Thursday, November 21, 2024
11/21/2024
PROJECT SUMMARY/ ABSTRACT Therapy with immune checkpoint inhibitors has substantially increased survival of patients with metastatic melanoma, lung cancer, head and neck cancer, bladder cancer, renal cell carcinoma and others. However, a majority of patients have very limited or no response to these drugs. In addition, a large fraction of patients have significant side effects including immune related adverse events (irAEs). Somatic mutation load, neoantigen burden, and some particular somatic mutations can help predict response to therapy; however, currently available predictors have only modest power to predict response and there are no good predictors of irAEs. Thus, novel biomarkers may be helpful in predicting irAEs and understanding their etiology. We hypothesize that irAEs are manifestations of autoimmunity in individuals who are genetically susceptible to autoimmune disorders and that the genetic variants underlying common autoimmune disorders will also be useful predictors for irAEs. Separately, we and others have demonstrated that autoimmunity may be associated with response to immunotherapies. Thus, we hypothesize that there will be shared genetic factors underlying response to immunotherapy and irAEs. We will test these hypotheses in a cohort of over 3000 patients with non-small lung cancer receiving programmed cell death 1 (PD-1) inhibitors. We will perform both targeted sequencing of the human leukocyte antigen (HLA) region and genotyping with a genome wide single nucleotide polymorphism (SNP) array. We will use these data to test the association between HLA and irAEs. We will also determine whether combinations of SNPs and HLA haplotypes known to be associated with autoimmune diseases can be used to predict irAEs. Finally, we will search for novel SNPs associated with irAEs. We will also investigate whether genetic factors that may affect survival of patients on immunotherapy. We will use the HLA sequence data and GWAS data to search for variants associated with overall survival. We will also leverage data from The Cancer Genome Atlas (TCGA) Project to identify genetic variants that affect immune signatures in the tumor known to be associated with response to immunotherapies such as lymphocyte infiltration and PDL1 expression. We will investigate whether the genetic variants identified in TCGA affect response to immunotherapies. Finally, we will investigate whether there is shared genetic predisposition to irAEs and to beneficial response from PD-1 inhibitors. At the conclusion of this work, we will develop an understanding of the genetic profile that underlies patients' risk of irAEs.
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