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Author

Chen Wang

Bio: Chen Wang is an academic researcher from Mayo Clinic. The author has contributed to research in topics: Medicine & Serous fluid. The author has an hindex of 33, co-authored 159 publications receiving 11490 citations. Previous affiliations of Chen Wang include Shanghai Jiao Tong University & University of Science and Technology of China.
Topics: Medicine, Serous fluid, Ovarian cancer, Cancer, Ankle


Papers
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Journal ArticleDOI
Gad Getz1, Stacey Gabriel1, Kristian Cibulskis1, Eric S. Lander1  +280 moreInstitutions (31)
02 May 2013-Nature
TL;DR: In this paper, the authors performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array-and-sequencing-based technologies, and classified them into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy number high.
Abstract: We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B. A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours.

3,719 citations

01 Jan 2013
TL;DR: The genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours, and these features are classified into four categories: POLE ultramutated, microsatellite instability hypermutated, copy- number low, and copy-number high.
Abstract: We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B. A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours.

2,448 citations

Journal ArticleDOI
05 Apr 2018-Cell
TL;DR: This work charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity.

1,841 citations

Journal ArticleDOI
TL;DR: These frequent DDR gene alterations in many human cancers have functional consequences that may determine cancer progression and guide therapy and a new machine-learning-based classifier developed from gene expression data allowed to identify alterations that phenocopy deleterious TP53 mutations.

706 citations

Journal ArticleDOI
Alison M. Taylor1, Alison M. Taylor2, Juliann Shih1, Gavin Ha2  +729 moreInstitutions (4)
TL;DR: The genomic and phenotypic correlates of cancer aneuploidy are defined and genome engineering is applied to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication.

660 citations


Cited by
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Journal ArticleDOI
Ludmil B. Alexandrov1, Serena Nik-Zainal2, Serena Nik-Zainal3, David C. Wedge1, Samuel Aparicio4, Sam Behjati5, Sam Behjati1, Andrew V. Biankin, Graham R. Bignell1, Niccolo Bolli5, Niccolo Bolli1, Åke Borg3, Anne Lise Børresen-Dale6, Anne Lise Børresen-Dale7, Sandrine Boyault8, Birgit Burkhardt8, Adam Butler1, Carlos Caldas9, Helen Davies1, Christine Desmedt, Roland Eils5, Jorunn E. Eyfjord10, John A. Foekens11, Mel Greaves12, Fumie Hosoda13, Barbara Hutter5, Tomislav Ilicic1, Sandrine Imbeaud14, Sandrine Imbeaud15, Marcin Imielinsk14, Natalie Jäger5, David T. W. Jones16, David T. Jones1, Stian Knappskog11, Stian Knappskog17, Marcel Kool11, Sunil R. Lakhani18, Carlos López-Otín18, Sancha Martin1, Nikhil C. Munshi19, Nikhil C. Munshi20, Hiromi Nakamura13, Paul A. Northcott16, Marina Pajic21, Elli Papaemmanuil1, Angelo Paradiso22, John V. Pearson23, Xose S. Puente18, Keiran Raine1, Manasa Ramakrishna1, Andrea L. Richardson20, Andrea L. Richardson22, Julia Richter22, Philip Rosenstiel22, Matthias Schlesner5, Ton N. Schumacher24, Paul N. Span25, Jon W. Teague1, Yasushi Totoki13, Andrew Tutt24, Rafael Valdés-Mas18, Marit M. van Buuren25, Laura van ’t Veer26, Anne Vincent-Salomon27, Nicola Waddell23, Lucy R. Yates1, Icgc PedBrain24, Jessica Zucman-Rossi14, Jessica Zucman-Rossi15, P. Andrew Futreal1, Ultan McDermott1, Peter Lichter24, Matthew Meyerson20, Matthew Meyerson14, Sean M. Grimmond23, Reiner Siebert22, Elias Campo28, Tatsuhiro Shibata13, Stefan M. Pfister11, Stefan M. Pfister16, Peter J. Campbell29, Peter J. Campbell2, Peter J. Campbell30, Michael R. Stratton2, Michael R. Stratton31 
22 Aug 2013-Nature
TL;DR: It is shown that hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types, and this results reveal the diversity of mutational processes underlying the development of cancer.
Abstract: All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.

7,904 citations

Journal ArticleDOI
TL;DR: This study showed that mismatch-repair status predicted clinical benefit of immune checkpoint blockade with pembrolizumab, and high somatic mutation loads were associated with prolonged progression-free survival.
Abstract: BackgroundSomatic mutations have the potential to encode “non-self” immunogenic antigens. We hypothesized that tumors with a large number of somatic mutations due to mismatch-repair defects may be susceptible to immune checkpoint blockade. MethodsWe conducted a phase 2 study to evaluate the clinical activity of pembrolizumab, an anti–programmed death 1 immune checkpoint inhibitor, in 41 patients with progressive metastatic carcinoma with or without mismatch-repair deficiency. Pembrolizumab was administered intravenously at a dose of 10 mg per kilogram of body weight every 14 days in patients with mismatch repair–deficient colorectal cancers, patients with mismatch repair–proficient colorectal cancers, and patients with mismatch repair–deficient cancers that were not colorectal. The coprimary end points were the immune-related objective response rate and the 20-week immune-related progression-free survival rate. ResultsThe immune-related objective response rate and immune-related progression-free survival ...

6,835 citations

Journal ArticleDOI
TL;DR: The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA with a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages.
Abstract: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.

5,294 citations

Journal ArticleDOI
TL;DR: A method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples and prediction accuracy is corroborated using 3,809 transcriptional profiles available elsewhere in the public domain.
Abstract: Infiltrating stromal and immune cells form the major fraction of normal cells in tumour tissue and not only perturb the tumour signal in molecular studies but also have an important role in cancer biology. Here we describe 'Estimation of STromal and Immune cells in MAlignant Tumours using Expression data' (ESTIMATE)--a method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples. ESTIMATE scores correlate with DNA copy number-based tumour purity across samples from 11 different tumour types, profiled on Agilent, Affymetrix platforms or based on RNA sequencing and available through The Cancer Genome Atlas. The prediction accuracy is further corroborated using 3,809 transcriptional profiles available elsewhere in the public domain. The ESTIMATE method allows consideration of tumour-associated normal cells in genomic and transcriptomic studies. An R-library is available on https://sourceforge.net/projects/estimateproject/.

4,651 citations

Journal Article
01 Sep 2013-Nature
TL;DR: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels as mentioned in this paper.
Abstract: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.

4,634 citations