Tumor mutation load is a biomarker of emerging significance in cancer immunotherapy. Both mutation load and neoantigen load, as measured by whole exome sequencing, have been shown, in several tumor types, to correlate with patient response to both CTLA4 and PD1 inhibition. Consequently, understanding the factors associated with increased tumor mutational burden is critically important to cancer patient treatment decisions. We sought to better understand the landscape of tumor mutation load and potential response to immunotherapy based on data from comprehensive genomic profiling (CGP) of ∼60,000 tumors from patients across ∼400 cancer types.
CGP profiling by hybridization capture of exonic regions from 236 or 315 cancer-related genes and select introns from 19 genes commonly rearranged in cancer was applied to ≥ 50ng of DNA extracted from >60,000 clinical FFPE cancer specimens. These libraries were sequenced to high, uniform median coverage (>500x) and assessed for base substitutions, short insertions and deletions, copy number alterations and gene fusions/rearrangements. Mutation load was accessed as the number of somatic, coding, base substitution and indel mutations, per megabase of genome examined.
We first validate that mutation load calculated based on CGP of the entire coding region of 315 genes (∼1.3 MB) provides a representative measurement of genome-wide mutational load. We quantify and provide detailed data describing mutation load across common tumor types and identify recurrent somatic mutations that are associated with significant increase in tumor mutation load. Our analysis expands significantly upon existing data that quantifies mutation load in hundreds of additional cancer types. Lower grade and pediatric malignancies were observed to have the lowest somatic mutation load, while diseases with significant known mutatgenic exposure such as lung and skin cancers were most highly mutated. Finally, the genomic alterations most associated with increased mutation load were loss of function mutations in mismatch-repair genes (MSH2, MSH6, MLH1 and PMS2), DNA replication genes (POLD1, POLE) and in TP53.
These data demonstrate that tumor mutational load can be accurately quantified using targeted CGP with a CLIA-certified assay that is already integrated into routine patient care. As the role of mutation burden as a biomarker for patient response to immune therapy becomes established, this approach can be used to identify both targeted and immune therapeutic options that are either approved or in clinical trial. Additionally, by characterizing the landscape of mutation load across the full spectrum of human cancer, we provide new data for the rational expansion of the patient population that can potentially benefit from immunotherapy.
Citation Format: Garrett M. Frampton, Riley C. Ennis, Zachary R. Chalmers, Roman Yelensky, Doron Lipson, Philip J. Stephens. The landscape of tumor mutation load across the entire spectrum of human cancer derived from 60,000 patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2629.