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This study investigates whether genetic variants in the EPAS1 gene, which are adaptive mutations found in high-altitude populations, make hepatocellular carcinoma (liver cancer) resistant to antiangiogenic tyrosine kinase inhibitor (TKI) drugs. Using data from 1,396 patients, cell lines, and multiple cancer databases, researchers found that EPAS1 loss-of-function variants correlate with reduced drug sensitivity across 11 different TKI medications through a HIF-2/STC2 signaling pathway. The findings suggest that inherited genetic background, not just tumor mutations, can determine treatment response, with Bayesian analysis yielding strong statistical support (posterior probability 0.970).
Why it matters
This research could explain why some liver cancer patients, particularly those from high-altitude adapted populations, do not respond to standard targeted therapies. The proposed AESI score and companion drug belzutifan may enable personalized treatment selection based on patients' inherited genetic variants, potentially improving outcomes for treatment-resistant cases.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Purpose: Whether host germline genetic variation determines tumor drug response remains underexplored. We evaluated whether EPAS1 (HIF-2) adaptive loss-of-function variants, enriched in high-altitude-adapted populations, predispose HCC to primary antiangiogenic TKI resistance through a HIF-2/STC2 signaling axis. Experimental Design: We integrated five independent data sources: the QHRCH-HCC retrospective cohort (n = 1,396), multi-ancestry iPSC-derived endothelial cell transcriptome data (GSE160906), TCGA pan-cancer data (LIHC, KIRC, LUAD, BRCA), GDSC2 pharmacogenomics (n = 951 cell lines; 11 antiangiogenic TKIs), and DepMap dependency data. The AESI_score integrated altitude, AFP-PIVKA-II inversion, platelet-altitude, and hemoglobin-altitude dimensions. Bayesian evidence integration employed the Effective Number of Independent Pieces of Evidence (ENIPE) method ({delta} = 0.504). Results: In QHRCH-HCC, altitude correlated positively with PIVKA-II ({rho} = +0.244, p = 0.0003) and with an altitude-adaptive genetic background score ({rho} = +0.517, p = 5.59×10-49). Under hypoxia, EPAS1 expression in high-altitude-adapted iPSC-ECs was reduced to 61.4% of controls (p = 0.0006), while STC2 remained relatively unaffected (89.2%, p = 0.180). In TCGA-LIHC, EPAS1[->]STC2 was weak ({rho} = 0.092) compared with HIF1A[->]STC2 ({rho} = 0.379, p = 2.21×10-14), establishing a negative control. Cross-cancer validation revealed strong EPAS1[->]STC2 in ccRCC ({rho} = 0.320, p = 3.47×10-14) but not in LUAD or BRCA. In GDSC2, EPAS1 correlated positively with IC50 of all 11 antiangiogenic TKIs (sign test p = 0.0005). Bayesian updating yielded posterior probability 0.970 (Log10BF = 1.99). Conclusions: EPAS1 LoF represents a germline determinant of TKI response, independent of tumor-acquired mutations. The AESI_score and HIF-2 inhibitor belzutifan constitute a predictive biomarker-therapeutic pair for genotype-stratified clinical validation. This hypothesis-generating study establishes a germline determinant framework for TKI resistance; definitive mechanistic validation will require prospective EPAS1 genotype-stratified cohorts (2023-ZJ-786).