Using whole-exome sequencing to quantify T or B cell burden (TCB/BCB) from rearranged TCR/Ig sequences and tumor mutation burden (TMB), Freeman and Sade-Feldman et al. identified a subgroup of melanoma patients treated with checkpoint blockade (CPB) with high immune infiltrate and high TMB associated with improved OS and response to CPB. Expression data from immune and tumor cells identified three gene pairs predictive of response and survival. The top gene pair was TBX3, a tumor-specific gene expressed in poorly differentiated melanomas, and MAP4K1, expressed in lymphocytes and DCs.
Contributed by Shishir Pant
ABSTRACT: 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.
Author Info: (1) Broad Institute of MIT and Harvard, Boston, MA 02142, USA (2) Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA (3) Department of Medicine, Ce
Author Info: (1) Broad Institute of MIT and Harvard, Boston, MA 02142, USA (2) Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA (3) Department of Medicine, Center for Cancer Research, Massachusetts General Hospital, Boston, MA 02114, USA (4) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA (5) Department of Cell Biology and Cancer Science, Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa 2611001, Israel (6) Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle 98109, WA, USA (7) Harvard University, Boston, MA 02138, USA (8) Department of Pathology, Massachusetts General Hospital, Boston 02114, MA, USA (9) Department of System Biology, Harvard Medical School, Boston, MA 02115, USA (10) Department of Medical Oncology, Massachusetts General Hospital, Boston, MA 02114, USA (11) Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA (12) Department of Surgery, Massachusetts General Hospital, Boston 02115, MA, USA (13) Department of Genetics, Harvard Medical School, Boston 02115, MA, USA (14) Department of Pathology, Harvard Medical School, Boston 02115, MA, USA (15) Department of Medicine, Harvard Medical School, Boston 02115, MA, USA (16) These authors contributed equally (17) Lead contact *Correspondence: gadgetz@broadinstitute.org (G.G.), nhacohen@mgh.harvard.edu (N.H.)
