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Eliezer M. Van Allen

Bio: Eliezer M. Van Allen is an academic researcher from Harvard University. The author has contributed to research in topics: Medicine & Prostate cancer. The author has an hindex of 73, co-authored 306 publications receiving 36742 citations. Previous affiliations of Eliezer M. Van Allen include Broad Institute & Massachusetts Institute of Technology.


Papers
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Journal ArticleDOI
08 Apr 2016-Science
TL;DR: The cellular ecosystem of tumors is begin to unravel and how single-cell genomics offers insights with implications for both targeted and immune therapies is unraveled.
Abstract: To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.

3,061 citations

Journal ArticleDOI
Dan R. Robinson1, Eliezer M. Van Allen2, Eliezer M. Van Allen3, Yi-Mi Wu1, Nikolaus Schultz4, Robert J. Lonigro1, Juan Miguel Mosquera, Bruce Montgomery5, Mary-Ellen Taplin3, Colin C. Pritchard5, Gerhardt Attard6, Gerhardt Attard7, Himisha Beltran, Wassim Abida4, Robert K. Bradley5, Jake Vinson4, Xuhong Cao1, Pankaj Vats1, Lakshmi P. Kunju1, Maha Hussain1, Felix Y. Feng1, Scott A. Tomlins, Kathleen A. Cooney1, David Smith1, Christine Brennan1, Javed Siddiqui1, Rohit Mehra1, Yu Chen4, Yu Chen8, Dana E. Rathkopf8, Dana E. Rathkopf4, Michael J. Morris4, Michael J. Morris8, Stephen B. Solomon4, Jeremy C. Durack4, Victor E. Reuter4, Anuradha Gopalan4, Jianjiong Gao4, Massimo Loda, Rosina T. Lis3, Michaela Bowden9, Michaela Bowden3, Stephen P. Balk10, Glenn C. Gaviola9, Carrie Sougnez2, Manaswi Gupta2, Evan Y. Yu5, Elahe A. Mostaghel5, Heather H. Cheng5, Hyojeong Mulcahy5, Lawrence D. True11, Stephen R. Plymate5, Heidi Dvinge5, Roberta Ferraldeschi6, Roberta Ferraldeschi7, Penny Flohr7, Penny Flohr6, Susana Miranda7, Susana Miranda6, Zafeiris Zafeiriou7, Zafeiris Zafeiriou6, Nina Tunariu7, Nina Tunariu6, Joaquin Mateo7, Joaquin Mateo6, Raquel Perez-Lopez7, Raquel Perez-Lopez6, Francesca Demichelis8, Francesca Demichelis12, Brian D. Robinson, Marc H. Schiffman8, David M. Nanus, Scott T. Tagawa, Alexandros Sigaras8, Kenneth Eng8, Olivier Elemento8, Andrea Sboner8, Elisabeth I. Heath13, Howard I. Scher4, Howard I. Scher8, Kenneth J. Pienta14, Philip W. Kantoff3, Johann S. de Bono6, Johann S. de Bono7, Mark A. Rubin, Peter S. Nelson, Levi A. Garraway2, Levi A. Garraway3, Charles L. Sawyers4, Arul M. Chinnaiyan 
21 May 2015-Cell
TL;DR: This cohort study provides clinically actionable information that could impact treatment decisions for affected individuals and identified new genomic alterations in PIK3CA/B, R-spondin, BRAF/RAF1, APC, β-catenin, and ZBTB16/PLZF.

2,713 citations

Journal ArticleDOI
Rehan Akbani, Kadir C. Akdemir, B. Arman Aksoy1, Monique Albert1  +348 moreInstitutions (1)
18 Jun 2015-Cell
TL;DR: This clinicopathological and multi-dimensional analysis suggests that the prognosis of melanoma patients with regional metastases is influenced by tumor stroma immunobiology, offering insights to further personalize therapeutic decision-making.

2,337 citations

Journal ArticleDOI
25 Mar 2016-Science
TL;DR: A relationship between clonal neoantigen burden and overall survival in primary lung adenocarcinomas and the impact of neoantigens intratumor heterogeneity (ITH) on antitumor immunity is demonstrated.
Abstract: As tumors grow, they acquire mutations, some of which create neoantigens that influence the response of patients to immune checkpoint inhibitors. We explored the impact of neoantigen intratumor heterogeneity (ITH) on antitumor immunity. Through integrated analysis of ITH and neoantigen burden, we demonstrate a relationship between clonal neoantigen burden and overall survival in primary lung adenocarcinomas. CD8+ tumor-infiltrating lymphocytes reactive to clonal neoantigens were identified in early-stage non–small cell lung cancer and expressed high levels of PD-1. Sensitivity to PD-1 and CTLA-4 blockade in patients with advanced NSCLC and melanoma was enhanced in tumors enriched for clonal neoantigens. T cells recognizing clonal neoantigens were detectable in patients with durable clinical benefit. Cytotoxic chemotherapy–induced subclonal neoantigens, contributing to an increased mutational load, were enriched in certain poor responders. These data suggest that neoantigen heterogeneity may influence immune surveillance and support therapeutic developments targeting clonal neoantigens.

2,284 citations

Journal ArticleDOI
Adam Abeshouse1, Jaeil Ahn1, Rehan Akbani1, Adrian Ally1  +308 moreInstitutions (1)
05 Nov 2015-Cell
TL;DR: The Cancer Genome Atlas (TCGA) has been used for a comprehensive molecular analysis of primary prostate carcinomas as discussed by the authors, revealing substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course.

2,109 citations


Cited by
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Journal ArticleDOI
Ludmil B. Alexandrov1, Serena Nik-Zainal2, Serena Nik-Zainal3, David C. Wedge1, Samuel Aparicio4, Sam Behjati1, Sam Behjati5, Andrew V. Biankin, Graham R. Bignell1, Niccolo Bolli1, Niccolo Bolli5, 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 Imielinsk15, Natalie Jäger5, David T. W. Jones16, David T. Jones1, Stian Knappskog17, Stian Knappskog11, 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. Richardson19, 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-Rossi15, Jessica Zucman-Rossi14, P. Andrew Futreal1, Ultan McDermott1, Peter Lichter24, Matthew Meyerson15, Matthew Meyerson19, Sean M. Grimmond23, Reiner Siebert22, Elias Campo28, Tatsuhiro Shibata13, Stefan M. Pfister16, Stefan M. Pfister11, Peter J. Campbell29, Peter J. Campbell2, Peter J. Campbell30, Michael R. Stratton31, Michael R. Stratton2 
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: An analytical strategy for integrating scRNA-seq data sets based on common sources of variation is introduced, enabling the identification of shared populations across data sets and downstream comparative analysis.
Abstract: Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

7,741 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

01 Jan 2016
TL;DR: The modern applied statistics with s is universally compatible with any devices to read, and is available in the digital library an online access to it is set as public so you can download it instantly.
Abstract: Thank you very much for downloading modern applied statistics with s. As you may know, people have search hundreds times for their favorite readings like this modern applied statistics with s, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some harmful virus inside their laptop. modern applied statistics with s is available in our digital library an online access to it is set as public so you can download it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the modern applied statistics with s is universally compatible with any devices to read.

5,249 citations

01 Feb 2009
TL;DR: This Secret History documentary follows experts as they pick through the evidence and reveal why the plague killed on such a scale, and what might be coming next.
Abstract: Secret History: Return of the Black Death Channel 4, 7-8pm In 1348 the Black Death swept through London, killing people within days of the appearance of their first symptoms. Exactly how many died, and why, has long been a mystery. This Secret History documentary follows experts as they pick through the evidence and reveal why the plague killed on such a scale. And they ask, what might be coming next?

5,234 citations