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现代生物医学进展 2017年第15期17卷 I0003-I0003页

作者： Huipeng Li, Elise T Courtois, Debarka Sengupta, Yuliana Tan Shyam Prabhakar Elise T Courtois, Yuliana Tan Paul Robson Debarka Sengupta Kok Hao Chen, Jolene Jie Lin Goh Paul Jongjoon Choi Say Li Kong, Axel M Hillmer Iain Beehuat Tan Clarinda Chua Iain Beehuat Tan Lim Kiat Hon Wah Siew Tan Mark Wong Lawrence J K Wee Iain Beehuat Tan Paul Robson Paul Robson Paul Robson Computational and Systems Biology Genome Institute of Singapore Singapore Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India Synthetic Biology Genome Institute of Singapore Singapore Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Department of Medical Oncology National Cancer Centre Singapore Singapore Department of Pathology Singapore General Hospital Singapore Department of Colorectal Surgery Singapore General Hospital Singapore Data Analytics Department Institute for Infocomm Research Singapore Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA Department of Biological Sciences National University of Singapore Singapore.

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测... 详细信息

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测序。”JAX科学家、这篇发表在Nature Genetics上的文章共同第一作者Elise Courtois说道。”我们可以根据肿瘤中的细胞组成将结直肠癌进一步分类。因为每种亚型的肿瘤病人生存率存在差别，我们的方法将为肿瘤医生提供更多的关于肿瘤预后和治疗的信息。”

关键词：单细胞分析结直肠癌癌细胞 Nat 细胞组成肿瘤病计算机技术细胞生物学

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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Digitising heart transplant rejection

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Lancet (London, England) 2022年第10345期400卷 17页

作者： Faisal Mahmood Eric J Topol Department of Pathology Brigham and Women's Hospital Harvard Medical School Boston MA 02115 USA Cancer Program Broad Institute of Harvard and MIT Cambridge MA USA Harvard Data Science Initiative Harvard University Cambridge MA USA. Electronic address: faisalmahmood@bwh.harvard.edu. Scripps Research Translational Institute Scripps Research La Jolla CA USA.

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*** - A plug-and-play solution for online systems medicine and network-based drug repurposing

arXiv

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arXiv 2023年

作者： Maier, Andreas Hartung, Michael Abovsky, Mark Adamowicz, Klaudia Bader, Gary D. Baier, Sylvie Blumenthal, David B. Chen, Jing Elkjaer, Maria L. Garcia-Hernandez, Carlos Helmy, Mohamed Hoffmann, Markus Jurisica, Igor Kotlyar, Max Lazareva, Olga Levi, Hagai List, Markus Lobentanzer, Sebastian Loscalzo, Joseph Malod-Dognin, Noel Manz, Quirin Matschinske, Julian Mee, Miles Oubounyt, Mhaned Pico, Alexander R. Pillich, Rudolf T. Poschenrieder, Julian M. Pratt, Dexter Pržulj, Nataša Sadegh, Sepideh Saez-Rodriguez, Julio Sarkar, Suryadipto Shaked, Gideon Shamir, Ron Trummer, Nico Turhan, Ugur Wang, Ruisheng Zolotareva, Olga Baumbach, Jan Institute for Computational Systems Biology University of Hamburg Hamburg Germany Division of Orthopaedic Surgery Schroeder Arthritis Institute Data Science Discovery Centre Osteoarthritis Research Program Krembil Research Institute UHN Toronto Canada Data Science Discovery Centre for Chronic Diseases Krembil Research Institute University Health Network 60 Leonard Avenue 5KD-407 TorontoONM5T 0S8 Canada Department of Molecular Genetics University of Toronto TorontoON Canada The Donnelly Centre University of Toronto TorontoON Canada Department of Computer Science University of Toronto TorontoON Canada Princess Margaret Cancer Centre University Health Network TorontoON Canada The Lunenfeld-Tanenbaum Research Institute Mount Sinai Hospital TorontoON Canada TUM School of Life Sciences Technical University of Munich Munich Germany Erlangen91052 Germany Department of Medicine University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Neurology Odense University Hospital Odense Denmark Institute of Clinical Research University of Southern Denmark Odense Denmark Institute of Molecular Medicine University of Southern Denmark Odense Denmark Barcelona08034 Spain Institute for Advanced Study Lichtenbergstrasse 2a GarchingD-85748 Germany Technical University of Munich Germany National Institute of Diabetes Digestive and Kidney Diseases BethesdaMD20892 United States Departments of Medical Biophysics and Computer Science University of Toronto Toronto Canada Institute of Neuroimmunology Slovak Academy of Sciences Bratislava Slovakia Heidelberg69120 Germany Heidelberg Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg69117 Germany Blavatnik School of Computer Science Tel-Aviv University Tel-Aviv Israel Heidelberg University Faculty of Medicine Heidelberg University Hospital Institute for Computational Biomedicine Bioquant Heidelberg Germany Department of Medicine Bri

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce ***, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, *** turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, *** has been successfully integrated with 21 computational systems medicine tools. Available at https://***, *** has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research. © 2023, CC BY.

关键词： data visualization

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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159P Spatial organization of B cells in the prediction and prognosis of gastric cancer

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Annals of Oncology 2024年 35卷 S1467-S1467页

作者： R. Tay M. Sachdeva Y.W. Kim M-C. Kook H. Kim J-H. Cheong G. Schmidt T. Yoshikawa T. Oshima H. Ma T. Sheng P. Tan H.I. Grabsch R. Sundar Yong Loo Lin School of Medicine NUS - National University of Singapore Singapore Medical Oncology Department NCIS - National University Cancer Institute Singapore Singapore Department of Cancer Policy and Population Health NCC - National Cancer Center Goyang Republic of Korea Department of Pathology NCC - National Cancer Center Goyang Republic of Korea Department of Pathology Severance Hospital - Yonsei University College of Medicine Seoul Republic of Korea Department of Surgery Yonsei University Seoul Republic of Korea Image Data Sciences AstraZeneca Computational Pathology GmbH Munich Germany Gastric Surgery National Cancer Center Hospital Tokyo Japan Department of Gastrointestinal Surgery Kanagawa Cancer Center Yokohama Japan Cancer and Stem Cell Biology Program Duke-NUS Graduate Medical School Singapore Genome Institute of Singapore A*STAR - Agency for Science Technology and Research Singapore Programme in Cancer & Stem Cell Biology Duke-NUS Graduate Medical School Singapore Pathology Maastricht University Medical Center (MUMC) Maastricht Netherlands Haematology-Oncology NUHS - National University Health System Singapore

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A Randomized Controlled Crossover Trial to Evaluate the Efficacy of AI-Assisted Heart Contouring

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International Journal of Radiation Oncology, Biology, Physics 2024年第2期120卷 S41-S41页

作者： Bitterman, D.S. Guthier, C.V. Shin, K.Y. Zeleznik, R. Doyle, P. Guevara, M. Kang, H. Dillon-Martin, M. Perkins, T. Orlina, L.T. Pei, Y. Bredfeldt, J.S. Catalano, P.J. Bellon, J.R. Punglia, R.S. Warren, L. Wong, J.S. Kozono, D.E. Mak, R.H. Department of Radiation Oncology Dana-Farber Cancer Institute/Brigham and Women’s Hospital Harvard Medical School Boston MA Department of Data Science Dana-Farber Cancer Institute Boston MA Artificial Intelligence in Medicine (AIM) Program at Harvard Boston MA Brigham and Women’s Hospital/Dana-Farber Boston MA United States Department of Radiation Oncology Brigham and Women’s Hospital/Dana-Farber Cancer Institute Boston MA Boston University Chobanian & Avedisian School of Medicine Boston MA Brigham and Women’s Hospital/Dana-Farber Boston MA Brigham and Women’s Hospital Boston MA Department of Radiation Oncology Dana-Farber Cancer Institute/Brigham and Women’s Hospital Boston MA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute Harvard Medical School Boston MA Dana-Farber/Brigham and Women’s Cancer Center Boston MA Department of Radiation Oncology Dana-Farber Cancer Institute Boston MA

Purpose/Objective(s)Artificial intelligence (AI) normal tissue contouring tools are now widely available and used in many treatment planning systems. However, few studies have prospectively demonstrated the value of such tools when employed in clinical workflows. We conducted a randomized controlled trial to assess the benefit of using an AI heart contouring algorithm to assist breast radiotherapy (RT) planning. Materials/MethodsA single institution, 2-arm randomized controlled crossover trial was undertaken between December 2021 and October 2023. A convolutional neural network for heart auto-contouring, which had median Dice 0.95 compared to gold standard contours and reduced contouring time by 50% in pre-clinical studies, was implemented as a scripted tool within a treatment planning system. Eligible patients had breast cancer planned for RT, with hearts contoured according to the randomization of the dosimetrist assigned to their plan. Dosimetrists were stratified by experience and randomized to (1) manual heart contouring first or (2) AI-assisted heart contouring first. AI-assisted contouring consisted of running the model within the treatment planning system and editing the contour as needed. After completing 5 cases on the initial contour strategy, dosimetrists crossed to the other strategy. Co-primary outcomes were feasibility and efficacy, defined as heart contouring time (measured by recording screen during contouring). Secondary endpoints included dosimetrist and treating physician contour assessments. The trial had 90% power to detect a 30% reduction in contour time with 2-sided type I error of 5%. ResultsOne hundred eighteen patients enrolled; 60 patients’ hearts were contoured manually and 58 with AI assistance. Eleven dosimetrists enrolled; 5 were randomized to manual first arm and 6 to AI-assisted first arm. There was no difference in manual vs. AI-assisted contour time overall (mean 277.3 ± 151.2 vs. 267.2 ± 199.0 seconds, P = 0.76), on the manual fi

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TRANSCEND CLL 004: PHASE 1 COHORT OF LISOCABTAGENE MARALEUCEL (LISO-CEL) COMBINED WITH IBRUTINIB (IBR) FOR PATIENTS (PTS) WITH R/R CLL/SLL

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Hematological Oncology 2021年第S2期39卷

作者： W. G. Wierda K. A. Dorritie J. Munoz D. M. Stephens S. Solomon H. H. Gillenwater L. Gong L. Yang K. Ogasawara J. Thorpe T. Siddiqi The University of Texas MD Anderson Cancer Center Department of Leukemia Division of Cancer Medicine Houston Texas USA UPMC Hillman Cancer Center Division of Hematology/Oncology Pittsburgh Pennsylvania USA Banner MD Anderson Cancer Center Department of Lymphoma/Myeloma Phoenix Arizona USA Hutsman Cancer Institute University of Utah Salt Lake City Utah USA Immunotherapy Program Northside Hospital Cancer Institute Atlanta Georgia USA Bristol Myers Squibb Global Clinical Development Seattle Washington USA Bristol Myers Squibb Clinical Research and Development Seattle Washington USA Bristol Myers Squibb Global Biometric and Data Science Seattle Washington USA Bristol Myers Squibb Clinical Pharmacology and Pharmacometrics Princeton New Jersey USA Bristol Myers Squibb Immunomodulatory therapies Seattle Washington USA City of Hope National Medical Center Department of Hematology & Hematopoietic Cell Transplantation Duarte California USA

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Leukemia Evolution and Resistance to Graft-Versus-Leukemia Responses Revealed By Mitochondrial DNA Mutations

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Blood 2024年 144卷 926-926页

作者： Livius Penter Nicoletta Cieri Katie Maurer Marwan Kwok Haoxiang Lyu Wesley S Lu Giacomo Oliveira Satyen H Gohil Ignaty Leshchiner Caleb Lareau Leif S Ludwig Donna S. Neuberg Haesook T. Kim Shuqiang Li Lars Bullinger Jerome Ritz Gad Getz Jacqueline S. Garcia Robert J. Soiffer Kenneth J. Livak Catherine J. Wu Department of Hematology Oncology and Cancer Immunology Campus Virchow Klinikum Charité - Universitätsmedizin Berlin Berlin Germany Department of Medical Oncology Dana-Farber Cancer Institute Berlin Germany Harvard Medical School Boston MA Broad Institute of MIT and Harvard Cambridge MA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA Institute of Cancer and Genomic Sciences University of Birmingham Bimingham United Kingdom Institute of Cancer and Genomic Sciences University of Birmingham Birmingham United Kingdom Queen Elizabeth Hospital Birmingham Centre for Clinical Haematology Birmingham United Kingdom Translational Immunogenomics Lab Dana-Farber Cancer Institute Boston MA Haematology University College Hospital London United Kingdom Cancer Program Broad Institute of MIT and Harvard Cambridge MA Memorial Sloan Kettering Cancer Center New York NY Berlin Institute of Health at Charité - Universitätsmedizin Berlin Berlin Germany Department of Data Science Dana-Farber Cancer Institute Boston MA Department of Hematology Oncology and Cancer Immunology Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin and Berlin Institute of Health Berlin Germany Department of Pathology Massachusetts General Hospital Boston MA

Graft-versus-leukemia (GvL) responses enable successful allogeneic hematopoietic cell transplantation (HCT), a cornerstone treatment for high-risk blood cancers such as acute myeloid leukemia (AML) or advanced chronic lymphocytic leukemia (CLL). Yet, monitoring of GvL effects remains challenging, including early detection of emerging immune escape or tracking of clonal evolution during phases of incomplete leukemia control. We hypothesized that mitochondrial DNA (mtDNA) mutation analysis would be an effective tool for sensitive monitoring of clonal evolution and measurable residual disease (MRD) that could yield new insights into the dynamics and cellular phenotypes of GvL response or resistance. To establish mtDNA mutations as natural genetic barcodes capable of resolving leukemic evolution, we analyzed 126 serially collected bulk RNA and whole-exome sequencing (WES) datasets of CD19 + sorted CLL cells from 34 individuals (median interval first-to-last sample 2,184 days, range 280-4,402). We discerned high correlation between changes in heteroplasmy of mtDNA mutations (RNA-seq) and cancer cell fraction (CCF, calculated from WES data) (r=0.84; p<0.001). In particular, heteroplasmy and CCF changes were smaller in genetically stable (n=8) compared to evolving (n=18) CLL (coefficient of variation 24 vs 60 [heteroplasmy] and 31 vs 57 [CCF]; p<0.001). Following HCT (n=8), shorter vs longer days-to-relapse (median 310 vs 1,082) was associated with lesser vs more changes in heteroplasmy (p=0.034), suggesting the ability to measure cumulative GvL effects with mtDNA mutations. In 3 cases, we obtained single cell (sc) DNA-seq profiles (Tapestri) from circulating CLL before and after HCT and directly detected co-evolution of somatic nuclear with mtDNA mutations. Thus, mtDNA mutations track with leukemia clones and their dynamics are highly consistent with changes in somatic nuclear DNA mutations. To assess mtDNA mutations as sensitive markers of MRD, we determined their median

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1507TiP Phase Ib multicenter study of trastuzumab deruxtecan (T-DXd) and immunotherapy with or without chemotherapy in first-line treatment of patients (pts) with advanced or metastatic nonsquamous non-small cell lung cancer (NSCLC) and HER2 overexpression (OE): DESTINY-Lung03

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Annals of Oncology 2023年 34卷 S848-S849页

作者： D. Planchard J.R. Brahmer J.C-H. Yang H.R. Kim R.K. Li J-Y. Han D.L. Cortinovis Y. Runglodvatana E. Nakajima A. Ragone M. Winter M. Gustavson Department of Medical Oncology Institut Gustave Roussy Villejuif France Thoracic Oncology Program The Johns Hopkins Kimmel Cancer Center Baltimore MD USA Medical Oncology Department National Taiwan University Hospital Taipei City Taiwan Department of Internal Medicine Division of Medical Oncology Yonsei Cancer Center Seoul Republic of Korea Medical Oncology Department St. Luke's Medical Center - Quezon City Quezon City Philippines Center for Lung Cancer National Cancer Center - Graduate School of Cancer Science and Policy Goyang Republic of Korea SC Oncologia Medica Fondazione IRCCS San Gerardo dei Tintori Monza Italy Division of Medical Oncology Vajira Hospital - Faculty of Medicine - Navamindradhiraj University Bangkok Thailand Late Development Oncology R&D AstraZeneca Gaithersburg MD USA Late Development Oncology R&D AstraZeneca Mississauga ON Canada Data Science and Quantitative Biology AstraZeneca Cambridge UK Translational Medicine Oncology R&D AstraZeneca Gaithersburg MD USA

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