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Peng YJ, Li YH, Du C, Guo YS, Song JT, Jia CY, Zhang X, Liu MJ, Wang ZM, Liu B, Yan SL, Yang YX, Tang XL, Lin GX, Li XY, Zhang Y, Yuan JH, Xu SK, Chen CD, Lu JH, Zou X, Wan CS, Hu QH. [The cases of tracing the source of patients infected with Omicron variant of SARS-CoV-2 based on wastewater-based epidemiology in Shenzhen]. Zhonghua Yi Xue Za Zhi 2024; 104:302-307. [PMID: 38246776 DOI: 10.3760/cma.j.cn112137-20231016-00766] [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: 01/23/2024]
Abstract
Wastewater-based epidemiology (WBE) is an emerging discipline, which has been applied to drug abuse tracking and infectious disease pathogen surveillance. During the COVID-19 epidemic, WBE has been applied to monitor the epidemic trend and SARS-CoV-2 variants etc. In order to detect hidden COVID-19 cases and prevent transmission in the community, wastewater surveillance system for monitoring SARS-CoV-2 RNA was developed in Shenzhen. The sewage sampling sites were set up in key places such as the port areas, urban villages and residential communities of Futian, Nanshan, Luohu and Yantian districts. From July 26 to November 30, 2022, a total of 369 sewage sampling sites were set up, covering 1.93 million people. Continuous sampling was carried out for 3 hours in the peak period of water use every day. Sewage virus enrichment and SARS-CoV-2 nucleic acid detection were carried out by polyethylene glycol precipitation method and RT-qPCR, and a positive water sample disposal process was molded. This article aims to introduce the case of source tracing of COVID-19 infected patients based on urban sewage in Shenzhen. The sewage monitoring of Honghu water treatment plant in Luohu District played an early warning role, and the source of infection was traced. In the disposal of positive water samples in Futian South Road, Futian District, the important experience of monitoring point layout was obtained. In the sewage monitoring of Nanshan village, Nanshan District, the existence of occult infection was revealed. Sharing the experience of tracing the source of COVID-19 patients to avoid the spread of COVID-19 in the community based on wastewater surveillance of SARS-CoV-2 RNA in Shenzhen, and summarizing the advantages and application prospects of sewage surveillance can provide new ideas for monitoring emerging or re-emerging pathogens that are known to exhibit gastrointestinal excretion in the future.
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Affiliation(s)
- Y J Peng
- Biosafety Research Center, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Y H Li
- Microbiology Laboratory, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - C Du
- Microbiology Laboratory, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Y S Guo
- Division of Public Health Emergency, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - J T Song
- Water Ecology and Environment Division, Shenzhen Ecology and Environment Bureau, Shenzhen 518040, China
| | - C Y Jia
- Water Ecology and Environment Division, Shenzhen Ecology and Environment Bureau, Shenzhen 518040, China
| | - X Zhang
- Water Ecology and Environment Division, Shenzhen Ecology and Environment Bureau, Shenzhen 518040, China
| | - M J Liu
- Futian District Water Affairs Bureau, Shenzhen 518035, China
| | - Z M Wang
- Futian District Water Affairs Bureau, Shenzhen 518035, China
| | - B Liu
- Division of Water Supply and Drainage Management, Futian District Water Affairs Bureau, Shenzhen 518035, China
| | - S L Yan
- Division of Drainage and Disaster Prevention, Nanshan District Water Affairs Bureau, Shenzhen 518052, China
| | - Y X Yang
- Division of Drainage and Disaster Prevention, Nanshan District Water Affairs Bureau, Shenzhen 518052, China
| | - X L Tang
- Luohu Management Branch of Ecology Environment Bureau of Shenzhen Municipality, Shenzhen 518001, China
| | - G X Lin
- Division of Environmental Management, Luohu Management Branch of Ecology Environment Bureau of Shenzhen Municipality, Shenzhen 518001, China
| | - X Y Li
- Futian District Center for Disease Control and Prevention, Shenzhen 518040, China
| | - Y Zhang
- Department of Microbiological Laboratory, Futian District Center for Disease Control and Prevention, Shenzhen 518040, China
| | - J H Yuan
- Nanshan District Center for Disease Control and Prevention, Shenzhen 518054, China
| | - S K Xu
- Department of Infectious Disease Control and Prevention, Nanshan District Center for Disease Control and Prevention, Shenzhen 518054, China
| | - C D Chen
- Luohu District Center for Disease Control and Prevention, Shenzhen 518020, China
| | - J H Lu
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - X Zou
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - C S Wan
- Biosafety Research Center, School of Public Health, Southern Medical University, Guangzhou 510515, China BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Q H Hu
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
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Shang QX, Xu K, Dai QG, Huang HD, Hu JL, Zou X, Chen LL, Wei Y, Li HP, Zhen Q, Cai W, Wang Y, Bao CC. [Analysis on the secondary attack rates of SARS-CoV-2 Omicron variant and the associated factors]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:1550-1557. [PMID: 37859370 DOI: 10.3760/cma.j.cn112150-20230227-00162] [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: 10/21/2023]
Abstract
Objective: To evaluate the secondary attack rates of the SARS-CoV-2 Omicron variant and the associated factors. Methods: A total of 328 primary cases and 40 146 close contacts of the SARS-CoV-2 Omicron variant routinely detected in local areas of Jiangsu Province from February to April 2022 were selected in this study, and those with positive nucleic acid test results during 7 days of centralized isolation medical observation were defined as secondary cases. The demographic information and clinical characteristics were collected, and the secondary attack rate (SAR) and the associated factors were analyzed by using a multivariate logistic regression model. Results: A total of 1 285 secondary cases of close contacts were reported from 328 primary cases, with a SAR of 3.2% (95%CI: 3.0%-3.4%). Among the 328 primary cases, males accounted for 61.9% (203 cases), with the median age (Q1, Q3) of 38.5 (27, 51) years old. Among the 1 285 secondary cases, males accounted for 59.1% (759 cases), with the median age (Q1, Q3) of 34 (17, 52) years old. The multivariate logistic regression model showed that the higher SAR was observed in the primary male cases (OR=1.632, 95%CI: 1.418-1.877), younger than 20 years old (OR=1.766, 95%CI: 1.506-2.072),≥60 years old (OR=1.869, 95%CI: 1.476-2.365), infected with the BA.2 strain branch (OR=2.906, 95%CI: 2.388-3.537), the confirmed common cases (OR=2.572, 95%CI: 2.036-3.249), and confirmed mild cases (OR=1.717, 95%CI: 1.486-1.985). Meanwhile, the higher SAR was observed in the close contacts younger than 20 years old (OR=2.604, 95%CI: 2.250-3.015),≥60 years old (OR=1.287, 95%CI: 1.052-1.573) and exposure for co-residence (OR=27.854, 95%CI: 23.470-33.057). Conclusion: The sex and age of the primary case of the Omicron variant, the branch of the infected strain, case severity of the primary case, as well as the age and contact mode of close contacts are the associated factors of SAR.
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Affiliation(s)
- Q X Shang
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - K Xu
- Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Q G Dai
- Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H D Huang
- Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J L Hu
- Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - X Zou
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - L L Chen
- Department of Acute Infectious Disease Control and Prevention, Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - Y Wei
- Department of Acute Infectious Disease Control and Prevention, Nantong Center for Disease Control and Prevention, Nantong 226007, China
| | - H P Li
- Department of Acute Infectious Disease Control and Prevention, Lianyungang Center for Disease Control and Prevention, Lianyungang 222003, China
| | - Q Zhen
- Department of Acute Infectious Disease Control and Prevention, Changzhou Center for Disease Control and Prevention, Changzhou 213003, China
| | - W Cai
- Department of Acute Infectious Disease Control and Prevention, Suqian Center for Disease Control and Prevention, Suqian 223899, China
| | - Y Wang
- Department of Acute Infectious Disease Control and Prevention, Yangzhou Center for Disease Control and Prevention, Yangzhou 225007, China
| | - C C Bao
- School of Public Health, Nanjing Medical University, Nanjing 211166, China Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
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Lu M, Qu Y, Ma A, Zhu J, Zou X, Lin G, Li Y, Liu X, Wen Z. [Prediction of 1p/19q codeletion status in diffuse lower-grade glioma using multimodal MRI radiomics]. Nan Fang Yi Ke Da Xue Xue Bao 2023; 43:1023-1028. [PMID: 37439176 DOI: 10.12122/j.issn.1673-4254.2023.06.19] [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: 07/14/2023]
Abstract
OBJECTIVE To develop a noninvasive method for prediction of 1p/19q codeletion in diffuse lower-grade glioma (DLGG) based on multimodal magnetic resonance imaging (MRI) radiomics. METHODS We collected MRI data from 104 patients with pathologically confirmed DLGG between October, 2015 and September, 2022. A total of 535 radiomics features were extracted from T2WI, T1WI, FLAIR, CE-T1WI and DWI, including 70 morphological features, 90 first order features, and 375 texture features. We constructed logistic regression (LR), logistic regression least absolute shrinkage and selection operator (LRlasso), support vector machine (SVM) and Linear Discriminant Analysis (LDA) radiomics models and compared their predictive performance after 10-fold cross validation. The MRI images were reviewed by two radiologists independently for predicting the 1p/19q status. Receiver operating characteristic curves were used to evaluate classification performance of the radiomics models and the radiologists. RESULTS The 4 radiomics models (LR, LRlasso, SVM and LDA) achieved similar area under the curve (AUC) in the validation dataset (0.833, 0.819, 0.824 and 0.819, respectively; P>0.1), and their predictive performance was all superior to that of resident physicians of radiology (AUC=0.645, P=0.011, 0.022, 0.016, 0.030, respectively) and similar to that of attending physicians of radiology (AUC=0.838, P>0.05). CONCLUSION Multiparametric MRI radiomics models show good performance for noninvasive prediction of 1p/19q codeletion status in patients with in diffuse lower-grade glioma.
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Affiliation(s)
- M Lu
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - Y Qu
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - A Ma
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - J Zhu
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - X Zou
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - G Lin
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - Y Li
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - X Liu
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - Z Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
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Liang FY, Lin PL, Lin XJ, Han P, Chen RH, Wang JY, Zou X, Huang XM. [Preliminary experience of gasless transoral vestibular robotic thyroidectomy]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2023; 58:596-601. [PMID: 37339900 DOI: 10.3760/cma.j.cn115330-20221108-00672] [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] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
Objective: To explore the feasibility and safety of the gasless transoral vestibular robotic thyroidectomy using skin suspension. Methods: The clinical data of 20 patients underwent gasless transoral vestibular robotic thyroidectomy in the Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University from February 2022 to May 2022 were retrospectively analyzed. Among them, 18 were females and 2 were males, aged (38.7±8.0) years old. The intraoperative blood loss, operation time, postoperative hospital stay, postoperative drainage volume, postoperative pain visual analogue scale (VAS) score, postoperative swallowing function swallowing impairment score-6 (SIS-6), postoperative aesthetic VAS score, postoperative voice handicap index-10 (VHI-10) voice quality, postoperative pathology and complications were recorded. SPSS 25.0 was used for statistical analysis of the data. Results: The operations were successfully completed without conversion to open surgery in all patients. Pathological examination showed papillary thyroid carcinoma in 18 cases, retrosternal nodular goiter in 1 case, and cystic change in goiter in 1 case. The operative time for thyroid cancer was 161.50 (152.75, 182.50) min [M (P25, P75), the same below] and the average operative time for benign thyroid diseases was 166.50 minutes. The intraoperative blood loss 25.00 (21.25, 30.00) ml. In 18 cases of thyroid cancer, the mean diameter of the tumors was (7.22±2.02) mm, and lymph nodes (6.56±2.14) were dissected in the central region, with a lymph node metastasis rate of 61.11%. The postoperative pain VAS score was 3.00 (2.25, 4.00) points at 24 hours, the mean postoperative drainage volume was (118.35±24.32) ml, the postoperative hospital stay was 3.00 (3.00, 3.75) days, the postoperative SIS-6 score was (4.90±1.58) points at 3 months, and the postoperative VHI-10 score was 7.50 (2.00, 11.00) points at 3 months. Seven patients had mild mandibular numbness, 10 patients had mild cervical numbness, and 3 patients had temporary hypothyroidism three months after surgery and 1 patient had skin flap burn, but recovered one month after surgery. All patients were satisfied with the postoperative aesthetic effects, and the postoperative aesthetic VAS score was 10.00 (10.00, 10.00). Conclusion: Gasless transoral vestibular robotic thyroidectomy using skin suspension is a safe and feasible option with good postoperative aesthetic effect, which can provide a new treatment option for some selected patients with thyroid tumors.
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Affiliation(s)
- F Y Liang
- Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumor in Guangdong Province, Guangzhou 510280, China
| | - P L Lin
- Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumor in Guangdong Province, Guangzhou 510280, China
| | - X J Lin
- Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumor in Guangdong Province, Guangzhou 510280, China
| | - P Han
- Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumor in Guangdong Province, Guangzhou 510280, China
| | - R H Chen
- Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumor in Guangdong Province, Guangzhou 510280, China
| | - J Y Wang
- Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumor in Guangdong Province, Guangzhou 510280, China
| | - X Zou
- Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumor in Guangdong Province, Guangzhou 510280, China
| | - X M Huang
- Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumor in Guangdong Province, Guangzhou 510280, China
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Wang HZ, Sun GX, Yan X, Su TH, Xu J, Li F, Liu X, Wang BD, Xin LM, Zou X. [Protective repair of discolored breast cancer HE sections by color transfer]. Zhonghua Bing Li Xue Za Zhi 2023; 52:507-511. [PMID: 37106297 DOI: 10.3760/cma.j.cn112151-20230110-00019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Affiliation(s)
- H Z Wang
- Department of Breast Surgery, Qingdao Central Hospital Affiliated to Qingdao University, Qingdao 266042, China
| | - G X Sun
- Department of Clinical Medicine, Qingdao University Medical College, Qingdao 266042, China
| | - X Yan
- Department of Pathology, Qingdao Central Hospital Affiliated to Qingdao University, Qingdao 266042, China
| | - T H Su
- Medical Record Room of Qingdao Central Hospital Affiliated to Qingdao University, Qingdao 266042, China
| | - J Xu
- Department of Pathology, Qingdao Central Hospital Affiliated to Qingdao University, Qingdao 266042, China
| | - F Li
- School of Computer Engineering and Science Shanghai University, Shanghai 200444, China
| | - X Liu
- Department of Breast Surgery, Qingdao Central Hospital Affiliated to Qingdao University, Qingdao 266042, China
| | - B D Wang
- Department of Breast Surgery, Qingdao Central Hospital Affiliated to Qingdao University, Qingdao 266042, China
| | - L M Xin
- School of Computer Engineering and Science Shanghai University, Shanghai 200444, China
| | - X Zou
- Department of Breast Surgery, Qingdao Central Hospital Affiliated to Qingdao University, Qingdao 266042, China
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Zou X, Yang JS, Chen WJ, Liang FY. [Two cases of Charcot-Marie-Tooth disease with hoarseness]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2023; 58:501-504. [PMID: 37151000 DOI: 10.3760/cma.j.cn115330-20221107-00668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Affiliation(s)
- X Zou
- Department of Otolaryngology-Head and Neck Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou 510280, China
| | - J S Yang
- Department of Otolaryngology-Head and Neck Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou 510280, China
| | - W J Chen
- Department of Otolaryngology-Head and Neck Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou 510280, China
| | - F Y Liang
- Department of Otolaryngology-Head and Neck Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou 510280, China
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Cheng YP, Kong DF, Zhang J, Lyu ZQ, Chen ZG, Xiong HW, Lu Y, Luo QS, Lyu QY, Zhao J, Wen Y, Wan J, Lu FF, Lu JH, Zou X, Zhang Z. [Epidemiological characteristics of a 2019-nCoV outbreak caused by Omicron variant BF.7 in Shenzhen]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:379-385. [PMID: 36942331 DOI: 10.3760/cma.j.cn112338-20221031-00926] [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] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
Objective: To explore the epidemiological characteristic of a COVID-19 outbreak caused by 2019-nCoV Omicron variant BF.7 and other provinces imported in Shenzhen and analyze transmission chains and characteristics. Methods: Field epidemiological survey was conducted to identify the transmission chain, analyze the generation relationship among the cases. The 2019-nCoV nucleic acid positive samples were used for gene sequencing. Results: From 8 to 23 October, 2022, a total of 196 cases of COVID-19 were reported in Shenzhen, all the cases had epidemiological links. In the cases, 100 were men and 96 were women, with a median of age, M (Q1, Q3) was 33(25, 46) years. The outbreak was caused by traverlers initial cases infected with 2019-nCoV who returned to Shenzhen after traveling outside of Guangdong Province.There were four transmission chains, including the transmission in place of residence and neighbourhood, affecting 8 persons, transmission in social activity in the evening on 7 October, affecting 65 persons, transmission in work place on 8 October, affecting 48 persons, and transmission in a building near the work place, affecting 74 persons. The median of the incubation period of the infection, M (Q1, Q3) was 1.44 (1.11, 2.17) days. The incubation period of indoor exposure less than that of the outdoor exposure, M (Q1, Q3) was 1.38 (1.06, 1.84) and 1.95 (1.22, 2.99) days, respcetively (Wald χ2=10.27, P=0.001). With the increase of case generation, the number and probability of gene mutation increased. In the same transmission chain, the proportion of having 1-3 mutation sites was high in the cases in the first generation. Conclusions: The transmission chains were clear in this epidemic. The incubation period of Omicron variant BF.7 infection was shorter, the transmission speed was faster, and the gene mutation rate was higher. It is necessary to conduct prompt response and strict disease control when epidemic occurs.
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Affiliation(s)
- Y P Cheng
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - D F Kong
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - J Zhang
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Z Q Lyu
- Central Laboratory,Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Z G Chen
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - H W Xiong
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Y Lu
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Q S Luo
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Q Y Lyu
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - J Zhao
- Institute for AIDS Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Y Wen
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - J Wan
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - F F Lu
- Fuyong Branch Center of Shenzhen Bao'an District Public Health Center, Shenzhen 518103, China
| | - J H Lu
- Central Office,Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - X Zou
- Central Office,Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Z Zhang
- Institute for Infectious Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
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Cui H, Zeng L, Li R, Li Q, Hong C, Zhu H, Chen L, Liu L, Zou X, Xiao L. Radiomics signature based on CECT for non-invasive prediction of response to anti-PD-1 therapy in patients with hepatocellular carcinoma. Clin Radiol 2023; 78:e37-e44. [PMID: 36257868 DOI: 10.1016/j.crad.2022.09.113] [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: 05/09/2022] [Revised: 08/07/2022] [Accepted: 09/02/2022] [Indexed: 01/18/2023]
Abstract
PURPOSE This study aimed to develop a radiomics signature (RS) based on contrast-enhanced computed tomography (CECT) and evaluate its potential predictive value in hepatocellular carcinoma (HCC) patients receiving anti-PD-1 therapy. METHOD CECT scans of 76 HCC patients who received anti-PD-1 therapy were obtained in this study (training group = 53 and validation group = 23). The least absolute shrinkage and selection operator (LASSO) regression was applied to select radiomics features of primary and metastatic lesions and establish a RS to predict lesion-level response. Then, a nomogram combined the mean RS (MRS) and clinical variables with patient-level response as the end point. RESULTS In the lesion-level analysis, the area under the curves (AUCs) of RS in the training and validation groups were 0.751 (95% CI, 0.668-0.835) and 0.734 (95% CI, 0.604-0.864), respectively. In the patient-level analysis, the AUCs of the nomogram in the training and validation groups were 0.897 (95% CI, 0.798-0.996) and 0.889 (95% CI, 0.748-1.000), respectively. The nomogram stratified patients into low- and high-risk groups, which showed a significant difference in progression-free survival (PFS) (p<0.05). CONCLUSIONS The RS is a noninvasive biomarker for predicting anti-PD-1 therapy response in patients with HCC. The nomogram may be of clinical use for identifying high-risk patients and formulating individualised treatments.
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Affiliation(s)
- H Cui
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China; Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - L Zeng
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - R Li
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Q Li
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - C Hong
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - H Zhu
- Department of Medical Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, China
| | - L Chen
- Department of Medical Quality Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - L Liu
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China; Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - X Zou
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - L Xiao
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China; Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
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Wu WB, Zhang XB, Liu YP, Zou X, You R, Xie YL, Duan XT, Li HF, Wen K, Peng L, Hua YJ, Huang PY, Sun R, Chen JH, Chen MY. Stent pretreatment for internal carotid artery exposed to necrotic lesions in nasopharyngeal carcinoma. Rhinology 2023; 0:3056. [PMID: 36715464 DOI: 10.4193/rhin22.451] [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: 01/31/2023]
Abstract
BACKGROUND Post radiation nasopharyngeal necrosis (PRNN) invading the internal carotid artery (ICA) contributes to the death of 69.2-72.7% of PRNN patients. ICA occlusion is an effective treatment to avoid fatal bleeding, while some patients are intolerant. We present a novel method that allows for these patients without interrupting blood flow through the ICA. METHODOLOGY This study enrolled patients with PRNN-invaded ICA who were not suitable for ICA occlusion from April 2020 to November 2022. ICA stent pretreatment was performed in the 36 patients and followed the endoscopic nasopharyngectomy (ENPG) or conservative treatment for PRNN. We report the survival outcome and incidence of complications after stent implantation and compare the survival outcomes of ENPG and conservative treatment for PRNN followed by stent implantation. RESULTS ICA stent pretreatment was performed in the 36 enrolled patients, among which 14 underwent ENPG, and 22 received conservative treatment. 27.8% patients died after a median follow-up of 15 months. The Kaplan-Meier estimates of overall survival were higher in the ENPG group than in the conservative treatment group. Karnofsky performance status (KPS) was significantly higher in the ENPG group than in the non-ENPG group. CONCLUSIONS The innovative application of ICA stents is a promising treatment to improve outcomes in patients with PRNN invading the ICA who are unsuitable for ICA embolization, especially when followed by endoscopic surgery. However, methods to avoid postoperative cerebral ischemia and nasopharyngeal hemorrhage still require further study.
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Affiliation(s)
- W-B Wu
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - X-B Zhang
- Department of Neurosurgery, The third affiliated hospital of Southern Medical University, Guangzhou, P. R. China
| | - Y-P Liu
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - X Zou
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - R You
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - Y-L Xie
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - X-T Duan
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - H-F Li
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - K Wen
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - L Peng
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - Y-J Hua
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - P-Y Huang
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - R Sun
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
| | - J-H Chen
- Department of Neurosurgery, The third affiliated hospital of Southern Medical University, Guangzhou, P. R. China
| | - M-Y Chen
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Sun Yat-sen University Cancer Center
- State Key Laboratory of Oncology in South China
- Collaborative Innovation Center for Cancer Medicine
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, P.R. China
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10
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Zhang H, Li Z, Zheng S, Zheng P, Liang X, Li Y, Bu X, Zou X. Range-aided drift-free cooperative localization and consistent reconstruction of multi-ground robots. IEEE Robot Autom Lett 2023. [DOI: 10.1109/lra.2023.3244721] [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: 02/18/2023]
Affiliation(s)
- H. Zhang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Z. Li
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - S. Zheng
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - P. Zheng
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - X. Liang
- State Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Y. Li
- State Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - X. Bu
- State Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - X. Zou
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
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11
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Gerstung M, Jolly C, Leshchiner I, Dentro SC, Gonzalez S, Rosebrock D, Mitchell TJ, Rubanova Y, Anur P, Yu K, Tarabichi M, Deshwar A, Wintersinger J, Kleinheinz K, Vázquez-García I, Haase K, Jerman L, Sengupta S, Macintyre G, Malikic S, Donmez N, Livitz DG, Cmero M, Demeulemeester J, Schumacher S, Fan Y, Yao X, Lee J, Schlesner M, Boutros PC, Bowtell DD, Zhu H, Getz G, Imielinski M, Beroukhim R, Sahinalp SC, Ji Y, Peifer M, Markowetz F, Mustonen V, Yuan K, Wang W, Morris QD, Spellman PT, Wedge DC, Van Loo P, Tarabichi M, Wintersinger J, Deshwar AG, Yu K, Gonzalez S, Rubanova Y, Macintyre G, Adams DJ, Anur P, Beroukhim R, Boutros PC, Bowtell DD, Campbell PJ, Cao S, Christie EL, Cmero M, Cun Y, Dawson KJ, Demeulemeester J, Donmez N, Drews RM, Eils R, Fan Y, Fittall M, Garsed DW, Getz G, Ha G, Imielinski M, Jerman L, Ji Y, Kleinheinz K, Lee J, Lee-Six H, Livitz DG, Malikic S, Markowetz F, Martincorena I, Mitchell TJ, Mustonen V, Oesper L, Peifer M, Peto M, Raphael BJ, Rosebrock D, Sahinalp SC, Salcedo A, Schlesner M, Schumacher S, Sengupta S, Shi R, Shin SJ, Spiro O, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Stein LD, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Vázquez-García I, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Vembu S, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Wheeler DA, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Yang TP, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Yao X, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Yuan K, Rozen SG, Rubanova Y, Rubin MA, Rubio-Perez C, Rudneva VA, Rusev BC, Ruzzenente A, Rätsch G, Sabarinathan R, Sabelnykova VY, Zhu H, Sadeghi S, Sahinalp SC, Saini N, Saito-Adachi M, Saksena G, Salcedo A, Salgado R, Salichos L, Sallari R, Saller C, Wang W, Salvia R, Sam M, Samra JS, Sanchez-Vega F, Sander C, Sanders G, Sarin R, Sarrafi I, Sasaki-Oku A, Sauer T, Morris QD, Sauter G, Saw RPM, Scardoni M, Scarlett CJ, Scarpa A, Scelo G, Schadendorf D, Schein JE, Schilhabel MB, Schlesner M, Spellman PT, Schlomm T, Schmidt HK, Schramm SJ, Schreiber S, Schultz N, Schumacher SE, Schwarz RF, Scolyer RA, Scott D, Scully R, Wedge DC, Seethala R, Segre AV, Selander I, Semple CA, Senbabaoglu Y, Sengupta S, Sereni E, Serra S, Sgroi DC, Shackleton M, Van Loo P, Shah NC, Shahabi S, Shang CA, Shang P, Shapira O, Shelton T, Shen C, Shen H, Shepherd R, Shi R, Spellman PT, Shi Y, Shiah YJ, Shibata T, Shih J, Shimizu E, Shimizu K, Shin SJ, Shiraishi Y, Shmaya T, Shmulevich I, Wedge DC, Shorser SI, Short C, Shrestha R, Shringarpure SS, Shriver C, Shuai S, Sidiropoulos N, Siebert R, Sieuwerts AM, Sieverling L, Van Loo P, Signoretti S, Sikora KO, Simbolo M, Simon R, Simons JV, Simpson JT, Simpson PT, Singer S, Sinnott-Armstrong N, Sipahimalani P, Aaltonen LA, Skelly TJ, Smid M, Smith J, Smith-McCune K, Socci ND, Sofia HJ, Soloway MG, Song L, Sood AK, Sothi S, Abascal F, Sotiriou C, Soulette CM, Span PN, Spellman PT, Sperandio N, Spillane AJ, Spiro O, Spring J, Staaf J, Stadler PF, Abeshouse A, Staib P, Stark SG, Stebbings L, Stefánsson ÓA, Stegle O, Stein LD, Stenhouse A, Stewart C, Stilgenbauer S, Stobbe MD, Aburatani H, Stratton MR, Stretch JR, Struck AJ, Stuart JM, Stunnenberg HG, Su H, Su X, Sun RX, Sungalee S, Susak H, Adams DJ, Suzuki A, Sweep F, Szczepanowski M, Sültmann H, Yugawa T, Tam A, Tamborero D, Tan BKT, Tan D, Tan P, Agrawal N, Tanaka H, Taniguchi H, Tanskanen TJ, Tarabichi M, Tarnuzzer R, Tarpey P, Taschuk ML, Tatsuno K, Tavaré S, Taylor DF, Ahn KS, Taylor-Weiner A, Teague JW, Teh BT, Tembe V, Temes J, Thai K, Thayer SP, Thiessen N, Thomas G, Thomas S, Ahn SM, Thompson A, Thompson AM, Thompson JFF, Thompson RH, Thorne H, Thorne LB, Thorogood A, Tiao G, Tijanic N, Timms LE, Aikata H, Tirabosco R, Tojo M, Tommasi S, Toon CW, Toprak UH, Torrents D, Tortora G, Tost J, Totoki Y, Townend D, Akbani R, Traficante N, Treilleux I, Trotta JR, Trümper LHP, Tsao M, Tsunoda T, Tubio JMC, Tucker O, Turkington R, Turner DJ, Akdemir KC, Tutt A, Ueno M, Ueno NT, Umbricht C, Umer HM, Underwood TJ, Urban L, Urushidate T, Ushiku T, Uusküla-Reimand L, Al-Ahmadie H, Valencia A, Van Den Berg DJ, Van Laere S, Van Loo P, Van Meir EG, Van den Eynden GG, Van der Kwast T, Vasudev N, Vazquez M, Vedururu R, Al-Sedairy ST, Veluvolu U, Vembu S, Verbeke LPC, Vermeulen P, Verrill C, Viari A, Vicente D, Vicentini C, VijayRaghavan K, Viksna J, Al-Shahrour F, Vilain RE, Villasante I, Vincent-Salomon A, Visakorpi T, Voet D, Vyas P, Vázquez-García I, Waddell NM, Waddell N, Wadelius C, Alawi M, Wadi L, Wagener R, Wala JA, Wang J, Wang J, Wang L, Wang Q, Wang W, Wang Y, Wang Z, Albert M, Waring PM, Warnatz HJ, Warrell J, Warren AY, Waszak SM, Wedge DC, Weichenhan D, Weinberger P, Weinstein JN, Weischenfeldt J, Aldape K, Weisenberger DJ, Welch I, Wendl MC, Werner J, Whalley JP, Wheeler DA, Whitaker HC, Wigle D, Wilkerson MD, Williams A, Alexandrov LB, Wilmott JS, Wilson GW, Wilson JM, Wilson RK, Winterhoff B, Wintersinger JA, Wiznerowicz M, Wolf S, Wong BH, Wong T, Ally A, Wong W, Woo Y, Wood S, Wouters BG, Wright AJ, Wright DW, Wright MH, Wu CL, Wu DY, Wu G, Alsop K, Wu J, Wu K, Wu Y, Wu Z, Xi L, Xia T, Xiang Q, Xiao X, Xing R, Xiong H, Alvarez EG, Xu Q, Xu Y, Xue H, Yachida S, Yakneen S, Yamaguchi R, Yamaguchi TN, Yamamoto M, Yamamoto S, Yamaue H, Amary F, Yang F, Yang H, Yang JY, Yang L, Yang L, Yang S, Yang TP, Yang Y, Yao X, Yaspo ML, Amin SB, Yates L, Yau C, Ye C, Ye K, Yellapantula VD, Yoon CJ, Yoon SS, Yousif F, Yu J, Yu K, Aminou B, Yu W, Yu Y, Yuan K, Yuan Y, Yuen D, Yung CK, Zaikova O, Zamora J, Zapatka M, Zenklusen JC, Ammerpohl O, Zenz T, Zeps N, Zhang CZ, Zhang F, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Anderson MJ, Zhang X, Zhang X, Zhang Y, Zhang Z, Zhao Z, Zheng L, Zheng X, Zhou W, Zhou Y, Zhu B, Ang Y, Zhu H, Zhu J, Zhu S, Zou L, Zou X, deFazio A, van As N, van Deurzen CHM, van de Vijver MJ, van’t Veer L, Antonello D, von Mering C, Anur P, Aparicio S, Appelbaum EL, Arai Y, Aretz A, Arihiro K, Ariizumi SI, Armenia J, Arnould L, Asa S, Assenov Y, Atwal G, Aukema S, Auman JT, Aure MRR, Awadalla P, Aymerich M, Bader GD, Baez-Ortega A, Bailey MH, Bailey PJ, Balasundaram M, Balu S, Bandopadhayay P, Banks RE, Barbi S, Barbour AP, Barenboim J, Barnholtz-Sloan J, Barr H, Barrera E, Bartlett J, Bartolome J, Bassi C, Bathe OF, Baumhoer D, Bavi P, Baylin SB, Bazant W, Beardsmore D, Beck TA, Behjati S, Behren A, Niu B, Bell C, Beltran S, Benz C, Berchuck A, Bergmann AK, Bergstrom EN, Berman BP, Berney DM, Bernhart SH, Beroukhim R, Berrios M, Bersani S, Bertl J, Betancourt M, Bhandari V, Bhosle SG, Biankin AV, Bieg M, Bigner D, Binder H, Birney E, Birrer M, Biswas NK, Bjerkehagen B, Bodenheimer T, Boice L, Bonizzato G, De Bono JS, Boot A, Bootwalla MS, Borg A, Borkhardt A, Boroevich KA, Borozan I, Borst C, Bosenberg M, Bosio M, Boultwood J, Bourque G, Boutros PC, Bova GS, Bowen DT, Bowlby R, Bowtell DDL, Boyault S, Boyce R, Boyd J, Brazma A, Brennan P, Brewer DS, Brinkman AB, Bristow RG, Broaddus RR, Brock JE, Brock M, Broeks A, Brooks AN, Brooks D, Brors B, Brunak S, Bruxner TJC, Bruzos AL, Buchanan A, Buchhalter I, Buchholz C, Bullman S, Burke H, Burkhardt B, Burns KH, Busanovich J, Bustamante CD, Butler AP, Butte AJ, Byrne NJ, Børresen-Dale AL, Caesar-Johnson SJ, Cafferkey A, Cahill D, Calabrese C, Caldas C, Calvo F, Camacho N, Campbell PJ, Campo E, Cantù C, Cao S, Carey TE, Carlevaro-Fita J, Carlsen R, Cataldo I, Cazzola M, Cebon J, Cerfolio R, Chadwick DE, Chakravarty D, Chalmers D, Chan CWY, Chan K, Chan-Seng-Yue M, Chandan VS, Chang DK, Chanock SJ, Chantrill LA, Chateigner A, Chatterjee N, Chayama K, Chen HW, Chen J, Chen K, Chen Y, Chen Z, Cherniack AD, Chien J, Chiew YE, Chin SF, Cho J, Cho S, Choi JK, Choi W, Chomienne C, Chong Z, Choo SP, Chou A, Christ AN, Christie EL, Chuah E, Cibulskis C, Cibulskis K, Cingarlini S, Clapham P, Claviez A, Cleary S, Cloonan N, Cmero M, Collins CC, Connor AA, Cooke SL, Cooper CS, Cope L, Corbo V, Cordes MG, Cordner SM, Cortés-Ciriano I, Covington K, Cowin PA, Craft B, Craft D, Creighton CJ, Cun Y, Curley E, Cutcutache I, Czajka K, Czerniak B, Dagg RA, Danilova L, Davi MV, Davidson NR, Davies H, Davis IJ, Davis-Dusenbery BN, Dawson KJ, De La Vega FM, De Paoli-Iseppi R, Defreitas T, Tos APD, Delaneau O, Demchok JA, Demeulemeester J, Demidov GM, Demircioğlu D, Dennis NM, Denroche RE, Dentro SC, Desai N, Deshpande V, Deshwar AG, Desmedt C, Deu-Pons J, Dhalla N, Dhani NC, Dhingra P, Dhir R, DiBiase A, Diamanti K, Ding L, Ding S, Dinh HQ, Dirix L, Doddapaneni H, Donmez N, Dow MT, Drapkin R, Drechsel O, Drews RM, Serge S, Dudderidge T, Dueso-Barroso A, Dunford AJ, Dunn M, Dursi LJ, Duthie FR, Dutton-Regester K, Eagles J, Easton DF, Edmonds S, Edwards PA, Edwards SE, Eeles RA, Ehinger A, Eils J, Eils R, El-Naggar A, Eldridge M, Ellrott K, Erkek S, Escaramis G, Espiritu SMG, Estivill X, Etemadmoghadam D, Eyfjord JE, Faltas BM, Fan D, Fan Y, Faquin WC, Farcas C, Fassan M, Fatima A, Favero F, Fayzullaev N, Felau I, Fereday S, Ferguson ML, Ferretti V, Feuerbach L, Field MA, Fink JL, Finocchiaro G, Fisher C, Fittall MW, Fitzgerald A, Fitzgerald RC, Flanagan AM, Fleshner NE, Flicek P, Foekens JA, Fong KM, Fonseca NA, Foster CS, Fox NS, Fraser M, Frazer S, Frenkel-Morgenstern M, Friedman W, Frigola J, Fronick CC, Fujimoto A, Fujita M, Fukayama M, Fulton LA, Fulton RS, Furuta M, Futreal PA, Füllgrabe A, Gabriel SB, Gallinger S, Gambacorti-Passerini C, Gao J, Gao S, Garraway L, Garred Ø, Garrison E, Garsed DW, Gehlenborg N, Gelpi JLL, George J, Gerhard DS, Gerhauser C, Gershenwald JE, Gerstein M, Gerstung M, Getz G, Ghori M, Ghossein R, Giama NH, Gibbs RA, Gibson B, Gill AJ, Gill P, Giri DD, Glodzik D, Gnanapragasam VJ, Goebler ME, Goldman MJ, Gomez C, Gonzalez S, Gonzalez-Perez A, Gordenin DA, Gossage J, Gotoh K, Govindan R, Grabau D, Graham JS, Grant RC, Green AR, Green E, Greger L, Grehan N, Grimaldi S, Grimmond SM, Grossman RL, Grundhoff A, Gundem G, Guo Q, Gupta M, Gupta S, Gut IG, Gut M, Göke J, Ha G, Haake A, Haan D, Haas S, Haase K, Haber JE, Habermann N, Hach F, Haider S, Hama N, Hamdy FC, Hamilton A, Hamilton MP, Han L, Hanna GB, Hansmann M, Haradhvala NJ, Harismendy O, Harliwong I, Harmanci AO, Harrington E, Hasegawa T, Haussler D, Hawkins S, Hayami S, Hayashi S, Hayes DN, Hayes SJ, Hayward NK, Hazell S, He Y, Heath AP, Heath SC, Hedley D, Hegde AM, Heiman DI, Heinold MC, Heins Z, Heisler LE, Hellstrom-Lindberg E, Helmy M, Heo SG, Hepperla AJ, Heredia-Genestar JM, Herrmann C, Hersey P, Hess JM, Hilmarsdottir H, Hinton J, Hirano S, Hiraoka N, Hoadley KA, Hobolth A, Hodzic E, Hoell JI, Hoffmann S, Hofmann O, Holbrook A, Holik AZ, Hollingsworth MA, Holmes O, Holt RA, Hong C, Hong EP, Hong JH, Hooijer GK, Hornshøj H, Hosoda F, Hou Y, Hovestadt V, Howat W, Hoyle AP, Hruban RH, Hu J, Hu T, Hua X, Huang KL, Huang M, Huang MN, Huang V, Huang Y, Huber W, Hudson TJ, Hummel M, Hung JA, Huntsman D, Hupp TR, Huse J, Huska MR, Hutter B, Hutter CM, Hübschmann D, Iacobuzio-Donahue CA, Imbusch CD, Imielinski M, Imoto S, Isaacs WB, Isaev K, Ishikawa S, Iskar M, Islam SMA, Ittmann M, Ivkovic S, Izarzugaza JMG, Jacquemier J, Jakrot V, Jamieson NB, Jang GH, Jang SJ, Jayaseelan JC, Jayasinghe R, Jefferys SR, Jegalian K, Jennings JL, Jeon SH, Jerman L, Ji Y, Jiao W, Johansson PA, Johns AL, Johns J, Johnson R, Johnson TA, Jolly C, Joly Y, Jonasson JG, Jones CD, Jones DR, Jones DTW, Jones N, Jones SJM, Jonkers J, Ju YS, Juhl H, Jung J, Juul M, Juul RI, Juul S, Jäger N, Kabbe R, Kahles A, Kahraman A, Kaiser VB, Kakavand H, Kalimuthu S, von Kalle C, Kang KJ, Karaszi K, Karlan B, Karlić R, Karsch D, Kasaian K, Kassahn KS, Katai H, Kato M, Katoh H, Kawakami Y, Kay JD, Kazakoff SH, Kazanov MD, Keays M, Kebebew E, Kefford RF, Kellis M, Kench JG, Kennedy CJ, Kerssemakers JNA, Khoo D, Khoo V, Khuntikeo N, Khurana E, Kilpinen H, Kim HK, Kim HL, Kim HY, Kim H, Kim J, Kim J, Kim JK, Kim Y, King TA, Klapper W, Kleinheinz K, Klimczak LJ, Knappskog S, Kneba M, Knoppers BM, Koh Y, Komorowski J, Komura D, Komura M, Kong G, Kool M, Korbel JO, Korchina V, Korshunov A, Koscher M, Koster R, Kote-Jarai Z, Koures A, Kovacevic M, Kremeyer B, Kretzmer H, Kreuz M, Krishnamurthy S, Kube D, Kumar K, Kumar P, Kumar S, Kumar Y, Kundra R, Kübler K, Küppers R, Lagergren J, Lai PH, Laird PW, Lakhani SR, Lalansingh CM, Lalonde E, Lamaze FC, Lambert A, Lander E, Landgraf P, Landoni L, Langerød A, Lanzós A, Larsimont D, Larsson E, Lathrop M, Lau LMS, Lawerenz C, Lawlor RT, Lawrence MS, Lazar AJ, Lazic AM, Le X, Lee D, Lee D, Lee EA, Lee HJ, Lee JJK, Lee JY, Lee J, Lee MTM, Lee-Six H, Lehmann KV, Lehrach H, Lenze D, Leonard CR, Leongamornlert DA, Leshchiner I, Letourneau L, Letunic I, Levine DA, Lewis L, Ley T, Li C, Li CH, Li HI, Li J, Li L, Li S, Li S, Li X, Li X, Li X, Li Y, Liang H, Liang SB, Lichter P, Lin P, Lin Z, Linehan WM, Lingjærde OC, Liu D, Liu EM, Liu FFF, Liu F, Liu J, Liu X, Livingstone J, Livitz D, Livni N, Lochovsky L, Loeffler M, Long GV, Lopez-Guillermo A, Lou S, Louis DN, Lovat LB, Lu Y, Lu YJ, Lu Y, Luchini C, Lungu I, Luo X, Luxton HJ, Lynch AG, Lype L, López C, López-Otín C, Ma EZ, Ma Y, MacGrogan G, MacRae S, Macintyre G, Madsen T, Maejima K, Mafficini A, Maglinte DT, Maitra A, Majumder PP, Malcovati L, Malikic S, Malleo G, Mann GJ, Mantovani-Löffler L, Marchal K, Marchegiani G, Mardis ER, Margolin AA, Marin MG, Markowetz F, Markowski J, Marks J, Marques-Bonet T, Marra MA, Marsden L, Martens JWM, Martin S, Martin-Subero JI, Martincorena I, Martinez-Fundichely A, Maruvka YE, Mashl RJ, Massie CE, Matthew TJ, Matthews L, Mayer E, Mayes S, Mayo M, Mbabaali F, McCune K, McDermott U, McGillivray PD, McLellan MD, McPherson JD, McPherson JR, McPherson TA, Meier SR, Meng A, Meng S, Menzies A, Merrett ND, Merson S, Meyerson M, Meyerson W, Mieczkowski PA, Mihaiescu GL, Mijalkovic S, Mikkelsen T, Milella M, Mileshkin L, Miller CA, Miller DK, Miller JK, Mills GB, Milovanovic A, Minner S, Miotto M, Arnau GM, Mirabello L, Mitchell C, Mitchell TJ, Miyano S, Miyoshi N, Mizuno S, Molnár-Gábor F, Moore MJ, Moore RA, Morganella S, Morris QD, Morrison C, Mose LE, Moser CD, Muiños F, Mularoni L, Mungall AJ, Mungall K, Musgrove EA, Mustonen V, Mutch D, Muyas F, Muzny DM, Muñoz A, Myers J, Myklebost O, Möller P, Nagae G, Nagrial AM, Nahal-Bose HK, Nakagama H, Nakagawa H, Nakamura H, Nakamura T, Nakano K, Nandi T, Nangalia J, Nastic M, Navarro A, Navarro FCP, Neal DE, Nettekoven G, Newell F, Newhouse SJ, Newton Y, Ng AWT, Ng A, Nicholson J, Nicol D, Nie Y, Nielsen GP, Nielsen MM, Nik-Zainal S, Noble MS, Nones K, Northcott PA, Notta F, O’Connor BD, O’Donnell P, O’Donovan M, O’Meara S, O’Neill BP, O’Neill JR, Ocana D, Ochoa A, Oesper L, Ogden C, Ohdan H, Ohi K, Ohno-Machado L, Oien KA, Ojesina AI, Ojima H, Okusaka T, Omberg L, Ong CK, Ossowski S, Ott G, Ouellette BFF, P’ng C, Paczkowska M, Paiella S, Pairojkul C, Pajic M, Pan-Hammarström Q, Papaemmanuil E, Papatheodorou I, Paramasivam N, Park JW, Park JW, Park K, Park K, Park PJ, Parker JS, Parsons SL, Pass H, Pasternack D, Pastore A, Patch AM, Pauporté I, Pea A, Pearson JV, Pedamallu CS, Pedersen JS, Pederzoli P, Peifer M, Pennell NA, Perou CM, Perry MD, Petersen GM, Peto M, Petrelli N, Petryszak R, Pfister SM, Phillips M, Pich O, Pickett HA, Pihl TD, Pillay N, Pinder S, Pinese M, Pinho AV. Author Correction: The evolutionary history of 2,658 cancers. Nature 2023; 614:E42. [PMID: 36697833 PMCID: PMC9931577 DOI: 10.1038/s41586-022-05601-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Moritz Gerstung
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK. .,European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany. .,Wellcome Sanger Institute, Cambridge, UK.
| | - Clemency Jolly
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Ignaty Leshchiner
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Stefan C. Dentro
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK
| | - Santiago Gonzalez
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Daniel Rosebrock
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Thomas J. Mitchell
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Yulia Rubanova
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Pavana Anur
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - Kaixian Yu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Maxime Tarabichi
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Amit Deshwar
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Jeff Wintersinger
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Kortine Kleinheinz
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.7700.00000 0001 2190 4373Heidelberg University, Heidelberg, Germany
| | - Ignacio Vázquez-García
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Kerstin Haase
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Lara Jerman
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK ,grid.8954.00000 0001 0721 6013University of Ljubljana, Ljubljana, Slovenia
| | - Subhajit Sengupta
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA
| | - Geoff Macintyre
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Salem Malikic
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Nilgun Donmez
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Dimitri G. Livitz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Marek Cmero
- grid.1008.90000 0001 2179 088XUniversity of Melbourne, Melbourne, Victoria Australia ,grid.1042.70000 0004 0432 4889Walter and Eliza Hall Institute, Melbourne, Victoria Australia
| | - Jonas Demeulemeester
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.5596.f0000 0001 0668 7884University of Leuven, Leuven, Belgium
| | - Steven Schumacher
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Yu Fan
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Xiaotong Yao
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Juhee Lee
- grid.205975.c0000 0001 0740 6917University of California Santa Cruz, Santa Cruz, CA USA
| | - Matthias Schlesner
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Paul C. Boutros
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.419890.d0000 0004 0626 690XOntario Institute for Cancer Research, Toronto, Ontario Canada ,grid.19006.3e0000 0000 9632 6718University of California, Los Angeles, CA USA
| | - David D. Bowtell
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, Melbourne, Victoria Australia
| | - Hongtu Zhu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Gad Getz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA USA ,grid.32224.350000 0004 0386 9924Department of Pathology, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Marcin Imielinski
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Rameen Beroukhim
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - S. Cenk Sahinalp
- grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada ,grid.411377.70000 0001 0790 959XIndiana University, Bloomington, IN USA
| | - Yuan Ji
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA ,grid.170205.10000 0004 1936 7822The University of Chicago, Chicago, IL USA
| | - Martin Peifer
- grid.6190.e0000 0000 8580 3777University of Cologne, Cologne, Germany
| | - Florian Markowetz
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Ville Mustonen
- grid.7737.40000 0004 0410 2071University of Helsinki, Helsinki, Finland
| | - Ke Yuan
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK ,grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Wenyi Wang
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Quaid D. Morris
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | | | - Paul T. Spellman
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - David C. Wedge
- grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK ,grid.454382.c0000 0004 7871 7212Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Peter Van Loo
- The Francis Crick Institute, London, UK. .,University of Leuven, Leuven, Belgium.
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Calabrese C, Davidson NR, Demircioğlu D, Fonseca NA, He Y, Kahles A, Lehmann KV, Liu F, Shiraishi Y, Soulette CM, Urban L, Greger L, Li S, Liu D, Perry MD, Xiang Q, Zhang F, Zhang J, Bailey P, Erkek S, Hoadley KA, Hou Y, Huska MR, Kilpinen H, Korbel JO, Marin MG, Markowski J, Nandi T, Pan-Hammarström Q, Pedamallu CS, Siebert R, Stark SG, Su H, Tan P, Waszak SM, Yung C, Zhu S, Awadalla P, Creighton CJ, Meyerson M, Ouellette BFF, Wu K, Yang H, Brazma A, Brooks AN, Göke J, Rätsch G, Schwarz RF, Stegle O, Zhang Z, Wu K, Yang H, Fonseca NA, Kahles A, Lehmann KV, Urban L, Soulette CM, Shiraishi Y, Liu F, He Y, Demircioğlu D, Davidson NR, Calabrese C, Zhang J, Perry MD, Xiang Q, Greger L, Li S, Liu D, Stark SG, Zhang F, Amin SB, Bailey P, Chateigner A, Cortés-Ciriano I, Craft B, Erkek S, Frenkel-Morgenstern M, Goldman M, Hoadley KA, Hou Y, Huska MR, Khurana E, Kilpinen H, Korbel JO, Lamaze FC, Li C, Li X, Li X, Liu X, Marin MG, Markowski J, Nandi T, Nielsen MM, Ojesina AI, Pan-Hammarström Q, Park PJ, Pedamallu CS, Pedersen JS, Pederzoli P, Peifer M, Pennell NA, Perou CM, Perry MD, Petersen GM, Peto M, Petrelli N, Pedamallu CS, Petryszak R, Pfister SM, Phillips M, Pich O, Pickett HA, Pihl TD, Pillay N, Pinder S, Pinese M, Pinho AV, Pedersen JS, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Siebert R, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Su H, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Tan P, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Teh BT, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Wang J, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Waszak SM, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Xiong H, Rozen SG, Rubanova Y, Rubin MA, Rubio-Perez C, Rudneva VA, Rusev BC, Ruzzenente A, Rätsch G, Sabarinathan R, Sabelnykova VY, Yakneen S, Sadeghi S, Sahinalp SC, Saini N, Saito-Adachi M, Saksena G, Salcedo A, Salgado R, Salichos L, Sallari R, Saller C, Ye C, Salvia R, Sam M, Samra JS, Sanchez-Vega F, Sander C, Sanders G, Sarin R, Sarrafi I, Sasaki-Oku A, Sauer T, Yung C, Sauter G, Saw RPM, Scardoni M, Scarlett CJ, Scarpa A, Scelo G, Schadendorf D, Schein JE, Schilhabel MB, Schlesner M, Zhang X, Schlomm T, Schmidt HK, Schramm SJ, Schreiber S, Schultz N, Schumacher SE, Schwarz RF, Scolyer RA, Scott D, Scully R, Zheng L, Seethala R, Segre AV, Selander I, Semple CA, Senbabaoglu Y, Sengupta S, Sereni E, Serra S, Sgroi DC, Shackleton M, Zhu J, Shah NC, Shahabi S, Shang CA, Shang P, Shapira O, Shelton T, Shen C, Shen H, 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Viksna J, Göke J, Vilain RE, Villasante I, Vincent-Salomon A, Visakorpi T, Voet D, Vyas P, Vázquez-García I, Waddell NM, Waddell N, Wadelius C, Rätsch G, Wadi L, Wagener R, Wala JA, Wang J, Wang J, Wang L, Wang Q, Wang W, Wang Y, Wang Z, Schwarz RF, Waring PM, Warnatz HJ, Warrell J, Warren AY, Waszak SM, Wedge DC, Weichenhan D, Weinberger P, Weinstein JN, Weischenfeldt J, Stegle O, Weisenberger DJ, Welch I, Wendl MC, Werner J, Whalley JP, Wheeler DA, Whitaker HC, Wigle D, Wilkerson MD, Williams A, Zhang Z, Wilmott JS, Wilson GW, Wilson JM, Wilson RK, Winterhoff B, Wintersinger JA, Wiznerowicz M, Wolf S, Wong BH, Wong T, Aaltonen LA, Wong W, Woo Y, Wood S, Wouters BG, Wright AJ, Wright DW, Wright MH, Wu CL, Wu DY, Wu G, Abascal F, Wu J, Wu K, Wu Y, Wu Z, Xi L, Xia T, Xiang Q, Xiao X, Xing R, Xiong H, Abeshouse A, Xu Q, Xu Y, Xue H, Yachida S, Yakneen S, Yamaguchi R, Yamaguchi TN, Yamamoto M, Yamamoto S, Yamaue H, Aburatani H, Yang F, Yang H, Yang JY, Yang L, Yang L, Yang S, Yang TP, 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Jayaseelan JC, Jayasinghe R, Jefferys SR, Jegalian K, Jennings JL, Jeon SH, Jerman L, Ji Y, Jiao W, Johansson PA, Johns AL, Johns J, Johnson R, Johnson TA, Jolly C, Joly Y, Jonasson JG, Jones CD, Jones DR, Jones DTW, Jones N, Jones SJM, Jonkers J, Ju YS, Juhl H, Jung J, Juul M, Juul RI, Juul S, Jäger N, Kabbe R, Kahles A, Kahraman A, Kaiser VB, Kakavand H, Kalimuthu S, von Kalle C, Kang KJ, Karaszi K, Karlan B, Karlić R, Karsch D, Kasaian K, Kassahn KS, Katai H, Kato M, Katoh H, Kawakami Y, Kay JD, Kazakoff SH, Kazanov MD, Keays M, Kebebew E, Kefford RF, Kellis M, Kench JG, Kennedy CJ, Kerssemakers JNA, Khoo D, Khoo V, Khuntikeo N, Khurana E, Kilpinen H, Kim HK, Kim HL, Kim HY, Kim H, Kim J, Kim J, Kim JK, Kim Y, King TA, Klapper W, Kleinheinz K, Klimczak LJ, Knappskog S, Kneba M, Knoppers BM, Koh Y, Komorowski J, Komura D, Komura M, Kong G, Kool M, Korbel JO, Korchina V, Korshunov A, Koscher M, Koster R, Kote-Jarai Z, Koures A, Kovacevic M, Kremeyer B, Kretzmer H, Kreuz M, 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Mustonen V, Mutch D, Muyas F, Muzny DM, Muñoz A, Myers J, Myklebost O, Möller P, Nagae G, Nagrial AM, Nahal-Bose HK, Nakagama H, Nakagawa H, Nakamura H, Nakamura T, Nakano K, Nandi T, Nangalia J, Nastic M, Navarro A, Navarro FCP, Neal DE, Nettekoven G, Newell F, Newhouse SJ, Newton Y, Ng AWT, Ng A, Nicholson J, Nicol D, Nie Y, Nielsen GP, Nielsen MM, Nik-Zainal S, Noble MS, Nones K, Northcott PA, Notta F, O’Connor BD, O’Donnell P, O’Donovan M, O’Meara S, O’Neill BP, O’Neill JR, Ocana D, Ochoa A, Oesper L, Ogden C, Ohdan H, Ohi K, Ohno-Machado L, Oien KA, Ojesina AI, Ojima H, Okusaka T, Omberg L, Ong CK, Ossowski S, Ott G, Ouellette BFF, P’ng C, Paczkowska M, Paiella S, Pairojkul C, Pajic M, Pan-Hammarström Q, Papaemmanuil E, Papatheodorou I, Paramasivam N, Park JW, Park JW, Park K, Park K, Park PJ, Parker JS, Parsons SL, Pass H, Pasternack D, Pastore A, Patch AM, Pauporté I, Pea A, Pearson JV. Author Correction: Genomic basis for RNA alterations in cancer. Nature 2023; 614:E37. [PMID: 36697831 PMCID: PMC9931574 DOI: 10.1038/s41586-022-05596-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
| | - Claudia Calabrese
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Natalie R. Davidson
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.5386.8000000041936877XWeill Cornell Medical College, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Deniz Demircioğlu
- grid.4280.e0000 0001 2180 6431National University of Singapore, Singapore, Singapore ,grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Nuno A. Fonseca
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Yao He
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - André Kahles
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Kjong-Van Lehmann
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Fenglin Liu
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Yuichi Shiraishi
- grid.26999.3d0000 0001 2151 536XThe University of Tokyo, Minato-ku, Japan
| | - Cameron M. Soulette
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Lara Urban
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Liliana Greger
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Siliang Li
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Dongbing Liu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Marc D. Perry
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.266102.10000 0001 2297 6811University of California, San Francisco, San Francisco, CA USA
| | - Qian Xiang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Fan Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Junjun Zhang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Peter Bailey
- grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Serap Erkek
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Katherine A. Hoadley
- grid.10698.360000000122483208The University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Yong Hou
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Matthew R. Huska
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Helena Kilpinen
- grid.83440.3b0000000121901201University College London, London, UK
| | - Jan O. Korbel
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Maximillian G. Marin
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Julia Markowski
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Tannistha Nandi
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Qiang Pan-Hammarström
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.4714.60000 0004 1937 0626Karolinska Institutet, Stockholm, Sweden
| | - Chandra Sekhar Pedamallu
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Reiner Siebert
- grid.410712.10000 0004 0473 882XUlm University and Ulm University Medical Center, Ulm, Germany
| | - Stefan G. Stark
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Hong Su
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Patrick Tan
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.428397.30000 0004 0385 0924Duke-NUS Medical School, Singapore, Singapore
| | - Sebastian M. Waszak
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Christina Yung
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Shida Zhu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Philip Awadalla
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada
| | - Chad J. Creighton
- grid.39382.330000 0001 2160 926XBaylor College of Medicine, Houston, TX USA
| | - Matthew Meyerson
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | | | - Kui Wu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Huanming Yang
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China
| | | | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
| | - Angela N. Brooks
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA ,grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - Jonathan Göke
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.410724.40000 0004 0620 9745National Cancer Centre Singapore, Singapore, Singapore
| | - Gunnar Rätsch
- ETH Zurich, Zurich, Switzerland. .,Memorial Sloan Kettering Cancer Center, New York, NY, USA. .,Weill Cornell Medical College, New York, NY, USA. .,SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,University Hospital Zurich, Zurich, Switzerland.
| | - Roland F. Schwarz
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), partner site Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oliver Stegle
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Zemin Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
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| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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13
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Peng M, Liu Y, Jia X, Wu Y, Zou X, Ke M, Cai K, Zhang L, Lu D, Xu A. Dietary Total Antioxidant Capacity and Cognitive Function in Older Adults in the United States: The NHANES 2011-2014. J Nutr Health Aging 2023; 27:479-486. [PMID: 37357333 DOI: 10.1007/s12603-023-1934-9] [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: 01/12/2023] [Accepted: 05/13/2023] [Indexed: 06/27/2023]
Abstract
OBJECTIVES Oxidative stress level takes part in the development of cognitive decline. However, the association between total antioxidant capacity (TAC) from diet and cognitive function is controversial. The aim of this study was to investigate the relationship between TAC and the cognitive function of older adults in the U.S. DESIGN A cross-sectional study. SETTING National Health and Nutrition Examination Surveys database. PARTICIPANTS 2712 older adults aged over 60 years. MEASUREMENTS TAC was calculated from 8 antioxidative vitamins based on the reference values for vitamin C equivalent antioxidant capacity obtained from individuals' 24 h dietary recall. Four memory-related assessments were employed [Immediate Recall test (IRT), Delayed Recall test (DRT), Animal Fluency test (AFT), and Digit Symbol Substitution test (DSST)]. RESULTS Among the 2712 participants, the median age was 68 years, and 50.4% were women. Participants in the group with higher TAC levels had relatively higher IRT, AFT and DSST scores (P=0.025, P=0.008, P<0.001, respectively). In adjusted weighted linear regression, log-transformed TAC was positively associated with AFT (β=1.10, 95%CI: 0.51, 1.70) and DSST (β=2.81, 95%CI: 1.16, 4.45). Compared with the first quartile, the participants in the second (Q2 vs. Q1, OR=0.66, 95%CI: 0.43,1.02) and fourth quartile (Q4 vs. Q1, OR=0.47, 95%CI:0.28, 0.78) of log-transformed TAC showed a decreased risk of impaired cognitive function (ICF) after adjusting for confounders. The dose-response analysis indicated a gradual descent in the risk of ICF as TAC increases. Diabetes mellitus (DM) mediated part of the effect of TAC on ICF. The relationship between TAC and ICF was more pronounced in subjects with DM (Q4 vs Q1, OR=0.36, 95%CI:0.17, 0.74). CONCLUSION Our findings support that higher dietary antioxidant potential was related to a decreased risk of cognitive dysfunction, particularly in the subjects with DM who may have oxidative injury. DM was one of the factors mediating the effect of TAC on ICF.
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Affiliation(s)
- M Peng
- Anding Xu, Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West, Guangzhou, 510630, Guangdong Province, China, ; Dan Lu, Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West, Guangzhou, 510630, Guangdong Province, China,
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14
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Xiao P, Pan Y, Cai F, Tu H, Liu J, Yang X, Liang H, Zou X, Yang L, Duan J, Xv L, Feng L, Liu Z, Qian Y, Meng Y, Du J, Mei X, Lou T, Yin X, Tan Z. A deep learning based framework for the classification of multi- class capsule gastroscope image in gastroenterologic diagnosis. Front Physiol 2022; 13:1060591. [PMID: 36467700 PMCID: PMC9716070 DOI: 10.3389/fphys.2022.1060591] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 11/07/2022] [Indexed: 07/30/2023] Open
Abstract
Purpose: The purpose of this paper is to develop a method to automatic classify capsule gastroscope image into three categories to prevent high-risk factors for carcinogenesis, such as atrophic gastritis (AG). The purpose of this research work is to develop a deep learning framework based on transfer learning to classify capsule gastroscope image into three categories: normal gastroscopic image, chronic erosive gastritis images, and ulcer gastric image. Method: In this research work, we proposed deep learning framework based on transfer learning to classify capsule gastroscope image into three categories: normal gastroscopic image, chronic erosive gastritis images, and ulcer gastric image. We used VGG- 16, ResNet-50, and Inception V3 pre-trained models, fine-tuned them and adjust hyperparameters according to our classification problem. Results: A dataset containing 380 images was collected for each capsule gastroscope image category, and divided into training set and test set in a ratio of 70%, and 30% respectively, and then based on the dataset, three methods, including as VGG- 16, ResNet-50, and Inception v3 are used. We achieved highest accuracy of 94.80% by using VGG- 16 to diagnose and classify capsule gastroscopic images into three categories: normal gastroscopic image, chronic erosive gastritis images, and ulcer gastric image. Our proposed approach classified capsule gastroscope image with respectable specificity and accuracy. Conclusion: The primary technique and industry standard for diagnosing and treating numerous stomach problems is gastroscopy. Capsule gastroscope is a new screening tool for gastric diseases. However, a number of elements, including image quality of capsule endoscopy, the doctors' experience and fatigue, limit its effectiveness. Early identification is necessary for high-risk factors for carcinogenesis, such as atrophic gastritis (AG). Our suggested framework will help prevent incorrect diagnoses brought on by low image quality, individual experience, and inadequate gastroscopy inspection coverage, among other factors. As a result, the suggested approach will raise the standard of gastroscopy. Deep learning has great potential in gastritis image classification for assisting with achieving accurate diagnoses after endoscopic procedures.
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Affiliation(s)
- Ping Xiao
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
- Department of Otorhinolaryngology Head and Neck Surgery, Shenzhen Children’s Hospital, Shenzhen, China
| | - Yuhang Pan
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Feiyue Cai
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
- Shenzhen Nanshan District General Practice Alliance, Shenzhen, China
| | - Haoran Tu
- Group International Division, Shenzhen Senior High School, Shenzhen, China
| | - Junru Liu
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Xuemei Yang
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Huanling Liang
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Xueqing Zou
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Li Yang
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Jueni Duan
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Long Xv
- Department of Gastroenterology and Hepatology, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Lijuan Feng
- Department of Gastroenterology and Hepatology, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Zhenyu Liu
- Department of Gastroenterology and Hepatology, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Yun Qian
- Department of Gastroenterology and Hepatology, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Yu Meng
- Department of Gastroenterology and Hepatology, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Jingfeng Du
- Department of Gastroenterology and Hepatology, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Xi Mei
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Ting Lou
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
| | - Xiaoxv Yin
- School of Public Health, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen Tan
- Health Management Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China
- Shenzhen Nanshan District General Practice Alliance, Shenzhen, China
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15
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Sidiqi B, Parakrama R, Demyan L, Eckstein J, Nosrati J, Chitti B, Pasha S, Pinto D, Zavadsky T, Zou X, Patruni S, Kapusta A, Weiss M, King D, Herman J, Ghaly M. Stereotactic Body Radiation Therapy (SBRT) in a Standardized Neoadjuvant Therapy Pathway for Pancreatic Cancer across a Geographically Large and Diverse Healthcare System. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1122] [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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16
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Zheng S, Li Z, Liu Y, Zhang H, Zheng P, Liang X, Li Y, Bu X, Zou X. UWB-VIO Fusion for Accurate and Robust Relative Localization of Round Robotic Teams. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3208354] [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: 11/10/2022]
Affiliation(s)
- S. Zheng
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Z. Li
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Y. Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - H. Zhang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - P. Zheng
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - X. Liang
- State Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Y. Li
- State Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - X. Bu
- State Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - X. Zou
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
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17
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Rouhani FJ, Zou X, Danecek P, Badja C, Amarante TD, Koh G, Wu Q, Memari Y, Durbin R, Martincorena I, Bassett AR, Gaffney D, Nik-Zainal S. Substantial somatic genomic variation and selection for BCOR mutations in human induced pluripotent stem cells. Nat Genet 2022; 54:1406-1416. [PMID: 35953586 PMCID: PMC9470532 DOI: 10.1038/s41588-022-01147-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 06/24/2022] [Indexed: 12/27/2022]
Abstract
We explored human induced pluripotent stem cells (hiPSCs) derived from different tissues to gain insights into genomic integrity at single-nucleotide resolution. We used genome sequencing data from two large hiPSC repositories involving 696 hiPSCs and daughter subclones. We find ultraviolet light (UV)-related damage in ~72% of skin fibroblast-derived hiPSCs (F-hiPSCs), occasionally resulting in substantial mutagenesis (up to 15 mutations per megabase). We demonstrate remarkable genomic heterogeneity between independent F-hiPSC clones derived during the same round of reprogramming due to oligoclonal fibroblast populations. In contrast, blood-derived hiPSCs (B-hiPSCs) had fewer mutations and no UV damage but a high prevalence of acquired BCOR mutations (26.9% of lines). We reveal strong selection pressure for BCOR mutations in F-hiPSCs and B-hiPSCs and provide evidence that they arise in vitro. Directed differentiation of hiPSCs and RNA sequencing showed that BCOR mutations have functional consequences. Our work strongly suggests that detailed nucleotide-resolution characterization is essential before using hiPSCs.
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Affiliation(s)
- Foad J Rouhani
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Department of Surgery, University of Cambridge, Cambridge, UK
| | - Xueqing Zou
- Early Cancer Institute, Hutchison/MRC Research Centre, Cambridge Biomedical Research Campus, Cambridge, UK
- Academic Department of Medical Genetics, Addenbrooke's Treatment Centre, Cambridge Biomedical Research Campus, Cambridge, UK
| | - Petr Danecek
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Cherif Badja
- Early Cancer Institute, Hutchison/MRC Research Centre, Cambridge Biomedical Research Campus, Cambridge, UK
- Academic Department of Medical Genetics, Addenbrooke's Treatment Centre, Cambridge Biomedical Research Campus, Cambridge, UK
| | - Tauanne Dias Amarante
- Early Cancer Institute, Hutchison/MRC Research Centre, Cambridge Biomedical Research Campus, Cambridge, UK
| | - Gene Koh
- Early Cancer Institute, Hutchison/MRC Research Centre, Cambridge Biomedical Research Campus, Cambridge, UK
- Academic Department of Medical Genetics, Addenbrooke's Treatment Centre, Cambridge Biomedical Research Campus, Cambridge, UK
| | - Qianxin Wu
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Yasin Memari
- Early Cancer Institute, Hutchison/MRC Research Centre, Cambridge Biomedical Research Campus, Cambridge, UK
| | - Richard Durbin
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Inigo Martincorena
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Andrew R Bassett
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Daniel Gaffney
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Genomics plc, King Charles House, Oxford, UK
| | - Serena Nik-Zainal
- Early Cancer Institute, Hutchison/MRC Research Centre, Cambridge Biomedical Research Campus, Cambridge, UK.
- Academic Department of Medical Genetics, Addenbrooke's Treatment Centre, Cambridge Biomedical Research Campus, Cambridge, UK.
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18
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Xu T, Lei T, Zou X, Wei C, Zhang N, Wang Z. EP08.02-152 Long-Term Survival With Anlotinib in a Patient With Advanced Undifferentiated Large-Cell Lung Cancer and Rare Tonsillar Metastasis. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.835] [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: 10/14/2022]
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19
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Lei T, Xu T, Zou X, Zhang N, Wei C, Wang Z. EP16.04-024 HMGB1-mediated Autophagy Promotes Gefitinib Resistance in Human Non-small Cell Lung Cancer. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.1132] [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: 10/14/2022]
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Ding X, Zhang W, You R, Zou X, Wang Z, Ouyang YF, Liu YL, Peng L, You-Ping L, Duan CY, Yang Q, Lin C, Yulong X, Chen SY, Gu CM, Huang P, Hua Y, Chen M. 663P Camrelizumab plus apatinib in patients with recurrent or metastatic nasopharyngeal carcinoma failing first-line therapy: An open-label, single-arm, phase II study. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.787] [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: 11/01/2022] Open
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21
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Hofer G, Calmanovici Pacoste L, Wang L, Xu H, Zou X. Dare to spin – well diffracting protein nanocrystals through on-vortex crystallisation. Acta Cryst Sect A 2022. [DOI: 10.1107/s2053273322095328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2023]
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22
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Pacoste L, Hofer G, Kumar R, Lebrette H, Choo Lee C, Xu H, Högbom M, Zou X. Charge refinement of metal ion cofactors in protein crystals using microED. Acta Cryst Sect A 2022. [DOI: 10.1107/s2053273322091392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2023]
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23
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Broadhurst E, Mailk T, Jensen E, Yesibolati M, Mølhave K, Xu H, Zou X. In situ liquid phase 3D ED/microED for studying polymorphism. Acta Cryst Sect A 2022. [DOI: 10.1107/s2053273322091562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2023]
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24
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Lightowler M, Li S, Ou X, Hofer G, Cho J, Zou X, Lu M, Xu H. Navigating crystal forms in pharmaceutical compounds by 3DED/microED. Acta Cryst Sect A 2022. [DOI: 10.1107/s2053273322091069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2023]
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Wang L, Hofer G, Zou X, Xu H. Protein crystallization 'de-optimization' for microED. Acta Cryst Sect A 2022. [DOI: 10.1107/s2053273322091434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2023]
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Ching PML, Zou X, Wu D, So RHY, Chen GH. Development of a wide-range soft sensor for predicting wastewater BOD 5 using an eXtreme gradient boosting (XGBoost) machine. Environ Res 2022; 210:112953. [PMID: 35182590 DOI: 10.1016/j.envres.2022.112953] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 02/06/2022] [Accepted: 02/10/2022] [Indexed: 06/14/2023]
Abstract
In wastewater monitoring, detecting extremely high pollutant concentrations is necessary to properly calibrate the treatment process. However, existing hardware sensors have a limited linear range which may fail to measure extremely high levels of pollutants; and likewise, the conventional "soft" model sensors are not suitable for the highly-skewed data distributions either. This study developed a new soft sensor by using eXtreme Gradient Boosting (XGBoost) machine learning to 'measure' the wastewater organics (in terms of 5-day biochemical oxygen demand (BOD5)). The soft sensor was tested on influent and effluent BOD5 of two different wastewater treatment plants to validate the results. The model results showed that XGBoost can detect these extreme values better than conventional soft sensors. This new soft sensor can function using a sparse input matrix via XGBoost's sparsity awareness algorithm - which can address the limitation of the conventional soft sensor with the fallibility of supporting hardware sensors even.
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Affiliation(s)
- P M L Ching
- Bioengineering Graduate Program, Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - X Zou
- Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Di Wu
- Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China; Center for Environmental and Energy Research, Ghent University Global Campus, Republic of Korea; Department of Green Chemistry and Technology, Ghent University, Belgium.
| | - R H Y So
- Department of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - G H Chen
- Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
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Parakrama R, Sidiqi B, Demyan L, Pasha S, Pinto D, Zavadsky T, Zou X, Patruni S, Kapusta A, Standring O, Weiss M, Herman J, King D. P-10 Standardization of a neoadjuvant therapy (NAT) pathway for pancreatic cancer across a geographically large and diverse healthcare system improves patient care and successful completion of NAT. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.102] [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: 11/01/2022] Open
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28
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Degasperi A, Zou X, Amarante TD, Martinez-Martinez A, Koh GCC, Dias JML, Heskin L, Chmelova L, Rinaldi G, Wang VYW, Nanda AS, Bernstein A, Momen SE, Young J, Perez-Gil D, Memari Y, Badja C, Shooter S, Czarnecki J, Brown MA, Davies HR, Nik-Zainal S. Substitution mutational signatures in whole-genome-sequenced cancers in the UK population. Science 2022; 376:science.abl9283. [PMID: 35949260 PMCID: PMC7613262 DOI: 10.1126/science.abl9283] [Citation(s) in RCA: 85] [Impact Index Per Article: 42.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Whole-genome sequencing (WGS) permits comprehensive cancer genome analyses, revealing mutational signatures, imprints of DNA damage and repair processes that have arisen in each patient's cancer. We performed mutational signature analyses on 12,222 WGS tumor-normal matched pairs, from patients recruited via the UK National Health Service. We contrasted our results to two independent cancer WGS datasets, the International Cancer Genome Consortium (ICGC) and Hartwig Foundation, involving 18,640 WGS cancers in total. Our analyses add 40 single and 18 double substitution signatures to the current mutational signature tally. Critically, we show for each organ, that cancers have a limited number of 'common' signatures and a long tail of 'rare' signatures. We provide a practical solution for utilizing this concept of common versus rare signatures in future analyses.
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Affiliation(s)
- Andrea Degasperi
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Xueqing Zou
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Tauanne Dias Amarante
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Andrea Martinez-Martinez
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Gene Ching Chiek Koh
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - João M. L. Dias
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Laura Heskin
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Lucia Chmelova
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Giuseppe Rinaldi
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Valerie Ya Wen Wang
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Arjun S. Nanda
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Aaron Bernstein
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Sophie E. Momen
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Jamie Young
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Daniel Perez-Gil
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Yasin Memari
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Cherif Badja
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Scott Shooter
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Jan Czarnecki
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Matthew A. Brown
- Genomics England, Queen Mary University of London, Dawson Hall, Charterhouse Square, London, EC1M 6BQ, UK
- Faculty of Life Sciences and Medicine, King’s College London, London SE19RT, UK
| | - Helen R. Davies
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Serena Nik-Zainal
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 9NB, UK
- MRC Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK
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Wang Y, Wang H, Song Y, Lv M, Mao Y, Song H, Wang Y, Nie G, Liu X, Cui J, Zou X. IR792-MCN@ZIF-8-PD-L1 siRNA drug delivery system enhances photothermal immunotherapy for triple-negative breast cancer under near-infrared laser irradiation. J Nanobiotechnology 2022; 20:96. [PMID: 35236356 PMCID: PMC8889783 DOI: 10.1186/s12951-022-01255-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [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: 04/27/2021] [Accepted: 01/09/2022] [Indexed: 11/24/2022] Open
Abstract
Background Despite extensive investigations on photothermal therapy, the clinical application is restricted due to poor stability, low therapeutic efficacy of photothermal therapy agents and its affinity loss in the multistep synthesis of delivery carriers. To address this, we designed an IR792-MCN@ZIF-8-PD-L1 siRNA (IM@ZP) nanoparticle drug delivery system. IM@ZP was prepared by in situ synthesis and physical adsorption, followed by characterization. Photothermal conversion ability of IM@ZP was assessed by irradiation of near-infrared (NIR) laser, followed by analysis of its effect on 4T1 cell viability, maturation of dendritic cells (DCs) and the secretion of related cytokines in vitro, and the changes of tumor infiltrating T cells and natural killer (NK) cells in vivo. Subcutaneous 4T1 tumor-bearing mouse and lung metastasis models were established to investigate the role of IM@ZP in killing tumor and inhibiting metastasis in vivo. Results IM@ZP was uniform nanoparticles of 81.67 nm with the characteristic UV absorption peak of IR792, and could effectively adsorb PD-L1 siRNA. Under the irradiation of 808 nm laser, IM@ZP exhibited excellent photothermal performance. IM@ZP could be efficiently uptaken by 4T1 cells, and had high transfection efficiency of PD-L1 siRNA. Upon NIR laser irradiation, IM@ZP effectively killed 4T1 cells, upregulated HSP70 expression, induced DC maturation and increased secretion of TNF-α and IL-6 in vitro. Moreover, in vivo experimental results revealed that IM@ZP enhanced photothermal immunotherapy as shown by promoted tumor infiltrating CD8 + and CD4 + T cells and NK cells, and inhibited tumor growth and lung metastasis. Conclusion Together, biocompatible IM@ZP nanoparticles result in high photothermal immunotherapy efficiency and may have a great potential as a delivery system for sustained cancer therapy. Graphical Abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s12951-022-01255-6.
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Affiliation(s)
- Yongmei Wang
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China.
| | - Haibo Wang
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Yuhua Song
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Meng Lv
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Yan Mao
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Hongming Song
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Yuanyuan Wang
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Gang Nie
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Xiaoyi Liu
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Jian Cui
- Breast Disease Center, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Xueqing Zou
- Department of Anesthesiology, The Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266071, Shandong, People's Republic of China.
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Zhang Z, Qiu S, Huang X, Jin K, Zhou X, Yang M, Lin T, Zou X, Yang Q, Yang L, Wei Q. Association between Testosterone and Serum Soluble α-Klotho in U.S. Males: NHANES 2011-2016. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00480-8] [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: 11/25/2022]
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31
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Wu G, Zou X, Wu Y, Zhang Z, Yuan Y, Zhang G, Xiao R, Wang X, Xu H, Liu F, Liao Y, Xia W, Huang R. Clinical study of urethroplasty combined free grafting of internal preputial lamina with onlay local pedicled flap. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00862-4] [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: 11/29/2022]
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32
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Novak J, Liu J, Zou X, Abuali T, Vazquez J, Kalash R, Evans B, Loscalzo M, Sun V, Brower J, Amini A. Radiation Oncologist Perceptions of Therapeutic Cannabis Use Among Cancer Patients. Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.07.1364] [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: 11/16/2022]
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Abstract
Whole-genome sequencing has brought the cancer genomics community into new territory. Thanks to the sheer power provided by the thousands of mutations present in each patient's cancer, we have been able to discern generic patterns of mutations, termed 'mutational signatures', that arise during tumorigenesis. These mutational signatures provide new insights into the causes of individual cancers, revealing both endogenous and exogenous factors that have influenced cancer development. This Review brings readers up to date in a field that is expanding in computational, experimental and clinical directions. We focus on recent conceptual advances, underscoring some of the caveats associated with using the mutational signature frameworks and highlighting the latest experimental insights. We conclude by bringing attention to areas that are likely to see advancements in clinical applications.
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Affiliation(s)
- Gene Koh
- Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Andrea Degasperi
- Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Xueqing Zou
- Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Sophie Momen
- Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Serena Nik-Zainal
- Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- MRC Cancer Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
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Zhou C, Xie X, Wu J, Guo B, Qin Y, Lin X, Liu M, Qiu L, Xiang J, Chen Z, Zou X. 1273P Sputum supernatant as a viable liquid biopsy in advanced non-small cell lung cancer. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.1875] [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: 11/17/2022] Open
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Liu Z, Zhou Y, Feng WN, Chen MY, Han G, Zou GR, Yang S, He Y, Zou X, Tang J, Zhang L, Cui L, Chen H, Li G, Jiang S, Gao J, Xiao L, Zhang Q, Yi W, Huang C. LBA64 Olanzapine, an alternative to dexamethasone for preventing nausea and vomiting induced by cisplatin-based doublet highly emetogenic chemotherapy: A non-inferiority, prospective, multi-centered, randomized, controlled, phase III clinical trial. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.2145] [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] Open
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36
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Kratz K, Artola-Borán M, Kobayashi-Era S, Koh G, Oliveira G, Kobayashi S, Oliveira A, Zou X, Richter J, Tsuda M, Sasanuma H, Takeda S, Loizou JI, Sartori AA, Nik-Zainal S, Jiricny J. FANCD2-Associated Nuclease 1 Partially Compensates for the Lack of Exonuclease 1 in Mismatch Repair. Mol Cell Biol 2021; 41:e0030321. [PMID: 34228493 PMCID: PMC8384067 DOI: 10.1128/mcb.00303-21] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 06/28/2021] [Indexed: 11/20/2022] Open
Abstract
Germline mutations in the mismatch repair (MMR) genes MSH2, MSH6, MLH1, and PMS2 are linked to cancer of the colon and other organs, characterized by microsatellite instability and a large increase in mutation frequency. Unexpectedly, mutations in EXO1, encoding the only exonuclease genetically implicated in MMR, are not linked to familial cancer and cause a substantially weaker mutator phenotype. This difference could be explained if eukaryotic cells possessed additional exonucleases redundant with EXO1. Analysis of the MLH1 interactome identified FANCD2-associated nuclease 1 (FAN1), a novel enzyme with biochemical properties resembling EXO1. We now show that FAN1 efficiently substitutes for EXO1 in MMR assays and that this functional complementation is modulated by its interaction with MLH1. FAN1 also contributes to MMR in vivo; cells lacking both EXO1 and FAN1 have an MMR defect and display resistance to N-methyl-N-nitrosourea (MNU) and 6-thioguanine (TG). Moreover, FAN1 loss amplifies the mutational profile of EXO1-deficient cells, suggesting that the two nucleases act redundantly in the same antimutagenic pathway. However, the increased drug resistance and mutator phenotype of FAN1/EXO1-deficient cells are less prominent than those seen in cells lacking MSH6 or MLH1. Eukaryotic cells thus apparently possess additional mechanisms that compensate for the loss of EXO1.
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Affiliation(s)
- Katja Kratz
- Institute of Molecular Cancer Research, University of Zurich, Zurich, Switzerland
| | - Mariela Artola-Borán
- Institute of Molecular Cancer Research, University of Zurich, Zurich, Switzerland
| | - Saho Kobayashi-Era
- Institute of Molecular Cancer Research, University of Zurich, Zurich, Switzerland
- Institute of Biochemistry of the ETH Zurich, Zurich, Switzerland
| | - Gene Koh
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- Academic Department of Medical Genetics, The Clinical School, University of Cambridge, Cambridge, United Kingdom
- MRC Cancer Unit, The Clinical School, University of Cambridge, Cambridge, United Kingdom
| | - Goncalo Oliveira
- Institute of Cancer Research, Department of Medicine I, Comprehensive Cancer Centre, Medical University of Vienna, Vienna, Austria
| | - Shunsuke Kobayashi
- Institute of Molecular Cancer Research, University of Zurich, Zurich, Switzerland
- Institute of Biochemistry of the ETH Zurich, Zurich, Switzerland
| | - Andreia Oliveira
- Institute of Molecular Cancer Research, University of Zurich, Zurich, Switzerland
- Institute of Biochemistry of the ETH Zurich, Zurich, Switzerland
| | - Xueqing Zou
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- Academic Department of Medical Genetics, The Clinical School, University of Cambridge, Cambridge, United Kingdom
- MRC Cancer Unit, The Clinical School, University of Cambridge, Cambridge, United Kingdom
| | - Julia Richter
- Institute of Biochemistry of the ETH Zurich, Zurich, Switzerland
| | - Masataka Tsuda
- Department of Radiation Genetics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Hiroyuki Sasanuma
- Department of Radiation Genetics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Shunichi Takeda
- Department of Radiation Genetics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Joanna I. Loizou
- Institute of Cancer Research, Department of Medicine I, Comprehensive Cancer Centre, Medical University of Vienna, Vienna, Austria
| | | | - Serena Nik-Zainal
- Academic Department of Medical Genetics, The Clinical School, University of Cambridge, Cambridge, United Kingdom
- MRC Cancer Unit, The Clinical School, University of Cambridge, Cambridge, United Kingdom
| | - Josef Jiricny
- Institute of Molecular Cancer Research, University of Zurich, Zurich, Switzerland
- Institute of Biochemistry of the ETH Zurich, Zurich, Switzerland
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Qian B, Hao Z, Wang J, Zou X, Zhang G. CD4+, CD8+ T lymphocytes is related to OPN, THP expression in the kidney during the formation of kidney stones caused by nanobacteria. Eur Urol 2021. [DOI: 10.1016/s0302-2838(21)00611-4] [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: 10/20/2022]
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38
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Zou X, Koh GCC, Nanda AS, Degasperi A, Urgo K, Roumeliotis TI, Agu CA, Badja C, Momen S, Young J, Amarante TD, Side L, Brice G, Perez-Alonso V, Rueda D, Gomez C, Bushell W, Harris R, Choudhary JS, Jiricny J, Skarnes WC, Nik-Zainal S. A systematic CRISPR screen defines mutational mechanisms underpinning signatures caused by replication errors and endogenous DNA damage. Nat Cancer 2021; 2:643-657. [PMID: 34164627 PMCID: PMC7611045 DOI: 10.1038/s43018-021-00200-0] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 03/17/2021] [Indexed: 02/02/2023]
Abstract
Mutational signatures are imprints of pathophysiological processes arising through tumorigenesis. We generated isogenic CRISPR-Cas9 knockouts (Δ) of 43 genes in human induced pluripotent stem cells, cultured them in the absence of added DNA damage, and performed whole-genome sequencing of 173 subclones. ΔOGG1, ΔUNG, ΔEXO1, ΔRNF168, ΔMLH1, ΔMSH2, ΔMSH6, ΔPMS1, and ΔPMS2 produced marked mutational signatures indicative of being critical mitigators of endogenous DNA modifications. Detailed analyses revealed mutational mechanistic insights, including how 8-oxo-dG elimination is sequence-context-specific while uracil clearance is sequence-context-independent. Mismatch repair (MMR) deficiency signatures are engendered by oxidative damage (C>A transversions), differential misincorporation by replicative polymerases (T>C and C>T transitions), and we propose a 'reverse template slippage' model for T>A transversions. ΔMLH1, ΔMSH6, and ΔMSH2 signatures were similar to each other but distinct from ΔPMS2. Finally, we developed a classifier, MMRDetect, where application to 7,695 WGS cancers showed enhanced detection of MMR-deficient tumors, with implications for responsiveness to immunotherapies.
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Affiliation(s)
- Xueqing Zou
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Gene Ching Chiek Koh
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Arjun Scott Nanda
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, University of Cambridge, Cambridge, UK
| | - Andrea Degasperi
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, UK
| | | | | | | | - Cherif Badja
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Sophie Momen
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, University of Cambridge, Cambridge, UK
| | - Jamie Young
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Tauanne Dias Amarante
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- MRC Cancer Unit, University of Cambridge, Cambridge, UK
| | - Lucy Side
- UCL Institute for Women's Health, Great Ormond Street Hospital, London, UK
- Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, UK
| | - Glen Brice
- Southwest Thames Regional Genetics Service, St George's University of London, London, UK
| | - Vanesa Perez-Alonso
- Pediatrics Department, Doce de Octubre University Hospital, i+12 Research Institute, Madrid, Spain
| | - Daniel Rueda
- Hereditary Cancer Laboratory, Doce de Octubre University Hospital, i+12 Research Institute, Madrid, Spain
| | | | | | - Rebecca Harris
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Jyoti S Choudhary
- The Institute of Cancer Research, Chester Beatty Laboratories, London, UK
| | - Josef Jiricny
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- Institute of Biochemistry, ETH Zurich, Zurich, Switzerland
| | - William C Skarnes
- Wellcome Sanger Institute, Hinxton, UK
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Serena Nik-Zainal
- Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- MRC Cancer Unit, University of Cambridge, Cambridge, UK.
- Wellcome Sanger Institute, Hinxton, UK.
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Zou X, Song XM, Wang J. [Biological features of cardiac endothelial cells and their role and mechanism on regulating heart failure]. Zhonghua Xin Xue Guan Bing Za Zhi 2021; 49:318-323. [PMID: 33874680 DOI: 10.3760/cma.j.cn112148-20200521-00418] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- X Zou
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100730, China
| | - X M Song
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100730, China
| | - J Wang
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100730, China
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Sun W, Zou X, Zhang W, Hu S, Ge K. [Clinical efficacy of anlotinib plus S-1 as a second-line therapy for recurrent or metastatic esophageal squamous cell carcinoma]. Nan Fang Yi Ke Da Xue Xue Bao 2021; 41:250-255. [PMID: 33624599 DOI: 10.12122/j.issn.1673-4254.2021.02.13] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
OBJECTIVE To investigate the efficacy of anlotinib plus S-1 for treatment of patients with recurrent or metastatic esophageal squamous cell carcinoma with failed first-line chemotherapy. OBJECTIVE Twenty-six patients with recurrent or metastatic esophageal squamous cell carcinoma patients who experienced progression after first-line paclitaxel plus platinum chemotherapy in our hospital between July, 2018 and February, 2020 were enrolled in this study. The patients received oral anlotinib along with S-1 treatment (anlotinib at 12 mg once daily and S-1 at 50 mg twice daily for two weeks; 3 weeks per cycle). The objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS) and adverse effects were evaluated for all the patients. OBJECTIVE No complete remission (CR) was observed in the 26 patients. Partial remission (PR) was achieved in 6 cases, stable disease (SD) in 12 cases, and progressive disease (PD) occurred in 8 cases, with an ORR of 23.1% and a DCR of 69.2% in these patients. The median PFS was 4.5 months (95%CI: 2.7-6.4 months). Univariate analysis showed that the patients with moderate or high tumor differentiation had significantly longer PFS than those with low tumor differentiation (6.1 months vs 1.9 months, P < 0.05). Multivariate analysis suggested that pathological differentiation grade (HR=6.778, 95%CI: 1.997-23.012) was an independent factor for a prolonged PFS. The adverse effects in the patients included mainly fatigue, hypertension and hand-foot syndrome, mostly of grade 1 to 2. OBJECTIVE Patients with recurrent or metastatic esophageal squamous cell carcinoma can benefit from a second-line anlotinib plus S-1 treatment, which has relatively mild adverse effects with a good safety profile.
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Affiliation(s)
- W Sun
- Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing 210029, China
| | - X Zou
- Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing 210029, China
| | - W Zhang
- Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing 210029, China
| | - S Hu
- Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing 210029, China
| | - K Ge
- Depaetment of Oncology, Liyang Hospital of Chinese Medicine, Jiangsu Provincial Hospital of Chinese Medicine Liyang Branch, Liyang 213300, China
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41
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Zhang D, Zou X, Song Y, Wu D. [Long non-coding RNA UPK1A-AS1 promotes glycolysis in hepatocellular carcinoma cells via stabilization of HIF-1 α]. Nan Fang Yi Ke Da Xue Xue Bao 2021; 41:193-199. [PMID: 33624591 DOI: 10.12122/j.issn.1673-4254.2021.02.05] [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: 11/24/2022]
Abstract
OBJECTIVE To investigate the effect of long non-coding RNA UPK1A-AS1 on glycolysis of hepatocellular carcinoma cells and its underlying molecular mechanisms. OBJECTIVE A hepatocellular carcinoma (HCC) cell line with lentivirus-mediated stable UPK1A-AS1 overexpression and the cells infected with a negative control lentiviral vector were cultured under normoxic (21% O2) or hypoxic (1% O2) conditions for 24 h. The effect of UPK1A-AS1 overexpression on glycolysis of the HCC cells was examined. The expressions of glycolysis-related genes HIF1A, GLUT1, HK1, HK2 and PGK1 were detected by qRTPCR, and the effect of UPK1A-AS1 overexpression on HRE activity was detected by dual luciferase report assay. The HCC cells were treated with cycloheximide to detect the effect of UPK1A-AS1 overexpression on the stability of HIF-1α protein. Immunoprecipitation assay was used to analyze the changes in ubiquitin modification of HIF-1α protein in response to UPK1A-AS1 overexpression. The effects of UPK1A-AS1 overexpression and RNA interference of HIF-1α expression on glucose consumption, lactate production and expressions of HRE activity and glycolysis-related genes (HK1, HK2 and PGK1) were examined in the HCC cells. OBJECTIVE Compared with the control group, overexpression of UPK1A-AS1 significantly promoted glucose consumption and lactate production in HCC cells under both normoxic and hypoxic conditions (P < 0.05). Overexpression of UPK1A-AS1 significantly increased the expression of glycolysis-related genes including HIF1A, GLUT1, HK1, HK2 and PGK1. Upregulation of UPK1A-AS1 obviously promoted the transcriptional activity of HRE (P < 0.05). Western blotting showed that UPK1A-AS1 overexpression obviously increased the stability of HIF-1α protein and significantly reduced ubiquitin modification of HIF-1α. Downregulation of HIF-1α obviously reversed the effect of UPK1A-AS1 overexpression in promoting glucose consumption, lactate production and HRE luciferase activity. Silencing HIF-1α also suppressed the upregulation of glycolysis-related gene expressions induced by UPK1A-AS1 overexpression (P < 0.05). OBJECTIVE The long noncoding RNA UPK1A-AS1 upregulates the expression of glycolysis-related genes by stabilizing the expression of HIF-1α, thereby promoting glycolysis level in HCC cells.
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Affiliation(s)
- D Zhang
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - X Zou
- Hepatology Unit and Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Y Song
- Hepatology Unit and Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - D Wu
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
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Davies HR, Broad KD, Onadim Z, Price EA, Zou X, Sheriff I, Karaa EK, Scheimberg I, Reddy MA, Sagoo MS, Ohnuma SI, Nik-Zainal S. Whole-Genome Sequencing of Retinoblastoma Reveals the Diversity of Rearrangements Disrupting RB1 and Uncovers a Treatment-Related Mutational Signature. Cancers (Basel) 2021; 13:754. [PMID: 33670346 PMCID: PMC7918943 DOI: 10.3390/cancers13040754] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 02/02/2021] [Accepted: 02/09/2021] [Indexed: 02/06/2023] Open
Abstract
The development of retinoblastoma is thought to require pathological genetic changes in both alleles of the RB1 gene. However, cases exist where RB1 mutations are undetectable, suggesting alternative pathways to malignancy. We used whole-genome sequencing (WGS) and transcriptomics to investigate the landscape of sporadic retinoblastomas derived from twenty patients, sought RB1 and other driver mutations and investigated mutational signatures. At least one RB1 mutation was identified in all retinoblastomas, including new mutations in addition to those previously identified by clinical screening. Ten tumours carried structural rearrangements involving RB1 ranging from relatively simple to extremely complex rearrangement patterns, including a chromothripsis-like pattern in one tumour. Bilateral tumours obtained from one patient harboured conserved germline but divergent somatic RB1 mutations, indicating independent evolution. Mutational signature analysis showed predominance of signatures associated with cell division, an absence of ultraviolet-related DNA damage and a profound platinum-related mutational signature in a chemotherapy-exposed tumour. Most RB1 mutations are identifiable by clinical screening. However, the increased resolution and ability to detect otherwise elusive rearrangements by WGS have important repercussions on clinical management and advice on recurrence risks.
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Affiliation(s)
- Helen R. Davies
- Academic Department of Medical Genetics, University of Cambridge, Addenbrooke’s Treatment Centre, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (H.R.D.); (X.Z.)
- MRC Cancer Unit, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Kevin D. Broad
- Institute of Ophthalmology, University College London, London EC1V 9EL, UK;
| | - Zerrin Onadim
- Retinoblastoma Genetic Screening Unit, The Royal London Hospital, Barts Health NHS Trust, London E1 1FR, UK; (Z.O.); (E.A.P.)
| | - Elizabeth A. Price
- Retinoblastoma Genetic Screening Unit, The Royal London Hospital, Barts Health NHS Trust, London E1 1FR, UK; (Z.O.); (E.A.P.)
| | - Xueqing Zou
- Academic Department of Medical Genetics, University of Cambridge, Addenbrooke’s Treatment Centre, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (H.R.D.); (X.Z.)
- MRC Cancer Unit, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0XZ, UK
| | - Ibrahim Sheriff
- Retinoblastoma Service, Royal London Hospital, Barts Health Trust, London E1 1FR, UK; (I.S.); (M.A.R.)
| | - Esin Kotiloğlu Karaa
- Pathology Department, Royal London Hospital, Barts Health NHS Trust, London E1 1FR, UK; (E.K.K.); (I.S.)
| | - Irene Scheimberg
- Pathology Department, Royal London Hospital, Barts Health NHS Trust, London E1 1FR, UK; (E.K.K.); (I.S.)
| | - M. Ashwin Reddy
- Retinoblastoma Service, Royal London Hospital, Barts Health Trust, London E1 1FR, UK; (I.S.); (M.A.R.)
- NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital, Institute of Ophthalmology, University College London, London EC1V 2PD, UK
| | - Mandeep S. Sagoo
- Institute of Ophthalmology, University College London, London EC1V 9EL, UK;
- Retinoblastoma Service, Royal London Hospital, Barts Health Trust, London E1 1FR, UK; (I.S.); (M.A.R.)
- NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital, Institute of Ophthalmology, University College London, London EC1V 2PD, UK
| | - Shin-ichi Ohnuma
- Institute of Ophthalmology, University College London, London EC1V 9EL, UK;
| | - Serena Nik-Zainal
- Academic Department of Medical Genetics, University of Cambridge, Addenbrooke’s Treatment Centre, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (H.R.D.); (X.Z.)
- MRC Cancer Unit, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0XZ, UK
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Gallier S, Atkin C, Reddy-Kolanu V, Parekh D, Zou X, Evison F, Ball S, Sapey E. Applying a COVID Virtual Ward model, assessing patient outcomes and staff workload. Acute Med 2021; 20:266-275. [PMID: 35072383 DOI: 10.52964/amja.0876] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
A COVID virtual ward (CVW) is recommended by NHS England, but 'usual care' outcomes have not been reported. A retrospective study of all adults with COVID-19 attending Queen Elizabeth Hospital Birmingham between 01/06/2020-31/01/2021, assessed against CVW criteria and followed for 28 days. Of 2301 COVID-19 patients, 571(25%) would have met CVW criteria. Of these, 325(57%) were discharged after review and 246(43%) admitted. Of admitted patients who met CVW criteria, 81% required hospital-supported therapies; 11% died. Of the 325 discharged, 13% re-presented, 9% with COVID-related symptoms, 2% required intensive care admission, and one died (0.3%). In this comparison, discharging patients without a CVW did not lead to more re-presentations, re-admissions, ITU escalations or deaths compared to published outcomes for hospitals with a CVW.
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Affiliation(s)
- S Gallier
- PIONEER Technical Director, Lead for Research Analytics Department of Health Informatics Health Informatics, University Hospitals Birmingham NHS Foundation Trust
| | - C Atkin
- NIHR Lecturer in Acute Medicine Institute of Inflammation and Ageing, University of Birmingham
| | - V Reddy-Kolanu
- Consultant in Acute Medicine University Hospitals Birmingham NHS Foundation Trust
| | - D Parekh
- Senior Lecturer in Acute Care, Birmingham Acute Care Research Group Institute of Inflammation and Ageing, University of Birmingham
| | - X Zou
- Research Analytics, Health Informatics University Hospitals Birmingham NHS Foundation Trust
| | - F Evison
- Senior Research Analysis Health Informatics, University Hospitals Birmingham NHS Foundation Trust
| | - S Ball
- Cheif Medical Officer, Director of Better Care Programme University Hospitals Birmingham NHS Foundation Trust
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Luo M, Zou X. morphological changes of retina in patients with Parkinson's disease and the role of α-synuclein in retinal damage. Parkinsonism Relat Disord 2020. [DOI: 10.1016/j.parkreldis.2020.06.201] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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45
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Wen Y, Zou X, Luo M. Vowel speech analysis for Parkinson's Disease. Parkinsonism Relat Disord 2020. [DOI: 10.1016/j.parkreldis.2020.06.368] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Zou X, Koh G, Nanda S, Degasperi A, Urgo K, Bushell W, Agu C, Perez-Alonso V, Rueda D, Foreman J, Harris R, Jiricny J, Skarnes B, Nik-Zainal S. Abstract 4887: Direct mutational consequences of CRISPR-cas9 gene-edited DNA repair genes. Cancer Res 2020. [DOI: 10.1158/1538-7445.am2020-4887] [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: 11/16/2022]
Abstract
Abstract
Cancer whole-genome sequencing has revealed characteristic mutational signatures associated with defective DNA repair that underpin human genetic diseases. To define the direct mutagenic effects of DNA repair deficiency at the genome-wide level, we investigate mutational signatures generated by CRISPR-Cas9-based knockouts of 42 genes involved in DNA repair/replication using a human-induced pluripotent stem cell line. Knockouts (Δ) of nine DNA repair genes reveal substitution/indel mutational signatures. Notably, dissection of signatures of defective mismatch repair (MMR) uncovers gene-specific characteristics including distinguishing features of ΔMLH1, ΔMSH2, and ΔMSH6 from ΔPMS2. This gene-specificity is also exhibited by hIPSCs derived from patients with autosomal recessive Constitutional Mismatch Repair Deficiency (CMMRD) that carry biallelic germline mutations of MMR genes. Furthermore, gene-specificity manifests in whole genome sequenced primary human cancers. Additionally, detailed analyses reveal putative sources of endogenous DNA damage that contribute to MMR signatures, including guanine oxidation, errors of DNA polymerases and reversed template slippage or double slippage. Finally, we find that using all mutational signatures of MMR-deficiency as identified in this study results in improved sensitivity and specificity in classifying MMR-deficient tumors, critical for accurate patient stratification for therapeutic intervention.
Citation Format: Xueqing Zou, Gene Koh, Scott Nanda, Andrea Degasperi, Katie Urgo, Wendy Bushell, Chukwuma Agu, Vanesa Perez-Alonso, Daniel Rueda, Julia Foreman, Rebecca Harris, Josef Jiricny, Bill Skarnes, Serena Nik-Zainal. Direct mutational consequences of CRISPR-cas9 gene-edited DNA repair genes [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4887.
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Affiliation(s)
- Xueqing Zou
- 1University of Cambridge, Cambridge, United Kingdom
| | - Gene Koh
- 1University of Cambridge, Cambridge, United Kingdom
| | - Scott Nanda
- 1University of Cambridge, Cambridge, United Kingdom
| | | | - Katie Urgo
- 2Sanger Institute, Cambridge, United Kingdom
| | | | | | | | - Daniel Rueda
- 3Doce de Octubre University Hospital, Madrid, Spain
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Zou X, Zou J, Zhang G, Liu Q, Xie T, He Z, Chen H. Knockout of Phosphatidylethanolamine Binding Protein 4 (PEBP4) Induces prostatovesiculitis via NF-κB signaling. EUR UROL SUPPL 2020. [DOI: 10.1016/s2666-1683(20)32699-9] [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: 10/23/2022] Open
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48
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Zou X, Zhang G, Wu G, Wang X, Xu H, Wu Y. Suprapubic robot-assisted laparoendoscopic single-site surgery (SRA-LESS) in urology (report of 16 cases). EUR UROL SUPPL 2020. [DOI: 10.1016/s2666-1683(20)32703-8] [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: 11/16/2022] Open
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49
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Degasperi A, Amarante TD, Czarnecki J, Shooter S, Zou X, Glodzik D, Morganella S, Nanda AS, Badja C, Koh G, Momen SE, Georgakopoulos-Soares I, Dias JML, Young J, Memari Y, Davies H, Nik-Zainal S. Author Correction: A practical framework and online tool for mutational signature analyses show intertissue variation and driver dependencies. Nat Cancer 2020; 1:748. [PMID: 35122044 DOI: 10.1038/s43018-020-0093-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Affiliation(s)
- Andrea Degasperi
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Tauanne Dias Amarante
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Jan Czarnecki
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Scott Shooter
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Xueqing Zou
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Dominik Glodzik
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Department of Clinical Sciences, Lund University, Lund, Sweden
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sandro Morganella
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Congenica Ltd, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Arjun S Nanda
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
| | - Cherif Badja
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Gene Koh
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Sophie E Momen
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
| | | | - João M L Dias
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
| | - Jamie Young
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Yasin Memari
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
| | - Helen Davies
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Serena Nik-Zainal
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK.
- Academic Laboratory of Medical Genetics, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
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Sun J, Zou X, Zhong L. CRISPR/dCas9-mediated activation of multiple endogenous target genes directly reprograms human foreskin fibroblasts into Leydig-like cells. EUR UROL SUPPL 2020. [DOI: 10.1016/s2666-1683(20)32626-4] [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: 10/23/2022] Open
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