Integrated analysis of the immunological and genetic status in and across cancer types: impact of mutational signatures beyond tumor mutational burden - Budczies, Jan; Seidel, Anja; Christopoulos, Petros; Endris, Volker; Kloor, Matthias; Gyorffy, Balazs; Seliger, Barbara; Schirmacher, Peter; Stenzinger, Albrecht; Denkert, Carsten (OncoImmunology, 2018)
Harnessing the immune system by checkpoint blockade has greatly expanded the therapeutic options for advanced cancer. Since the efficacy of immunotherapies is influenced by the molecular make-up of the tumor and its crosstalk with the immune system, comprehensive analysis of genetic and immunologic tumor characteristics is essential to gain insight into mechanisms of therapy response and resistance. We investigated the association of immune cell contexture and tumor genetics including tumor mutational burden (TMB), copy number alteration (CNA) load, mutant allele heterogeneity (MATH) and specific mutational signatures (MutSigs) using TCGA data of 5722 tumor samples from 21 cancer types. Among all genetic variables, MutSigs associated with DNA repair deficiency and AID/APOBEC gene activity showed the strongest positive correlations with immune parameters. For smoking-related and UV-light-exposure associated MutSigs a few positive correlations were identified, while MutSig 1 (clock-like process) correlated non-significantly or negatively with the major immune parameters in most cancer types. High TMB was associated with high immune cell infiltrates in some but not all cancer types, in contrast, high CNA load and high MATH were mostly associated with low immune cell infiltrates. While a bi- or multimodal distribution of TMB was observed in colorectal, stomach and endometrial cancer where its levels were associated with POLE/POLD1 mutations and MSI status, TMB was unimodal distributed in the most other cancer types including NSCLC and melanoma. In summary, this study uncovered specific genetic-immunology associations in major cancer types and suggests that mutational signatures should be further investigated as interesting candidates for response prediction beyond TMB.
Gesehen am 22.10.2019