ArticlePloS one2026
Leveraging expression quantitative trait loci information in single-cell resolution to identify cell-specific genes for Basal cell carcinoma.
Article in PloS one, 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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5 authors.
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Abstract
backgroundBasal cell carcinoma (BCC), the most common skin cancer, is driven by UV-induced DNA damage and shaped by immune surveillance. Although GWAS has identified over 140 risk loci, their cell-type-specific effects remain obscured by tissue-level averaging.
methodsWe integrated BCC GWAS summary statistics from a UK-based cohort (17,416 cases, 375,455 controls) with single-cell expression quantitative trait locus (sc-eQTL) data from 12 immune cell types in the OneK1K resource. Using the OTTERS framework combined with ACAT-O, we performed single-cell transcriptome-wide association analysis (scTWAS); bulk TWAS using GTEx whole blood served as a conventional tissue-averaged benchmark for comparison, rather than a definitive gold standard. Functional enrichment was conducted via Gene Ontology (GO).
resultsBulk TWAS using GTEx whole blood identified 35 BCC-associated genes (FDR < 0.05), including MC1R and CASP8. In contrast, single-cell transcriptome-wide association study (scTWAS) across 12 OneK1K cell types revealed 207 non-redundant susceptibility genes, predominantly in CD4ET, MONOC, and BIN. Functional enrichment uncovered cell-type-specific programs: MHC class II antigen presentation (CD4ET), PRR-mediated innate immunity (MONOC), and pro-inflammatory secretion (BIN)-all absent in bulk results.
conclusionOur exploratory scTWAS using healthy donor PBMC-derived eQTLs uncovered cell-type-specific BCC associations missed by bulk analyses, providing hypothesis-generating insights into immune-related genetic effects in BCC. This underscores how single-cell resolution can overcome signal dilution from cellular heterogeneity, though validation in tumor-derived immune populations is warranted.
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