Integrative Tumor and Immune Cell Multi-omic Analyses Predict Response to Immune Checkpoint Blockade in Melanoma

Valsamo Anagnostou, Daniel C. Bruhm, Noushin Niknafs, James R. White, Xiaoshan M. Shao, John William Sidhom, Julie Stein, Hua Ling Tsai, Hao Wang, Zineb Belcaid, Joseph Murray, Archana Balan, Leonardo Ferreira, Petra Ross-Macdonald, Megan Wind-Rotolo, Alexander S. Baras, Janis Taube, Rachel Karchin, Robert B. Scharpf, Catherine GrassoAntoni Ribas, Drew M. Pardoll, Suzanne L. Topalian, Victor E. Velculescu

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


In this study, we incorporate analyses of genome-wide sequence and structural alterations with pre- and on-therapy transcriptomic and T cell repertoire features in immunotherapy-naive melanoma patients treated with immune checkpoint blockade. Although tumor mutation burden is associated with improved treatment response, the mutation frequency in expressed genes is superior in predicting outcome. Increased T cell density in baseline tumors and dynamic changes in regression or expansion of the T cell repertoire during therapy distinguish responders from non-responders. Transcriptome analyses reveal an increased abundance of B cell subsets in tumors from responders and patterns of molecular response related to expressed mutation elimination or retention that reflect clinical outcome. High-dimensional genomic, transcriptomic, and immune repertoire data were integrated into a multi-modal predictor of response. These findings identify genomic and transcriptomic characteristics of tumors and immune cells that predict response to immune checkpoint blockade and highlight the importance of pre-existing T and B cell immunity in therapeutic outcomes.

Original languageEnglish
Article number100139
JournalCell Reports Medicine
Issue number8
StatePublished - 17 Nov 2020
Externally publishedYes


  • T cell repertoire
  • cancer genomics
  • immune checkpoint blockade
  • integrative predictive model
  • melanoma
  • multi-omics


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