Mutation patterns in genes encoding interferon signaling and antigen presentation: A pan‐cancer survey with implications for the use of immune checkpoint inhibitors

Abstract

Blockade of immune checkpoints has become a powerful tool in cancer medicine, which is effective across various solid cancer types and hematologic malignancies. While immunohistochemical detection of PD-L1 expression in tumor cells, immune cells, or both has been introduced as predictive biomarker in several clinical trials, shortcomings and limitations of this approach were quickly recognized. As a single biomarker is unlikely to adequately reflect the complex interplay between immune cells and cancer, various genetic determinants of therapy success, including microsatellite instability, mutational burden, and PD-L1 amplification, are being investigated. Very recent work indicates that mutations in B2M, JAK1, and JAK2 render melanoma resistant to immune checkpoint blockade, thus serving as negative response predictors. Using the TCGA dataset, we performed a pan-cancer analysis of potentially damaging mutations in key genes implicated in antigen presentation and interferon-gamma signaling and investigated associations with transcript levels of immune checkpoint genes, cytolytic activity, and mutational burden. For B2M, JAK1, and JAK2, we observed overall mutation frequencies of 1.8%, 2%, and 2.6%, respectively, and found significant associations with mutational burden. On pathway level, melanoma as well as bladder, gastric, and lung cancer were most frequently affected by putative resistance mutations with mutation rates of 27%-50% in the antigen presentation pathway and of 16%-21% in the interferon signaling pathway. Our analysis suggests that a significant number of tumors harbor mutations that may negatively interfere with immune checkpoint inhibition, or confer a higher likelihood of resistance for which a second hit is ultimately required. Since these mutations are prevalent in treatment-naïve tumors, genetic screening prior to therapy might complement current approaches at predicting response to immune checkpoint blockade.

Spatially Resolved Transcriptomics Enables Dissection of Genetic Heterogeneity in Stage III Cutaneous Malignant Melanoma

“…The gene expression profile of the lymphoid factor involved HLA genes and CD74, the latter of which has been shown to be associated with favorable recurrence-free survival and overall survival in stage III melanoma (42). The expression of HLA genes is essential for immune-mediated regression of metastases, with certain HLA variants causing resistance to immune therapy (43)(44). There may thus be a link between HLA genotype and the immunoediting of oncogenes and tumor suppressors (45).…”

“…These genes have been linked with tumor growth regulation through the GADD45/JNK pathway in other cancers such as in glioblastomas (FTL; ref. 47), along with loss of immunogenicity and acquired resistance to PD-1 blockade in patients with melanoma through defects in the pathways involved in interferon-receptor signaling, such as B2M, and in antigen presentation (43,44,48).…”

Integrated analysis of the immunological and genetic status in and across cancer types: impact of mutational signatures beyond tumor mutational burden

“…12 To overcome these limitations, several novel and complementary biomarkers are currently under investigation. Additional to negative predictors of response, [13][14][15][16] which might play an increasingly important role in the near future, tumor mutational burden (TMB) approximating neo-antigenicity 17,18 was observed to predict response to various checkpoint agents in different cancer types. 11,19,20 The potential of TMB as biomarker for immune therapy response independent from PD-L1 was demonstrated in phase III non-small cell lung carcinoma (NSCLC) trials including a retrospective analysis of the Checkmate 026 trial and more recent corroborative data obtained from the Checkmate 227 trial.…”

Failed immune responses across multiple pathologies share pan-tumor and circulating lymphocytic targets

“…To identify TIL phenotypes contributing to responses, pan-cancer studies have correlated epithelial-to-mesenchymal transition and immune activation (2), in which immune activation and CD8 + TIL landscapes are associated with favorable prognostic genes (3). Pretreatment pan-cancer surveillance of IFN signaling and antigen presentation factors (4) or pan-cancer immunophenoscore (5) may become adopted by mainstream oncology. Com-prehensive multi-cancer databases vastly extend our knowledge of tumorigenesis by providing avenues for deciphering diagnostic pan-cancer signatures distinguishing tumor types and having prognostic, predictive, and therapeutic potential (6,7).…”