Amplification-Driven S100A11 Overexpression in Hepatocellular Carcinoma Is Linked to Metabolic Reprogramming, ECM Remodelling, and Immune Evasion: A Pan-Cancer Genomic Study
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Background
S100A11, a calcium-binding S100 family protein, is increasingly implicated in carcinogenesis, yet its molecular regulation and clinical relevance across cancers remain unclear. Hepatocellular Carcinoma (HCC) carries a dismal prognosis, in part due to a lack of reliable biomarkers for early detection and risk stratification.
Methods
We conducted a pan-cancer analysis of S100A11 genomic alterations across 43 studies (112,646 samples), encompassing copy number alterations, somatic mutations, and DNA methylation. HCC-specific analyses evaluated S100A11 expression, diagnostic performance, co-expression networks, and pathway enrichment using TCGA-LIHC data, with univariate and multivariate Cox regression to assess survival associations.
Results
S100A11 alterations were predominantly driven by copy number amplification, with the highest frequencies in lung, uterine, and hepatobiliary cancers. Copy number amplification showed a consistent inverse relationship with promoter methylation, indicating amplification-driven transcriptional activation. In HCC, S100A11 was markedly overexpressed compared with normal liver tissue, with strong diagnostic discriminatory capacity. Although high S100A11 expression trended towards inferior overall survival, this did not reach statistical significance in multivariate analysis. Co-expression and pathway analyses linked S100A11 to metabolic reprogramming, extracellular matrix remodelling, and immune dysregulation.
Conclusion
These findings establish S100A11 as a context-dependent oncogenic regulator highly expressed and a candidate diagnostic marker in HCC.
Simple Summary
S100A11, a calcium-binding S100 family protein, is increasingly implicated in carcinogenesis, yet its molecular regulation and clinical relevance across cancers remain unclear. Hepatocellular carcinoma (HCC) has a dismal prognosis, in part due to delayed detection and less effective risk stratification. In the present study, we integrated genomic, epigenetic, and transcriptomic data to characterize S100A11 alterations in HCC and assess their association with patient survival, with the aim of defining its potential as a prognostic biomarker.
