Identifying a Clinically Applicable Mutational Burden Threshold as a Potential Biomarker of Response to Immune Checkpoint Therapy in Solid Tumors.

PURPOSE: An association between mutational burden and response to immune checkpoint therapy has been documented in several cancer types. The potential for such a mutational burden threshold to predict response to immune checkpoint therapy was evaluated in several clinical datasets, where mutational burden was measured either by whole-exome sequencing (WXS) or using commercially available sequencing panels.
METHODS: WXS and RNA-seq data of 33 solid cancer types from TCGA were analyzed to determine whether a robust immune checkpoint activating mutation (iCAM) burden threshold associated with evidence of immune checkpoint activation exists in these cancers that may serve as a biomarker for response to immune checkpoint blockade therapy.
RESULTS: We find that a robust iCAM threshold, associated with signatures of immune checkpoint activation, exists in 8 of 33 solid cancers: melanoma, lung adenocarcinoma, colon adenocarcinoma, endometrial cancer, stomach adenocarcinoma, cervical cancer, ER+HER2- breast cancer, and bladder-urothelial cancer. Tumors with mutational burden higher than the threshold (iCAM+) also had clear histologic evidence of lymphocytic infiltration. In published datasets of melanoma, lung adenocarcinoma and colon cancer, patients with iCAM+ tumors had significantly better response to immune checkpoint therapy compared to those with iCAM- tumors. ROC analysis using TCGA predictions as gold standard showed that iCAM+ tumors are accurately identifiable using clinical sequencing assays, such as FoundationOne or StrandAdvantage. Using the FoundationOne derived threshold, analysis of 113 melanoma tumors, showed that iCAM+ patients have significantly better response to immune checkpoint therapy. iCAM+ and iCAM- tumors have distinct mutation patterns and different immune microenvironments.
CONCLUSION: In 8 solid cancers, a mutational burden threshold exists that may predict response to immune checkpoint blockade. This threshold is identifiable using available clinical sequencing assays.