1
|
Song MF, Ma LY, Shen C, Zhao Q, Zhao CY. [Liver cancer treatment with mitochondrial homeostasis]. Zhonghua Gan Zang Bing Za Zhi 2024; 32:257-261. [PMID: 38584111 DOI: 10.3760/cma.j.cn501113-20231107-00175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Systemic treatment, including molecular targeted therapy, immunotherapy, and chemotherapy, is an important means of achieving long-term survival in patients with intermediate-and advanced-stage liver cancer. However, some patients are insensitive to treatment and even develop drug resistance. Mitochondria are the center of cellular energy metabolism and, at the same time, are the priority targets for systemic therapy. Mitochondrial homeostasis plays an important role in the treatment of liver cancer. The relationship between the two advances is elucidated so as to provide better ideas for the clinical treatment of liver cancer.
Collapse
Affiliation(s)
- M F Song
- Department of Infectious Disease, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| | - L Y Ma
- Department of Infectious Disease, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| | - C Shen
- Department of Infectious Disease, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| | - Q Zhao
- Quality Management and Control Office, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| | - C Y Zhao
- Department of Infectious Disease, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| |
Collapse
|
2
|
Peidli S, Green TD, Shen C, Gross T, Min J, Garda S, Yuan B, Schumacher LJ, Taylor-King JP, Marks DS, Luna A, Blüthgen N, Sander C. scPerturb: harmonized single-cell perturbation data. Nat Methods 2024; 21:531-540. [PMID: 38279009 DOI: 10.1038/s41592-023-02144-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 12/04/2023] [Indexed: 01/28/2024]
Abstract
Analysis across a growing number of single-cell perturbation datasets is hampered by poor data interoperability. To facilitate development and benchmarking of computational methods, we collect a set of 44 publicly available single-cell perturbation-response datasets with molecular readouts, including transcriptomics, proteomics and epigenomics. We apply uniform quality control pipelines and harmonize feature annotations. The resulting information resource, scPerturb, enables development and testing of computational methods, and facilitates comparison and integration across datasets. We describe energy statistics (E-statistics) for quantification of perturbation effects and significance testing, and demonstrate E-distance as a general distance measure between sets of single-cell expression profiles. We illustrate the application of E-statistics for quantifying similarity and efficacy of perturbations. The perturbation-response datasets and E-statistics computation software are publicly available at scperturb.org. This work provides an information resource for researchers working with single-cell perturbation data and recommendations for experimental design, including optimal cell counts and read depth.
Collapse
Affiliation(s)
- Stefan Peidli
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität, Berlin, Germany.
- Institute of Biology, Humboldt-Universität, Berlin, Germany.
| | - Tessa D Green
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Ciyue Shen
- Departments of Cell Biology and Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | | | - Joseph Min
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Samuele Garda
- Institute of Biology, Humboldt-Universität, Berlin, Germany
- Institute for Computer Science, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Bo Yuan
- Departments of Cell Biology and Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Linus J Schumacher
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | | | - Debora S Marks
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Augustin Luna
- Departments of Cell Biology and Systems Biology, Harvard Medical School, Boston, MA, USA.
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
- Broad Institute, Cambridge, MA, USA.
- Computational Biology Branch, National Library of Medicine and Developmental Therapeutics Branch, National Cancer Institute, Bethesda, MD, USA.
| | - Nils Blüthgen
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität, Berlin, Germany.
- Institute of Biology, Humboldt-Universität, Berlin, Germany.
| | - Chris Sander
- Departments of Cell Biology and Systems Biology, Harvard Medical School, Boston, MA, USA.
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
- Broad Institute, Cambridge, MA, USA.
| |
Collapse
|
3
|
Song MF, Ma LY, Zhao Q, Shen C, Zhao CY. [Research progress on the mechanism and response strategies of molecular targeted drug resistance in liver cancer]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:1108-1112. [PMID: 38016782 DOI: 10.3760/cma.j.cn501113-20220723-00393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/30/2023]
Abstract
Molecular targeted drugs are one of the treatments for hepatocellular carcinoma (HCC), the primary factor influencing their therapeutic efficacy is drug resistance. Diminished drug intake, greater efflux, improved DNA damage repair capacity, aberrant signal pathways, hypoxia, epithelial-mesenchymal cell transition, and the cellular autophagy system are summarized herein as aspects of the drug resistance mechanism. Simultaneously, effective strategies for addressing drug resistance are elaborated, providing ideas for better clinical treatment of HCC.
Collapse
Affiliation(s)
- M F Song
- Department of Infectious Disease, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| | - L Y Ma
- Department of Infectious Disease, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| | - Q Zhao
- Quality Management and Control Office, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| | - C Shen
- Department of Infectious Disease, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| | - C Y Zhao
- Department of Infectious Disease, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
| |
Collapse
|
4
|
Liu K, Chen YJ, Su J, Fan XK, Yu H, Qin Y, Yang J, Zhu Z, Guan HY, Shen C, Pan EC, Lu Y, Zhou JY, Wu M. [Association of category of dietary intake and physical activity with the risk of mortality in patients with type 2 diabetes mellitus: a prospective cohort study]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1591-1598. [PMID: 37875446 DOI: 10.3760/cma.j.cn112338-20230328-00188] [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: 10/26/2023]
Abstract
Objective: To investigate the association between dietary intake and physical activity category and their combined effects on all-cause and cause-specific mortality risk in patients with type 2 diabetes mellitus (T2DM). Methods: Between December 2013 and December 2021, a prospective cohort study was conducted on 19 863 T2DM patients in Changshu City, Qingjiangpu District (formerly Qinghe District), and Huai'an District, included in the national basic health service management. Information on deaths and underlying causes of death was obtained from the Jiangsu Provincial CDC and Prevention Death Surveillance System. Cox proportional hazards models were used to estimate the intensity of associations between dietary intake, physical activity, and their combined effects with all-cause and cause-specific mortality in patients with T2DM. Results: As of December 31, 2021, the research subjects had been followed up for 150 283 person-years, with a median follow-up time of 8.15 years. During the follow-up period, 3 293 people died, including 1 124 deaths from cardiovascular disease (CVD) and 875 deaths from cancer. Cox regression analysis showed that compared with the population of 0-1 recommended food group, those having more than five recommended food groups had a 19% lower risk of all-cause mortality [hazard ratio (HR)=0.81, 95%CI: 0.70-0.94] and a 33% lower risk of all-cause mortality (HR=0.67, 95%CI: 0.52-0.87). Compared with the T2DM population in the physical activity Q1 group, the risk of all-cause mortality, CVD mortality, and cancer mortality among the physical activity Q4 group reduced by 50% (HR=0.50, 95%CI: 0.45-0.56), 50% (HR=0.50, 95%CI: 0.41-0.61), and 27% (HR=0.73, 95%CI: 0.60-0.88), respectively. The combined effect showed that compared with the population in the intake of food categories 0-2 and low physical activity groups, the risk of all-cause, CVD mortality, and cancer mortality in the intake of food categories 4-9 and high physical activity groups reduced by 55% (HR=0.45, 95%CI: 0.38-0.53), 56% (HR=0.44, 95%CI: 0.32-0.59), and 40% (HR=0.60, 95%CI: 0.44-0.82), respectively. Conclusion: Type of dietary intake, physical activity, and their combined effects are associated with a reduced mortality risk in patients with T2DM.
Collapse
Affiliation(s)
- K Liu
- School of Public Health, Southeast University, Nanjing 210009, China
| | - Y J Chen
- Department of Non-communicable Chronic Disease Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing 210003, China
| | - J Su
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - X K Fan
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H Yu
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Y Qin
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Yang
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Z Zhu
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H Y Guan
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - C Shen
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - E C Pan
- Department of Chronic Disease Prevention and Control, Huai'an City Center for Disease Control and Prevention, Huai'an 223001, China
| | - Y Lu
- Department of Chronic Disease Prevention and Control, Suzhou City Center for Disease Control and Prevention, Suzhou 215004, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - M Wu
- School of Public Health, Southeast University, Nanjing 210009, China Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| |
Collapse
|
5
|
Morse R, Beaty B, Moon DH, Green R, Xu V, Weiss J, Sheth S, Patel S, Blumberg J, Hackman T, Lumley C, Patel S, Yarbrough W, Huff SB, Repka MC, Dagan R, Amdur RJ, Chera BS, Shen C, Chen X. Long-Term Outcomes of De-Intensified Chemoradiotherapy for Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma. Int J Radiat Oncol Biol Phys 2023; 117:S123-S124. [PMID: 37784319 DOI: 10.1016/j.ijrobp.2023.06.464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To report long-term oncologic outcomes among patients with human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) treated with definitive de-intensified chemoradiotherapy. MATERIALS/METHODS Major criteria for de-intensification were (1) AJCC 7th edition T0-T3, N0-N2c, M0 (AJCC 8th edition T0-T3, N0-N2, M0), (2) pathologically confirmed p16 positive, and (3) no or minimal/remote smoking history (non-mutated p53 if ≥30 pack-years). Treatment was 60 Gy intensity-modulated radiotherapy with first-choice concurrent cisplatin 30 mg/m2 once per week (alternative regimens permissible for cisplatin ineligible patients). Patients with T0-T2 N0-1 (AJCC 7th edition) were recommended 60 Gy radiation alone. Systemic therapy received included: cisplatin 30 mg/m2 (n = 122), cetuximab (n = 15), cisplatin 40 mg/m2 (n = 12), carboplatin/paclitaxel (n = 2), and radiation alone (n = 25). Kaplan Meier estimates for overall survival (OS), progression-free survival (PFS), locoregional control (LRC), and freedom from distant metastasis (FFDM) were calculated. Cox regression models were used for comparisons among subgroups. RESULTS A total 176 patients received de-intensified treatment (n = 153 prospective protocol, n = 23 off-protocol). Median follow-up was 52.6 months (range 5.3 - 102.0, 90.8% with minimum 2-year follow-up); 56.8% (n = 100) were never smokers and 43.2% (n = 76) former smokers; former smokers had median 9 pack-years smoking history (range 0.25 - 50) with 46% ≥10 pack-years. Outcomes were as follows: 2-year OS 99.4% and 5-year OS 91.8%; 2-year PFS 94.1% and 5-year PFS 84.3%; 2-year LRC 98.3% and 5-year LRC 95.8%; 2-year FFDM 95.8% and 5-year FFDM 93.2%. Median time to progression events were 21.1 months (range, 7.2 - 54.1) with 37.5% (6 of 16) of recurrences occurring after 24 months. Six total locoregional events occurred (five recurrences and one site of persistent disease), within the 60 Gy planning target volume. Twenty-three patients with T0-T2 N0-1 disease received radiation alone with 2-year PFS 92.9% (5-year 83.8%) and 2-year LRC 100% (5-year 95.2%). Outcomes for former smokers with ≥10 pack-years were comparable to patients with less or no smoking history (2-year PFS 94.1% vs 94.1%; 5-year PFS 90.6% vs 82.7%; HR 0.58, p = 0.38). Early results suggest similar oncologic outcomes among those treated off-protocol (median follow-up 25.6 months) with 1 of 23 patients experiencing locoregional recurrence. CONCLUSION Dose de-intensification of 60 Gy radiotherapy with weekly cisplatin results in favorable long-term tumor control in patients with HPV-associated OPSCC. De-intensified 60 Gy alone may be efficacious in carefully selected patients with T0-T2 N0-1 (AJCC 7th edition) disease. Inclusion of biologically favorable patients with more extensive former smoking history in de-intensification clinical trials may be warranted.
Collapse
Affiliation(s)
- R Morse
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - B Beaty
- Albert Einstein College of Medicine, Bronx, NY
| | - D H Moon
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - R Green
- University of North Carolina Hospitals, Chapel Hill, NC
| | - V Xu
- University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - J Weiss
- University of North Carolina Lineberger Comprehensive Cancer Center, Chapel Hill, NC
| | - S Sheth
- University of North Carolina Lineberger Comprehensive Cancer Center, Chapel Hill, NC
| | - S Patel
- University of North Carolina Hospitals, Chapel Hill, NC
| | | | - T Hackman
- Department of Otolaryngology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - C Lumley
- UNC School of Medicine, Chapel Hill, NC
| | - S Patel
- UNC School of Medicine, Chapel Hill, NC
| | | | - S B Huff
- University of Carolina, Chapel Hill, NC
| | - M C Repka
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - R Dagan
- University of Florida Health Proton Therapy Institute, Jacksonville, FL
| | - R J Amdur
- University of Florida Hospitals, Gainesville, FL
| | - B S Chera
- Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - X Chen
- Case Western Reserve University School of Medicine, Cleveland, OH
| |
Collapse
|
6
|
Young MD, Rohlman A, Shen C, Casey DL. The Role of Whole Abdomen and Pelvis Radiation Therapy in Desmoplastic Small Round Cell Tumor. Int J Radiat Oncol Biol Phys 2023; 117:S133. [PMID: 37784343 DOI: 10.1016/j.ijrobp.2023.06.485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Desmoplastic small round cell tumor (DSRCT) is a rare entity that typically presents in adolescent and young adult men with widespread abdominopelvic disease. The benefit of whole abdomen and pelvis radiation therapy (WAPRT) after chemotherapy and maximal surgical resection is unknown. Our objective was to evaluate the oncologic benefit and toxicity of WAPRT in this rare and aggressive disease. MATERIALS/METHODS We conducteda retrospective review of patients with DSRCT treated at our institution primarily between 2018-2021. The cumulative incidence (CI) of intra-abdominopelvic failure was compared among those who received WAPRT after chemotherapy and surgery vs those who received chemotherapy and surgery alone without WAPRT utilizing Gray's method. Progression-free survival (PFS) and overall survival (OS) were also compared among patients who did and did not receive WAPRT using the Kaplan-Meier method from the date of surgery. Toxicity was graded per CTCAE v5.0 criteria. RESULTS Twenty-eight patients were included (median age 17.5 years; range 6-38 years; 78% male, 22% female). All patients received chemotherapy with VDC/IE, all but one underwent extensive tumor resection, and all but two received HIPEC at time of resection. Nineteen patients (median age 13 years) received WAPRT after surgery, while 9 patients (median age 24 years) were treated with systemic therapy and surgery alone. Patients who received WAPRT were generally treated to 30 Gy in 20 fractions utilizing intensity-modulated radiation therapy (IMRT), with a boost to gross disease to a total dose of 45-50 Gy in 9 patients. Median follow up was 20 months. The CI of intra-abdominopelvic failure at 12 and 24 months was 16% and 50% with WAPRT vs 74% and 87% without WAPRT (p = 0.003), with a median time from surgery to intra-abdominopelvic failure of 15 months after WAPRT vs 5 months without. PFS was also improved with WAP-RT (94% and 83% at 12 and 24 months) vs without WAPRT (67% and 0% at 12 and 24 months), p = 0.001. Among those who received WAPRT, patients who received a boost to gross disease had similar intra-abdominopelvic control as those who had no gross disease to boost and received WAPRT only (CI at 24 months 50% without boost vs 48% with, p = 0.95). OS did not differ between those who did and did not receive WAPRT (OS at 24 months, 88% vs 83%, p = 0.89). Most toxicities after WAPRT were mild, including grade 1-2 fatigue, nausea, and vomiting, with the exception of one patient who developed veno-occlusive disease. CONCLUSION Although limited by selection bias and short follow up, our study shows durable intra-abdominopelvic control and an improvement in PFS after WAPRT with IMRT, without an effect on OS. Additional larger, prospective investigations evaluating the value and toxicity of WAPRT for DSRCT are warranted.
Collapse
Affiliation(s)
- M D Young
- Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - A Rohlman
- University of North Carolina Chapel Hill, Chapel Hill, NC
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - D L Casey
- Memorial Sloan Kettering Cancer Center, New York, NY
| |
Collapse
|
7
|
Wang K, Shen C, Pacholke HD, Deal A, Pearlstein KA, Weiner AA, Xu V, Danquah F, Wahl DR, Jackson WC, Dess RT, Dragovic AF, Marks LB, Chera BS, Kim MM. Results of a Multi-institutional Randomized Phase 3 Trial of Parotid-Sparing Whole Brain Radiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:S74-S75. [PMID: 37784566 DOI: 10.1016/j.ijrobp.2023.06.387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Observational studies have reported that xerostomia is common after conventional whole brain radiotherapy (WBRT) and associated with parotid dose. In this multi-institutional, single-blind randomized controlled trial, we hypothesized that patient-reported xerostomia is reduced in patients randomized to parotid-sparing vs. standard WBRT fields. MATERIALS/METHODS Between 2018 and 2021, patients receiving conventional WBRT (30-35 Gy in 10-15 fractions) for any diagnosis were enrolled at 3 academic institutions. Patients were randomized between standard WBRT fields covering the C1 vertebra with no prospective parotid delineation (control) vs. parotid-sparing fields without C1 coverage (experimental). Patients completed the University of Michigan Xerostomia Questionnaire (Scored 0-100, higher is worse) at baseline, EndRT, 2 weeks, 1 month, 3 months, and 6 months. Patients were excluded from toxicity analyses if baseline xerostomia score was >50 or if they did not complete any post-baseline questionnaires. The primary endpoint was proportion of patients with ≥15 point absolute increase in xerostomia score from baseline to 1 month; 108 patients were needed for an 80% power to detect a 22% absolute difference (1-sided significance of 0.05). The secondary endpoint was the rate of marginal failures. RESULTS The study closed early after 56 patients were randomized. Median survival was 4.6 months. 46 patients (23 in each arm) were eligible for analysis. Mean parotid dose was 17 vs. 10 Gy in the standard vs. parotid-sparing arms, respectively. The table below shows mean xerostomia score and proportion of patients with ≥15 increase in xerostomia score at each time point. There was no difference in the proportion of patients experiencing ≥15 increase in xerostomia score at 1 month, though there was a trend toward lower xerostomia score at 1 month in patients randomized to parotid-sparing fields (p = 0.07, Table). Xerostomia rates were also significantly improved in the parotid-sparing arm at EndRT (p = 0.03), but no longer-term difference was observed with greater attrition at 3 and 6 months. On linear regression, there was a trend toward association between mean parotid dose and xerostomia score at 1 month (p = 0.06). There were no reported marginal failures in either arm. CONCLUSION Parotid-sparing without coverage of the C1 vertebra appears safe and may meaningfully reduce acute xerostomia in patients with limited life expectancy who are candidates for conventional WBRT, although the study was underpowered to detect a significant difference at 1 month.
Collapse
Affiliation(s)
- K Wang
- Department of Radiation Oncology, University of Cincinnati, Cincinnati, OH
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | | | - A Deal
- University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - K A Pearlstein
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - A A Weiner
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - V Xu
- University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - F Danquah
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - D R Wahl
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - W C Jackson
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - R T Dess
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - A F Dragovic
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - L B Marks
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - B S Chera
- Medical University of South Carolina, Charleston, SC
| | - M M Kim
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| |
Collapse
|
8
|
Hall J, Wang K, Lui KP, Darawsheh R, Shumway JW, Carey LA, Hayes KR, Lee CB, Moschos S, Sengupta S, Chaudhary R, Yogendran L, Struve TD, Vatner RE, Pater LE, Breneman JC, Weiner AA, Shen C. Safety and Efficacy of Stereotactic Radiosurgery with Concurrent Targeted Systemic Therapy for Brain Metastases. Int J Radiat Oncol Biol Phys 2023; 117:e107. [PMID: 37784639 DOI: 10.1016/j.ijrobp.2023.06.882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Data describing the safety and efficacy of central nervous system (CNS)-active targeted systemic therapies in combination with stereotactic radiosurgery (SRS, 1 fraction) and/or radiotherapy (SRT, 3-5 fractions) for brain metastases are emerging but limited. We report rates of local and intracranial failure and radiation necrosis in patients receiving CNS-active targeted systemic therapy and SRS/SRT. MATERIALS/METHODS We retrospectively identified patients with intact brain metastases at two institutions from 2009-2022 who were treated with SRS/SRT and CNS-active targeted systemic therapy in any sequence. Patients were followed for a minimum of 3 months after SRS/SRT with brain MRI. Patients typically stopped the targeted agent 2-4 days prior to radiation and resumed 2-4 days after. Targeted therapies included inhibitors of ALK/ROS1 (Alectinib, Ceritinib, Crizotinib, Lorlatinib), EGFR (Afatinib, Erlotinib, Gefitinib, Osimertinib), BRAF (Dabrafenib, Encorafenib, Vemurafenib), MEK (Binimetinib, Trametinib), CDK 4/6 (Abemaciclib, Palbociclib, Ribociclib), HER2 (Afatinib, Lapatinib, Neratinib, Pertuzumab, Trastuzumab, T-DM1, T-DXd, Tucatinib), KRAS (Adagrasib and Sotorasib), PARP (Niraparib, Olaparib), VEGF(R) (Axitinib, Bevacizumab, Ramucirumab), and less-selective tyrosine (receptor) kinase inhibitors (Bosutinib, Brigatinib, Entrectinib, Lenvatinib, Pazopanib, Sorafenib, Sunitinib). Local failure (LF) and radiation necrosis were determined radiographically with clinical impression (grade 2 (symptomatic) or higher (G2+)) and compared between different systemic agents. RESULTS The study included 95 patients with 310 metastases (SRS 246, SRT 64 metastases). Most common primary histologies were non-small cell lung cancer (36% 34/95), breast cancer (28% 27/95), and melanoma (16% 15/95). Overall survival at 1 and 2 years was 80% (76/95) and 55% (52/95), respectively. Median follow-up was 16.6 (range 3-91) months. Median tumor size was 7mm (range 1-75mm). Median number of brain metastases per patient was 2.5 (range 1-12). The G2+ radiation necrosis rate was 5.8% (18/310) while the LF rate was 9.7% (30/310) per metastasis. There was no significant difference in G2+ radiation necrosis by class of targeted therapy. Sixty-two percent (59/95) of patients experienced distant intracranial failure. Median intracranial progression free survival (PFS) was 8.0 (range 0.4-61.4) months. CONCLUSION Although heterogeneous, patients treated with SRS/SRT and ongoing CNS-active targeted systemic therapies have on average >6 month intracranial PFS and little evidence of significant toxicity. We observed <6% G2+ radiation necrosis for this cohort, and no particular class of agent was associated with a significantly higher rate of G2+ radiation necrosis.
Collapse
Affiliation(s)
- J Hall
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - K Wang
- Department of Radiation Oncology, University of Cincinnati, Cincinnati, OH
| | - K P Lui
- Department of Radiation Oncology, University of Cincinnati, Cincinnati, OH
| | - R Darawsheh
- University of North Carolina, Chapel Hill, NC
| | - J W Shumway
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - L A Carey
- Division of Oncology, University of North Carolina, Chapel Hill, NC
| | - K Reeder Hayes
- Division of Oncology, University of North Carolina, Chapel Hill, NC
| | - C B Lee
- Division of Oncology, University of North Carolina, Chapel Hill, NC
| | - S Moschos
- Division of Oncology, University of North Carolina, Chapel Hill, NC
| | - S Sengupta
- Department of Neurology, University of Cincinnati, Cincinnati, OH
| | - R Chaudhary
- Division of Oncology, University of Cincinnati, Cincinnati, OH
| | - L Yogendran
- Department of Neurology, University of Cincinnati, Cincinnati, OH
| | - T D Struve
- Department of Radiation Oncology, University of Cincinnati, Cincinnati, OH
| | - R E Vatner
- Department of Radiation Oncology, University of Cincinnati, Cincinnati, OH
| | - L E Pater
- Department of Radiation Oncology, University of Cincinnati, Cincinnati, OH
| | - J C Breneman
- Department of Radiation Oncology, University of Cincinnati, Cincinnati, OH
| | - A A Weiner
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| |
Collapse
|
9
|
Morse R, Nelson TJ, Liu HC, Williamson CW, Sacco A, Chitti BS, Henderson G, Todd J, Chen X, Gan GN, Rahn D, Sharabi A, Thompson CA, Zou J, Lominska CE, Shen C, Chera BS, Mell LK. Comparison of Standard vs. Relative Risk Models to Define Candidates for Deintensification in Locoregionally Advanced P16+ Oropharyngeal Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e608-e609. [PMID: 37785830 DOI: 10.1016/j.ijrobp.2023.06.1979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Various methods to identify candidates for treatment deintensification with p16+ oropharyngeal squamous cell carcinoma (OPSCC) have been used, but the optimal approach is unknown. MATERIALS/METHODS Multi-institutional cohort study of 385 patients with previously untreated p16+ OPSCC undergoing definitive radiotherapy (RT) with or without systemic therapy between 2009-2020. Chemotherapy intensity was categorized as high (bolus cisplatin and/or induction chemotherapy), medium (weekly cisplatin), or low (non-cisplatin or RT alone). Standard favorable vs. unfavorable risk was defined using NRG HN005 eligibility criteria. High vs. low relative risk (RR) group was defined using the HNCIG omega score (≥ 0.80 vs. < 0.80), which quantifies the proportion of a patient's overall event risk due to cancer. We used multivariable ordinal logistic regression to estimate effects of age (yrs), sex, performance status (PS), Charlson comorbidity index (CCI), T/N (AJCC 8th), current smoking, and pack-years (> 10 vs. ≤ 10) on treatment allocation. Effects on relative event hazards were estimated using generalized competing event regression. RESULTS Median follow-up time was 44.2 months. Chemotherapy intensity was high in 206 (54%), medium in 108 (28%), and low in 71 (18%). 280 patients (73%) were unfavorable risk and 197 (51%) were high RR. 178 patients (46%) had discordant risk classification. On univariable analysis, significant predictors of higher intensity chemotherapy (normalized odds ratio (OR)) were CCI 0-1 (OR 1.49, 95% CI: 1.23-1.79), high omega score (OR 1.46; 1.20-1.77), decreased age (OR 1.43; 1.18-1.74), and PS 0 (OR 1.22; 1.01-1.48). Controlling for CCI, higher omega score was associated with significantly higher odds of intensive chemotherapy (OR 1.35; 1.10-1.65, but unfavorable risk (HN005 ineligibility) was not (OR 1.19; 0.98-1.44). Higher omega score was also associated with significantly higher RR for cancer recurrence (Rec) vs. competing mortality (CM) events (relative HR (rHR) 1.76; 1.12-2.75), but unfavorable risk was not (rHR 1.05; 0.63-1.75). Among patients receiving cisplatin, 50 favorable risk patients (58%) had high RR; all of their event risk was due to cancer recurrence (Table). The 110 unfavorable risk patients (48%) with low omega score had significantly lower RR for cancer events compared to the high omega score group (rHR 0.49; 0.29-0.84). CONCLUSION Many patients with favorable risk p16+ OPSCC have high relative risk for cancer events, which correlates with a benefit of intensive treatment. The HNCIG omega score is a strong predictor of allocation to intensive chemotherapy and may help identify candidates for deintensification.
Collapse
Affiliation(s)
- R Morse
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - T J Nelson
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA
| | - H C Liu
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA
| | - C W Williamson
- UCSD Radiation Oncology and Applied Medicine, La Jolla, CA
| | - A Sacco
- University of California San Diego, San Diego
| | - B S Chitti
- Northwell Health Cancer Institute, Lake Success, NY
| | - G Henderson
- University of California San Diego, Department of Radiation Medicine & Applied Sciences, La Jolla, CA
| | - J Todd
- Yale University, New Haven, CT
| | - X Chen
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - G N Gan
- Department of Radiation Oncology, University of Kansas School of Medicine, Kansas City, KS
| | - D Rahn
- University of California San Diego, Department of Radiation Medicine & Applied Sciences, La Jolla, CA
| | - A Sharabi
- UC San Diego, Moores Cancer Center, Department of Radiation Medicine and Applied Sciences, La Jolla, CA
| | - C A Thompson
- University of North Carolina, Department of Epidemiology, Chapel Hill, NC
| | - J Zou
- Department of Family Medicine and Public Health and Department of Mathematics, University of California San Diego, La Jolla, CA
| | - C E Lominska
- Department of Radiation Oncology, University of Kansas School of Medicine, Kansas City, KS
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - B S Chera
- Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - L K Mell
- University of California San Diego, La Jolla, CA
| |
Collapse
|
10
|
Kotecha R, McDermott MW, Chen C, Ferreira C, Hanft S, Shen C, Wanebo J, Smith K, Wardak Z, Patel T, Chamoun R, Hoang KB, Choutka O, Rodriguez A, Shah M, Brachman DG, Campbell L, Patel S. Surgically Targeted Radiation Therapy (STaRT) for Brain Metastases: Initial Experience from a Prospective Multi-Institutional Registry. Int J Radiat Oncol Biol Phys 2023; 117:e120. [PMID: 37784668 DOI: 10.1016/j.ijrobp.2023.06.908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Resection and intraoperative brachytherapy for patients with large, operable brain metastasis allows for both relief of mass effect and the delivery of radiotherapy (RT) to the resection cavity with a favorable dosimetric profile. The objective of this study was to analyze early patterns-of-care and treatment-related toxicity outcomes for brain metastasis patients treated with surgically targeted radiation therapy (STaRT) using a novel brachytherapy carrier. MATERIALS/METHODS Patients with brain metastasis, de novo and recurrent disease, who enrolled onto a prospective multi-institutional observational study (NCT04427384) were the subject of this analysis. Patients underwent resection and immediate implantation of bioresorbable, conformable, 20 mm x 20 mm x 4 mm collagen tile brachytherapy device(s) containing four uniform-intensity Cesium-131 sources. Toxicities were categorized using the CTCAE v5.0 adverse event (AE) criteria. RESULTS From 10/2020 to 01/2023, 13 participating sites enrolled and treated 48 patients with 51 metastases (13 with de novo and 35 patients with recurrent brain metastases), and 3 patients had 2 lesions implanted at the same procedure. Median age was 61 years (range: 28-80), 52% were female, and the most common primary types were lung (56%) and breast (13%). The median maximum pre-operative dimension was 3.4 cm (range: 1.7-5.7) and median pre-operative tumor volume 13.7cm3 (range: 1.7-132). 64% had received prior RT with a median time from last RT to STaRT of 14.6 months range: 3.5-57.3). Median KPS at screening was 80 (range: 50-100), and remained stable at post op visit (80, range: 50-100), and at 3-months following treatment (80, range 50-100), respectively (p>0.05). The median time for implantation was 3 minutes (range: 0.4-30). At a median follow-up of 4 months (range: <1-18), no patient experienced a radiation-attributed AE, and only 1 attributable Gr >3 AE was noted (Gr 5 intracerebral hemorrhage deemed probably related to surgery and unrelated to the implanted device). CONCLUSION Early results from this prospective multi-center trial demonstrate the feasibility and safety of STaRT. The lack of radiation-related AE, even with short follow-up, is intriguing given the relatively large lesion size and proportion of patients treated for recurrent, previously irradiated disease. Additional follow-up will provide data on tumor control outcomes and radiation necrosis rates using this novel technique.
Collapse
Affiliation(s)
- R Kotecha
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, FL
| | - M W McDermott
- Department of Neurosurgery, Miami Neuroscience Institute, Baptist Health South Florida, Miami, FL
| | - C Chen
- Department of Neurosurgery, University of Minnesota Medical School, Minneapolis, MN
| | - C Ferreira
- Department of Radiation Oncology, University of Minnesota Medical School, Minneapolis, MN
| | - S Hanft
- Westchester Medical Center, Valhalla, NY
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - J Wanebo
- Honor Health Research Institute, Scottsdale, AZ
| | - K Smith
- Barrow Neurological Institute, Phoenix, AZ
| | - Z Wardak
- University of Texas Southwestern Medical Center, Dallas, TX
| | - T Patel
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX
| | - R Chamoun
- University of Kansas Medical Center, Kansas City, KS
| | - K B Hoang
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA
| | - O Choutka
- St. Alphonsus Regional Medical Center, Boise, ID
| | - A Rodriguez
- University of Arkansas for Medical Sciences, Director of Neurosurgical Oncology, Little Rock, AR
| | - M Shah
- Department of Neurological Surgery, Indiana University School of Medicine, Indianapolis, IN; Indiana University Health North Hospital, Indianapolis, IN
| | | | | | - S Patel
- GT Medical Technologies, Tempe, AZ
| |
Collapse
|
11
|
Yoo Y, Gibson E, Zhao G, Sandu A, Re T, Das J, Hesheng W, Kim MM, Shen C, Lee YZ, Kondziolka D, Ibrahim M, Lian J, Jain R, Zhu T, Parmar H, Comaniciu D, Balter J, Cao Y. An Automated Brain Metastasis Detection and Segmentation System from MRI with a Large Multi-Institutional Dataset. Int J Radiat Oncol Biol Phys 2023; 117:S88-S89. [PMID: 37784596 DOI: 10.1016/j.ijrobp.2023.06.414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Developments of automated systems for brain metastasis (BM) detection and segmentation from MRI for assisting early detection and stereotactic radiosurgery (SRS) have been reported but most based upon relatively small datasets from single institutes. This work aims to develop and evaluate a system using a large multi-institutional dataset, and to improve both identification of small/subtle BMs and segmentation accuracy of large BMs. MATERIALS/METHODS A 3D U-Net system was trained and evaluated to detect and segment intraparenchymal BMs with a size > 2mm using 1856 MRI volumes from 1791 patients treated with SRS from seven institutions (1539 volumes for training, 183 for validation, and 134 for testing). All patients had 3D post-Gd T1w MRI scans pre-SRS. Gross tumor volumes (GTVs) of BMs for SRS were curated by each institute first. Then, additional efforts were spent to create GTVs for the untreated and/or uncontoured BMs, including central reviews by two radiologists, to improve accuracy of ground truth. The training dataset was augmented with synthetic BMs of 3773 MRIs using a 3D generative pipeline. Our system consists of two U-Nets with one using small 3D patches dedicated for detecting small BMs and another using large 3D patches for segmenting large BMs, and a random-forest based fusion module for combining the two network outputs. The first U-Net was trained with 3D patches containing at least one BM < 0.1 cm3. For detection performance, we measured BM-level sensitivity and case-level false-positive (FP) rate. For segmentation performance, we measured BM-level Dice similarity coefficient (DSC) and 95-percentile Hausdorff distance (HD95). We also stratified performances based upon BM sizes. RESULTS For 739 BMs in the 134 testing cases, the overall lesion-level sensitivity was 0.870 with an average case-level FP of 1.34±1.92 (95% CI: 1.02-1.67). The sensitivity was >0.969 for the BMs >0.1 cm3, but dropped to 0.755 for the BMs < 0.1 cm3 (Table 1). The average DSC and HD95 for all detected BMs were 0.786 and 1.35mm. The worse performance for BMs > 20 cm3 was caused by a case with 83 cm3 GTV and artifacts in the MRI volume. CONCLUSION We achieved excellent detection sensitivity and segmentation accuracy for BMs > 0.1 cm3, and promising performance for small BMs (<0.1cm3) with a controlled FP rate using a large multi-institutional dataset. Clinical utility for assisting early detection and SRS planning will be investigated. Table 1: Per-lesion detection and segmentation performance stratified by individual BM size. N is the number of BMs in each category.
Collapse
Affiliation(s)
- Y Yoo
- Siemens Healthineers, Princeton, NJ
| | - E Gibson
- Siemens Healthineers, Princeton, NJ
| | - G Zhao
- Siemens Healthineers, Princeton, NJ
| | - A Sandu
- Siemens Healthineers, Princeton, NJ
| | - T Re
- Siemens Healthineers, Princeton, NJ
| | - J Das
- Siemens Healthineers, Princeton, NJ
| | | | - M M Kim
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - Y Z Lee
- University of North Carolina, Chapel Hill, NC
| | - D Kondziolka
- Department of Neurosurgery, NYU Langone Health, New York, NY
| | - M Ibrahim
- University of Michigan, Ann Arbor, MI
| | - J Lian
- University of North Carolina, Chapel Hill, NC
| | - R Jain
- New York University, New York, NY
| | - T Zhu
- Washington University, St. Louis, MO
| | - H Parmar
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | | | - J Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Y Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| |
Collapse
|
12
|
Fried DV, Ahmidouch M, Shen C, Das SK, Marks LB, Chera BS. Identifying a Dose Constraint for the Parotid Ducts: Impact on Patient Reported Xerostomia and Comparison to Conventional Parotid Gland Mean Dose Sparing. Int J Radiat Oncol Biol Phys 2023; 117:S100. [PMID: 37784267 DOI: 10.1016/j.ijrobp.2023.06.053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) (1) Identify a dose constraint for the parotid ducts to reduce patient reported xerostomia and compare effectiveness to QUANTEC constraint. (2) Determine if conventionally planned patients meet this constraint by using atlas-based duct segmentation. MATERIALS/METHODS (1) 38 patients with oropharyngeal squamous cell carcinoma (OPSCC) were treated prospectively on trial with MRI sialography guided parotid duct sparing radiation therapy (parotid duct sparing cohort). These patients were compared to a historical cohort of 89 similar patients treated with conventional parotid gland mean dose sparing for salivary gland dosimetry and patient reported xerostomia (PRO-CTCAE ≥ Moderate). (2) A contour atlas comprised of 24 patients with MRI sialograms was created. Atlas-based segmentation was generated on the remaining 14 patients with MRI sialograms to assess for contour accuracy. Atlas-based parotid duct contours were generated on 111 patients treated with conventional parotid gland mean dose sparing to facilitate a dosimetric comparison to the parotid duct sparing cohort. RESULTS (1) In the parotid duct sparing cohort, patients whose parotid ducts (bilateral) were planned for a mean dose <14 Gy reported significantly (p<0.01) lower rates of xerostomia compared to patients whose ducts were planned to receive >14 Gy (26% (5/19) versus 86% (12/14) at 6 months post-RT and 22% (4/18) versus 73% (8/11) at 12 months post-RT). This improvement compares favorably to the QUANTEC constraint of bilateral parotid glands < 25 Gy (see Table). (2) The atlas-based duct contours were found to have a mean distance-to-agreement of 5mm and an average absolute dose difference of 4.5 Gy compared to the MRI sialography defined duct contours. The average duct dose for those undergoing MRI sialography guided duct sparing was found to be 13.5 Gy compared to an estimated (via atlas-based segmentation) 22.3 Gy for those receiving conventional parotid gland mean dose sparing (p < 0.01). 20% (22/111) patients receiving conventional parotid gland mean dose sparing met the 14 Gy parotid duct constraint versus 60% of patients undergoing MRI sialography guided parotid duct sparing. CONCLUSION Parotid duct sparing (parotid duct dose <14 Gy) was both more effective (∼50% [76% to 26%] absolute xerostomia reduction at 6mo and ∼24% [46% to 22%] absolute xerostomia reduction at 12 mo) and more achievable (∼60% of patients vs ∼35% patients) than mean dose parotid gland sparing per QUANTEC constraint. Atlas-based segmentation estimated that MRI sialography guided parotid duct sparing reduced the parotid duct dose by 9 Gy and that only 20% of patients met the parotid duct dose constraint (<14 Gy) with conventional parotid gland mean dose sparing.
Collapse
Affiliation(s)
- D V Fried
- Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - M Ahmidouch
- University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - S K Das
- Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - L B Marks
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - B S Chera
- Department of Radiation Oncology, Medical University of South Carolina, Charleston, SC
| |
Collapse
|
13
|
Zarabi H, Helis CA, Russell G, Huang J, Liu W, Soltys SG, Mendoza M, Braunstein SE, Salans MA, Wang TJC, Gallitto M, Shi W, Cappelli L, Shen C, Young MD, Mignano JE, Halasz LM, Barbour AB, Masters AH, Chan MD. Multi-Institutional Report of Re-Irradiation for Recurrent High-Grade Glioma. Int J Radiat Oncol Biol Phys 2023; 117:S85-S86. [PMID: 37784590 DOI: 10.1016/j.ijrobp.2023.06.408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Significant heterogeneity exists with regards to prior published reports of re-irradiation (re-RT) in patients with recurrent high grade glioma (HGG). A multi-institutional database of 10 academic centers across the United States was created to analyze prognostic outcomes for re-RT for recurrent HGG, which included WHO Grade III and Grade IV tumors. MATERIALS/METHODS Patients with HGG who had initially received standard radiotherapy (RT) and were subsequently treated with a course of re-RT at recurrence were included in the study. Factors assessed to delineate a significant association with overall survival (OS) and toxicity included age, KPS, number of relapses, dose, use of bevacizumab (BEV) or temozolomide (TMZ), time from prior RT, histology, RT target, re-RT target> 5cm and extent of resection, and MGMT methylation status. The Kaplan-Meier Method was used to estimate OS. Cox proportional hazards regression models were used to identify factors associated with OS. Toxicity outcomes were assessed using logistic regression. Significance was assumed if p<0.05. Data management and decision management software were used for all analyses. RESULTS Between 2001 and 2022, 280 patients from 10 academic institutions were treated with re-RT for diagnosis of recurrent HGG. 133 patients (71.1%) had a histologic glioblastoma (GBM) at the time of re-RT, with the remainder having Grade 3 gliomas. Median dose delivered at re-RT was 47 Gy BED10 (IQR 47 - 53 Gy BED10), with the most common regimen being 35 Gy in 10 fractions. 83 patients (56%) had GTV greater than 5 cm treated with re-RT. 183 patients (79%) received concurrent systemic therapy, including 95 (41%) who received concurrent TMZ and 86 (45%) who received concurrent BEV. Median OS for the entire cohort was 10 months. Increasing dose at re-RT was associated with improved OS (OR 0.80 95% CI 0.67-0.95, p = 0.10 per 10 Gy BED10), as was dose greater than 47 Gy BED10, which is equivalent to 35 Gy in 10 fractions (OR 0.70, 95% CI 0.54-0.91). Concurrent TMZ was also associated with improved OS (OR 0.68, 95% CI 0.46-0.83, p < 0.01). 32/143 (22%) patients evaluable for toxicity experienced Grade 2 or greater adverse radiation effect (ARE). Use of BEV was associated with decreased toxicity (OR 0.45, 95% CI 0.21-0.98, p = 0.05). Dose at re-RT (OR 1.07 per 10 Gy BED10, p = 0.78), a GTV > 5cm (OR 1.39, p = 0.44), and the use of concurrent TMZ (OR 1.90, p = 0.10) were not associated with Grade 2 or greater ARE. CONCLUSION Higher dose of re-RT and use of concurrent TMZ led to improved OS in recurrent HGG patients without an associated increased rate of ARE. Use of BEV decreased the likelihood of Grade 2 or greater ARE in the re-RT setting for these recurrent HGG patients.
Collapse
Affiliation(s)
- H Zarabi
- Department of Radiation Oncology, Wake Forest School of Medicine, Winston-Salem, NC
| | - C A Helis
- Department of Radiation Oncology, Wake Forest School of Medicine, Winston-Salem, NC
| | - G Russell
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC
| | - J Huang
- Washington University School of Medicine in St. Louis, Department of Radiation Oncology, St. Louis, MO
| | - W Liu
- University of Iowa, Iowa City, IA
| | - S G Soltys
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - M Mendoza
- Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, CA
| | - S E Braunstein
- University of California San Francisco, Department of Radiation Oncology, San Francisco, CA
| | - M A Salans
- University of California San Francisco, San Francisco, CA
| | | | - M Gallitto
- Department of Radiation Oncology, Columbia University Irving Medical Center, New York, NY
| | - W Shi
- Thomas Jefferson University Hospital, Philadelphia, PA
| | - L Cappelli
- Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, PA
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - M D Young
- Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - J E Mignano
- Tufts Medical Center, Department of Radiation Oncology, Boston, MA
| | - L M Halasz
- Department of Radiation Oncology, University of Washington/ Fred Hutchinson Cancer Center, Seattle, WA
| | | | | | - M D Chan
- Department of Radiation Oncology, Wake Forest School of Medicine, Winston-Salem, NC
| |
Collapse
|
14
|
Steele EM, Payne MM, Weiner AA, Casey DL, Shen C. Factors Associated with Short Interval from Treatment to Death in Patients Treated with Stereotactic Body Radiotherapy for Lung Metastases: Experience at a Large Academic Facility. Int J Radiat Oncol Biol Phys 2023; 117:e152. [PMID: 37784737 DOI: 10.1016/j.ijrobp.2023.06.973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Stereotactic body radiotherapy (SBRT) is increasingly used to treat patients with lung metastases, as several studies have demonstrated a survival benefit in patients with oligometastatic disease, while in other cases it is used for palliation as in the re-irradiation setting. With increasing use, we queried whether SBRT is given more frequently toward the end of life for patients with lung metastases and assessed factors associated with a shorter interval from SBRT to death. MATERIALS/METHODS A sample of patients who received stereotactic body radiation therapy (SBRT) to lung metastases between 2014-2022 at a single academic institution were identified. Medical records were reviewed for patient demographic, disease, and treatment details, including age, sex, race, insurance status, Karnofsky performance status (KPS), and time from SBRT to death. Descriptive statistics including chi-square and t-test analyses were used to compare patients who did versus did not die within 180 days of completion of SBRT. RESULTS A total of 81 episodes of SBRT for lung metastases were identified. Of these, median age was 68 years (range 22-86), 82.7% had KPS >70, a majority had Medicare/Medicaid (61.7%, 50/81) or private insurance (33.3%, 27/81), and 63% were male. Only 9 of the 81 patients (11.1%) died within 180 days of SBRT completion. Death within 180 days occurred in 7.3% of treatments prior to 2018 compared to 15.0% of more recent treatments, but this difference was not statistically significant (p = 0.27; Table 1). Non-White race, KPS ≤70, and lack of insurance were all associated with increased likelihood of death within 180 days of SBRT (p<0.001 all comparisons). CONCLUSION Few patients treated with SBRT for lung metastases in our series died within 180 days of SBRT completion, and there did not appear to be a significant increase in 180-day mortality post-SBRT in recent years. While limited by the small number of events, race, KPS, and insurance status were significantly associated with likelihood of death within 180 days of SBRT. Additional work is needed to better appreciate what patients may benefit from SBRT for lung metastases. Table 1: Characteristics of patients that did versus did not die within 180 days of SBRT for lung metastases.
Collapse
Affiliation(s)
- E M Steele
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - M M Payne
- University of North Carolina, Chapel Hill, NC
| | - A A Weiner
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - D L Casey
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| |
Collapse
|
15
|
Hall J, Dance MJ, Nguyen L, Repka MC, Chen X, Shen C. Hippocampal-Sparing Radiotherapy in Primary Sinonasal and Cutaneous Head and Neck Malignancies: A Feasibility Study. Int J Radiat Oncol Biol Phys 2023; 117:e586-e587. [PMID: 37785776 DOI: 10.1016/j.ijrobp.2023.06.1931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Patients with primary sinonasal and cutaneous head and neck (H&N) malignancies often receive meaningful hippocampal doses, but the hippocampus is not a classic avoidance structure in radiation planning of these primary sites. This series characterizes the feasibility and tradeoffs of hippocampal-sparing radiotherapy (HSRT) for patients with primary sinonasal and cutaneous H&N malignancies. MATERIALS/METHODS We retrospectively identified patients at a single institution treated definitively for primary sinonasal or cutaneous malignancies of the H&N. Each patient received (chemo)radiation and all received clinically-significant radiation dose to one or both hippocampi. We created new HSRT plans for each patient with intensity-modulated radiotherapy using original target and organ-at-risk (OAR) volumes. Hippocampi were contoured based on Radiation Therapy Oncology Group guidelines. Absolute and relative differences in radiation dose to the hippocampi, planning target volumes (PTV), and OARs were recorded. We used paired-samples t-tests to compare hippocampal and PTV dosimetric measures with and without HSRT. RESULTS Thirty-seven patients were included (22 sinonasal, 11 cutaneous H&N, and 4 parotid primary tumors). Median prescription dose was 6600cGy (range: 5000-7440cGy). The most common fractionation regimens were 200cGy/fraction daily (51%, 19/37 patients) and 120cGy/fraction twice daily (41%, 15/37 patients). There were significant decreases in hippocampal Dmax and D100% using HSRT without compromising PTV coverage (Table 1). HSRT resulted in a relative increase of mean lacrimal gland dose by an average of 3.8%, optic chiasm Dmax by 1.3%, and whole brain Dmax of 1.2%. However, other OAR doses were lower with HSRT, including parotid gland mean dose, lens Dmax, optic nerve Dmax, cochlea mean dose, brainstem Dmax, and whole brain mean dose. CONCLUSION HSRT is feasible and results in meaningful radiation dose reduction to the hippocampi without reducing PTV coverage or increasing dose to other OARs. The hippocampi should be regularly included as avoidance structures when treating primary sinonasal and cutaneous H&N tumors with radiation. We suggest target hippocampal constraints of Dmax < 1600cGy and D100% < 500cGy when feasible (without compromising PTV coverage). The clinical significance of HSRT in patients with primary H&N tumors should be investigated prospectively.
Collapse
Affiliation(s)
- J Hall
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - M J Dance
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - L Nguyen
- North Carolina School of Science and Mathematics, Durham, NC
| | - M C Repka
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - X Chen
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| |
Collapse
|
16
|
Morse R, Stepp WH, Oldan J, Huang BY, Tasoulas J, Chera BS, Chen X, Hackman T, Shen C. Definitive Chemoradiation Treatment Response Evaluation Using NI-RADS and ctHPVDNA for HPV-Associated Oropharyngeal Squamous Cell Carcinoma. Int J Radiat Oncol Biol Phys 2023; 117:S150-S151. [PMID: 37784382 DOI: 10.1016/j.ijrobp.2023.06.570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To compare the evaluation of treatment response among patients with human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) treated with definitive (chemo)radiotherapy (CRT). MATERIALS/METHODS Patients with locally advanced HPV-associated OPSCC treated with definitive radiotherapy (RT) or CRT from 2019 to 2022 at a single institution were reviewed. Patients underwent standard 3-month post-CRT positron emission tomography/computed tomography (PET/CT) scan with or without contrast enhanced CT (CECT) of the head and neck. Plasma circulating tumor HPV DNA (ctHPVDNA) was collected from 2-8 months post-CRT. Equivocal findings on post-CRT imaging prompted repeat evaluation. Imaging response was assessed via NI-RADS (Neck Imaging Reporting and Data System) risk classification and independently reviewed by two board certified radiologists, both blinded to outcomes and ctHPVDNA values. RESULTS Our cohort of 52 patients included: 87% males; median age 61.5; 63% never smokers, 31% former smokers, 6% current smokers; 44% tonsil primary, 46% base of tongue; 4% T0, 25% T1, 40% T2, 12% T3, 17% T4; 6% N0, 15% N1, 2% N2a, 44% N2b, 25% N2c, 8% N3 (AJCC 7th edition). Concurrent systemic therapy was received in 90%. During this period 71 PET/CTs and 15 CECTs were reviewed for treatment response evaluation; 44% (23/52) patients required additional imaging for equivocal findings; 62 ctHPVDNA blood samples were co-analyzed for treatment evaluation. The highest risk classification score between mucosa, primary, and/or neck site was: 42% NI-RADS 1, 48% NI-RADS 2, and 10% NI-RADS 3. Only patients with locoregional disease recurrence/progression were included for evaluation comparison between imaging and circulating biomarkers. No cancer events occurred without imaging and/or ctHPVDNA detection. Patients with NI-RADS score ≥2 during first post-CRT imaging evaluation more frequently underwent additional imaging (70% vs 30%, p<0.001). NI-RADS risk classification suggested 5 locoregional events (2 true positives, 3 false positives) resulting in 100% sensitivity, 94% specificity, 40% positive predictive value (PPV), and 100% negative predictive value (NPV). Circulating tumor HPV-DNA identified 2 locoregional events (2 true positives, 0 false positives) resulting in 100% sensitivity, 100% specificity, 100% PPV, and 100% NPV. Salvage operations were performed in 2 of 3 patients with false positive disease by NI-RADS classification without any evidence of cancer on final pathology. CONCLUSION While limited by the small number of recurrence events in this cohort, ctHPVDNA for HPV-associated OPSCC in conjunction with post-treatment imaging evaluation may limit the need for repeat imaging and unwarranted salvage operations that increase patient worry, morbidity, and financial toxicity. Additional prospective study is warranted.
Collapse
Affiliation(s)
- R Morse
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - W H Stepp
- Department of Otolaryngology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - J Oldan
- Department of Radiology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - B Y Huang
- Department of Radiology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - J Tasoulas
- Department of Otolaryngology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - B S Chera
- Department of Radiation Oncology, Medical University of South Carolina, Charleston, SC
| | - X Chen
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - T Hackman
- Department of Otolaryngology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - C Shen
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, NC
| |
Collapse
|
17
|
Chen YJ, Qin Y, Yu H, Zhu Z, Shen C, Lu Y, Cheng TT, Zhang N, Gu SJ, Zhou JY, Wu M, Su J. [A prospective cohort study of long-term fasting blood glucose variability and risk of mortality in patients with type 2 diabetes]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1099-1105. [PMID: 37482713 DOI: 10.3760/cma.j.cn112338-20221226-01084] [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: 07/25/2023]
Abstract
Objective: To investigate the association between long-term fasting blood glucose (FPG) variability and all-cause mortality in patients with type 2 diabetes. Methods: A total of 7 174 type 2 diabetic patients included in National Basic Public Health Service Program in Changshu of Jiangsu Province were recruited as participants. Long-term glucose variability was assessed using standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) across FPG measurements at the more than three visits. Death information were mainly obtained from the death registry system in Jiangsu. Then Cox proportional hazards regression models were used to estimate the associations of four variability indicators and all-cause mortality's hazard ratios (HRs) and their 95%CIs. Results: Among 55 058.50 person-years of the follow-up, the mean follow-up time was 7.67 years, and 898 deaths occurred during the follow-up period. After adjustment, compared with T1 group, the Cox regression model showed that HRs of T3 group in SD, CV, ARV and VIM were 1.24 (95%CI: 1.03-1.49), 1.20 (95%CI: 1.01-1.43), 1.28 (95%CI: 1.07-1.55) and 1.20 (95%CI:1.01-1.41), respectively. HRs of per 1 SD higher SD, CV, ARV and VIM were 1.13 (95%CI: 1.06-1.21), 1.08 (95%CI: 1.01-1.15), 1.05 (95%CI: 1.00-1.12) and 1.09 (95%CI: 1.02-1.16) for all-cause mortality, respectively. In the stratified analysis, age, gender, hypoglycemic agent and insulin uses had no effect on the above associations (all P for interaction >0.05). Conclusion: Long-term FPG glycemic variability was positively associated with the risk of all-cause mortality in type 2 diabetes patients.
Collapse
Affiliation(s)
- Y J Chen
- Department of Non-communicable Chronic Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing 210003, China
| | - Y Qin
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H Yu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Z Zhu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - C Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Y Lu
- Department of Non-communicable Chronic Disease Prevention, Suzhou Prefectural Center for Disease Control and Prevention, Suzhou 215004, China
| | - T T Cheng
- Department of Infectious Disease Control Division, Suzhou National New & Hi-Tech Industrial Development Zone (Huqiu District) Center for Disease Control and Prevention, Suzhou 215163, China
| | - N Zhang
- Changshu County Center for Disease Control and Prevention, Changshu 215500, China
| | - S J Gu
- Department of Non-communicable Chronic Disease Prevention, Changshu County Center for Disease Control and Prevention, Changshu 215500, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - M Wu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Su
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| |
Collapse
|
18
|
Shen C, Ying XR, Wu GF, Xia D. [Three cases of primary small cell neuroendocrine carcinoma of the upper urinary tract and review of the literature]. Zhonghua Zhong Liu Za Zhi 2023; 45:525-529. [PMID: 37355472 DOI: 10.3760/cma.j.cn112152-20220331-00221] [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] [Subscribe] [Scholar Register] [Indexed: 06/26/2023]
Affiliation(s)
- C Shen
- Department of Urology, Shaoxing People's Hospital, Shaoxing 312000, China
| | - X R Ying
- Department of Urology, Shaoxing People's Hospital, Shaoxing 312000, China
| | - G F Wu
- Department of Urology, Shaoxing People's Hospital, Shaoxing 312000, China
| | - D Xia
- Department of Urology, the First Affiliated Hospital of Zhejiang University, Hangzhou 310000, China
| |
Collapse
|
19
|
Liu JH, Xie HK, Su J, Zhu Z, Pan EC, Lu Y, Wan FP, Yan QY, Zhang N, Gu SJ, Wu M, Zhou JY, Shen C. [The distribution of blood pressure and associated factors of the elderly with type 2 diabetes in Jiangsu Province]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:614-625. [PMID: 37165808 DOI: 10.3760/cma.j.cn112150-20221111-01101] [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: 05/12/2023]
Abstract
Objective: To investigate the distribution of blood pressure and analyze the associated factors of blood pressure of the elderly with type 2 diabetes in Jiangsu Province. Methods: The elderly over 60 years old participants with type 2 diabetes in the communities of Huai'an City and Changshu City, Jiangsu Province were selected in this study. They were divided into two groups: taking antihypertensive drugs and not taking antihypertensive drugs. The demographic characteristics, such as age and sex, and relevant factors were collected by questionnaire. The systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by physical examination. The percentile of SBP and DBP in each age group of men and women were described. The kernel density estimation curve was used to show the blood pressure distribution. The trend of blood pressure with age was fitted by locally weighted regression. The logistic regression model was used to analyze relevant factors of blood pressure. Results: A total of 12 949 participants were included in this study, including 7 775 patients in the antihypertensive drug group and 5 174 patients in the group without antihypertensive drugs. The SBP of participants was concentrated at 140-160 mmHg, and their DBP was concentrated at 75-85 mmHg. There were significant differences in the distribution of blood pressure among the subgroups of body mass index (BMI) and rural areas whether taking antihypertensive drugs and not. For participants aged under 80 years old, the SBP showed an increasing trend with age and the DBP showed a decreasing trend with age. Age, BMI ≥24 kg/m2, fasting blood glucose ≥7.0 mmol/L, living in rural areas and no smoking were influencing factors of the elevated SBP; BMI ≥24 kg/m2, male, living in rural areas, no smoking, drinking alcohol and not receiving drug hypoglycemic treatment were influencing factors of the elevated DBP. Conclusion: The SBP of older diabetic adults in Jiangsu Province is at a high level, and the distribution of blood pressure is significantly different between men and women in taking antihypertensive drugs group. The SBP presents a rising trend and the DBP is decreasing at the age of 60-80 years. The blood pressure level of this population are mainly affected by age, BMI, urban and rural areas, smoking.
Collapse
Affiliation(s)
- J H Liu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - H K Xie
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - J Su
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Z Zhu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - E C Pan
- Center for Disease Control and Prevention of Huai'an City, Huai'an 223002, China
| | - Y Lu
- Department of Non-communicable Chronic Disease Control, Center for Disease Control and Prevention of Suzhou City, Suzhou 215004, China
| | - F P Wan
- Department of Non-communicable Chronic Disease Control, Center for Disease Control and Prevention of Qingjiangpu District in Huai'an City, Huai'an 223021, China
| | - Q Y Yan
- Department of Non-communicable Chronic Disease Control, Center for Disease Control and Prevention of Huai'an District in Huai'an City, Huai'an 223229, China
| | - N Zhang
- Center for Disease Control and Prevention of Changshu and Suzhou City, Suzhou 215500, China
| | - S J Gu
- Center for Disease Control and Prevention of Changshu and Suzhou City, Suzhou 215500, China
| | - M Wu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - C Shen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| |
Collapse
|
20
|
Pang Y, Kukull W, Sano M, Albin RL, Shen C, Zhou J, Dodge HH. Predicting Progression from Normal to MCI and from MCI to AD Using Clinical Variables in the National Alzheimer's Coordinating Center Uniform Data Set Version 3: Application of Machine Learning Models and a Probability Calculator. J Prev Alzheimers Dis 2023; 10:301-313. [PMID: 36946457 PMCID: PMC10033942 DOI: 10.14283/jpad.2023.10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Clinical trials are increasingly focused on pre-manifest and early Alzheimer's disease (AD). Accurately predicting clinical progressions from normal to MCI or from MCI to dementia/AD versus non-progression is challenging. Accurate identification of symptomatic progressors is important to avoid unnecessary treatment and improve trial efficiency. Due to large inter-individual variability, biomarker positivity and comorbidity information are often insufficient to identify those destined to have symptomatic progressions. Using only clinical variables, we aimed to predict clinical progressions, estimating probabilities of progressions with a small set of variables selected by machine learning approaches. This work updates our previous work that was applied to the National Alzheimer's Coordinating Center (NACC) Uniform Data Set Version 2 (V2), by using the most recent version (V3) with additional analyses. We generated a user-friendly conversion probability calculator which can be used for effectively pre-screening trial participants.
Collapse
Affiliation(s)
- Y Pang
- Hiroko H. Dodge, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA,
| | | | | | | | | | | | | |
Collapse
|
21
|
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.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
22
|
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, Shepherd R, Shi R, Zhu S, Shi Y, Shiah YJ, Shibata T, Shih J, Shimizu E, Shimizu K, Shin SJ, Shiraishi Y, Shmaya T, Shmulevich I, Awadalla P, Shorser SI, Short C, Shrestha R, Shringarpure SS, Shriver C, Shuai S, Sidiropoulos N, Siebert R, Sieuwerts AM, Sieverling L, Creighton CJ, Signoretti S, Sikora KO, Simbolo M, Simon R, Simons JV, Simpson JT, Simpson PT, Singer S, Sinnott-Armstrong N, Sipahimalani P, Meyerson M, Skelly TJ, Smid M, Smith J, Smith-McCune K, Socci ND, Sofia HJ, Soloway MG, Song L, Sood AK, Sothi S, Ouellette BFF, Sotiriou C, Soulette CM, Span PN, Spellman PT, Sperandio N, Spillane AJ, Spiro O, Spring J, Staaf J, Stadler PF, Wu K, Staib P, Stark SG, Stebbings L, Stefánsson ÓA, Stegle O, Stein LD, Stenhouse A, Stewart C, Stilgenbauer S, Stobbe MD, Yang H, Stratton MR, Stretch JR, Struck AJ, Stuart JM, Stunnenberg HG, Su H, Su X, Sun RX, Sungalee S, Susak H, Göke J, Suzuki A, Sweep F, Szczepanowski M, Sültmann H, Yugawa T, Tam A, Tamborero D, Tan BKT, Tan D, Tan P, Schwarz RF, Tanaka H, Taniguchi H, Tanskanen TJ, Tarabichi M, Tarnuzzer R, Tarpey P, Taschuk ML, Tatsuno K, Tavaré S, Taylor DF, Stegle O, Taylor-Weiner A, Teague JW, Teh BT, Tembe V, Temes J, Thai K, Thayer SP, Thiessen N, Thomas G, Thomas S, Zhang Z, Thompson A, Thompson AM, Thompson JFF, Thompson RH, Thorne H, Thorne LB, Thorogood A, Tiao G, Tijanic N, Timms LE, Brazma A, Tirabosco R, Tojo M, Tommasi S, Toon CW, Toprak UH, Torrents D, Tortora G, Tost J, Totoki Y, Townend D, Rätsch G, Traficante N, Treilleux I, Trotta JR, Trümper LHP, Tsao M, Tsunoda T, Tubio JMC, Tucker O, Turkington R, Turner DJ, Brooks AN, Tutt A, Ueno M, Ueno NT, Umbricht C, Umer HM, Underwood TJ, Urban L, Urushidate T, Ushiku T, Uusküla-Reimand L, Brazma A, 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, Brooks AN, Veluvolu U, Vembu S, Verbeke LPC, Vermeulen P, Verrill C, Viari A, Vicente D, Vicentini C, VijayRaghavan K, 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, Yang Y, Yao X, Yaspo ML, Adams DJ, Yates L, Yau C, Ye C, Ye K, Yellapantula VD, Yoon CJ, Yoon SS, Yousif F, Yu J, Yu K, Agrawal N, Yu W, Yu Y, Yuan K, Yuan Y, Yuen D, Yung CK, Zaikova O, Zamora J, Zapatka M, Zenklusen JC, Ahn KS, Zenz T, Zeps N, Zhang CZ, Zhang F, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Ahn SM, Zhang X, Zhang X, Zhang Y, Zhang Z, Zhao Z, Zheng L, Zheng X, Zhou W, Zhou Y, Zhu B, Aikata H, 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, Akbani R, von Mering C, Akdemir KC, Al-Ahmadie H, Al-Sedairy ST, Al-Shahrour F, Alawi M, Albert M, Aldape K, Alexandrov LB, Ally A, Alsop K, Alvarez EG, Amary F, Amin SB, Aminou B, Ammerpohl O, Anderson MJ, Ang Y, Antonello D, 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. 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
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
23
|
Li Q, Shen C, Wang C. [Pancreatic β-cell dedifferentiation detected by flow cytometry]. Zhonghua Nei Ke Za Zhi 2022; 61:1318-1323. [PMID: 36456511 DOI: 10.3760/cma.j.cn112138-20220111-00032] [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] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Objective: To establish a method for detecting pancreatic β-cell dedifferentiation using flow cytometry. Methods: Experimental study. Min6 (mouse β cell line), αTC1-6 (mouse α cell line), HepG2 (human hepatocellular carcinoma cells) and mouse F9 cells (mouse teratocarcinoma cell) were cultured with conventional medium. Min6 cells were treated with interleukin-1β (IL-1β) in combined with tumor necrosis factor α (TNFα), or palmitic acid (PA) overnight and stained with anti-chromogranin A (ChgA), anti-insulin (Ins), anti-glucagon (Gcg), anti-SRY-box transcription factor 9 (Sox9) and anti-octamer binding transcription factor 4 (Oct4) antibodies, respectively. Flow cytometry was applied to detect the pression of ChgA, Ins, Gcg, Sox9, and Oct4 in the cells, respectively. Unpaired Student t test was used for statistical analysis. Results: Flow cytometry analyses showed that Ins and ChgA were highly expressed in Min6 cells, Gcg was highly expressed in αTC1-6, Sox9 was highly expressed in HepG2, and Oct4 was highly expressed in F9 cells, respectively (around 90%). Treatment of Min6 cells with IL-1β+TNFα significantly decreased Ins positive staining cells (92.775%±1.702% vs. 97.125%±0.246%, P=0.045), while increased Sox9 positive staining cells (41.675%±0.390% vs. 25.875%±3.348%, P=0.003). No significant changes in ChgA and Oct4 expression could be viewed (both P>0.05). PA treatment elevated the number of Gcg positive staining cells (54.500%±3.597% vs. 41.160%±3.007%, P=0.022). The levels of mRNA expression by qPCR of the above proteins were in consistent with the levels of protein expression by flow cytometry in Min6 cells. Conclusion: Flow cytometry can be used to detect proteins expressed in dedifferentiated models of β cells, which provides a new method for identify dedifferentiation of pancreatic β cells.
Collapse
Affiliation(s)
- Q Li
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - C Shen
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - C Wang
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| |
Collapse
|
24
|
Shen C, Kry S, Buchsbaum J, Milano M, Inskip P, Francis J, WIlson M, Whelan K, Mayo C, Olch A, Constine L, Terezakis S, Vogelius I. Retinopathy, Optic Neuropathy and Cataract in Childhood Cancer Survivors Treated with Radiotherapy: A Report from the Pediatric Normal Tissue Effects in the Clinic (PENTEC) Initiative. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.572] [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]
|
25
|
Hall J, Sud S, Casey D, Poellmann M, Bu J, Wang A, Hong S, Shen C. Prospective Characterization of Circulating Tumor Cell Kinetics in Patients with Locoregional Head and Neck Cancer Receiving Definitive Therapy. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1318] [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]
|
26
|
Shumway J, Tan X, Drossopoulos P, Torras M, File M, Joshi T, Ruhashya A, Yanagihara T, Shen C. A Brain Metastases Survival Model Using an Ensemble Tree Approach. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.949] [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]
|
27
|
Steele E, Shen C, Tan X, Casey D. The Impact of Radiation Therapy on the Incidence of Second Malignant Neoplasm among Adolescent and Young Adult Cancer Survivors. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1705] [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]
|
28
|
Liem X, De Baere T, Seiwert T, Shen C, Papai Z, Moreno V, Takacsi-Nagy Z, Helferich F, Thariat J, Gooi Z, Vivar O, Farber L, Yom S, Bossi P, Ferris R, Hackman T, Tourneau CL, Rodriguez J, Hoffmann C. International Guidelines for Intratumoral and Intranodal Injection of NTBXR3 Nanoparticles in Head and Neck Cancers. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1365] [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]
|
29
|
Shen C, Ducassou A, Bonvalot S, Chajon E, Farber L, Vivar O, Tyan P, De Baere T, Dicker A, Hoffmann C, Tourneau CL. 3-Dimensional Volumetric Distribution and Dispersion Analysis of the Radioenhancer NBTXR3 in Various Solid Malignancies. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.353] [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]
|
30
|
Chen YJ, Su J, Qin Y, Shen C, Pan EC, Yu H, Lu Y, Zhang N, Zhou JY, Wu M. [A prospective cohort study on socioeconomic status and risk of all-cause mortality among patients with type 2 diabetes based on latent class analysis]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1619-1625. [PMID: 36456494 DOI: 10.3760/cma.j.cn112338-20220107-00010] [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] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Objective: To investigate the relationship between socioeconomic status (SES) and all-cause mortality in patients with type 2 diabetes. Methods: A total of 17 553 patients with type 2 diabetes were recruited under the National Basic Public Health Service Project in Changshu county, Qingjiangpu district, and Huai'an district in Huai'an city of Jiangsu province as participants. Latent class analysis was applied to classify the individuals based on five socioeconomic indicators. Then, Cox proportional hazards regression models were used to estimate the associations of different levels of SES with all-cause mortality, and stratified analysis was performed according to age and area. Results: Among 100 529.08 person-years of the fo1low-up, the median follow-up time was 5.7 years, and 1 829 deaths occurred during the follow-up period. According to the relevant results of the latent class model, the model of the "three classes" was the best. The related population was then divided into low SES (8 256 people, 47.0%), medium SES (4 427 people, 25.2%), and high SES groups (4 870 people, 27.8%). Compared to patients with high SES, the multivariate-adjusted hazard ratio (95%CI) of all-cause mortality associated with low SES for males and females were 1.84 (1.53-2.21) and 1.41 (1.51-1.72), respectively. Stratified analysis showed that the hazard ration (95%CI) of all-cause mortality associated with low SES for males and females were 1.99 (1.12-2.95) and 2.01 (1.20-3.23), respectively, in people younger than 60 years old, and were 1.90 (1.57-2.31) and 1.40 (1.13-1.73) in people over 60 years old. The HR values (95%CI) for all-cause mortality associated with low SES for the male and females were 1.54 (1.17-2.04) and 1.27 (1.02-1.59) in the urban population with 2.11 (1.55-2.85) and 2.64 (1.17-3.35) in rural population, respectively. Conclusions: Lower SES increased the risk of all-cause mortality in type 2 diabetic patients, which is more significant in younger and rural populations.
Collapse
Affiliation(s)
- Y J Chen
- Department of Non-communicable Chronic Disease Control, Nanjing Municipal Center for Disease Control and Prevention, Nanjing 210003, China
| | - J Su
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Y Qin
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - C Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - E C Pan
- Huai'an Center for Disease Control and Prevention, Huai'an 223001, China
| | - H Yu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Y Lu
- Department of Non-communicable Chronic Disease Control, Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - N Zhang
- Changshu Center for Disease Control and Prevention, Changshu 215500, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - M Wu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| |
Collapse
|
31
|
Wei ZL, Qian XW, Wang P, Jiang WJ, Wang HS, Shen C, Wang WJ, Hou J, Wang YH, Huang Y, Wang XC, Zhai XW. [Analysis of risk factors and prognosis of cytomegalovirus infection post umbilical cord blood stem cell transplantation in children with primary immunodeficiency diseases]. Zhonghua Er Ke Za Zhi 2022; 60:1019-1025. [PMID: 36207848 DOI: 10.3760/cma.j.cn112140-20220501-00403] [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] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To investigate the risk factors and outcomes of cytomegalovirus (CMV) infection post umbilical cord blood stem cell transplantation (UCBT) in children with primary immunodeficiency diseases (PID). Methods: Clinical data of 143 PID children who received UCBT in the Children's Hospital of Fudan University from January 2015 to June 2020 were collected retrospectively. CMV-DNA in the plasma was surveilled once or twice a week within 100 days post-UCBT. According to the CMV-DNA test results, children were divided into the CMV-infected group and the CMV-uninfected group. The incidence and risk factors of CMV infection were analyzed. At 1-month post-UCBT, the absolute lymphocyte count, ratio of lymphocyte subsets and immunoglobulin levels were compared between those whose CMV infection developed 1-month later post-UCBT and those not. Mann-Whitney U test and chi-squared test were used for comparision between groups. Kaplan-Meier survival analysis was used to analyze the impact of CMV infection on survival. Results: Among 143 patients, there were 113 males and 30 females, with a age of 14 (8, 27) months at UCBT. Chronic granulomatosis disease (n=49), very-early-onset inflammatory bowel disease (n=43) and severe combined immunodefiency (n=29) were the three main kinds of PID. The rate of CMV infection was 21.7% (31/143), and the time of infection occurring was 44 (31, 49) days post-UCBT. The incidence of recurrent CMV infection was 4.2% (6/143) and refractory CMV infection was 4.9% (7/143).There was no significant difference in the first time CMV-DNA copy and peak CMV-DNA copy during treatment between the recurrent CMV infection group and the non-recurrent CMV infection group (32.8 (18.3, 63.1)×106 vs. 22.5 (13.2, 31.9)×106 copies/L, Z=-0.95, P=0.340;35.2 (20.2, 54.6)×106 vs. 28.4 (24.1, 53.5)×106copies/L, Z=-0.10, P=0.920), so were those between the refractory CMV infection group and non-refractory CMV infection group (21.8 (13.1, 32.2)×106 vs. 25.9 (14.2, 12.2)×106copies/L, Z=-1.04, P=0.299; 47.7 (27.9, 77.6)×106 vs. 27.7 (19.7,51.8)×106copies/L, Z=-1.49, P=0.137). The CMV-infected group accepted more reduced-intensity conditioning (RIC) regimen than the CMV-uninfected group (45.2% (14/31) vs. 25.0% (28/112), χ2=4.76, P<0.05). The rate of CMV-seropositive recipients and Ⅱ-Ⅳ acute graft versus host diseases (aGVHD) are significantly higher in the CMV-infected group than the CMV-uninfected group (100% (31/31) vs. 78.6% (88/112), 64.5% (20/31) vs. 26.8% (30/112), χ2=7.98,15.20, both P<0.05). The follow-up time was 31.6 (13.2, 45.9) months, CMV infection had no effect on overall survival (OS) rate (χ2=0.02, P=0.843). There was significant difference in the survival rate among three groups of refractory CMV infection, non-refractory CMV infection and the CMV-uninfected (4/7 vs.95.8% (23/24) vs. 86.6% (97/112), χ2=5.91, P=0.037), while there was no significant difference in the survival rate among three groups of recurrent CMV infection, non-recurrent CMV infection and the CMV-uninfected (5/6 vs. 88.0% (22/25) vs. 86.6% (97/112), χ2=0.43, P=0.896). Children who developed CMV infection after 30 days post-UCBT had lower absolute count and rate of CD4+ T cells and immunoglobulin G (IgG) level than those in the CMV-uninfected group (124.1 (81.5, 167.6) ×106 vs. 175.5 (108.3, 257.2) ×106/L, 0.240 (0.164, 0.404) vs. 0.376 (0.222, 0.469), 9.3 (6.2, 14.7) vs. 13.6 (10.7, 16.4) g/L, Z=-2.48, -2.12,-2.47, all P<0.05), but have higher rate of CD8+T cells than those in CMV-uninfected group (0.418 (0.281, 0.624) vs. 0.249 (0.154, 0.434), Z=-2.56, P=0.010). Conclusions: RIC regimen, grade Ⅱ-Ⅳ aGVHD and CMV-seropositive recipients are the main risk factors associated with CMV infection in PID patients post-UCBT. Survival rate of children with refractory CMV infection after UCBT is reduced. Immune reconstitution in children after UCBT should be regularly monitored, and frequency of CMV-DNA monitoring should be increased for children with delayed immune reconstitution.
Collapse
Affiliation(s)
- Z L Wei
- Department of Hematology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - X W Qian
- Department of Hematology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - P Wang
- Department of Hematology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - W J Jiang
- Department of Hematology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - H S Wang
- Department of Hematology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - C Shen
- Department of Hematology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - W J Wang
- Department of Immunology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - J Hou
- Department of Immunology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Y H Wang
- Department of Gastroenterology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Y Huang
- Department of Gastroenterology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - X C Wang
- Department of Immunology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - X W Zhai
- Department of Hematology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| |
Collapse
|
32
|
Darras B, Hagenacker T, Finkel R, Mercuri E, Montes J, Kuntz N, Farrar M, Sansone V, Berger Z, MacCannell D, Shen C, Paradis A, Bohn J, Wagner J, Somera-Molina K. P.100 Rationale/design of the phase 3b ASCEND study of investigational higher dose nusinersen in participants with SMA previously treated with risdiplam. Neuromuscul Disord 2022. [DOI: 10.1016/j.nmd.2022.07.185] [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: 11/07/2022]
|
33
|
Li T, Xie J, Shen C, Cheng D, Shi Y, Wu Z, Deng X, Chen H, Shen B, Peng C, Li H, Zhan Q, Zhu Z. Retraction Note: Upregulation of long noncoding RNA ZEB1-AS1 promotes tumor metastasis and predicts poor prognosis in hepatocellular carcinoma. Oncogene 2022; 41:4839. [PMID: 36180782 DOI: 10.1038/s41388-022-02480-x] [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: 11/09/2022]
Affiliation(s)
- T Li
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - J Xie
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - C Shen
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - D Cheng
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Y Shi
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Z Wu
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - X Deng
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - H Chen
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - B Shen
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - C Peng
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - H Li
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Q Zhan
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Z Zhu
- Department of Hepato-Bilio-Pancreatic Surgery, Shanghai Institute of Digestive Surgery, Rui Jin Hospital affiliated with Shanghai Jiaotong University, Shanghai, People's Republic of China.
| |
Collapse
|
34
|
Liu X, Grace SL, Ghisi GLM, Shi W, Shen C, Oh P, Zhang Y. Controlled pilot test of a translated cardiac rehabilitation education curriculum in percutaneous coronary intervention patients in a middle-income country delivered using WeChat: acceptability, engagement, satisfaction and preliminary outcomes. Health Educ Res 2022; 37:314-332. [PMID: 36087021 DOI: 10.1093/her/cyac022] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 08/10/2022] [Accepted: 08/23/2022] [Indexed: 06/15/2023]
Abstract
In China, despite the rapid increase in percutaneous coronary interventions (PCIs), cardiac rehabilitation (CR) is just burgeoning, leaving a need for comprehensive evidence-based education curricula. This pilot study assessed the acceptability of Simplified Chinese CR education delivered via booklets and videos on WeChat asynchronously and the impact on improving knowledge, risk factors, health behaviors and quality of life. In this pre-post, controlled, observational study, interested PCI patients received the 12-week intervention or usual care and WeChat without education. Participants completed validated surveys, including the Coronary Artery Disease Education-Questionnaire and Self-Management Scale. Acceptability (14 Likert-type items), engagement (minutes per week) and satisfaction were assessed in intervention participants. Ninety-six patients consented to participate (n = 49 intervention), of which 66 (68.8%) completed the follow-up assessments. Twenty-seven (77.1%) retained intervention participants engaged with the materials, rating content as highly acceptable (all means ≥4/5) and satisfactory (2.19 ± 0.48/3); those engaging more with the intervention were significantly more satisfied (P = 0.03). While participants in both groups achieved some improvements, only intervention participants had significant increases in disease-related knowledge, reductions in body mass index and triglycerides, as well as improvements in diet (all P < 0.05). In this first study validating the recently translated CR patient education intervention, acceptability and benefits have been supported.
Collapse
Affiliation(s)
- X Liu
- School of Nursing, Shanghai Jiao Tong University, 227 Chongqing South Rd, Shanghai 200025, China
| | - S L Grace
- Faculty of Health, York University, Toronto M3J 1P3, Canada
- KITE-Toronto Rehabilitation Institute & Peter Munk Cardiac Centre, University Health Network, University of Toronto, Canada
| | - G L M Ghisi
- Cardiovascular Prevention and Rehabilitation Program, Toronto Rehabilitation Institute, University Health Network, University of Toronto, 347 Rumsey Road, Toronto, Ontario M4G 2R6, Canada
| | - W Shi
- Faculty of Medicine and Health, The University of Sydney Charles Perkins Centre, Sydney 2006, Australia
| | - C Shen
- Cardiology, Shanghai Sixth People's Hospital, 600 Yishan Rd, Shanghai 200233, China
| | - P Oh
- CardiovascularPrevention and Rehabilitation Program, KITE-Toronto Rehabilitation Institute, University Health Network, University of Toronto, 347 Rumsey Road, Toronto, Ontario M4G 2R6, Canada
| | - Y Zhang
- School of Nursing, Shanghai Jiao Tong University, 227 Chongqing South Rd, Shanghai 200025, China
| |
Collapse
|
35
|
de Baere T, Shen C, Ducassou A, Bonvalot S, Chajon E, Farber L, Vivar O, Tyan P, Koay E, Lin S, Liao Z, Dicker A, Hoffmann C, Le Tourneau C. 489P Analysis of 3-dimensional volumetric distribution and dispersion of the radioenhancer NBTXR3 in various solid malignancies. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.617] [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: 11/28/2022] Open
|
36
|
Werner R, Furrer K, Shen C, Wang Y, Curioni-Fontecedro A, Guckenberger M, Matter A, Fang V, Opitz I. EP08.03-006 Survival After Radical Treatment of Oligometastatic Non-small Cell Lung Cancer: A Multicenter Analysis. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.862] [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: 11/28/2022]
|
37
|
Wang JN, Li TT, Fang JL, Tang S, Zhang Y, Deng FC, Shen C, Shi WY, Liu YY, Chen C, Sun QH, Wang YW, Du YJ, Dong HR, Shi XM. [Associations between personal fine particulate matter and blood lipid profiles: A panel study in Chinese people aged 60-69 years]. Zhonghua Yu Fang Yi Xue Za Zhi 2022; 56:897-901. [PMID: 35899340 DOI: 10.3760/cma.j.cn112150-20220525-00527] [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] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To explore the association between short-term exposures to fine particulate matter (PM2.5) on blood lipids in the elderly. Methods: In this panel study, five repeated measurements were performed on 76 people aged 60-69 in Jinan city. Each participant had a PM2.5 monitor for 72 hours before each health examination, including a questionnaire survey, physical examination, and biological sample collection. Serum triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were examined, and non-HDL-C concentrations were calculated by subtracting HDL-C from TC. The generalized linear mixed-effects model was used to quantify the association of personal PM2.5 exposure at different lag with blood lipids and dyslipidemia. Results: The age of 70 participants was (65.0±2.8) years, of which 48.6% (34/70) were males. The BMI of participants was (25.0±2.5) kg/m2. Their TC, TG, LDL-C, HDL-C, and non-HDL-C concentrations were (5.75±1.32), (1.55±0.53), (3.27±0.94), (1.78±0.52), and (3.97±1.06) mmol/L, respectively. Generalized linear mixed-effects model showed that after adjusting for confounding factors, at lag 72 hours, each 10 μg/m3 increase in PM2.5 was associated with the percentage change in TC, LDL-C, HDL-C and non-HDL-C about 1.77% (95%CI: 1.22%-2.32%), 1.90% (95%CI: 1.18%-2.63%), 1.99% (95%CI: 1.37%-2.60%) and 1.74% (95%CI: 1.11%-2.37%), and the OR values (95%CI) of hypercholesterolemia, hypertriglyceridemia and hyperbetalipoproteinemia were 1.11 (1.01-1.22), 1.33 (1.03-1.71) and 1.15 (1.01-1.31), respectively. Conclusion: There is a significant association of short-term PM2.5 exposure with the concentration of blood lipids and the risk of dyslipidemia in the elderly.
Collapse
Affiliation(s)
- J N Wang
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - T T Li
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - J L Fang
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - S Tang
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Y Zhang
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - F C Deng
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - C Shen
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - W Y Shi
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Y Y Liu
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - C Chen
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Q H Sun
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Y W Wang
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Y J Du
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - H R Dong
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - X M Shi
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| |
Collapse
|
38
|
Shen C, Gharleghi R, Li DD, Beier S. Helical Flow in Healthy and Diseased Patient-specific Coronary Bifurcations. Annu Int Conf IEEE Eng Med Biol Soc 2022; 2022:3977-3980. [PMID: 36086059 DOI: 10.1109/embc48229.2022.9871374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Helical flow (HF) exists in healthy and diseased coronary bifurcations and was found to have a protective atherosclerotic vascular effect in other vessels. However, the role of HF in patient-specific human coronary arteries still needs further study, and is therefore the objective of this study in both healthy and diseased bifurcations. Computational studies were conducted on 16 patient-specific coronary bifurcations, including eight healthy and eight identical cases with idealized narrowing to represent disease. In general, higher HF intensity may have a favorable effect as it corelated to the reduction of the percentage vessel area exposed to adverse time averaged wall shear stress (TAWSS%) in both healthy and diseased models. The HF intensity and distribution of each model varies due to the complex shape of patient-specific models. The presence of disease appears to have an important impact on the downstream HF patterns and the TAWSS distributions. Clinical Relevance- By understanding the relationship between HF and hemodynamics, HF may be used as a predictor for the formation and progression of atherosclerotic plaque in coronary arteries instead of near-wall WSS measures, which can be determined with higher accuracy in vivo.
Collapse
|
39
|
Shen C, Schlager C, Rajan D, Pouryahya M, Lin M, Mountain V, Wapinski I, Taylor-Weiner A, Glass B, Egger R, Beck A. Abstract 1922: Application of an interpretable graph neural network to predict gene expression signatures associated with tertiary lymphoid structures in histopathological images. Cancer Res 2022. [DOI: 10.1158/1538-7445.am2022-1922] [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
Background: Tertiary lymphoid structures (TLS) are vascularized lymphocyte aggregates in the tumor microenvironment (TME) that correlate with better patient outcomes. Previous studies identified a 12 chemokine gene expression signature associated with disease progression and the type and degree of TLS. These signatures could provide insight important for clinical decision making during pathologic evaluation, but predicting gene expression from whole slide images (WSI) may be impeded by low prediction accuracy and lack of interpretability. Here we report an artificial intelligence (AI)-based, state-of-the-art workflow to predict the 12-chemokine TLS gene signature from lung cancer WSI, and identify histological features relevant to model predictions.
Methods: Models were trained using 538 cases of paired lung cancer WSI and mRNA-seq expression data (The Cancer Genome Atlas). Cell and tissue classifiers, based on convolutional neural networks (CNN) were trained on WSI, and a graph neural network (GNN) model that leverages the relative spatial arrangement of the CNN-identified cells and tissues was used to predict gene expression. GNN predictions of TLS signature genes were compared with the predictions of models trained using hand-crafted, task-specific features (TLS feature models) describing the number, size, and cellular composition of identified TLS. The Pearson correlation coefficient was used to assess the accuracy of GNN and TLS feature model predictions. GNNExplainer1, a tool that simultaneously identifies a subgraph and a subset of node features important for predictions, was applied to interpret the GNN model predictions.
Results: GNN model predictions show reasonable accuracy: GNN models significantly predicted mRNA expression of all 12 genes (p<0.05), and the predicted expression of six genes was moderately correlated with ground-truth measurements (Pearson-r>0.5). The correlation of GNN predictions was higher than that of the TLS feature models for all 12 signature genes. The GNNExplainer identified relevant features including the mean and standard deviation of lymphocyte count, and fraction of lymphocytes in cancer stroma. Subgraphs selected by the GNNExplainer focus on, but extend beyond, regions of human-annotated TLS objects, indicating that TLS may influence gene expression and the TME in regions beyond their immediate vicinity.
Conclusion: Here, we show a comparison of two interpretable AI methods for the prediction of TLS-induced gene expression from WSI. The outperforming GNN-based approach is highly reproducible and accurate, predicting histopathology features relevant to TLS that may be used to inform patient prognosis and treatment. These methods could be applied to predict additional clinically relevant transcriptomic signatures. 1. Ying, R, et al. 2019. arXiv:1903.03894v4
Citation Format: Ciyue Shen, Collin Schlager, Deepta Rajan, Maryam Pouryahya, Mary Lin, Victoria Mountain, Ilan Wapinski, Amaro Taylor-Weiner, Benjamin Glass, Robert Egger, Andrew Beck. Application of an interpretable graph neural network to predict gene expression signatures associated with tertiary lymphoid structures in histopathological images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1922.
Collapse
|
40
|
Mu M, Cai Z, Shen C, Wang J, Zhao Z, Zhang B. P-220 The efficacy of preoperative imatinib in locally advanced gastrointestinal stromal tumors: A single-center retrospective analysis. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.310] [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
|
41
|
Cai Z, Zhao Z, Mu M, Shen C, Zhang B. P-215 Liver transplantation for hilar cholangiocarcinoma: A systematic review and meta-analysis. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.305] [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
|
42
|
Pham V, Shen Y, Shen C. P-112 Oleic acid promotes the malignant transformation of Kras-mutant colonic organoids via the expansion of tumorigenic stem cells and abnormal Paneth cells through upregulation of NFATc family. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.202] [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: 11/28/2022] Open
|
43
|
Tran T, Huang R, Shen C. P-98 Diabetes promotes the progression of pancreatic ductal adenocarcinoma via the interaction between transforming acinar cells and cancer cells through AKT/CEBPβ/LCN2 pathway. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.188] [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
|
44
|
Morse R, Beaty B, Scanga L, Blumberg J, Patel S, Shen C, Chera B. Diagnostic Accuracy of FNA to Determine HPV Status in HPV-Associated Oropharyngeal Squamous Cell Carcinoma. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2021.12.073] [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]
|
45
|
Zhang JH, Shen C, Shang TH, Liu JL. Difference responses of soil fungal communities to cattle and chicken manure composting application. J Appl Microbiol 2022; 133:323-339. [PMID: 35338761 DOI: 10.1111/jam.15549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 03/05/2022] [Accepted: 03/24/2022] [Indexed: 12/01/2022]
Abstract
AIMS Cattle and poultry manure composting are often applied on agricultural lands but the fungal community composition before and after application in soils is still unclear. Describe soil fungal diversity after manure applications contribute to the correct resource use of livestock and poultry manures. METHODS AND RESULTS Fresh manure samples were obtained from 10 beef cow farms and 12 egg-laying poultry farms at five distinct phases of rearing. Surface soil samples were collected from vegetable plots within the farms after manure application at 15, 30 and 45 t hm-2 . Using high-throughput sequencing techniques, the ITS region was utilized to describe soil fungus populations. The fungal OTUs, Chao1 and ACE of cattle manure were relative higher in fattening stage (>12 months), the OTUs and ACE of chicken manure were the highest in the initial laying stage (16-24 weeks). The fungal diversity indices of vegetable soils hadn't linear change after cow or chicken manure application compared with the control. Ascomycota (84.7% of total sequences), Neocallimastigomycota (9.69%), and Basidiomycota (4.6%) were the dominant phyla in cattle manure. Ascomycota (88.9%) also predominated in chicken manure, followed by Basidiomycota (8.9%). Following both cattle and chicken manure application, the abundance of Ascomycota decreased, while Basidiomycota and Chytridiomycota increased in the soils. None of the dominant genus increased or decreased linearly with the increase of cattle and chicken composting application rate. The fungal dominant genera of the soils with and without manure composting application were mostly affected by soil pH and EC than manure. Pearson's correlation analysis revealed that organic matter, Cu and Hg contents were strongly linked to the fungal diversity and the abundance of specific taxa in cattle manure. In chicken manure, OM, TN and Zn were major factors controlling the fungal diversity and community composition. Soil pH, EC, and Cu, Zn, Cd, Hg and As content had pronounced effects on beneficial and pathogenic genus in soil with and without manure composting. Beneficial fungal genus such as Aspergillus, Plectosphaerella, Acremonium, Meyerozyma and fungal pathogenic like Fusarium, Cladosporium, Verticillium were sensitive to properties (EC, pH, OM) and heavy metals (Cu, Zn, Hg) contents of environment, relatively. The study can serve as an applicable contribution helping in farms management (especially to cattle and poultry breeding) and improve their resource use of livestock and poultry manure. CONCLUSIONS Soil heterogeneity rather than manure determines fungal communities in the vegetable fields, but we can encourage the sensible use of cattle and chicken manure in agroecosystems. SIGNIFICANCE AND IMPACT OF THE STUDY This study will help the farmers regulate the dosage of feed components which can increase the number of beneficial fungal genus or reduce the number of pathogenic fungal genus, improve their resource use of livestock and poultry manure, and encourage the sensible use of cattle and chicken manure in agroecosystems.
Collapse
Affiliation(s)
- J H Zhang
- School of Life Sciences, Ningxia University, Yinchuan 750021, China.,School of Ecology and Environment, Ningxia University, Yinchuan 750021, China.,Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwestern China, Ningxia University, Yinchuan 750021, China
| | - C Shen
- School of Life Sciences, Ningxia University, Yinchuan 750021, China
| | - T H Shang
- School of Geography and Planning, Ningxia University, Yinchuan 750021, China
| | - J L Liu
- School of Ecology and Environment, Ningxia University, Yinchuan 750021, China.,Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwestern China, Ningxia University, Yinchuan 750021, China
| |
Collapse
|
46
|
Lin Y, Shen C, Guo XK, Li Y, Wang DD, Chen X, Wang Z, Wu K, Tao KX, Wu CQ. [Safety evaluation of hyperthermic intraperitoneal chemotherapy in patients with local advanced gastric cancer after radical resection for prevention of peritoneal metastasis]. Zhonghua Wei Chang Wai Ke Za Zhi 2022; 25:48-55. [PMID: 35067034 DOI: 10.3760/cma.j.cn441530-20210514-00206] [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] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: Patients with advanced gastric cancer have a poor prognosis and a possibility of peritoneal metastasis even if receiving gastrectomy. Hyperthermic intraperitoneal chemotherapy (HIPEC) can effectively kill free cancer cells or small lesions in the abdominal cavity. At present, preventive HIPEC still lacks safety evaluation in patients with locally advanced gastric cancer. This study aims to explore the safety of radical resection combined with HIPEC in patients with locally advanced gastric cancer. Methods: A descriptive case series study was carried out. Clinicopathological data of 130 patients with locally advanced gastric cancer who underwent radical resection + HIPEC at the Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from January 2020 to February 2021 were retrospectively analyzed. Inclusion criteria: (1) locally advanced gastric adenocarcinoma confirmed by postoperative pathology; (2) no distant metastasis was found before surgery; (3) radical resection; (4) at least one HIPEC treatment was performed. Exclusion criteria: (1) incomplete clinicopathological data; (2) tumor metastasis was found during operation; (3) concomitant with other tumors. HIPEC method: all the patients received the first HIPEC immediately after D2 radical resection, and returned to the ward after waking up from anesthesia; the second and the third HIPEC were carried out according to the patient's postoperative recovery and tolerance; interval between two HIPEC treatments was 48 h. Observation indicators: (1) basic information, including gender, age, body mass index, etc.; (2) treatment status; (3) perioperative adverse events: based on the standard of common adverse events published by the US Department of Health and Public Health (CTCAE 5.0), the adverse events of grade 2 and above during the treatment period were recorded, including hypoalbuminemia, bone marrow cell reduction, wound complications, abdominal infection, lung infection, gastroparesis, anemia, postoperative bleeding, anastomotic leakage, intestinal obstruction, pleural effusion, abdominal distension, impaired liver function, and finally a senior professional title chief physician reviewed the above adverse events and made a safety evaluation of the patient; (4) association between times of HIPEC treatment and adverse events in perioperative period; (5) analysis of risk factors for adverse events in perioperative period. Results: Among the 130 patients, 79 were males and 51 were females with a median age of 59 (54, 66) years and an average body mass index of (23.9±7.4) kg/m(2). The tumor size was (5.4±3.0) cm and 100 patients (76.9%) had nerve invasion. All the 130 patients received radical resection + HIPEC and 125 (96.2%) patients underwent laparoscopic surgery. The mean operative time was (345.6±52.3) min and intraoperative blood loss was (82.0±36.5) ml. One HIPEC treatment was performed in 54 patients (41.5%), 2 HIPEC treatments were in 57 (43.8%), and 3 HIPEC treatments were in 19 (14.6%). The average postoperative hospital stay was (13.1±7.5) d. A total of 57 patients (43.8%) had 71 cases of postoperative complications of different degrees. Among them, the incidence of hypoalbuminemia was 22.3% (29/130), and the grade 2 and above anemia was 15.4% (20/130), lung infection was 3.8% (5/130), bone marrow cell suppression was 3.7% (4/130), abdominal cavity infection was 2.3% (3/130), and liver damage was 2.3% (3/130), wound complications was 1.5% (2/130), abdominal distension was 1.5% (2/130), anastomotic leakage was 0.8% (1/130), gastroparesis was 0.8% (1/130) and intestinal obstruction was 0.8% (1/130), etc. These adverse events were all improved by conservative treatments. There were no statistically significant differences in the incidence of adverse events during the perioperative period among patients undergoing 1, 2, and 3 times of HIPEC treatments (all P>0.05). Univariate and multivariate logistic analyses showed that age > 60 years (OR: 2.346, 95%CI: 1.069-5.150, P=0.034) and neurological invasion (OR: 2.992, 95%CI: 1.050-8.523, P=0.040) were independent risk factors for adverse events in locally advanced gastric cancer patients undergoing radical resection+HIPEC (both P<0.05). Conclusions: Radical surgery + HIPEC does not significantly increase the incidence of perioperative complications in patients with advanced gastric cancer. The age >60 years and nerve invasion are independent risk factors for adverse events in these patients.
Collapse
Affiliation(s)
- Y Lin
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - C Shen
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - X K Guo
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Y Li
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - D D Wang
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - X Chen
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Z Wang
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - K Wu
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - K X Tao
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - C Q Wu
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| |
Collapse
|
47
|
Shen C, Gharleghi R, Li DD, Stevens M, Dokos S, Beier S. Secondary flow in bifurcations - Important effects of curvature, bifurcation angle and stents. J Biomech 2021; 129:110755. [PMID: 34601214 DOI: 10.1016/j.jbiomech.2021.110755] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [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: 12/28/2020] [Revised: 09/01/2021] [Accepted: 09/16/2021] [Indexed: 12/27/2022]
Abstract
Coronary bifurcations have complex flow patterns including secondary flow zones and helical flow, which directly affect pathophysiological mechanisms such as the development of atherosclerosis. The objective of this study was to generate insights into the effects of curvature, bifurcation angle and the presence of stents on flow patterns and resulting haemodynamics in coronary left main bifurcations. The blood flow and associated metrics were modelled in both idealised and patient-specific bifurcations with varying curvature and bifurcation angles with and without stents, resulting in a total of 128 geometries considered. The results showed that larger curvature of bifurcating vessels has a significant influence on secondary flow, especially with distance to the bifurcation region, causing a skew, spin and asymmetry of Dean vortices, an increase in helical flow intensity with symmetry loss, and a decrease in adversely low time-average wall shear stress (TAWSS). Generally, asymmetric flow patterns coincided with adversely low TAWSS regions. In identical stented geometries, the presence of the stents induced local recirculation immediately adjacent to the stent struts, thus generating adversely low TAWSS in these areas, with some effect on the overall secondary flow. Overall, the effect of stents outweighed the effect of curvature and BA. This new knowledge contributes to a better understanding of the joint effects of curvature, bifurcation angle, and stents on flow patterns and haemodynamics in coronary bifurcations.
Collapse
Affiliation(s)
- C Shen
- School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney NSW 2052, Australia.
| | - R Gharleghi
- School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney NSW 2052, Australia
| | - D D Li
- School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney NSW 2052, Australia
| | - M Stevens
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney NSW 2052, Australia
| | - S Dokos
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney NSW 2052, Australia
| | - S Beier
- School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney NSW 2052, Australia
| |
Collapse
|
48
|
Boltz T, Moritz J, Ayres V, Showman C, Jaczynski J, Shen C. Modeling thermal inactivation of Salmonella Typhimurium in mash broiler feed. J APPL POULTRY RES 2021. [DOI: 10.1016/j.japr.2021.100208] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
|
49
|
Shen C, Frakes J, Niu J, Rosenberg A, Weiss J, Caudell J, Jameson K, Said P, Seiwert T. NBTXR3 Activated by Radiotherapy in Combination With Nivolumab or Pembrolizumab in Patients With Advanced Cancers: A Phase I Trial. Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.07.1075] [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]
|
50
|
Shumway J, Torras M, Hayes KR, Jolly T, Dees E, Ray E, Carey L, Shen C. Outcomes of Patients With HER2-Positive Breast Cancer Metastatic to Brain Treated With HER2-Targeted Systemic Therapy and Stereotactic Radiosurgery. Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.07.1558] [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: 11/30/2022]
|