Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma
Noam Auslander,Gao Zhang,Joo Sang Lee,Joo Sang Lee,Dennie T. Frederick,Benchun Miao,Tabea Moll,Tian Tian,Zhi Wei,Sanna Madan,Sanna Madan,Ryan J. Sullivan,Genevieve M. Boland,Keith T. Flaherty,Meenhard Herlyn,Eytan Ruppin,Eytan Ruppin +16 more
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TLDR
IMPRES is a predictor of ICB response in melanoma which encompasses 15 pairwise transcriptomics relations between immune checkpoint genes and achieves an overall accuracy of AUC = 0.83, outperforming existing predictors and capturing almost all true responders while misclassifying less than half of the nonresponders.Abstract:
Immune checkpoint blockade (ICB) therapy provides remarkable clinical gains and has been very successful in treatment of melanoma. However, only a subset of patients with advanced tumors currently benefit from ICB therapies, which at times incur considerable side effects and costs. Constructing predictors of patient response has remained a serious challenge because of the complexity of the immune response and the shortage of large cohorts of ICB-treated patients that include both ‘omics’ and response data. Here we build immuno-predictive score (IMPRES), a predictor of ICB response in melanoma which encompasses 15 pairwise transcriptomics relations between immune checkpoint genes. It is based on two key conjectures: (i) immune mechanisms underlying spontaneous regression in neuroblastoma can predict melanoma response to ICB, and (ii) key immune interactions can be captured via specific pairwise relations of the expression of immune checkpoint genes. IMPRES is validated on nine published datasets1–6 and on a newly generated dataset with 31 patients treated with anti-PD-1 and 10 with anti-CTLA-4, spanning 297 samples in total. It achieves an overall accuracy of AUC = 0.83, outperforming existing predictors and capturing almost all true responders while misclassifying less than half of the nonresponders. Future studies are warranted to determine the value of the approach presented here in other cancer types. A gene signature identified in spontaneously regressing neuroblastoma identifies responders to immune checkpoint blockade among patients with melanoma with accuracy superior to previously reported biomarkers.read more
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Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic
Timothy A. Chan,Mark Yarchoan,Elizabeth M. Jaffee,Charles Swanton,Sergio A. Quezada,Albrecht Stenzinger,Solange Peters +6 more
TL;DR: TMB, in concert with PD-L1 expression, has been demonstrated to be a useful biomarker for ICB selection across some cancer types; however, further prospective validation studies are required.
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ImmuCellAI: A Unique Method for Comprehensive T-Cell Subsets Abundance Prediction and its Application in Cancer Immunotherapy.
TL;DR: Application of ImmuCellAI to immunotherapy datasets reveals that the abundance of dendritic cells, cytotoxic T, and gamma delta T cells is significantly higher both in comparisons of on‐treatment versus pre‐treatment and responders versus non‐responders.
Journal ArticleDOI
Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma
David Liu,David Liu,Bastian Schilling,Bastian Schilling,Derek Liu,Derek Liu,Antje Sucker,Elisabeth Livingstone,Livnat Jerby-Arnon,Lisa Zimmer,Ralf Gutzmer,Imke Satzger,Carmen Loquai,Stephan Grabbe,Natalie I. Vokes,Natalie I. Vokes,Claire A. Margolis,Claire A. Margolis,Jake Conway,Jake Conway,Meng Xiao He,Meng Xiao He,Haitham Elmarakeby,Haitham Elmarakeby,Felix Dietlein,Felix Dietlein,Diana Miao,Diana Miao,Adam Tracy,Helen Gogas,Simone M. Goldinger,Jochen Utikal,Jochen Utikal,Christian U. Blank,Ricarda Rauschenberg,Dagmar von Bubnoff,Angela M. Krackhardt,Angela M. Krackhardt,Benjamin Weide,Sebastian Haferkamp,Felix Kiecker,Ben Izar,Ben Izar,Levi A. Garraway,Aviv Regev,Keith T. Flaherty,Annette Paschen,Eliezer M. Van Allen,Eliezer M. Van Allen,Dirk Schadendorf +49 more
TL;DR: In this paper, the authors analyzed a clinically annotated cohort of patients with melanoma treated with anti-PD1 ICB, with whole-exome and whole-transcriptome sequencing of pre-treatment tumors.
Journal ArticleDOI
Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition
Kevin Litchfield,Kevin Litchfield,James L. Reading,Clare Puttick,Krupa Thakkar,Krupa Thakkar,Christopher Abbosh,Robert B Bentham,Thomas B.K. Watkins,Rachel Rosenthal,Dhruva Biswas,Andrew Rowan,Emilia L. Lim,Maise Al Bakir,Virginia Turati,José Afonso Guerra-Assunção,Lucia Conde,Andrew Furness,Sunil Kumar Saini,Sine Reker Hadrup,Javier Herrero,Se-Hoon Lee,Se-Hoon Lee,Peter Van Loo,Tariq Enver,James Larkin,Matthew D. Hellmann,Samra Turajlic,Samra Turajlic,Sergio A. Quezada,Nicholas McGranahan,Charles Swanton,Charles Swanton +32 more
TL;DR: In this article, the authors collated whole-exome and transcriptomic data for >1,000 CPI-treated patients across seven tumor types, utilizing standardized bioinformatics workflows and clinical outcome criteria to validate multivariable predictors of CPI sensitization.
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Genomic correlates of response to immune checkpoint blockade
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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.
Journal Article
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Arman Aksoy,Giovanni Ciriello,Gideon Dresdner,Jianjiong Gao,Benjamin Gross,Anders Jacobsen,André Kahles,Marc Ladanyi,William H. Lee,Kjong-Van Lehmann,Martin L. Miller,Ricardo Ramirez,Gunnar Rätsch,Boris Reva,Chris Sander,Nikolaus Schultz,Yasin Senbabaoglu,Ronglai Shen,Rileen Sinha,S. Onur Sumer,Yichao Sun,Barry S. Taylor,Nils Weinhold,Suzanne S. Fei,Paul T. Spellman,Christopher C. Benz,Daniel E. Carlin,Melisssa Cline,Brian Craft,Kyle Ellrott,Mary Goldman,David Haussler,Singer Ma,Sam Ng,Evan O. Paull,Amie Radenbaugh,Sofie R. Salama,Artem Sokolov,Joshua M. Stuart,Teresa Swatloski,Vladislav Uzunangelov,Peter Waltman,Christina Yau,Jing Zhu,Stanley R. Hamilton,Scott Abbott,Rachel Abbott,Nathan D. Dees,Kim D. Delehaunty,Li Ding,David J. Dooling,James M. Eldred,Catrina Fronick,Robert S. Fulton,Lucinda Fulton,Joelle Kalicki-Veizer,Krishna-Latha Kanchi,Cyriac Kandoth,Daniel C. Koboldt,David E. Larson,Timothy J. Ley,Ling Lin,Charles Lu,Vincent Magrini,Elaine R. Mardis,Michael D. McLellan,Joshua F. McMichael,Christopher A. Miller,Michelle O'Laughlin,Craig Pohl,Heather Schmidt,Scott M. Smith,Jason Walker,John W. Wallis,Michael C. Wendl,Richard K. Wilson,Todd Wylie,Qunyuan Zhang,Robert A. Burton,Mark A. Jensen,Ari B. Kahn,Todd Pihl,David Pot,Yunhu Wan,Douglas A. Levine,Aaron D. Black,Jay Bowen,Jessica Frick,Julie M. Gastier-Foster,Hollie A. Harper,Carmen Helsel,Kristen M. Leraas,Tara M. Lichtenberg,Cynthia McAllister,Nilsa C. Ramirez,Samantha Sharpe,Lisa Wise,Erik Zmuda,Stephen J. Chanock,Tanja Davidsen,John A. Demchok,Greg Eley,Ina Felau,Brad Ozenberger,Margi Sheth,Heidi J. Sofia,Louis M. Staudt,Roy Tarnuzzer,Zhining Wang,Liming Yang,Jiashan Zhang,Larsson Omberg,Adam A. Margolin,Benjamin J. Raphael,Fabio Vandin,Hsin-Ta Wu,Mark D.M. Leiserson,Stephen C. Benz,Charles J. Vaske,Houtan Noushmehr,Denise M. Wolf,Laura van 't Veer,Eric A. Collisson,Dimitris Anastassiou,Tai-Hsien Ou Yang,Nuria Lopez-Bigas,Abel Gonzalez-Perez,David Tamborero,Zheng Xia,Wei Li,Dong-Yeon Cho,Teresa M. Przytycka,Mark P. Hamilton,Sean E. McGuire,Sven Nelander,Patrik Johansson,Rebecka Jörnsten,Teresia Kling,Jose Miguel Sanchez,Kenna R. Mills Shaw +337 more
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.
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