Literature DB >> 27956380

Somatic Mutations and Neoepitope Homology in Melanomas Treated with CTLA-4 Blockade.

Tavi Nathanson1, Arun Ahuja1, Alexander Rubinsteyn1, Bulent Arman Aksoy1, Matthew D Hellmann2,3, Diana Miao4,5, Eliezer Van Allen4,5, Taha Merghoub2,3,6, Jedd D Wolchok2,3,6, Alexandra Snyder7,3, Jeff Hammerbacher1.   

Abstract

Immune checkpoint inhibitors are promising treatments for patients with a variety of malignancies. Toward understanding the determinants of response to immune checkpoint inhibitors, it was previously demonstrated that the presence of somatic mutations is associated with benefit from checkpoint inhibition. A hypothesis was posited that neoantigen homology to pathogens may in part explain the link between somatic mutations and response. To further examine this hypothesis, we reanalyzed cancer exome data obtained from our previously published study of 64 melanoma patients treated with CTLA-4 blockade and a new dataset of RNA-Seq data from 24 of these patients. We found that the ability to accurately predict patient benefit did not increase as the analysis narrowed from somatic mutation burden, to inclusion of only those mutations predicted to be MHC class I neoantigens, to only including those neoantigens that were expressed or that had homology to pathogens. The only association between somatic mutation burden and response was found when examining samples obtained prior to treatment. Neoantigen and expressed neoantigen burden were also associated with response, but neither was more predictive than somatic mutation burden. Neither the previously described tetrapeptide signature nor an updated method to evaluate neoepitope homology to pathogens was more predictive than mutation burden. Cancer Immunol Res; 5(1); 84-91. ©2016 AACR. ©2016 American Association for Cancer Research.

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Year:  2016        PMID: 27956380      PMCID: PMC5253347          DOI: 10.1158/2326-6066.CIR-16-0019

Source DB:  PubMed          Journal:  Cancer Immunol Res        ISSN: 2326-6066            Impact factor:   11.151


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Journal:  Cell       Date:  2015-08-27       Impact factor: 41.582

2.  Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them).

Authors:  Daniel Berrar; Peter Flach
Journal:  Brief Bioinform       Date:  2011-03-21       Impact factor: 11.622

3.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

4.  Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients.

Authors:  Roy S Herbst; Jean-Charles Soria; Marcin Kowanetz; Gregg D Fine; Omid Hamid; Michael S Gordon; Jeffery A Sosman; David F McDermott; John D Powderly; Scott N Gettinger; Holbrook E K Kohrt; Leora Horn; Donald P Lawrence; Sandra Rost; Maya Leabman; Yuanyuan Xiao; Ahmad Mokatrin; Hartmut Koeppen; Priti S Hegde; Ira Mellman; Daniel S Chen; F Stephen Hodi
Journal:  Nature       Date:  2014-11-27       Impact factor: 49.962

5.  Safety, activity, and immune correlates of anti-PD-1 antibody in cancer.

Authors:  Suzanne L Topalian; F Stephen Hodi; Julie R Brahmer; Scott N Gettinger; David C Smith; David F McDermott; John D Powderly; Richard D Carvajal; Jeffrey A Sosman; Michael B Atkins; Philip D Leming; David R Spigel; Scott J Antonia; Leora Horn; Charles G Drake; Drew M Pardoll; Lieping Chen; William H Sharfman; Robert A Anders; Janis M Taube; Tracee L McMiller; Haiying Xu; Alan J Korman; Maria Jure-Kunkel; Shruti Agrawal; Daniel McDonald; Georgia D Kollia; Ashok Gupta; Jon M Wigginton; Mario Sznol
Journal:  N Engl J Med       Date:  2012-06-02       Impact factor: 91.245

6.  Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer.

Authors:  Naiyer A Rizvi; Matthew D Hellmann; Alexandra Snyder; Pia Kvistborg; Vladimir Makarov; Jonathan J Havel; William Lee; Jianda Yuan; Phillip Wong; Teresa S Ho; Martin L Miller; Natasha Rekhtman; Andre L Moreira; Fawzia Ibrahim; Cameron Bruggeman; Billel Gasmi; Roberta Zappasodi; Yuka Maeda; Chris Sander; Edward B Garon; Taha Merghoub; Jedd D Wolchok; Ton N Schumacher; Timothy A Chan
Journal:  Science       Date:  2015-03-12       Impact factor: 47.728

7.  Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota.

Authors:  Marie Vétizou; Jonathan M Pitt; Romain Daillère; Patricia Lepage; Nadine Waldschmitt; Caroline Flament; Sylvie Rusakiewicz; Bertrand Routy; Maria P Roberti; Connie P M Duong; Vichnou Poirier-Colame; Antoine Roux; Sonia Becharef; Silvia Formenti; Encouse Golden; Sascha Cording; Gerard Eberl; Andreas Schlitzer; Florent Ginhoux; Sridhar Mani; Takahiro Yamazaki; Nicolas Jacquelot; David P Enot; Marion Bérard; Jérôme Nigou; Paule Opolon; Alexander Eggermont; Paul-Louis Woerther; Elisabeth Chachaty; Nathalie Chaput; Caroline Robert; Christina Mateus; Guido Kroemer; Didier Raoult; Ivo Gomperts Boneca; Franck Carbonnel; Mathias Chamaillard; Laurence Zitvogel
Journal:  Science       Date:  2015-11-05       Impact factor: 47.728

8.  PD-1 blockade induces responses by inhibiting adaptive immune resistance.

Authors:  Paul C Tumeh; Christina L Harview; Jennifer H Yearley; I Peter Shintaku; Emma J M Taylor; Lidia Robert; Bartosz Chmielowski; Marko Spasic; Gina Henry; Voicu Ciobanu; Alisha N West; Manuel Carmona; Christine Kivork; Elizabeth Seja; Grace Cherry; Antonio J Gutierrez; Tristan R Grogan; Christine Mateus; Gorana Tomasic; John A Glaspy; Ryan O Emerson; Harlan Robins; Robert H Pierce; David A Elashoff; Caroline Robert; Antoni Ribas
Journal:  Nature       Date:  2014-11-27       Impact factor: 49.962

9.  Prediction of protein-destabilizing polymorphisms by manual curation with protein structure.

Authors:  Craig Alan Gough; Keiichi Homma; Yumi Yamaguchi-Kabata; Makoto K Shimada; Ranajit Chakraborty; Yasuyuki Fujii; Hisakazu Iwama; Shinsei Minoshima; Shigetaka Sakamoto; Yoshiharu Sato; Yoshiyuki Suzuki; Masahito Tada-Umezaki; Ken Nishikawa; Tadashi Imanishi; Takashi Gojobori
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10.  Structural interplay between germline interactions and adaptive recognition determines the bandwidth of TCR-peptide-MHC cross-reactivity.

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  55 in total

1.  Cancer Stem Cells in the Immune Microenvironment.

Authors:  Dong-Sup Lee; Keunhee Oh
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

2.  High tumor mutation burden predicts better efficacy of immunotherapy: a pooled analysis of 103078 cancer patients.

Authors:  Dedong Cao; Huilin Xu; Ximing Xu; Tao Guo; Wei Ge
Journal:  Oncoimmunology       Date:  2019-06-16       Impact factor: 8.110

Review 3.  Promising clinical application of ctDNA in evaluating immunotherapy efficacy.

Authors:  Li Li; Jun Zhang; Xiaoyue Jiang; Qin Li
Journal:  Am J Cancer Res       Date:  2018-10-01       Impact factor: 6.166

4.  Neoantigen Dissimilarity to the Self-Proteome Predicts Immunogenicity and Response to Immune Checkpoint Blockade.

Authors:  Lee P Richman; Robert H Vonderheide; Andrew J Rech
Journal:  Cell Syst       Date:  2019-10-09       Impact factor: 10.304

Review 5.  Informatics for cancer immunotherapy.

Authors:  J Hammerbacher; A Snyder
Journal:  Ann Oncol       Date:  2017-12-01       Impact factor: 32.976

Review 6.  Monitoring immune-checkpoint blockade: response evaluation and biomarker development.

Authors:  Mizuki Nishino; Nikhil H Ramaiya; Hiroto Hatabu; F Stephen Hodi
Journal:  Nat Rev Clin Oncol       Date:  2017-06-27       Impact factor: 66.675

7.  Identification of essential genes for cancer immunotherapy.

Authors:  Shashank J Patel; Neville E Sanjana; Rigel J Kishton; Arash Eidizadeh; Suman K Vodnala; Maggie Cam; Jared J Gartner; Li Jia; Seth M Steinberg; Tori N Yamamoto; Anand S Merchant; Gautam U Mehta; Anna Chichura; Ophir Shalem; Eric Tran; Robert Eil; Madhusudhanan Sukumar; Eva Perez Guijarro; Chi-Ping Day; Paul Robbins; Steve Feldman; Glenn Merlino; Feng Zhang; Nicholas P Restifo
Journal:  Nature       Date:  2017-08-07       Impact factor: 49.962

8.  Tumor Immunity and Survival as a Function of Alternative Neopeptides in Human Cancer.

Authors:  Andrew J Rech; David Balli; Alejandro Mantero; Hemant Ishwaran; Katherine L Nathanson; Ben Z Stanger; Robert H Vonderheide
Journal:  Cancer Immunol Res       Date:  2018-01-16       Impact factor: 11.151

Review 9.  Tumor immune microenvironment in head and neck cancers.

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10.  Multimodel preclinical platform predicts clinical response of melanoma to immunotherapy.

Authors:  Eva Pérez-Guijarro; Howard H Yang; Romina E Araya; Rajaa El Meskini; Helen T Michael; Suman Kumar Vodnala; Kerrie L Marie; Cari Smith; Sung Chin; Khiem C Lam; Andres Thorkelsson; Anthony J Iacovelli; Alan Kulaga; Anyen Fon; Aleksandra M Michalowski; Willy Hugo; Roger S Lo; Nicholas P Restifo; Shyam K Sharan; Terry Van Dyke; Romina S Goldszmid; Zoe Weaver Ohler; Maxwell P Lee; Chi-Ping Day; Glenn Merlino
Journal:  Nat Med       Date:  2020-04-13       Impact factor: 53.440

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