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INTERNATIONAL CONGRESS OF

CancerGenetics

• Immune-Related Genetic Polymorphisms as Predictors of Checkpoint Inhibitor Response in Solid Tumors

• Arman Taran,^1,* Mina Shirmohammadpour,² Bahman Mirzaei,³
  1. Department of Microbiology and Virology, Faculty of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
  2. Department of Microbiology and Virology, Faculty of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
  3. Department of Biostatistics and Epidemiology, Faculty of Medicine, Zanjan University of Medical Sciences
  
  
  
• Introduction: Immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 and CTLA-4 pathways have revolutionized cancer treatment, yet significant variability exists in patient responses. Growing evidence suggests that host genetic variations, particularly in immune-related genes, may serve as critical determinants of ICI efficacy and toxicity. Single nucleotide polymorphisms (SNPs) in genes regulating T-cell activation, cytokine signaling, and antigen presentation have emerged as potential biomarkers for treatment stratification. This review examines the current understanding of how immunomodulatory polymorphisms influence ICI outcomes across melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma, focusing on clinically actionable genetic markers that could enable precision immunotherapy approaches.
• Methods: A systematic analysis was conducted of 58 clinical studies (2015-2023) investigating immune-related polymorphisms in ICI-treated patients. The review incorporated data from over 12,000 patients across three tumor types, with particular attention to prospective pharmacogenomic cohorts. Polymorphisms were selected based on genome-wide association studies (GWAS) significance (p<5×10-8) and mechanistic plausibility. Key analyzed genes included PD-1 (PDCD1), CTLA-4, CD274 (PD-L1), LAG-3, and IFN-γ pathways. Treatment outcomes were standardized using RECIST v1.1 criteria, with meta-analysis of objective response rates (ORR) and progression-free survival (PFS) across genotype groups. Functional validation studies using CRISPR-edited T-cell models were included where available.
• Results: The analysis revealed several clinically relevant associations between immune polymorphisms and ICI outcomes. The PD-1 rs11568821 GG genotype correlated with superior ORR in melanoma (48% vs 28% in AA/AG; p=0.003) and longer median PFS (11.2 vs 5.8 months; HR 0.62, 95% CI 0.47-0.81). Mechanistically, this variant enhanced PD-1 protein stability and prolonged T-cell activation. For CTLA-4 blockade, the rs231775 AA genotype predicted both improved response (NSCLC ORR: 34% vs 18%; p=0.01) and increased immune-related adverse events (irAEs; 42% vs 23%, p=0.002), suggesting a shared genetic basis for efficacy and toxicity. IFN-γ pathway polymorphisms demonstrated tumor-specific effects. The IFNGR1 rs1327474 A allele was associated with nearly doubled ORR in RCC (40% vs 22%; p=0.004) but showed no benefit in NSCLC. LAG-3 rs870849 CC carriers exhibited significantly prolonged overall survival across tumor types (median OS 34.5 vs 18.2 months; HR 0.54, 95% CI 0.39-0.75), potentially due to enhanced MHC class II recognition. Unexpectedly, combinatorial polymorphism analysis revealed non-linear interactions. Patients carrying both favorable PD-1 rs11568821 and CTLA-4 rs231775 genotypes showed synergistic improvement (melanoma ORR 58% vs 21% in double-negative; p<0.001), suggesting polygenic models may outperform single-marker approaches. Functional studies confirmed these polymorphisms alter immune synapse formation duration and cytokine secretion profiles.
• Conclusion: Immune-related genetic polymorphisms represent promising biomarkers for ICI response prediction, though their clinical utility requires context-specific interpretation. The PD-1 rs11568821 and CTLA-4 rs231775 variants demonstrate particularly robust associations across multiple cancers, with potential for pre-treatment genotyping to guide therapy selection. However, the observed tumor-type specificity of certain polymorphisms (e.g., IFNGR1 in RCC) underscores the need for disease-focused validation. Future directions should prioritize: 1) development of integrated genetic-clinical predictive models, 2) prospective trials of genotype-directed ICI dosing, and 3) mechanistic studies of how polymorphisms alter tumor-immune cell interactions. Standardization of pharmacogenomic testing protocols will be essential for translating these findings into routine clinical practice.
• Keywords: immune checkpoint inhibitors, PD-1 polymorphisms, CTLA-4 variants