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Record W2897299514 · doi:10.1158/2159-8290.cd-18-0804

Integrative Molecular Characterization of Malignant Pleural Mesothelioma

2018· article· en· W2897299514 on OpenAlexaff
Julija Hmeljak, Francisco Sánchez-Vega, Katherine A. Hoadley, Juliann Shih, Chip Stewart, David I. Heiman, Patrick Tarpey, Ludmila Danilova, Esther Drill, Ewan A. Gibb, Reanne Bowlby, Rupa S. Kanchi, Hatice U. Osmanbeyoglu, Yoshitaka Sekido, Jumpei Takeshita, Yulia Newton, Kiley Graim, Manaswi Gupta, Carl M. Gay, Lixia Diao, David L. Gibbs, Vésteinn Thórsson, Lisa Iype, Havish S. Kantheti, David T. Severson, Gloria Ravegnini, Patrice Desmeules, Achim A. Jungbluth, William D. Travis, Sanja Đačić, Lucian R. Chirieac, Françoise Galateau-Sallé, Junya Fujimoto, Aliya N. Husain, Henrique C.S. Silveira, Valerie W. Rusch, Robert C. Rintoul, Harvey I. Pass, Hedy L. Kindler, Marjorie G. Zauderer, David J. Kwiatkowski, Raphael Bueno, Anne S. Tsao, Jenette Creaney, Tara M. Lichtenberg, Kristen Leraas, Jay Bowen, Ina Felau, Jean C. Zenklusen, Rehan Akbani, Andrew D. Cherniack, Michael S. Noble, Jonathan A. Fletcher, A. Gordon Robertson, Ronglai Shen, Hiroyuki Aburatani, B. W. Robinson, Peter J. Campbell, Marc Ladanyi, Adrian Ally, Pavana Anur, Joshua Armenia, J. Todd Auman, Miruna Balasundaram, Saianand Balu, Stephen B. Baylin, Michael J. Becich, Carmen Behrens, Rameen Beroukhim, Craig M. Bielski, Tom Bodenheimer, Denise Brooks, Flavio Mavignier Cárcano, Rebecca Carlsen, André Lopes Carvalho, Dorothy Cheung, Juok Cho, Eric Chuah, Sudha Chudamani, Carrie Cibulskis, Leslie Cope, Daniel Crain, Erin Curley, Assunta De Rienzo, Timothy Defreitas, John A. Demchok, Noreen Dhalla, Rajiv Dhir, Michaël Feldman, Martin L. Ferguson, Shiro Fukuda, Stacey Gabriel, Jianjiong Gao, Johanna Gardner, Julie M. Gastier-Foster, Nils Gehlenborg, Mark Gerken, Gad Getz, Chandra Goparaju, Benjamin Groß, Guangwu Guo, Seiki Hasegawa, David Haussler, D. Neil Hayes, Zachary Heins, Robert A. Holt, Alan P. Hoyle, Carolyn M. Hutter, Steven J.M. Jones, Corbin D. Jones, Jaegil Kim, Nobuyuki Kondo, Thomas Krausz, Ritika Kundra, Kozo Kuribayashi, Phillip H. Lai, Peter W. Laird, Michael S. Lawrence, Darlene Lee, Pei Lin, Jia Liu, Wenbin Liu, Eric Minwei Liu, Laxmi Lolla, Adhemar Longatto‐Filho, Yiling Lu, James D. Luketich, Yussanne Ma, Dennis T. Maglinte, David Mallory, Marco A. Marra, Michael Mayo, Jonathan Melamed, Shaowu Meng, Matthew Meyerson, Piotr A. Mieczkowski, Gordon B. Mills, Richard A. Moore, César A. Moran, Scott Morris, Lisle E. Mose, Andrew J. Mungall, Karen Mungall, Takashi Nakano, Rashi Naresh, Angelica Ochoa, Joel S. Parker, Joseph Paulauskis, Arjun Pennathur, Nathan A. Pennell, Robert Penny, Charles M. Perou, Todd Pihl, Nilsa C. Ramirez, Doris M. Rassl, Glen Reid, Rui Manuel Reis, Sheila M. Reynolds, David C. Rice, William G. Richards, Jeffrey Roach, Sara Sadeghi, Gordon Saksena, Chris Sander, Ayuko Sato, Cristovam Scapulatempo‐Neto, Jacqueline E. Schein, Nikolaus Schultz, Steven E. Schumacher, Tanguy Y. Seiwert, Candace Shelton, Troy Shelton, Robert L. Sheridan, Yan Shi, Yuichi Shiraishi, Ilya Shmulevich, Janae V. Simons, Payal Sipahimalani, Tara Skelly, Heidi J. Sofia, Matthew G. Soloway, Paul T. Spellman, Joshua M. Stuart, Qiang Sun, Angela Tam, Donghui Tan, Roy Tarnuzzer, Kenji Tatsuno, Barry S. Taylor, Nina Thiessen, Eric Thompson, Kane Tse, Tohru Tsujimura, Federico Valdivieso, David Van Den Berg, Nico van Zandwijk, Umadevi Veluvolu, Luciano de Souza Viana, Douglas Voet, Yunhu Wan, Jing Wang, Joellen Weaver, John N. Weinstein, Daniel J. Weisenberger, Matthew D. Wilkerson, Lisa Wise, Ignacio I. Wistuba, Tina Wong, Ye Wu, Shogo Yamamoto, Liming Yang, Jiashan Zhang, Hailei Zhang, Hongxin Zhang, Erik Zmuda

Bibliographic record

VenueCancer Discovery · 2018
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsBC Cancer AgencyCanada's Michael Smith Genome Sciences CentreGenome British Columbia
FundersNational Cancer InstituteNational Human Genome Research InstituteNational Institutes of HealthBritish Lung Foundation
KeywordsLoss of heterozygosityBAP1BiologyMesotheliomaCancer researchImmune checkpointImmunotherapyImmune systemGeneMedicineImmunologyPathologyGeneticsMelanomaAllele

Abstract

fetched live from OpenAlex

Abstract Malignant pleural mesothelioma (MPM) is a highly lethal cancer of the lining of the chest cavity. To expand our understanding of MPM, we conducted a comprehensive integrated genomic study, including the most detailed analysis of BAP1 alterations to date. We identified histology-independent molecular prognostic subsets, and defined a novel genomic subtype with TP53 and SETDB1 mutations and extensive loss of heterozygosity. We also report strong expression of the immune-checkpoint gene VISTA in epithelioid MPM, strikingly higher than in other solid cancers, with implications for the immune response to MPM and for its immunotherapy. Our findings highlight new avenues for further investigation of MPM biology and novel therapeutic options. Significance: Through a comprehensive integrated genomic study of 74 MPMs, we provide a deeper understanding of histology-independent determinants of aggressive behavior, define a novel genomic subtype with TP53 and SETDB1 mutations and extensive loss of heterozygosity, and discovered strong expression of the immune-checkpoint gene VISTA in epithelioid MPM. See related commentary by Aggarwal and Albelda, p. 1508. This article is highlighted in the In This Issue feature, p. 1494

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.274
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations618
Published2018
Admission routes1
Has abstractyes

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