Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma

Freeman SS*, Sade-Feldman M*, Kim J, Stewart C, Gonye ALK, Ravi A, Arniella MB, Gushterova I, LaSalle TJ, Blaum EM, Yizhak K, Frederick DT, Sharova T, Leshchiner I, Elagina L, Spiro OG, Livitz D, Rosebrock D, Aguet F, Carrot-Zhang J, Ha G, Lin Z, Chen JH, Barzily-Rokni M, Hammond MR, Vitzthum von Eckstaedt HC, Blackmon SM, Jiao YJ, Gabriel S, Lawrence DP, Duncan LM, Stemmer-Rachamimov AO, Wargo JA, Flaherty KT, Sullivan RJ, Boland GM, Meyerson M, Getz G#^, Hacohen N#^
Cell Reports Medcine 3 (2) (2022)


Immune checkpoint blockade (CPB) improves melanoma outcomes, but many patients still do not respond. Tumor mutational burden (TMB) and tumor-infiltrating T cells are associated with response, and integrative models improve survival prediction. However, integrating immune/tumor-intrinsic features using data from a single assay (DNA/RNA) remains underexplored. Here, we analyze whole-exome and bulk RNA sequencing of tumors from new and published cohorts of 189 and 178 patients with melanoma receiving CPB, respectively. Using DNA, we calculate T cell and B cell burdens (TCB/BCB) from rearranged TCR/Ig sequences and find that patients with TMBhigh and TCBhigh or BCBhigh have improved outcomes compared to other patients. By combining pairs of immune- and tumor-expressed genes, we identify three gene pairs associated with response and survival, which validate in independent cohorts. The top model includes lymphocyte-expressed MAP4K1 and tumor-expressed TBX3. Overall, RNA or DNA-based models combining immune and tumor measures improve predictions of melanoma CPB outcomes.

Getz Lab Authors
* First Authors
# Senior Authors
^ Corresponding Authors
Full text
(# of citations)