Aim: Hepatocellular carcinoma (HCC) displays both shared and ethnicity-specific molecular characteristics. Using transcriptomic data from The Cancer Genome Atlas (TCGA), we compared gene expression profiles between Asian and Caucasian HCC patients. Methods: Gene expression profiles were analyzed using the PyDESeq2 implementation of DESeq2, applying size factor normalization and dispersion estimation. Differentially expressed genes (DEGs) were identified with thresholds of false discovery rate (FDR) of < 0.05 and |log2FC| ≥ 1.0. Gene annotation, visualization, and pathway enrichment were conducted using Sanbomics, seaborn, and gene set enrichment analysis (GSEA) via the GSEApy package. Results: A total of 387 and 250 genes were commonly upregulated and downregulated, respectively, in both populations, including the upregulations of GPC3 and PLVAP and the downregulations of FCN3 and OIT3, indicating their potential as universal HCC markers. Conversely, 16 genes were upregulated in Asians but downregulated in Caucasians, and 25 showed the reverse pattern. Asian-specific upregulation of AKR1B10, UBE2C, and S100P suggests links to viral etiology and immune modulation, while MDK, LCN2, and NQO1 were upregulated in Caucasians, implicating proliferative and metabolic roles. Functional enrichment analysis revealed distinct immune and metabolic pathways. Asians showed elevated ubiquitin ligase activity and suppressed inflammatory responses, while Caucasians exhibited enhanced cytokine signaling, complement activation, and xenobiotic metabolism. Conclusions: These findings highlight key molecular differences in HCC across ethnicities and emphasize the value of TCGA data for identifying both shared targets and population-specific therapeutic strategies. Understanding these differences is crucial for advancing precision oncology and developing tailored interventions.

Racial disparities in hepatocellular carcinoma: a TCGA-based gene expression study of Caucasian and Asian populations / Rasyak, M.R., Jayanti, S., Disoma, C., Pardamean, B., Sukowati, C.. - In: EXPLORATION OF TARGETED ANTI-TUMOR THERAPY. - ISSN 2692-3114. - ELETTRONICO. - 6:(2025), pp. 1002344."-"-1002344."-". [10.37349/etat.2025.1002344]

Racial disparities in hepatocellular carcinoma: a TCGA-based gene expression study of Caucasian and Asian populations

Jayanti, Sri
Secondo
;
Disoma, Cyrollah;Sukowati, Caecilia
Ultimo
2025-01-01

Abstract

Aim: Hepatocellular carcinoma (HCC) displays both shared and ethnicity-specific molecular characteristics. Using transcriptomic data from The Cancer Genome Atlas (TCGA), we compared gene expression profiles between Asian and Caucasian HCC patients. Methods: Gene expression profiles were analyzed using the PyDESeq2 implementation of DESeq2, applying size factor normalization and dispersion estimation. Differentially expressed genes (DEGs) were identified with thresholds of false discovery rate (FDR) of < 0.05 and |log2FC| ≥ 1.0. Gene annotation, visualization, and pathway enrichment were conducted using Sanbomics, seaborn, and gene set enrichment analysis (GSEA) via the GSEApy package. Results: A total of 387 and 250 genes were commonly upregulated and downregulated, respectively, in both populations, including the upregulations of GPC3 and PLVAP and the downregulations of FCN3 and OIT3, indicating their potential as universal HCC markers. Conversely, 16 genes were upregulated in Asians but downregulated in Caucasians, and 25 showed the reverse pattern. Asian-specific upregulation of AKR1B10, UBE2C, and S100P suggests links to viral etiology and immune modulation, while MDK, LCN2, and NQO1 were upregulated in Caucasians, implicating proliferative and metabolic roles. Functional enrichment analysis revealed distinct immune and metabolic pathways. Asians showed elevated ubiquitin ligase activity and suppressed inflammatory responses, while Caucasians exhibited enhanced cytokine signaling, complement activation, and xenobiotic metabolism. Conclusions: These findings highlight key molecular differences in HCC across ethnicities and emphasize the value of TCGA data for identifying both shared targets and population-specific therapeutic strategies. Understanding these differences is crucial for advancing precision oncology and developing tailored interventions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3149639
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