After adjusting for confounders, AKI defined by KDIGO or pROCK criteria was an independent risk factor of death in PICU (AHR=2.04, 2.73,95%CI 1.27-3.29, 1.74-4.28, both P<0.01), and the risk of death was higher when using the pROCK compared with the KDIGO criteria. As for the KDIGO criteria, mild AKI was not associated with the mortality in PICU (P=0.702), while severe AKI was associated with increased mortality (P<0.001). As for the pROCK criteria, both mild and severe AKI were risk factors of PICU death in children (HR=3.51, 6.70, 95%CI 1.94-6.34, 4.30-10.44, both P<0.001). In addition, The AKI severity was positively associated with the mortality. Conclusions: The AKI incidence and staging varied depending on the used diagnostic criteria. The KDIGO definition is more sensitive, while the pROCK-defined AKI is more strongly associated with high mortality rate.
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Affiliation(s)
- Y X Kuai
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - M Li
- Pediatric Intensive Care Unit, Anhui Provincial Children's Hospital, Hefei 230002, China
| | - Z Jiang
- Pediatric Intensive Care Unit, Xuzhou Children's Hospital, Xuzhou 221002, China
| | - J Chen
- Pediatric Intensive Care Unit, Children's Hospital of Soochow University, Suzhou 215000, China
| | - Z J Bai
- Pediatric Intensive Care Unit, Children's Hospital of Soochow University, Suzhou 215000, China
| | - X Z Li
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - G P Lu
- Pediatric Intensive Care Unit, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Y H Li
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
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Jiang Z, Xu XL, Zhuang PY. [Frontier technology and research progress in the diagnostics and therapeutics of voice diseases: report from the Voice Foundation 52nd Anniversary Symposium]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2023; 58:1024-1028. [PMID: 37840170 DOI: 10.3760/cma.j.cn115330-20230619-00289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Affiliation(s)
- Z Jiang
- Department of Voice Medicine, Zhongshan Hospital, Xiamen University; Key Laboratory of Voice of Xiamen City, Xiamen 361004, China
| | - X L Xu
- Department of Voice Medicine, Zhongshan Hospital, Xiamen University; Key Laboratory of Voice of Xiamen City, Xiamen 361004, China
| | - P Y Zhuang
- Department of Voice Medicine, Zhongshan Hospital, Xiamen University; Key Laboratory of Voice of Xiamen City, Xiamen 361004, China
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Ji C, Li F, Yuan Y, Zhang H, Bian L, Zhang S, Wang T, Li J, Jiang Z. Novel Anti-HER2 Antibody-Drug Conjugates Versus T-DM1 for HER2-Positive Metastatic Breast Cancer After Tyrosine Kinase Inhibitors Treatment. Oncologist 2023; 28:e859-e866. [PMID: 37218076 PMCID: PMC10546815 DOI: 10.1093/oncolo/oyad127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/13/2023] [Indexed: 05/24/2023] Open
Abstract
BACKGROUND Antibody-drug conjugates (ADCs) have been the preferred regimens for human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC) after trastuzumab. Unfortunately, there is little data showing which ADCs should be chosen for those patients whose treatment with tyrosine kinase inhibitors (TKIs) failed. This study aims to analyze the efficacy and safety between novel anti-HER2 ADCs and trastuzumab emtansine (T-DM1) for those with TKIs failure. MATERIALS AND METHODS HER2-positive MBC using ADCs from January 2013 to June 2022 were included, and all of them were treated with TKIs. The primary study endpoint was progression-free survival (PFS), and the secondary study endpoints were objective response rate (ORR), clinical benefit rate (CBR), and safety. RESULTS A total of 144 patients with 73 patients in the novel anti-HER2 ADCs group and 71 patients in the T-DM1 group. In these novel ADCs, 30 patients received trastuzumab deruxtecan (T-Dxd), 43 patients receive other novel ADCs. The median PFS in the novel ADCs group and T-DM1 group were 7.0 months versus 4.0 months, respectively, and ORR was 54.8% versus 22.5%, CBR was 65.8% versus 47.9%, respectively. In subgroups analysis, the PFS were both significantly improved in patients receiving T-Dxd and other novel ADCs compared with T-DM1. The most common grades 3-4 adverse events in the novel anti-HER-2 ADCs group were neutropenia (20.5%) and thrombocytopenia (28.1%) in the T-DM1 group. CONCLUSIONS In patients with HER2-positive MBC previously treated with TKIs, both T-Dxd and other novel anti-HER2 ADCs yielded statistically significant better PFS than T-DM1 did, with tolerable toxicities.
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Affiliation(s)
- Chenchen Ji
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
| | - Feng Li
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
| | - Yang Yuan
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
| | - Huiqiang Zhang
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
| | - Li Bian
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
| | - Shaohua Zhang
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
| | - Tao Wang
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
| | - Jianbin Li
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
- Department of Medical Molecular Biology, Beijing Institute of Biotechnology, Academy of Military Medical Sciences, Beijing, People’s Republic of China
| | - Zefei Jiang
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
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Hoke JC, Ippoliti M, Rosenberg E, Abanin D, Acharya R, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Eppens D, Erickson C, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Martin O, McClean JR, McEwen M, Miao KC, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O’Brien TE, Omonije S, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Mi X, Khemani V, Roushan P. Measurement-induced entanglement and teleportation on a noisy quantum processor. Nature 2023; 622:481-486. [PMID: 37853150 PMCID: PMC10584681 DOI: 10.1038/s41586-023-06505-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/01/2023] [Indexed: 10/20/2023]
Abstract
Measurement has a special role in quantum theory1: by collapsing the wavefunction, it can enable phenomena such as teleportation2 and thereby alter the 'arrow of time' that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space-time3-10 that go beyond the established paradigms for characterizing phases, either in or out of equilibrium11-13. For present-day noisy intermediate-scale quantum (NISQ) processors14, the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping9,15-17 to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling3,4 to measurement-induced teleportation18. We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors.
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Li Y, Zhang J, Cai W, Wang C, Yu Z, Jiang Z, Lai K, Wang Y, Yang G. CREB3L2 Regulates Hemidesmosome Formation during Epithelial Sealing. J Dent Res 2023; 102:1199-1209. [PMID: 37555472 DOI: 10.1177/00220345231176520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/10/2023] Open
Abstract
The long-term success rate of dental implants can be improved by establishing a favorable biological sealing with a high-quality epithelial attachment. The application of mesenchymal stem cells (MSCs) holds promise for facilitating the soft tissue integration around implants, but the molecular mechanism is still unclear and the general application of MSC sheet for soft tissue integration is also relatively unexplored. We found that gingival tissue-derived MSC (GMSC) sheet treatment significantly promoted the expression of hemidesmosome (HD)-related genes and proteins in gingival epithelial cells (GECs). The formation of HDs played a key role in strengthening peri-implant epithelium (PIE) sealing. Further, high-throughput transcriptome sequencing showed that GMSC sheet significantly upregulated the PI3K/AKT pathway, confirming that cell adhesion and HD expression in GECs were regulated by GMSC sheet. We observed that the expression of transcription factor CREB3L2 in GECs was downregulated. After treatment with PI3K pathway inhibitor LY294002, CREB3L2 messenger RNA and protein expression levels were upregulated. Further experiments showed that overexpression or knockdown of CREB3L2 could significantly inhibit or promote HD-related genes and proteins, respectively. We confirmed that CREB3L2 was a transcription factor downstream of the PI3K/AKT pathway and participated in the formation of HDs regulated by GMSC sheet. Finally, through the establishment of early implant placement model in rats, we clarified the molecular function of CREB3L2 in PIE sealing as a mechanical transmission molecule in GECs. The application of GMSC sheet-implant complex could enhance the formation of HDs at the implant-PIE interface and decrease the penetration distance of horseradish peroxidase between the implant and PIE. Meanwhile, GMSC sheet reduced the length of CREB3L2 protein expression on PIE. These findings elucidate the potential function and molecular mechanism of MSC sheet regulating the epithelial sealing around implants, providing new insights and ideas for the application of stem cell therapy in regenerative medicine.
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Affiliation(s)
- Y Li
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - J Zhang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - W Cai
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - C Wang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - Z Yu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - Z Jiang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - K Lai
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - Y Wang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - G Yang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
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Lang Y, Jiang Z, Sun L, Xiang L, Ren L. Hybrid-Supervised Deep Learning for Proton-Acoustic Reconstruction for 3D In Vivo Proton Dose Verification. Int J Radiat Oncol Biol Phys 2023; 117:e682-e683. [PMID: 37786007 DOI: 10.1016/j.ijrobp.2023.06.2145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Proton-acoustic (PA) image has shown great potential to provide real-time 3D dose verification of proton therapy. However, the PA image quality suffers from severe limited view artifacts, which significantly impairs its accuracy for dose verification. In this study, we developed a hybrid-supervised deep learning method for PA reconstruction to address the limited-view issues. MATERIALS/METHODS Our method consists of two stages. In the first stage, a transformer-based network was proposed to reconstruct initial pressure maps from protoacoustic signals. The network was first trained using supervision by the iteratively reconstructed pressure map and then fine-tuned using transfer learning and self-supervision based on the data fidelity constraint. In the second stage, the PA image was further enhanced by a 3D U-net. The final PA images were converted to dose maps using conversion coefficients derived from CT images. Data from 126 prostate cancer patients treated by proton therapy were collected under an IRB protocol and were split into 86 and 40 patients for model training and testing, respectively. Data of each patient contains the planning CT scan, the corresponding clinical treatment plan, and the dose map calculated by commercial software. The radiofrequency signals were generated by performing proton acoustic simulation based on CT images and the ground truth pressure map derived from the treatment plan. An ultrasound detector matrix with 64 × 64 size and 500kHz central frequency was simulated under the perineum to acquire the signals in the prostate area. In the testing results, the method's accuracy was evaluated using Root-mean-squared-error (RMSE) and structural-similarity-index-measure (SSIM) between the reconstructed and ground truth pressure map and dose distribution. RESULTS Testing results showed that the reconstructed pressure map achieved an average RMSE/SSIM of 0.0292/0.96, demonstrating excellent 3D information with details. Dose maps derived from the pressure map achieved an average RMSE/SSIM of 0.018/0.99 with a gamma index of 94.7% and 95.7% for 1%/3 mm and 1%/5 mm criteria compared to the ground truth dose maps. The reconstruction time was 6s, which can be further reduced using GPU. CONCLUSION Our study achieves start-of-the-art performance in the challenging task of direct reconstruction from limited-view radiofrequency signals, demonstrating the great promise of PA imaging as a highly efficient and accurate tool for in-vivo 3D proton dose verification. Such high-precision 3D online dose verification can substantially reduce the range uncertainties of proton therapy to significantly improve its precision and outcomes.
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Affiliation(s)
- Y Lang
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD
| | | | - L Sun
- University of California, Irvine, CA
| | - L Xiang
- University of California, Irvine, CA
| | - L Ren
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD
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Zhang G, Jiang Z, Wang L. A Radiotherapy Positioning Method for Both Coarse Guidance and Precise Verification Based on Integration of AR and Optical Surface Imaging. Int J Radiat Oncol Biol Phys 2023; 117:e743-e744. [PMID: 37786156 DOI: 10.1016/j.ijrobp.2023.06.2280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Traditional methods of radiotherapy positioning have shortcomings such as fragile skin-markers, additional doses and lack of information integration. Emerging technologies may provide alternatives for the relevant clinical practice. We proposed a noninvasive radiotherapy positioning method integrating augmented reality (AR) and optical surface, and evaluated its feasibility in clinical workflow. MATERIALS/METHODS AR and structured light-based surface were integrated to implement the coarse-to-precise positioning through two coherent steps, i) the AR-based coarse guidance. To implement quality assurance, recognition of face and pattern was used for patient authentication, case association and accessory validation in AR scenes. The holographic images reconstructed from simulation computed tomography (CT) images, guided the initial posture correction by virtual-real alignment. ii) optical surface-based precise verification. The point clouds were fused, with the calibration and pose estimation of structured light cameras, and segmented according to the preset regions of interest (ROIs). The global-to-local registration for cross-source point clouds was achieved to calculate couch shifts in 6 degrees-of-freedom (DoF), which were ultimately transmitted to AR scenes. The evaluation based on phantom and human-body (4 volunteers) included, i) quality assurance workflow, ii) errors of both steps and correlation analysis, and iii) receiver operating characteristic (ROC). RESULTS The maximum errors in phantom evaluation were 3.4±2.5 mm in Vrt and 1.4±1.0° in Pitch for the coarse guidance step, while 1.6±0.9 mm in Vrt and 0.6±0.4° in Pitch for the precise verification step. The Pearson correlation coefficients between precise verification and cone beam CT (CBCT) results were distributed in the interval [0.81, 0.85]. In ROC analysis, the areas under the curve (AUC) were 0.87 and 0.89 for translation and rotation respectively. In human body-based evaluation, the errors of thorax and abdomen (T&A) were significantly greater than those of head and neck (H&N) in Vrt (2.6±1.3 vs. 1.7±1.1, p<0.01), Lng (2.4±1.3 vs. 1.4±0.1, p<0.01) and Rtn (0.8±0.5 vs. 0.6±0.4, p = 0.03) while relatively similar in Lat (1.7±1.0 vs. 1.9±1.1, p = 0.13). CONCLUSION The combination of AR and optical surface has utility and feasibility for patient positioning, in terms of both safety and accuracy.
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Affiliation(s)
- G Zhang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Ji'nan, China
| | - Z Jiang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Ji'nan, China
| | - L Wang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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Yang Y, He Y, Fan Z, Chen X, Liu Y, Zhang C, Jiang H, Wang X, Wang X, Xie F, Wang S, Luo B, Kang H, Wang T, Jiang Z, Yuan P, Xu B, Xu L, Liu Y, Li J, Xie Y, Wang T, Ouyang T. Author Correction: Phase III study of HR-positive/HER2-negative/lymph node-positive breast cancer non-responsive to primary chemotherapy: a randomized trial. NPJ Breast Cancer 2023; 9:62. [PMID: 37488099 PMCID: PMC10366133 DOI: 10.1038/s41523-023-00567-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/26/2023] Open
Affiliation(s)
- Yang Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yingjian He
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Zhaoqing Fan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China.
| | - Xue Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yiqiang Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Chao Zhang
- Beijing Chao Yang Hospital, Breast Disease Department, Beijing, China
| | - Hongchuan Jiang
- Beijing Chao Yang Hospital, Breast Disease Department, Beijing, China
| | - Xin Wang
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Xiang Wang
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Fei Xie
- Peking University People's Hospital, Breast Cancer Center, Beijing, China
| | - Shu Wang
- Peking University People's Hospital, Breast Cancer Center, Beijing, China
| | - Bin Luo
- Beijing Tsinghua Changgeng Hospital, Breast Disease Department, Beijing, China
| | - Hua Kang
- Xuan Wu Hospital Capital Medical University, Breast Disease Department, Beijing, China
| | - Tao Wang
- 307 Hospital of PLA, Breast Cancer Department, Beijing, China
| | - Zefei Jiang
- 307 Hospital of PLA, Breast Cancer Department, Beijing, China
| | - Peng Yuan
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Binhe Xu
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Ling Xu
- Peking University First Hospital, Breast Cancer Center, Beijing, China
| | - Yinhua Liu
- Peking University First Hospital, Breast Cancer Center, Beijing, China
| | - Jinfeng Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yuntao Xie
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Tianfeng Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Tao Ouyang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
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Yang FL, Chen X, Zheng F, Liu XX, Sun N, Li RQ, Jiang Z, Han J, Yang J. [Targeting microRNA-125b inhibited the metastasis of Alisertib resistance cells through mediating p53 pathway]. Zhonghua Zhong Liu Za Zhi 2023; 45:499-507. [PMID: 37355468 DOI: 10.3760/cma.j.cn112152-20200511-00438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/26/2023]
Abstract
Objective: To clarify the mechanisms involvement in Alisertib-resistant colorectal cells and explore a potential target to overcome Alisertib-resistance. Methods: Drug-resistant colon cancer cell line (named as HCT-8-7T cells) was established and transplanted into immunodeficient mice. The metastasis in vivo were observed. Proliferation and migration of HCT-8-7T cells and their parental cells were assessed by colony formation and Transwell assay, respectively. Glycolytic capacity and glutamine metabolism of cells were analyzed by metabolism assays. The protein and mRNA levels of critical factors which are involved in mediating glycolysis and epithelial-mesenchymal transition (EMT) were examined by western blot and reverse transcription-quantitative real-time polymerase chain reaction(RT-qPCR), respectively. Results: In comparison with the mice transplanted with HCT-8 cells, which were survival with limited metastatic tumor cells in organs, aggressive metastases were observed in liver, lung, kidney and ovary of HCT-8-7T transplanted mice (P<0.05). The levels of ATP [(0.10±0.01) mmol/L], glycolysis [(81.77±8.21) mpH/min] and the capacity of glycolysis [(55.50±3.48) mpH/min] in HCT-8-7T cells were higher than those of HCT-8 cells [(0.04±0.01) mmol/L, (27.77±2.55) mpH/min and(14.00±1.19) mpH/min, respectively, P<0.05]. Meanwhile, the levels of p53 protein and mRNA in HCT-8-7T cells were potently decreased as compared to that in HCT-8 cells (P<0.05). However, the level of miRNA-125b (2.21±0.12) in HCT-8-7T cells was significantly elevated as compared to that in HCT-8 cells (1.00±0.00, P<0.001). In HCT-8-7T cells, forced-expression of p53 reduced the colon number (162.00±24.00) and the migration [(18.53±5.67)%] as compared with those in cells transfected with control vector [274.70±40.50 and (100.00±29.06)%, P<0.05, respectively]. Similarly, miR-125b mimic decreased the glycolysis [(25.28±9.51) mpH/min] in HCT-8-7T cells as compared with that [(54.38±12.70)mpH/min, P=0.003] in HCT-8-7T cells transfected with control. Meanwhile, in comparison with control transfected HCT-8-7T cells, miR-125b mimic also significantly led to an increase in the levels of p53 and β-catenin, in parallel with a decrease in the levels of PFK1 and HK1 in HCT-8-7T cells (P<0.05). Conclusions: Silencing of p53 by miR-125b could be one of the mechanisms that contributes to Alisertib resistance. Targeting miR-125b could be a strategy to overcome Alisertib resistance.
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Affiliation(s)
- F L Yang
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Xuzhou 221000, China
| | - X Chen
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - F Zheng
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Xuzhou 221000, China
| | - X X Liu
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - N Sun
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - R Q Li
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - Z Jiang
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Xuzhou 221000, China
| | - J Han
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - J Yang
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
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Yang Y, He Y, Fan Z, Chen X, Liu Y, Zhang C, Jiang H, Wang X, Wang X, Xie F, Wang S, Luo B, Kang H, Wang T, Jiang Z, Yuan P, Xu B, Xu L, Liu Y, Li J, Xie Y, Wang T, Ouyang T. Phase III study of HR-positive/HER2-negative/lymph node-positive breast cancer non-responsive to primary chemotherapy: a randomized trial. NPJ Breast Cancer 2023; 9:54. [PMID: 37344451 PMCID: PMC10284834 DOI: 10.1038/s41523-023-00553-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 05/19/2023] [Indexed: 06/23/2023] Open
Abstract
There are few studies focus on post-neoadjuvant treatment in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-)/lymph node-positive (LN+) breast cancer, a multi-center, open-label, randomized, controlled phase III trial was conducted to evaluate pathological response-guided non-cross-resistant adjuvant chemotherapy in patients with HR+/HER2-/LN+ breast cancer who were non-responsive to primary chemotherapy. Patients received four cycles of non-cross-resistant adjuvant chemotherapy plus endocrine therapy (ET), or ET alone. Forty patients responsive to neoadjuvant chemotherapy and with Miller and Payne G4 or G5 and LN- status were assigned to the observation group. Distant disease-free survival was the primary endpoint. The final intention-to-treat analysis comprised 379 patients. After a median follow-up period of 72.4 months, the 5-year distant disease-free survival was 92% and 90% in the chemotherapy plus ET and ET-alone groups, respectively. Comparatively, the observation group showed a trend towards better distant disease-free survival. For patients non-responsive to neoadjuvant chemotherapy, adjuvant non-cross-resistant chemotherapy did not significantly improve distant disease-free survival compared to ET alone.
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Affiliation(s)
- Yang Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yingjian He
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Zhaoqing Fan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China.
| | - Xue Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yiqiang Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Chao Zhang
- Beijing Chao Yang Hospital, Breast Disease Department, Beijing, China
| | - Hongchuan Jiang
- Beijing Chao Yang Hospital, Breast Disease Department, Beijing, China
| | - Xin Wang
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Xiang Wang
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Fei Xie
- Peking University People's Hospital, Breast Cancer Center, Beijing, China
| | - Shu Wang
- Peking University People's Hospital, Breast Cancer Center, Beijing, China
| | - Bin Luo
- Beijing Tsinghua Changgeng Hospital, Breast Disease Department, Beijing, China
| | - Hua Kang
- Xuan Wu Hospital Capital Medical University, Breast Disease Department, Beijing, China
| | - Tao Wang
- 307 Hospital of PLA, Breast Cancer Department, Beijing, China
| | - Zefei Jiang
- 307 Hospital of PLA, Breast Cancer Department, Beijing, China
| | - Peng Yuan
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Binhe Xu
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Ling Xu
- Peking University First Hospital, Breast Cancer Center, Beijing, China
| | - Yinhua Liu
- Peking University First Hospital, Breast Cancer Center, Beijing, China
| | - Jinfeng Li
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Yuntao Xie
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Tianfeng Wang
- Cancer Hospital, Chinese Academy of Medical Sciences, Breast Cancer Department, Beijing, China
| | - Tao Ouyang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Breast Center, Peking University Cancer Hospital & Institute, Beijing, China
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Yuan Y, Zhang S, Wang T, Bian L, Yan M, Yin Y, Song Y, Wen Y, Li J, Jiang Z. Efficacy and clinical outcome of chemotherapy and endocrine therapy as first-line treatment in patients with hormone receptor-positive HER2-negative metastatic breast cancer. Chin Med J (Engl) 2023; 136:1459-1467. [PMID: 37101355 PMCID: PMC10278751 DOI: 10.1097/cm9.0000000000002676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Indexed: 04/28/2023] Open
Abstract
BACKGROUND Endocrine therapy (ET) and ET-based regimens are the preferred first-line treatment options for hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (HR+/HER2- MBC), while chemotherapy (CT) is commonly used in clinical practice. The aim of this study was to investigate the efficacy and clinical outcome of ET and CT as first-line treatment in Chinese patients with HR+/HER2- MBC. METHODS Patients diagnosed with HR+/HER2-MBC between January 1st, 1996 and September 30th, 2018 were screened from the Chinese Society of Clinical Oncology Breast Cancer database. The initial and maintenance first-line treatment, progression-free survival (PFS), and overall survival (OS) were analyzed. RESULTS Among the 1877 included patients, 1215 (64.7%) received CT and 662 (35.3%) received ET as initial first-line treatment. There were no statistically significant differences in PFS and OS between patients receiving ET and CT as initial first-line treatment in the total population (PFS: 12.0 vs. 11.0 months, P = 0.22; OS: 54.0 vs . 49.0 months, P =0.09) and propensity score matched population. For patients without disease progression after at least 3 months of initial therapy, maintenance ET following initial CT (CT-ET cohort, n = 449) and continuous schedule of ET (ET cohort, n = 527) had longer PFS than continuous schedule of CT (CT cohort, n = 406) in the total population (CT-ET cohort vs. CT cohort: 17.0 vs . 8.5 months; P <0.01; ET cohort vs . CT cohort: 14.0 vs . 8.5 months; P <0.01) and propensity score matched population. OS in the three cohorts yielded the same results as PFS. CONCLUSIONS ET was associated with similar clinical outcome to CT as initial first-line treatment. For patients without disease progression after initial CT, switching to maintenance ET showed superiority in clinical outcome over continuous schedule of CT.
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Affiliation(s)
- Yang Yuan
- Department of Oncology No. 4 Ward, The Fifth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing 100071, China
| | - Shaohua Zhang
- Department of Oncology No. 3 Ward, The Fifth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing 100071, China
| | - Tao Wang
- Department of Oncology No. 4 Ward, The Fifth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing 100071, China
| | - Li Bian
- Department of Oncology No. 3 Ward, The Fifth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing 100071, China
| | - Min Yan
- Department of Breast Disease, Henan Breast Cancer Center, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan 450008 China
| | - Yongmei Yin
- Department of Breast Cancer, Jiangsu Province Hospital & The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029 China
| | - Yuhua Song
- Department of Breast Cancer Center, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 260000 China
| | - Yi Wen
- Medical Department, Medpion (Beijing) Medical Technology Co., Ltd, Beijing 100062 China
| | - Jianbin Li
- Department of Oncology No. 3 Ward, The Fifth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing 100071, China
| | - Zefei Jiang
- Department of Oncology No. 3 Ward, The Fifth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing 100071, China
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Han C, Pan Y, Liu C, Yang X, Li J, Wang K, Sun Z, Liu H, Jin G, Fang F, Pan X, Tang T, Chen X, Pang S, Ma L, Wang X, Ren Y, Liu M, Liu F, Jiang M, Zhao J, Lu C, Lu Z, Gao D, Jiang Z, Pei J. Assessing the decision quality of artificial intelligence and oncologists of different experience in different regions in breast cancer treatment. Front Oncol 2023; 13:1152013. [PMID: 37361565 PMCID: PMC10289408 DOI: 10.3389/fonc.2023.1152013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 04/26/2023] [Indexed: 06/28/2023] Open
Abstract
Background AI-based clinical decision support system (CDSS) has important prospects in overcoming the current informational challenges that cancer diseases faced, promoting the homogeneous development of standardized treatment among different geographical regions, and reforming the medical model. However, there are still a lack of relevant indicators to comprehensively assess its decision-making quality and clinical impact, which greatly limits the development of its clinical research and clinical application. This study aims to develop and application an assessment system that can comprehensively assess the decision-making quality and clinical impacts of physicians and CDSS. Methods Enrolled adjuvant treatment decision stage early breast cancer cases were randomly assigned to different decision-making physician panels (each panel consisted of three different seniority physicians in different grades hospitals), each physician made an independent "Initial Decision" and then reviewed the CDSS report online and made a "Final Decision". In addition, the CDSS and guideline expert groups independently review all cases and generate "CDSS Recommendations" and "Guideline Recommendations" respectively. Based on the design framework, a multi-level multi-indicator system including "Decision Concordance", "Calibrated Concordance", " Decision Concordance with High-level Physician", "Consensus Rate", "Decision Stability", "Guideline Conformity", and "Calibrated Conformity" were constructed. Results 531 cases containing 2124 decision points were enrolled; 27 different seniority physicians from 10 different grades hospitals have generated 6372 decision opinions before and after referring to the "CDSS Recommendations" report respectively. Overall, the calibrated decision concordance was significantly higher for CDSS and provincial-senior physicians (80.9%) than other physicians. At the same time, CDSS has a higher " decision concordance with high-level physician" (76.3%-91.5%) than all physicians. The CDSS had significantly higher guideline conformity than all decision-making physicians and less internal variation, with an overall guideline conformity variance of 17.5% (97.5% vs. 80.0%), a standard deviation variance of 6.6% (1.3% vs. 7.9%), and a mean difference variance of 7.8% (1.5% vs. 9.3%). In addition, provincial-middle seniority physicians had the highest decision stability (54.5%). The overall consensus rate among physicians was 64.2%. Conclusions There are significant internal variation in the standardization treatment level of different seniority physicians in different geographical regions in the adjuvant treatment of early breast cancer. CDSS has a higher standardization treatment level than all physicians and has the potential to provide immediate decision support to physicians and have a positive impact on standardizing physicians' treatment behaviors.
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Affiliation(s)
- Chunguang Han
- Department of Pediatric Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yubo Pan
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Breast Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Chang Liu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Breast Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiaowei Yang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Breast Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jianbin Li
- Department of Breast Cancer, Fifth Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Kun Wang
- Department of Breast Cancer, Cancer Center, Guangdong Provincial People's Hospital and Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhengkui Sun
- Department of Breast Oncology Surgery, Jiangxi Cancer Hospital (The Second People's Hospital of Jiangxi Province), Nanchang, China
| | - Hui Liu
- Department of Breast Surgery, Henan Provincial People's Hospital, Zhengzhou, China
| | - Gongsheng Jin
- Department of Oncological Surgery, the First Affiliated Hospital of Bengbu Medical College, Bengbu, China
| | - Fang Fang
- Department of Thyroid and Breast surgery, the First Affiliated Hospital of Wannan Medical College (Yijishan Hospital), Wuhhu, China
| | - Xiaofeng Pan
- Department of Thyroid and Breast surgery, the First Affiliated Hospital of Wannan Medical College (Yijishan Hospital), Wuhhu, China
| | - Tong Tang
- Department of General Surgury, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiao Chen
- Department of General Surgury, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Shiyong Pang
- Department of General Surgery, Lu'an People's Hospital of Anhui Province (Lu'an Hospital of Anhui Medical University), Lu'an, China
| | - Li Ma
- Department of Thyroid and Breast Surgery, Anqing Municipal Hospital (Anqing Hospital Affiliated to Anhui Medical University), Anqing, China
| | - Xiaodong Wang
- Department of Thyroid and Breast Surgery, The people's hospital of Bozhou (Bozhou Hospital Affiliated to Anhui Medical University), Bozhou, China
| | - Yun Ren
- Department of Thyroid and Breast surgery, Department of Oncological Surgery, Taihe county people's hospital (The Taihe hospital of Wannan Medical College), Fuyang, China
| | - Mengyou Liu
- Department of Thyroid and Breast surgery, Lixin County People's Hospital, Bozhou, China
| | - Feng Liu
- Department of Breast Surgery, Fuyang Cancer Hospital, Fuyang, China
| | - Mengxue Jiang
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jiqi Zhao
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Chenyang Lu
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zhengdong Lu
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Dongjing Gao
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zefei Jiang
- Department of Breast Cancer, Fifth Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Jing Pei
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Breast Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
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Andersen TI, Lensky YD, Kechedzhi K, Drozdov IK, Bengtsson A, Hong S, Morvan A, Mi X, Opremcak A, Acharya R, Allen R, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Babbush R, Bacon D, Bardin JC, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Chou C, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Del Toro Barba A, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Dau AG, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hilton J, Hoffmann MR, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lester BJ, Lill AT, Liu W, Locharla A, Lucero E, Malone FD, Martin O, McClean JR, McCourt T, McEwen M, Miao KC, Mieszala A, Mohseni M, Montazeri S, Mount E, Movassagh R, Mruczkiewicz W, Naaman O, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O’Brien TE, Omonije S, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Boixo S, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Kim EA, Aleiner I, Roushan P. Non-Abelian braiding of graph vertices in a superconducting processor. Nature 2023; 618:264-269. [PMID: 37169834 DOI: 10.1038/s41586-023-05954-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 03/14/2023] [Indexed: 06/09/2023]
Abstract
Indistinguishability of particles is a fundamental principle of quantum mechanics1. For all elementary and quasiparticles observed to date-including fermions, bosons and Abelian anyons-this principle guarantees that the braiding of identical particles leaves the system unchanged2,3. However, in two spatial dimensions, an intriguing possibility exists: braiding of non-Abelian anyons causes rotations in a space of topologically degenerate wavefunctions4-8. Hence, it can change the observables of the system without violating the principle of indistinguishability. Despite the well-developed mathematical description of non-Abelian anyons and numerous theoretical proposals9-22, the experimental observation of their exchange statistics has remained elusive for decades. Controllable many-body quantum states generated on quantum processors offer another path for exploring these fundamental phenomena. Whereas efforts on conventional solid-state platforms typically involve Hamiltonian dynamics of quasiparticles, superconducting quantum processors allow for directly manipulating the many-body wavefunction by means of unitary gates. Building on predictions that stabilizer codes can host projective non-Abelian Ising anyons9,10, we implement a generalized stabilizer code and unitary protocol23 to create and braid them. This allows us to experimentally verify the fusion rules of the anyons and braid them to realize their statistics. We then study the prospect of using the anyons for quantum computation and use braiding to create an entangled state of anyons encoding three logical qubits. Our work provides new insights about non-Abelian braiding and, through the future inclusion of error correction to achieve topological protection, could open a path towards fault-tolerant quantum computing.
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Li J, Zhou J, Wang H, Liu Z, Fan Z, Liu Y, Geng C, Xiao Y, Jiang Z. Trends in Disparities and Transitions of Treatment in Patients With Early Breast Cancer in China and the US, 2011 to 2021. JAMA Netw Open 2023; 6:e2321388. [PMID: 37389867 DOI: 10.1001/jamanetworkopen.2023.21388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/01/2023] Open
Abstract
Importance Breast cancer treatment has profoundly improved in China recently. However, trends in disparities and transitions of treatment in early-stage cancer between China and the US are not well known. Objective To identify changes for patients with early breast cancer by using large databases from China and the US. Design, Setting, and Participants This multicenter cross-sectional study used the Chinese Society of Clinical Oncology Breast Cancer (CSCO BC) database from hospitals in 13 provinces in China and the Flatiron Health (hereinafter referred to as Flatiron) database from more than 280 community oncology clinics in the US. Patients with stage I to III breast cancer diagnosed from January 1, 2011, to December 31, 2021, were included. Data were analyzed from June 10 to December 1, 2022. Main Outcomes and Measures The distribution of age, clinical stage, and cancer subtypes at diagnosis were examined overall and by year. The mean annual percent change (MAPC) from 2011 to 2021 in systemic therapy and surgery was also analyzed. Results A total of 57 720 patients with early breast cancer were screened from the CSCO BC (n = 45 970) and Flatiron (n = 11 750) databases. The median age at diagnosis in China among the 41 449 patients included in the age analysis was 47 (IQR, 40-56) years; in the US, the median age was 64 (IQR, 54-73) years. Among patients with clinical stage data in the CSCO BC (n = 22 794) and Flatiron (n = 4413) databases, the proportion of stage I cancer was 7250 (31.8%) vs 2409 (54.6%); stage II cancer, 10 043 (44.1%) vs 1481 (33.6%); and stage III cancer, 5501 (24.1%) vs 523 (11.9%). The proportion of hormone receptor-positive cancer in China was 69.8%, lower than that in the US (87.5%). For patients with ERBB2 (formerly HER2 or HER2/neu)-positive cancer, the proportion in China (30.2%) was higher than that in the US (15.6%). For neoadjuvant therapy, the annual rate increased from 247 of 1553 (15.9%) to 200 of 790 (25.3%) in China, with an MAPC of -4.4% (95% CI, -50.6% to 85.0%; P = .89). For patients with ERBB2-positive cancer, the proportion treated with trastuzumab in early-stage cancer in China increased significantly, with an MAPC of 22.1% (95% CI, 17.4%-26.9%; P < .001), and overtook that in the Flatiron database since 2017 (1684 [68.5%] vs 550 [62.5%]; P < .001). Conclusions and Relevance The findings of this cross-sectional study suggest that disparities in treatment of early breast cancer narrowed between China and the US during the study period. The rapid growth of trastuzumab treatment in China was suggestive of differential access to targeted ERBB2 therapy.
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Affiliation(s)
- Jianbin Li
- Senior Department of Oncology, The Fifth Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China
- Department of Medical Molecular Biology, Institute of Biotechnology, Academy of Military Medical Sciences, Beijing, China
| | - Jifang Zhou
- Department of Public Administration, China Pharmaceutical University, Jiangning Campus, Nanjing, China
| | - Haibo Wang
- Breast Cancer Center, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zhenzhen Liu
- Department of Breast Disease, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China
| | - Zhimin Fan
- Department of Breast Surgery, General Surgery Center, First Hospital of Jilin University, Changchun, China
| | - Yinhua Liu
- Department of Breast Surgery, Peking University First Hospital, Beijing, China
| | - Cuizhi Geng
- Breast Cancer Center, Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yue Xiao
- Department of Public Administration, China Pharmaceutical University, Jiangning Campus, Nanjing, China
| | - Zefei Jiang
- Senior Department of Oncology, The Fifth Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China
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30
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Zhou Y, Zhou J, Hao X, Shi H, Li X, Wang A, Hu Z, Yang Y, Jiang Z, Wang T. Efficacy relevance of PD-L1 expression on circulating tumor cells in metastatic breast cancer patients treated with anti-PD-1 immunotherapy. Breast Cancer Res Treat 2023:10.1007/s10549-023-06972-6. [PMID: 37227611 DOI: 10.1007/s10549-023-06972-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 05/03/2023] [Indexed: 05/26/2023]
Abstract
PURPOSE Breast cancer has become the leading cause of cancer mortality in women. Although immune checkpoint inhibitors targeting programmed death-1 (PD-1) are promising, it remains unclear whether PD-L1 expression on circulating tumor cells (CTCs) has predictive and prognostic values in predicting and stratifying metastatic breast cancer (MBC) patients who can benefit from anti-PD-1 immunotherapy. METHODS Twenty six MBC patients that received anti-PD-1 immunotherapy were enrolled in this study. The peptide-based Pep@MNPs method was used to isolate and enumerate CTCs from 2.0 ml of peripheral venous blood. The expression of PD-L1 on CTCs was evaluated by an established immunoscoring system categorizing into four classes (negative, low, medium, and high). RESULTS Our data showed that 92.3% (24/26) of patients had CTCs, 83.3% (20/26) of patients had PD-L1-positive CTCs, and 65.4% (17/26) of patients had PD-L1-high CTCs. We revealed that the clinical benefit rate (CBR) of patients with a cut-off value of ≥ 35% PD-L1-high CTCs (66.6%) was higher than the others (29.4%). We indicated that PD-L1 expression on CTCs from MBC patients treated with anti-PD-1 monotherapy was dynamic. We demonstrated that MBC patients with a cut-off value of ≥ 35% PD-L1-high CTCs had longer PFS (P = 0.033) and OS (P = 0.00058) compared with patients with a cut-off value of < 35% PD-L1-high CTCs. CONCLUSION Our findings suggested that PD-L1 expression on CTCs could predict the therapeutic response and clinical outcomes, providing a valuable predictive and prognostic biomarker for patients treated with anti-PD-1 immunotherapy.
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Affiliation(s)
- Ying Zhou
- Fujian Key Laboratory of Translational Research in Cancer and Neurodegenerative Diseases, Fujian Provincial Key Laboratory of Brain Aging and Neurodegenerative Diseases, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing, China
| | - Jinmei Zhou
- Breast Cancer Department, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiaopeng Hao
- Department of General Surgery, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Haoyuan Shi
- Fujian Key Laboratory of Translational Research in Cancer and Neurodegenerative Diseases, Fujian Provincial Key Laboratory of Brain Aging and Neurodegenerative Diseases, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing, China
| | - Xuejie Li
- Fujian Key Laboratory of Translational Research in Cancer and Neurodegenerative Diseases, Fujian Provincial Key Laboratory of Brain Aging and Neurodegenerative Diseases, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing, China
| | - Anqi Wang
- Fujian Key Laboratory of Translational Research in Cancer and Neurodegenerative Diseases, Fujian Provincial Key Laboratory of Brain Aging and Neurodegenerative Diseases, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing, China
| | - Zhiyuan Hu
- Fujian Key Laboratory of Translational Research in Cancer and Neurodegenerative Diseases, Fujian Provincial Key Laboratory of Brain Aging and Neurodegenerative Diseases, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing, China.
- School of Nanoscience and Technology, Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China.
- School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan, China.
| | - Yanlian Yang
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing, China.
- School of Nanoscience and Technology, Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China.
| | - Zefei Jiang
- Breast Cancer Department, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
| | - Tao Wang
- Breast Cancer Department, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
- Anhui Medical University, Hefei, China.
- Southern Medical University, Guangzhou, China.
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Liu L, Zhu M, Wang Y, Wan B, Jiang Z. [Molecular pathological mechanism of liver metabolic disorder in mice with severe spinal muscular atrophy]. Nan Fang Yi Ke Da Xue Xue Bao 2023; 43:852-858. [PMID: 37313828 DOI: 10.12122/j.issn.1673-4254.2023.05.22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
OBJECTIVE To explore the molecular pathological mechanism of liver metabolic disorder in severe spinal muscular atrophy (SMA). METHODS The transgenic mice with type Ⅰ SMA (Smn-/- SMN20tg/2tg) and littermate control mice (Smn+/- SMN20tg/2tg) were observed for milk suckling behavior and body weight changes after birth. The mice with type Ⅰ SMA mice were given an intraperitoneal injection of 20% glucose solution or saline (15 μL/12 h), and their survival time was recorded. GO enrichment analysis was performed using the RNA-Seq data of the liver of type Ⅰ SMA and littermate control mice, and the results were verified using quantitative real-time PCR. Bisulfite sequencing was performed to examine CpG island methylation level in Fasn gene promoter region in the liver of the neonatal mice. RESULTS The neonatal mice with type Ⅰ SMA showed normal milk suckling behavior but had lower body weight than the littermate control mice on the second day after birth. Intraperitoneal injection of glucose solution every 12 h significantly improved the median survival time of type Ⅰ SMA mice from 9±1.3 to 11± 1.5 days (P < 0.05). Analysis of the RNA-Seq data of the liver showed that the expression of the target genes of PPARα related to lipid metabolism and mitochondrial β oxidation were down-regulated in the liver of type Ⅰ SMA mice. Type Ⅰ SMA mice had higher methylation level of the Fasn promoter region in the liver than the littermate control mice (76.44% vs 58.67%). In primary cultures of hepatocytes from type Ⅰ SMA mice, treatment with 5-AzaC significantly up-regulated the expressions of the genes related to lipid metabolism by over 1 fold (P < 0.01). CONCLUSION Type Ⅰ SMA mice have liver metabolic disorder, and the down-regulation of the target genes of PPARα related to lipid and glucose metabolism due to persistent DNA methylation contributes to the progression of SMA.
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Affiliation(s)
- L Liu
- Suzhou Medical College of Soochow University, Suzhou 215000, China
| | - M Zhu
- Suzhou Medical College of Soochow University, Suzhou 215000, China
| | - Y Wang
- Suzhou Medical College of Soochow University, Suzhou 215000, China
| | - B Wan
- Suzhou Medical College of Soochow University, Suzhou 215000, China
| | - Z Jiang
- Suzhou Medical College of Soochow University, Suzhou 215000, China
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Li J, Yuan Y, Bian L, Lin Q, Yang H, Ma L, Xin L, Li F, Zhang S, Wang T, Liu Y, Jiang Z. A comparison between clinical decision support system and clinicians in breast cancer. Heliyon 2023; 9:e16059. [PMID: 37215843 PMCID: PMC10192819 DOI: 10.1016/j.heliyon.2023.e16059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 04/28/2023] [Accepted: 05/04/2023] [Indexed: 05/24/2023] Open
Abstract
Objective We are building a clinical decision support system (CSCO AI) for breast cancer patients to improve the efficiency of clinical decision-making. We aimed to assess cancer treatment regimens given by CSCO AI and different levels of clinicians. Methods 400 breast cancer patients were screened from the CSCO database. Clinicians with similar levels were randomly assigned one of the volumes (200 cases). CSCO AI was asked to assess all cases. Three reviewers were independently asked to evaluate the regimens from clinicians and CSCO AI. Regimens were masked before evaluation. The primary outcome was the proportion of high-level conformity (HLC). Results The overall concordance between clinicians and CSCO AI was 73.9% (3621/4900). It was 78.8% (2757/3500) in the early-stage, higher than that in the metastatic stage (61.7% [864/1400], p < 0.001). The concordance was 90.7% (635/700) and 56.4% (395/700) in adjuvant radiotherapy and second-line therapy respectively. HLC in CSCO AI was 95.8% (95%CI:94.0%-97.6%), significantly higher than that in clinicians (90.8%, 95%CI:89.8%-91.8%). Considering professions, the HLC of surgeons was 85.9%, lower than that of CSCO AI (OR = 0.25,95%CI: 0.16-0.41). The most significant difference in HLC was in first-line therapy (OR = 0.06, 95%CI:0.01-0.41). When clinicians were divided according to their levels, there was no statistical significance between CSCO AI and higher level clinicians. Conclusions Decision from CSCO AI for breast cancer was superior than most clinicians did except in second-line therapy. The improvements in process outcomes suggest that CSCO AI can be widely used in clinical practice.
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Affiliation(s)
- Jianbin Li
- Department of Oncology, The Fifth Medical Centre of Chinese PLA General Hospital, Beijing, China
- Department of Medical Molecular Biology, Beijing Institute of Biotechnology, Academy of Military Medical Sciences, Beijing
| | - Yang Yuan
- Department of Oncology, The Fifth Medical Centre of Chinese PLA General Hospital, Beijing, China
| | - Li Bian
- Department of Oncology, The Fifth Medical Centre of Chinese PLA General Hospital, Beijing, China
| | - Qiang Lin
- Department of Oncology, The Fifth Medical Centre of Chinese PLA General Hospital, Beijing, China
| | - Hua Yang
- Department of Oncology, Affiliated Hospital of Hebei University, Baoding, China
| | - Li Ma
- Department of General Surgery, Fourth Affiliated Hospital of Hebei Medical University, Shijiazhuang, China
| | - Ling Xin
- Department of Breast Surgery, Peking University First Hospital, Beijing, China
| | - Feng Li
- Department of Oncology, The Fifth Medical Centre of Chinese PLA General Hospital, Beijing, China
| | - Shaohua Zhang
- Department of Oncology, The Fifth Medical Centre of Chinese PLA General Hospital, Beijing, China
| | - Tao Wang
- Department of Oncology, The Fifth Medical Centre of Chinese PLA General Hospital, Beijing, China
| | - Yinhua Liu
- Department of Breast Surgery, Peking University First Hospital, Beijing, China
| | - Zefei Jiang
- Department of Oncology, The Fifth Medical Centre of Chinese PLA General Hospital, Beijing, China
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Shao ZM, Pang D, Yang H, Li W, Wang S, Cui S, Liao N, Wang YS, Wang C, Chang YC, Wang HC, Kang SY, Seo JH, Shen K, Laohawiriyakamol S, Jiang Z, Huang L, Wang H, Lamour F, Song G, Restuccia E. Abstract PD18-03: Final analysis of the Phase III PEONY trial: long-term efficacy and safety of neoadjuvant–adjuvant pertuzumab or placebo, plus trastuzumab and docetaxel, in patients with HER2-positive early or locally advanced breast cancer. Cancer Res 2023. [DOI: 10.1158/1538-7445.sabcs22-pd18-03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Abstract
BACKGROUND In the Phase II NeoSphere study (NCT00545688), dual HER2 blockade with pertuzumab (P) + trastuzumab (H), + docetaxel (D) significantly increased pathologic complete response (pCR) vs. H+D in the neoadjuvant setting for HER2-positive early breast cancer (EBC), locally advanced (LA) BC, or inflammatory BC, with supportive progression- and disease-free survival (DFS) data. Consistently, the randomized, multicenter, double-blind, placebo (Pla)-controlled Phase III PEONY trial (NCT02586025) significantly improved total pCR (tpCR; primary endpoint) with P+H+D vs. H+D in an Asian population, and safety data were in-line with the known P safety profile. We present the final analysis of long-term efficacy (at 3 and 5 years) and safety from the study.
METHODS Patients had centrally confirmed HER2-positive EBC (T2–3, N0–1) or LABC (T2–3, N2 or N3; T4, any N) and were randomized 2:1 to four neoadjuvant P+H+D or Pla+H+D cycles every 3 weeks. P: 840 mg loading/420 mg maintenance doses (or Pla); H: 8 mg/kg loading/6 mg/kg maintenance; D: 75 mg/m2. Patients then received three fluorouracil, epirubicin, and cyclophosphamide cycles, followed by 13 of P+H or Pla+H in the adjuvant setting for up to 1 year. Long-term outcomes (event-free survival [EFS], DFS, overall survival [OS]; all secondary endpoints) were assessed by Kaplan–Meier methods, Cox proportional hazards models, and a two-sided log-rank test (stratified by disease category and hormone receptor status).
RESULTS Data cut-off was Mar 14, 2022, and 329 patients were randomized; 219 to P; 110, to Pla. Safety populations were 218 and 110 patients, respectively. Baseline characteristics were well balanced. Most patients received the full HER2-targeted cycles. Median follow-up was 62.9 months. Long-term efficacy data are shown in the table.
During the overall treatment period, 70.6% of patients in the P+H+D arm and 68.2% in the Pla+H+D arm experienced grade ≥3 adverse events (AEs); the most common (in ≥5% of patients in either arm) being neutropenia (59.2% vs. 55.5%), leukopenia (34.4% vs. 34.5%), and febrile neutropenia (5.0% vs. 3.6%). Of the most common any-grade AEs (in ≥30% of patients in either arm), diarrhea was more common in the P+H+D arm (40.8% vs. 17.3% in the Pla+H+D arm). Serious AEs were reported in 17.0% and 13.6% of patients, respectively. No primary cardiac events (heart failure [New York Heart Association grade III or IV] or significant decline of left ventricular ejection fraction) or secondary cardiac events occurred during any study periods.
CONCLUSIONS Long-term efficacy endpoints (EFS, DFS, and OS) were supportive of the primary endpoint results (tpCR) and suggested a clinically meaningful improvement with P+H vs. Pla+H when administered before and after surgery for one year of anti-HER2- therapy. Safety data were in-line with the known P safety profile and generally comparable between arms, with the exception of diarrhea.
PEONY adds to the totality of data showing the benefit of the P+H+D regimen in HER2-positive EBC.
Table 1: Long-term efficacy data
Citation Format: Zhi-Ming Shao, Da Pang, Hongjian Yang, Wei Li, Shusen Wang, Shude Cui, Ning Liao, Yong-Sheng Wang, Chuan Wang, Yuan-Ching Chang, Hwei-Chung Wang, Seok Yun Kang, Jae Hong Seo, Kunwei Shen, Suphawat Laohawiriyakamol, Zefei Jiang, Liang Huang, Haiyan Wang, François Lamour, Grace Song, Eleonora Restuccia. Final analysis of the Phase III PEONY trial: long-term efficacy and safety of neoadjuvant–adjuvant pertuzumab or placebo, plus trastuzumab and docetaxel, in patients with HER2-positive early or locally advanced breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD18-03.
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Affiliation(s)
| | - Da Pang
- 2Harbin Medical University Cancer Hospital, Harbin, China
| | - Hongjian Yang
- 3Cancer Hospital of The University of Chinese Academy of Sciences, Hangzhou, China
| | - Wei Li
- 4The First Hospital of Jilin University, Changchun
| | - Shusen Wang
- 5Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Shude Cui
- 6Department of Breast Surgery, Affiliated Tumor Hospital of Zhengzhou University
| | - Ning Liao
- 7Department of Breast Cancer, Cancer Center, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yong-Sheng Wang
- 8Shandong Cancer Hospital & Institute, Jinan, Shandong, China, China (People’s Republic)
| | | | | | | | - Seok Yun Kang
- 12Department of Hematology–Oncology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Jae Hong Seo
- 13Division of Oncology/Hematology, Department of Internal Medicine, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Kunwei Shen
- 14Breast Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Zefei Jiang
- 16Medicine–Oncology, The Affiliated Hospital of Military Medical Sciences (The 307th Hospital of Chinese People’s Liberation Army), Beijing, China
| | | | - Haiyan Wang
- 18Roche Product Development, Shanghai, People’s Republic of China
| | - François Lamour
- 19F. Hoffmann-La Roche Ltd, Basel, Switzerland. Current affiliation: Alentis Therapeutics, Basel, Switzerland
| | - Grace Song
- 20Biometrics, Hangzhou Tigermed Consulting Co., Ltd., Shanghai, China
| | - Eleonora Restuccia
- 21Product Development Oncology - F. Hoffmann-La Roche Ltd, Basel, Switzerland
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Zhou Y, Zhou J, Shi H, Hu Z, Yang Y, Jiang Z, Wang T. Abstract P5-02-12: Prognostic relevance of PD-L1 expression on circulating tumor cells in metastatic breast cancer patients treated with anti-PD-1 immunotherapy. Cancer Res 2023. [DOI: 10.1158/1538-7445.sabcs22-p5-02-12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Abstract
Rationale: Breast cancer has become the leading cause of cancer mortality in women. Although immune checkpoint inhibitors targeting programmed death-1 (PD-1) are promising, it remains unclear whether PD-L1 expression on circulating tumor cells (CTCs) has predictive and prognostic values in predict and stratify metastatic breast cancer (MBC) patients who can benefit from anti-PD-1 immunotherapy. Methods: Twenty six MBC patients that received anti-PD-1 immunotherapy were enrolled in this study. The peptide-based Pep@MNPs method was used to isolate and enumerate CTCs from 2.0 ml of peripheral venous blood. The expression of PD-L1 on CTCs was evaluated by an established immunoscoring system categorizing into four classes (negative, low, medium, and high). Results: Our data showed that 92.3% (24/26) of patients had CTCs, 83.3% (20/26) of patients had PD-L1-positive CTCs, and 65.4% (17/26) of patients had PD-L1-high CTCs. We revealed that the clinical benefit rate (CBR) of patients with a cut-off value of ≥ 35% PD-L1-high CTCs (66.6%) was higher than the others (29.4%). We indicated that PD-L1 expression on CTCs from MBC patients treated with anti-PD-1 monotherapy was dynamic. We demonstrated that MBC patients with a cut-off value of ≥ 35% PD-L1-high CTCs had longer PFS (P< 0.05) and OS (P< 0.01) compared with patients with a cut-off value of < 35% PD-L1-high CTCs. Conclusion: Our findings suggested that PD-L1 expression on CTCs could predict the therapeutic response and clinical outcomes, providing a valuable predictive and prognostic biomarker for patients treated with anti-PD-1 immunotherapy.
Citation Format: Ying Zhou, Jinmei Zhou, Haoyuan Shi, Zhiyuan Hu, Yanlian Yang, Zefei Jiang, Tao Wang. Prognostic relevance of PD-L1 expression on circulating tumor cells in metastatic breast cancer patients treated with anti-PD-1 immunotherapy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-02-12.
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Affiliation(s)
- Ying Zhou
- 1Fujian Medical University, National Center for Nanoscience and Technology of China
| | - Jinmei Zhou
- 2The Fifth Medical Center of PLA General Hospital
| | - Haoyuan Shi
- 3Fujian Medical University, National Center for Nanoscience and Technology of China
| | - Zhiyuan Hu
- 4Fujian Medical University, National Center for Nanoscience and Technology of China, University of Chinese Academy of Sciences, Wuhan Institute of Technology
| | - Yanlian Yang
- 5National Center for Nanoscience and Technology of China, University of Chinese Academy of Sciences
| | - Zefei Jiang
- 6The Fifth Medical Center of PLA General Hospital
| | - Tao Wang
- 7The Fifth Medical Center of PLA General Hospital
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Zhan K, Zhang X, Wang B, Jiang Z, Fang X, Yang S, Jia H, Li L, Cao G, Zhang K, Ma X. Response to: COVID-19 and diabetes-double whammy. QJM 2023; 116:144-145. [PMID: 35178559 DOI: 10.1093/qjmed/hcac048] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 02/10/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- K Zhan
- College of Public Health, Southwest Medical University, Luzhou, Sichuan, China
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing, China
| | - X Zhang
- Department of General Surgery, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - B Wang
- Pulmonary and Critical Care Medicine Center, Chinese PLA Respiratory Disease Institute, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Z Jiang
- Yidu Cloud Technology Co. Ltd, Beijing, China
| | - X Fang
- College of Public Health, Southwest Medical University, Luzhou, Sichuan, China
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing, China
| | - S Yang
- Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - H Jia
- College of Public Health, Southwest Medical University, Luzhou, Sichuan, China
| | - L Li
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - G Cao
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - K Zhang
- Department of Outpatients, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - X Ma
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing, China
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Zhan K, Zhang X, Wang B, Jiang Z, Fang X, Yang S, Jia H, Li L, Cao G, Zhang K, Ma X. Response to: Glycemic control and COVID-19 outcomes: the missing metabolic players. QJM 2023; 116:91-92. [PMID: 35166838 PMCID: PMC9383446 DOI: 10.1093/qjmed/hcac044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 02/07/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- K Zhan
- From the College of Public Health, Southwest Medical University, Xianglin street 1, Luzhou, Sichuan 646000, China
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - X Zhang
- Department of General Surgery, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - B Wang
- Pulmonary and Critical Care Medicine Center, Chinese PLA Respiratory Disease Institute, Xinqiao Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - Z Jiang
- Yidu Cloud Technology Co. Ltd, North Huayuan Road 35, Beijing 100071, China
| | - X Fang
- From the College of Public Health, Southwest Medical University, Xianglin street 1, Luzhou, Sichuan 646000, China
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - S Yang
- Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - H Jia
- From the College of Public Health, Southwest Medical University, Xianglin street 1, Luzhou, Sichuan 646000, China
| | - L Li
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - G Cao
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - K Zhang
- Department of Outpatients, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - X Ma
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
- Address correspondence to X. Ma, Department of General Surgery, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China. ,
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Xu B, Li H, Jiang Z, Gu L, Tang J, Xie H, Pan Y, Liu Y, Cui S, Wang X, Cai L, Zhang Y, Zhao H, Shao Z, Shao Z. Adjuvant tamoxifen switched to exemestane treatment in postmenopausal women with estrogen receptor-positive early breast cancer: A pragmatic, multicenter, and prospective clinical trial in China. Chin J Cancer Res 2022; 34:592-600. [PMID: 36714346 PMCID: PMC9829502 DOI: 10.21147/j.issn.1000-9604.2022.06.07] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 11/18/2022] [Indexed: 01/12/2023] Open
Abstract
Objective This post-approval safety study assessed the efficacy and safety of exemestane after 2-3 years of tamoxifen treatment among postmenopausal women with estrogen receptor-positive (ER+) early breast cancer in China. Methods Enrolled patients had received 2-3 years of tamoxifen and were then switched to exemestane for completion of 5 consecutive years of adjuvant endocrine therapy. The primary endpoint was the time from enrollment to the first occurrence of locoregional/distant recurrence of the primary breast cancer, appearance of a second primary or contralateral breast cancer, or death due to any cause. Other endpoints included the proportion of patients experiencing each event, incidence rate per annum, relationships between human epidermal growth factor receptor 2 status and time to event, and relationship between disease history variables and time to event. Results Overall, 558 patients were included in the full analysis set: 397 (71.1%) completed the study, 20 experienced an event, and 141 discontinued [47 owing to an adverse event (AE); 37 no longer willing to participate]. Median duration of treatment was 29.5 (range, 0.1-57.7) months. Median time to event was not reached. Event-free survival probability at 36 months was 91.4% (95% CI, 87.7%-95.1%). The event incidence over the total exposure time of exemestane therapy was 3.5 events/100 person-years (20/565). Multivariate analysis showed an association between tumor, lymph node, and metastasis stage at initial diagnosis and time to event [hazard ratio: 1.532 (95% CI, 1.129-2.080); P=0.006]. Most AEs were grade 1 or 2 in severity, with arthralgia (7.7%) being the most common treatment-related AE. Conclusions This study supports the efficacy and safety of exemestane in postmenopausal Chinese women with ER+ breast cancer previously treated with adjuvant tamoxifen for 2-3 years. No new safety signals were identified in the Chinese population.
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Affiliation(s)
- Binghe Xu
- Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Huiping Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Breast Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Zefei Jiang
- Department of Breast Cancer, the Fifth Medical Center of Chinese PLA General Hospital, Beijing 100071, China
| | - Lin Gu
- Department of Breast Cancer, Tianjin Cancer Institute and Hospital, Tianjin 300060, China
| | - Jinhai Tang
- Department of Breast Cancer, Jiangsu Provincial Hospital, Nanjing 210029, China
| | - Hui Xie
- Department of Breast Cancer, Jiangsu Provincial Hospital, Nanjing 210029, China
| | - Yueyin Pan
- Department of Breast Cancer, the First Affiliated Hospital of China University of Science and Technology, Hefei 230001, China
| | - Yunjiang Liu
- Department of Breast Cancer, the Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China
| | - Shude Cui
- Department of Breast Cancer, Henan Cancer Hospital, Zhengzhou 450008, China
| | - Xiaojia Wang
- Department of Breast Cancer, Zhejiang Cancer Hospital, Hangzhou 310012, China
| | - Li Cai
- Department of Breast Cancer, Harbin Medical University Cancer Hospital, Harbin 150081, China
| | - Yiqiong Zhang
- Department of Clinical Development, Pfizer (China) R&D Co. Ltd, Shanghai 201203, China
| | - Huadong Zhao
- Department of Statistics, Pfizer (China) R&D Co. Ltd, Shanghai 201203, China
| | - Zhimin Shao
- Department of Breast Surgery, Shanghai Cancer Center/Cancer Institute, Shanghai Medical College, Fudan University, Shanghai 200032, China,Zhimin Shao. Department of Breast Surgery, Shanghai Cancer Center/Cancer Institute, Shanghai Medical College, Fudan University, Shanghai 200032, China.
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Wu J, Jiang Z, Liu Z, Yang B, Yang H, Tang J, Wang K, Liu Y, Wang H, Fu P, Zhang S, Liu Q, Wang S, Huang J, Wang C, Wang S, Wang Y, Zhen L, Zhu X, Wu F, Lin X, Zou J. Neoadjuvant pyrotinib, trastuzumab, and docetaxel for HER2-positive breast cancer (PHEDRA): a double-blind, randomized phase 3 trial. BMC Med 2022; 20:498. [PMID: 36575513 PMCID: PMC9795751 DOI: 10.1186/s12916-022-02708-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 12/12/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Pyrotinib (an irreversible pan-ErbB inhibitor) plus capecitabine has survival benefits and acceptable tolerability in patients with HER2-positive metastatic breast cancer. We further assessed addition of pyrotinib to trastuzumab and docetaxel in the neoadjuvant setting. METHODS In this multicenter, double-blind, phase 3 study (PHEDRA), treatment-naive women with HER2-positive early or locally advanced breast cancer were randomly assigned (1:1) to receive four neoadjuvant cycles of oral pyrotinib or placebo (400 mg) once daily, plus intravenous trastuzumab (8 mg/kg loading dose, followed by 6 mg/kg) and docetaxel (100 mg/m2) every 3 weeks. The primary endpoint was the total pathological complete response (tpCR; ypT0/is and ypN0) rate per independent central review. RESULTS Between Jul 23, 2018, and Jan 8, 2021, 355 patients were randomly assigned, 178 to the pyrotinib group and 177 to the placebo group. The majority of patients completed four cycles of neoadjuvant treatment as planned (92.7% and 97.7% in the pyrotinib and placebo groups, respectively). The tpCR rate was 41.0% (95% CI 34.0 to 48.4) in the pyrotinib group compared with 22.0% (95% CI 16.6 to 28.7) in the placebo group (difference, 19.0% [95% CI 9.5 to 28.4]; one-sided P < 0.0001). The objective response rate per investigator was 91.6% (95% CI 86.6 to 94.8) in the pyrotinib group and 81.9% (95% CI 75.6 to 86.9) in the placebo group after the neoadjuvant treatment, resulting in an increase of 9.7% (95% CI 2.7 to 16.6). The most common grade 3 or worse adverse events were diarrhea (79 [44.4%] in the pyrotinib group and nine [5.1%] in the placebo group), neutropenia (33 [18.5%] and 36 [20.3%]), and decreased white blood cell count (29 [16.3%] and 24 [13.6%]). No deaths were reported during neoadjuvant treatment. CONCLUSIONS The primary endpoint of the study was met. Neoadjuvant pyrotinib, trastuzumab, and docetaxel significantly improved the tpCR rate compared with placebo, trastuzumab, and docetaxel, with manageable toxicity, providing a new option for HER2-positive early or locally advanced breast cancer. TRIAL REGISTRATION ClinicalTrials.gov, NCT03588091.
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Affiliation(s)
- Jiong Wu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, No.270, Dong'an Road, Xuhui District, Shanghai, 200032, China.
| | - Zefei Jiang
- Department of Medical Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Zhenzhen Liu
- Department of Breast Disease, Henan Breast Cancer Center, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Benlong Yang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, No.270, Dong'an Road, Xuhui District, Shanghai, 200032, China
| | - Hongjian Yang
- Breast Surgery, Zhejiang Cancer Hospital, Hangzhou, China
| | - Jinhai Tang
- Breast Surgery, Jiangsu Province Hospital, Nanjing, China
| | - Kun Wang
- Department of Breast Cancer, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yunjiang Liu
- Breast Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Haibo Wang
- Breast Disease Center, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Peifen Fu
- Breast Surgery, The First Affiliated Hospital Zhejiang University, Hangzhou, China
| | - Shuqun Zhang
- Oncology Department, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Qiang Liu
- Department of Breast Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Shusen Wang
- Internal Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Jian Huang
- Breast Surgery, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Chuan Wang
- Department of Breast Surgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Shu Wang
- Department of Breast Surgery, Peking University People's Hospital, Beijing, China
| | - Yongsheng Wang
- Department of Breast, Shandong Cancer Hospital, Jinan, China
| | - Linlin Zhen
- Department of Thyroid and Breast Surgery, The Affiliated Huai'an No.1 People's Hospital of Nanjing Medical University, Huai'an, China
| | - Xiaoyu Zhu
- Clinical Research & Development, Jiangsu Hengrui Pharmaceuticals Co., Ltd, Shanghai, China
| | - Fei Wu
- Clinical Research & Development, Jiangsu Hengrui Pharmaceuticals Co., Ltd, Shanghai, China
| | - Xiang Lin
- Clinical Research & Development, Jiangsu Hengrui Pharmaceuticals Co., Ltd, Shanghai, China
| | - Jianjun Zou
- Clinical Research & Development, Jiangsu Hengrui Pharmaceuticals Co., Ltd, Shanghai, China
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39
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Wang LL, Hong H, Zhang YR, Shi HB, Chen L, Jiang HB, Jiang Z, Wu Z. [Cost-effectiveness prediction of AIDS interventions among men who have sex with men in Ningbo]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:2008-2014. [PMID: 36572477 DOI: 10.3760/cma.j.cn112338-20220410-00275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Objective: To provide information reference for resource allocation and decision-making in related fields, the cost-effectiveness of HIV input among men who have sex with men (MSM) in Ningbo. Different intervention coverages were compared. Methods: Taking MSM as the target population, data were collected and modeled by Optima HIV for the corresponding HIV health output and the budget under different intervention coverages. Results: According to the estimated size of the MSM population, which was 19 584 in Ningbo in 2020, if the coverage of 2020 baseline intervention is maintained in the next ten years, the number of HIV cases, new HIV infections, and HIV-related deaths among this population will show an upward trend. It is estimated that from 2021 to 2030, 7.9% of new infections and 1.7% of deaths can be avoided and the relevant funding investment comed to 2.4 time the baseline if the intervention coverage rate expanded to 3.0 times the 2020 baseline. After the coverage rate of intervention expanded to 3 times the baseline, it continued to grow, the health effect did not increase. Conclusions: At present, expanding the baseline coverage of HIV-related intervention projects among MSM in Ningbo and increasing capital investment will still reverse HIV-related death and reduce new infections. Moreover, there is a saturation point of the intervention effect. Researchers and policymakers must explore more effective interventions/combinations to obtain more significant health outcomes.
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Affiliation(s)
- L L Wang
- School of Health Management, Anhui Medical University, Hefei 230032, China
| | - H Hong
- Ningbo municipal Center for Disease Control and Prevention, Ningbo 315010, China
| | - Y R Zhang
- School of Health Management, Anhui Medical University, Hefei 230032, China
| | - H B Shi
- Ningbo municipal Center for Disease Control and Prevention, Ningbo 315010, China
| | - L Chen
- Department of HIV/AIDS and STDS Control and Prevention, Zhejiang Center for Disease Control and Prevention, Hangzhou 310000, China
| | - H B Jiang
- Ningbo municipal Center for Disease Control and Prevention, Ningbo 315010, China
| | - Z Jiang
- Division of Health Education and Behavioral Intervention, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Zunyou Wu
- Division of Health Education and Behavioral Intervention, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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40
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Pinzón-Arteaga C, Wang Y, Wei Y, Scatolin G, Liu L, Yu L, Jiang Z, Wu J. 234 Bovine blastocyst-like structures derived from pluripotent stem cell cultures. Reprod Fertil Dev 2022. [DOI: 10.1071/rdv35n2ab234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/09/2022] Open
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41
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Scatolin G, Wang Y, Zhu L, Gutierrez-Castillo E, Jiang Z. 92 A single cell atlas of bovine peri-implantation embryo development. Reprod Fertil Dev 2022. [DOI: 10.1071/rdv35n2ab92] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
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42
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Morvan A, Andersen TI, Mi X, Neill C, Petukhov A, Kechedzhi K, Abanin DA, Michailidis A, Acharya R, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Basso J, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Del Toro Barba A, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Flores Burgos L, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Grajales Dau A, Gross JA, Habegger S, Hamilton MC, Harrigan MP, Harrington SD, Hoffmann M, Hong S, Huang T, Huff A, Huggins WJ, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev AY, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lester BJ, Lill AT, Liu W, Locharla A, Malone F, Martin O, McClean JR, McEwen M, Meurer Costa B, Miao KC, Mohseni M, Montazeri S, Mount E, Mruczkiewicz W, Naaman O, Neeley M, Nersisyan A, Newman M, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Olenewa R, Opremcak A, Potter R, Quintana C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shvarts V, Skruzny J, Smith WC, Strain D, Sterling G, Su Y, Szalay M, Torres A, Vidal G, Villalonga B, Vollgraff-Heidweiller C, White T, Xing C, Yao Z, Yeh P, Yoo J, Zalcman A, Zhang Y, Zhu N, Neven H, Bacon D, Hilton J, Lucero E, Babbush R, Boixo S, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Aleiner I, Ioffe LB, Roushan P. Formation of robust bound states of interacting microwave photons. Nature 2022; 612:240-245. [PMID: 36477133 PMCID: PMC9729104 DOI: 10.1038/s41586-022-05348-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/14/2022] [Indexed: 12/12/2022]
Abstract
Systems of correlated particles appear in many fields of modern science and represent some of the most intractable computational problems in nature. The computational challenge in these systems arises when interactions become comparable to other energy scales, which makes the state of each particle depend on all other particles1. The lack of general solutions for the three-body problem and acceptable theory for strongly correlated electrons shows that our understanding of correlated systems fades when the particle number or the interaction strength increases. One of the hallmarks of interacting systems is the formation of multiparticle bound states2-9. Here we develop a high-fidelity parameterizable fSim gate and implement the periodic quantum circuit of the spin-½ XXZ model in a ring of 24 superconducting qubits. We study the propagation of these excitations and observe their bound nature for up to five photons. We devise a phase-sensitive method for constructing the few-body spectrum of the bound states and extract their pseudo-charge by introducing a synthetic flux. By introducing interactions between the ring and additional qubits, we observe an unexpected resilience of the bound states to integrability breaking. This finding goes against the idea that bound states in non-integrable systems are unstable when their energies overlap with the continuum spectrum. Our work provides experimental evidence for bound states of interacting photons and discovers their stability beyond the integrability limit.
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Affiliation(s)
- A Morvan
- Google Research, Mountain View, CA, USA
| | | | - X Mi
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - A Michailidis
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - R Acharya
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - J Basso
- Google Research, Mountain View, CA, USA
| | | | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | - D Eppens
- Google Research, Mountain View, CA, USA
| | | | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | | | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- Centre for Quantum Computation and Communication Technology, Centre for Quantum Software and Information, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, New South Wales, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Y Kitaev
- Google Research, Mountain View, CA, USA
- Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA
| | | | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | - F Malone
- Google Research, Mountain View, CA, USA
| | - O Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
- Department of Physics, University of California, Santa Barbara, CA, USA
| | | | - K C Miao
- Google Research, Mountain View, CA, USA
| | - M Mohseni
- Google Research, Mountain View, CA, USA
| | | | - E Mount
- Google Research, Mountain View, CA, USA
| | | | - O Naaman
- Google Research, Mountain View, CA, USA
| | - M Neeley
- Google Research, Mountain View, CA, USA
| | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | - R Olenewa
- Google Research, Mountain View, CA, USA
| | | | - R Potter
- Google Research, Mountain View, CA, USA
| | | | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | - W C Smith
- Google Research, Mountain View, CA, USA
| | - D Strain
- Google Research, Mountain View, CA, USA
| | | | - Y Su
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | - Z Yao
- Google Research, Mountain View, CA, USA
| | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | | | - I Aleiner
- Google Research, Mountain View, CA, USA.
| | - L B Ioffe
- Google Research, Mountain View, CA, USA.
| | - P Roushan
- Google Research, Mountain View, CA, USA.
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43
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Mi X, Sonner M, Niu MY, Lee KW, Foxen B, Acharya R, Aleiner I, Andersen TI, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Basso J, Bengtsson A, Bortoli G, Bourassa A, Brill L, Broughton M, Buckley BB, Buell DA, Burkett B, Bushnell N, Chen Z, Chiaro B, Collins R, Conner P, Courtney W, Crook AL, Debroy DM, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Flores L, Forati E, Fowler AG, Giang W, Gidney C, Gilboa D, Giustina M, Dau AG, Gross JA, Habegger S, Harrigan MP, Hoffmann M, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Kafri D, Kechedzhi K, Khattar T, Kim S, Kitaev AY, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Lee J, Laws L, Liu W, Locharla A, Martin O, McClean JR, McEwen M, Meurer Costa B, Miao KC, Mohseni M, Montazeri S, Morvan A, Mount E, Mruczkiewicz W, Naaman O, Neeley M, Neill C, Newman M, O’Brien TE, Opremcak A, Petukhov A, Potter R, Quintana C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schuster C, Shearn MJ, Shvarts V, Strain D, Su Y, Szalay M, Vidal G, Villalonga B, Vollgraff-Heidweiller C, White T, Yao Z, Yeh P, Yoo J, Zalcman A, Zhang Y, Zhu N, Neven H, Bacon D, Hilton J, Lucero E, Babbush R, Boixo S, Megrant A, Chen Y, Kelly J, Smelyanskiy V, Abanin DA, Roushan P. Noise-resilient edge modes on a chain of superconducting qubits. Science 2022; 378:785-790. [DOI: 10.1126/science.abq5769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Inherent symmetry of a quantum system may protect its otherwise fragile states. Leveraging such protection requires testing its robustness against uncontrolled environmental interactions. Using 47 superconducting qubits, we implement the one-dimensional kicked Ising model, which exhibits nonlocal Majorana edge modes (MEMs) with
ℤ
2
parity symmetry. We find that any multiqubit Pauli operator overlapping with the MEMs exhibits a uniform late-time decay rate comparable to single-qubit relaxation rates, irrespective of its size or composition. This characteristic allows us to accurately reconstruct the exponentially localized spatial profiles of the MEMs. Furthermore, the MEMs are found to be resilient against certain symmetry-breaking noise owing to a prethermalization mechanism. Our work elucidates the complex interplay between noise and symmetry-protected edge modes in a solid-state environment.
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Affiliation(s)
- X. Mi
- Google Research, Mountain View, CA, USA
| | - M. Sonner
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - M. Y. Niu
- Google Research, Mountain View, CA, USA
| | - K. W. Lee
- Google Research, Mountain View, CA, USA
| | - B. Foxen
- Google Research, Mountain View, CA, USA
| | | | | | | | - F. Arute
- Google Research, Mountain View, CA, USA
| | - K. Arya
- Google Research, Mountain View, CA, USA
| | - A. Asfaw
- Google Research, Mountain View, CA, USA
| | | | - J. C. Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - J. Basso
- Google Research, Mountain View, CA, USA
| | | | | | | | - L. Brill
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - Z. Chen
- Google Research, Mountain View, CA, USA
| | - B. Chiaro
- Google Research, Mountain View, CA, USA
| | | | - P. Conner
- Google Research, Mountain View, CA, USA
| | | | | | | | - S. Demura
- Google Research, Mountain View, CA, USA
| | | | - D. Eppens
- Google Research, Mountain View, CA, USA
| | | | - L. Faoro
- Google Research, Mountain View, CA, USA
| | - E. Farhi
- Google Research, Mountain View, CA, USA
| | - R. Fatemi
- Google Research, Mountain View, CA, USA
| | - L. Flores
- Google Research, Mountain View, CA, USA
| | - E. Forati
- Google Research, Mountain View, CA, USA
| | | | - W. Giang
- Google Research, Mountain View, CA, USA
| | - C. Gidney
- Google Research, Mountain View, CA, USA
| | - D. Gilboa
- Google Research, Mountain View, CA, USA
| | | | - A. G. Dau
- Google Research, Mountain View, CA, USA
| | | | | | | | | | - S. Hong
- Google Research, Mountain View, CA, USA
| | - T. Huang
- Google Research, Mountain View, CA, USA
| | - A. Huff
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - Z. Jiang
- Google Research, Mountain View, CA, USA
| | - C. Jones
- Google Research, Mountain View, CA, USA
| | - D. Kafri
- Google Research, Mountain View, CA, USA
| | | | | | - S. Kim
- Google Research, Mountain View, CA, USA
| | - A. Y. Kitaev
- Google Research, Mountain View, CA, USA
- Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA
| | | | | | - A. N. Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P. Laptev
- Google Research, Mountain View, CA, USA
| | - K.-M. Lau
- Google Research, Mountain View, CA, USA
| | - J. Lee
- Google Research, Mountain View, CA, USA
| | - L. Laws
- Google Research, Mountain View, CA, USA
| | - W. Liu
- Google Research, Mountain View, CA, USA
| | | | - O. Martin
- Google Research, Mountain View, CA, USA
| | | | - M. McEwen
- Google Research, Mountain View, CA, USA
- Department of Physics, University of California, Santa Barbara, CA, USA
| | | | | | | | | | - A. Morvan
- Google Research, Mountain View, CA, USA
| | - E. Mount
- Google Research, Mountain View, CA, USA
| | | | - O. Naaman
- Google Research, Mountain View, CA, USA
| | - M. Neeley
- Google Research, Mountain View, CA, USA
| | - C. Neill
- Google Research, Mountain View, CA, USA
| | - M. Newman
- Google Research, Mountain View, CA, USA
| | | | | | | | - R. Potter
- Google Research, Mountain View, CA, USA
| | | | | | - N. Saei
- Google Research, Mountain View, CA, USA
| | - D. Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - D. Strain
- Google Research, Mountain View, CA, USA
| | - Y. Su
- Google Research, Mountain View, CA, USA
| | - M. Szalay
- Google Research, Mountain View, CA, USA
| | - G. Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T. White
- Google Research, Mountain View, CA, USA
| | - Z. Yao
- Google Research, Mountain View, CA, USA
| | - P. Yeh
- Google Research, Mountain View, CA, USA
| | - J. Yoo
- Google Research, Mountain View, CA, USA
| | | | - Y. Zhang
- Google Research, Mountain View, CA, USA
| | - N. Zhu
- Google Research, Mountain View, CA, USA
| | - H. Neven
- Google Research, Mountain View, CA, USA
| | - D. Bacon
- Google Research, Mountain View, CA, USA
| | - J. Hilton
- Google Research, Mountain View, CA, USA
| | - E. Lucero
- Google Research, Mountain View, CA, USA
| | | | - S. Boixo
- Google Research, Mountain View, CA, USA
| | | | - Y. Chen
- Google Research, Mountain View, CA, USA
| | - J. Kelly
- Google Research, Mountain View, CA, USA
| | | | - D. A. Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
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44
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Toi M, Boyle F, Im YH, Reinisch M, Molthrop D, Jiang Z, Wei R, Sapunar F, Grimes BR, Nabinger SC, Johnston SRD. Adjuvant Abemaciclib Combined with Endocrine Therapy: Efficacy Results in monarchE Cohort 1. Oncologist 2022; 28:e77-e81. [PMID: 36342342 PMCID: PMC9847542 DOI: 10.1093/oncolo/oyac234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 09/29/2022] [Indexed: 11/09/2022] Open
Abstract
The monarchE Cohort 1 patient population was enrolled based on high-risk clinicopathological features that can easily be identified as part of routine clinical breast cancer evaluation. Efficacy data from Cohort 1 demonstrate substantial evidence of benefit for adjuvant abemaciclib+ET in patients with HR+, HER2- early breast cancer at high risk of recurrence (ClinicalTrials.gov: NCT03155997 [monarchE]).
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Affiliation(s)
- Masakazu Toi
- Corresponding author: Masakazu Toi, PhD, Breast Cancer Unit, Kyoto University Hospital, Breast Surgery, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaracho, Sakyo-ku, Kyoto 606-8507, Japan; Tel: +81 75 751 3660; Fax: +81 75 751 3616; E-mail:
| | - Frances Boyle
- Patricia Ritchie Centre for Cancer Care and Research, Mater Hospital, Sydney, Australia,University of Sydney, Sydney, Australia
| | - Young-Hyuck Im
- Division of Hematology/Medical Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | | | - David Molthrop
- Hematology and Oncology, Florida Cancer Specialists & Research Institute, Orlando, FL, USA
| | - Zefei Jiang
- Department of Breast Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China
| | - Ran Wei
- Lilly Corporate Center, Eli Lilly and Company, Indianapolis, IN, USA
| | - Francisco Sapunar
- Lilly Corporate Center, Eli Lilly and Company, Indianapolis, IN, USA
| | - Brenda R Grimes
- Lilly Corporate Center, Eli Lilly and Company, Indianapolis, IN, USA
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Yue JL, Jiang Z, Sun RJ, Fu B, Zhang HD, Pan XL, Liu DY. [Giant esophageal tumor presenting as pharyngeal mass: a report of three cases]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2022; 57:1341-1343. [PMID: 36404662 DOI: 10.3760/cma.j.cn115330-20220321-00124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Affiliation(s)
- J L Yue
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
| | - Z Jiang
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
| | - R J Sun
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China
| | - B Fu
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
| | - H D Zhang
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China
| | - X L Pan
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
| | - D Y Liu
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
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Zhou J, Wu X, Zhang H, Wang X, Yuan Y, Zhang S, Jiang Z, Wang T. Clinical outcomes of tucidinostat-based therapy after prior CDK4/6 inhibitor progression in hormone receptor-positive heavily pretreated metastatic breast cancer. Breast 2022; 66:255-261. [PMID: 36375386 PMCID: PMC9661714 DOI: 10.1016/j.breast.2022.10.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/31/2022] [Accepted: 10/31/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND CDK4/6 inhibitors combined with endocrine therapy are standard first- or second-line treatment for patients with HR-positive and HER2-negative advanced breast cancer, however, there is currently no optimal recommendation for therapeutic strategies after progression on CDK4/6i. The aim of this study is to analyze the efficacy and safety of HDAC inhibitor Tucidinostat combined with endocrine therapy in patients after prior CDK4/6 inhibitor progression. METHODS The pathological and clinical data of 44 HR-positive and HER2-negative breast cancer patients treated with tucidinostat after progression on CDK4/6i at the Breast Oncology Department of the Fifth Medical Center of the PLA General Hospital from July 2019 to October 2021 were retrospectively analyzed. Observation indexes included progression-free survival (PFS), overall survival (OS), clinical benefit rate (CBR), objective response rate (ORR) and adverse events. At the same time, we attempted to identify potential genomic predictors using available next-generation sequencing (NGS). RESULTS A total of 44 patients were enrolled in this study. Median follow-up was 10 months (1-26 months) by the data cutoff date (February 2022). The CBR was 6.8% (3/44), the median PFS was 2.0 months (95% CI 1.9-2.1), and the median OS was 14 months (95% CI 6.3-21.7). The mPFS was 4.1 months (95%CI: 0-8.2) in patients with 1 metastatic site, and the mPFS was 4.5 months (95%CI: 4.2-4.8) in patients who received sequential tucidinostat after CDK4/6i failure. Multivariate analysis showed that patients with 1 metastatic site or sequential tucidinostat treatment after failure of CDK4/6i were more likely to benefit from tucidinostat combined with endocrine therapy. Preliminary data showed PIK3CA mutation may be associated with resistance of tucidinostat therapy. No grade 4 adverse events and no treatment-related deaths were recorded in the study. Dose reductions because of adverse events occurred in 4 (9.1%) patients. CONCLUSIONS This study preliminarily shows that tucidinostat combined with endocrine therapy may be an optional sequential strategy for patients with HR+/HER2-advanced breast cancer that has progressed on CDK4/6 inhibitor, especially for these with lower tumor burden and fewer prior palliative treatment.
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Affiliation(s)
- Jinmei Zhou
- Breast Cancer Department of Oncology Institute, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xuexue Wu
- Breast Cancer Department of Oncology Institute, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Huiqiang Zhang
- Breast Cancer Department of Oncology Institute, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiaobo Wang
- Breast Cancer Department of Oncology Institute, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yang Yuan
- Breast Cancer Department of Oncology Institute, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Shaohua Zhang
- Breast Cancer Department of Oncology Institute, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Zefei Jiang
- Breast Cancer Department of Oncology Institute, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China,Corresponding author.
| | - Tao Wang
- Breast Cancer Department of Oncology Institute, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China,Anhui Medical University, Hefei, China,Southern Medical University, Guangzhou, China,Corresponding author. Breast Cancer Department of Oncology Institute, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
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Jiang Z, Liang Y, Wang X, Zhuang M, Feng M, Kuang Y. A Radiomics-Based Light Gradient Boosting Machine to Predict Radiation-Induced Toxicities in Nasopharynx Cancer Patients Receiving Chemoradiotherapy. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Chen J, Zhang H, Zhou J, Wu Z, Wu X, Zhang S, Jiang Z, Wang T. Efficacy and safety of pyrotinib and radiotherapy vs. pyrotinib-based therapy in patients with HER2 + breast cancer with brain metastasis: a retrospective cohort study. Ann Transl Med 2022; 10:1228. [PMID: 36544628 PMCID: PMC9761172 DOI: 10.21037/atm-22-5352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 11/17/2022] [Indexed: 11/25/2022]
Abstract
Background At present, local therapy, such as surgery and radiotherapy, is the mainstay treatment for brain metastasis and anti-human epidermal growth factor receptor type 2 (HER2)-targeted therapy has been shown to be efficacious for HER2+ breast cancer (BC) patients with brain metastasis. However, Clinical studies comparing the combined effects of the two treatments are lacking. This study sought to investigate the efficacy and safety of pyrotinib and radiotherapy versus pyrotinib-based therapy in treating HER2+ BC patients with brain metastasis. Methods This retrospective, observational study collected data from 79 HER2+ BC patients with brain metastasis who received pyrotinib-based therapy from May 2018 to December 2021. Among these patients, 35 received pyrotinib-based therapy concurrently with, or within 3 months before or after, brain radiotherapy (Group A), and 44 received pyrotinib-based therapy as the primary regimen (with no restriction as to whether they had received brain radiotherapy previously or not, the interval between receiving radiotherapy and receiving pyrotinib was >3 months) (Group B). Patient information was collected by the Electronic Medical Records System. The primary endpoints were progression-free survival (PFS) and overall survival (OS). The secondary endpoints were the objective response rate (ORR), the clinical benefit rate (CBR), and safety. The assessment of adverse effects was based on CTCAE5.0. Results The intracranial ORRs were 48.6% in Group A and 20.5% (9/44) in Group B (P=0.015). The intracranial CBRs were 80.0% in Group A and 65.9% in Group B. The median intracranial PFS times (IC-PFS) were 15.0 months and 9.0 months in Group A and Group B, respectively (P=0.385). There was no statistically significant difference in OS between the 2 groups (95.0 vs. 98.0 months, P=0.872). The subgroup analysis showed that patients with active brain metastasis who received pyrotinib and radiotherapy had a longer IC-PFS time than those who received pyrotinib-based therapy(P=0.056). No serious adverse reactions (e.g., acute brain edema, cognitive dysfunction, or treatment-related death events) were observed. Conclusions Pyrotinib combined with radiotherapy is recommended for HER2+ breast cancer active brain metastasis patients who can tolerate radiotherapy and pyrotinib. Pyrotinib-based therapy may be considered for patients who cannot tolerate radiotherapy and pyrotinib.
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Affiliation(s)
- Jiaxin Chen
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital and Medical School, Beijing, China
| | - Huiqiang Zhang
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jinmei Zhou
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Zisheng Wu
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital and Medical School, Beijing, China
| | - Xuexue Wu
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Shaohua Zhang
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Zefei Jiang
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Tao Wang
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital and Medical School, Beijing, China;,Anhui Medical University, Hefei, China;,Southern Medical University, Guangzhou, China
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Li J, Li X, Jiang Z, Hu C, Liu J, Huo J, Liu B. Predicting the probability of malignant pathological type of kidney cancer based on mass size: A retrospective study. Prog Urol 2022; 32:849-855. [PMID: 36068150 DOI: 10.1016/j.purol.2022.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 07/30/2022] [Accepted: 08/11/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Different degrees of malignancy of renal cell carcinoma (RCC) correspond to dissimilar therapies, and the prediction of malignancy of kidney cancer based on tumor size is still not fully studied. METHODS We evaluated a total of 50,776 patients with T1-T2, N0, M0 RCC diagnosed between 2004 to 2015 based on the Surveillance, Epidemiology, and End Results database. Three and four fuhrman grade clear cell RCC, three and four fuhrman grade papillary RCC, collecting duct RCC, sarcomatoid differentiation RCC and unclassified RCC were classified as aggressive RCC. The other RCC was classified as indolent RCC. The probability of aggressive and indolent was estimated according to tumor size using a logistic regression model. Differences in survival between subgroups were assessed using the Kaplan-Meier method. RESULTS There were 38,003 cases of indolent tumor and 12,773 cases of aggressive tumor totally. As tumor size increases, the predicted probability of an aggressive tumor also increases. Concretely, kidney cancers of 2cm, 3cm and 4cm were estimated to be 19.6%, 21.6% and 23.7% more likely to be aggressive. And for the same tumor size, clear cell RCC in men is more likely to be invasive relative to women and other kidney cancer pathology types. In addition, both the overall and tumor-specific survival are longer for indolent tumors than for aggressive tumors. CONCLUSION We evaluated the degree of malignancy of different sizes RCC in a retrospective study. This result may be helpful in the choice of initial therapy strategies for kidney cancer patients.
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Affiliation(s)
- J Li
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - X Li
- Kunshan Hospital of Traditional Chinese Medicine, Kunshan, Jiangsu, China
| | - Z Jiang
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - C Hu
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - J Liu
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - J Huo
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - B Liu
- The Comprehensive Cancer Centre of Nanjing Drum Tower Hospital, 321, zhongshan Road, 210008 Nanjing, China.
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Subramanian J, Gregg J, Berktas M, Jiang Z, Li J, Taylor A, Leighl N. EP08.02-080 EGFR Testing Practices, Treatment Choice and Clinical Outcomes in Advanced NSCLC in a Real-World Setting. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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