ArticleFrontiers in immunology2026
A machine learning approach to a nine-SNP immunogenetic score for prognostic stratification in cervical cancer.
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: While human papillomavirus (HPV) is the primary driver of cervical cancer (CC), host immune-related genetic variations are thought to influence clinical heterogeneity. The role of combined immune-related single nucleotide polymorphisms (SNPs) in defining patient subgroups remains underexplored in focused, candidate-gene studies. Methods: We genotyped nine functional SNPs across TNF-α (rs361525, rs1800629), *IL-1β* (rs16944), IFN-γ (rs2430561), *IL-1RN* (rs2234663), *IL-10* (rs3024490, rs1800872, rs1800871), and *IL-6* (rs1474348) in a cohort of 130 Tunisian CC patients. Principal component analysis (PCA), multi-dimensional scaling (MDS), K-means clustering, and random forest modeling were used to explore SNP-based patient subgroups and identify genetic profiles associated with survival. Results: A high-risk genetic profile, comprising seven SNPs, was identified in 20% of patients. PCA indicated that *IL-10* and TNF-α variants accounted for 38.5% of the observed genetic variance. Unsupervised clustering suggested three distinct SNP-based subgroups with differing genetic architectures. The TNF-α -238 A allele was associated with borderline higher odds of adenocarcinoma (OR 4.57, 95% CI: 0.95-21.95, p=0.050), while the *IL-1β* -511 T allele appeared protective (OR 0.45, 95% CI: 0.19-1.07, p=0.049). Random forest analysis identified the IFN-γ rs2430561 variant as the top predictor of advanced FIGO stage. A nine-SNP polygenic risk score (PRS) was significantly associated with reduced overall survival (HR 2.45, log-rank p<.001) and remained an independent prognostic factor in multivariable analysis. Pathway analysis implicated TNF-α signaling, IL-10 anti-inflammatory, and IL-1 cytokine pathways. Conclusions: This focused, candidate-gene analysis identifies prognostic SNP-based subgroups and a nine-SNP polygenic risk score associated with survival in cervical cancer. While this work provides a foundation for immunogenetic risk stratification, the findings are derived from a limited SNP panel in a single cohort. Future validation in larger, independent cohorts with genome-wide data is required to confirm these preliminary genetic associations and to determine their relationship to broader molecular subgroups.
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