Gender Disparity in Hepatocellular Carcinoma Survival: Exploiting Tissue-Specific Protein Interaction Networks to Unveil Prognostic Gene Modules

Introduction: Men are 3 times more likely to develop Hepatocellular Carcinoma (HCC) and often have poorer responses to treatment. Our study seeks to identify sex-specific disease gene modules that characterize the molecular mechanisms sponsoring differential survival outcomes in males vs females. Methods: We employed a series of computational methods to investigate the molecular characteristics of HCC. First, we constructed a protein-protein interaction (PPI) network using validated protein interactions in liver tissue. Next, we employed a widely used algorithm called DIseAse MOdule Detection (DIAMOnD) to identify disease modules within the PPI network. To focus on HCC specific gene activity, we used a curated set of genes associated with cell state switching in HCC, as well as previously identified HCC disease genes, as seed genes in the PPI network. This integration allowed us to identify a novel set of 230 potential disease genes, forming a DIAMOnD gene module (Figure 1A).These submodules represent groups of genes with high interconnectedness, suggesting important functional clusters within the larger module. We conducted Cox regression analysis using the The Cancer Genome Atlas Liver Hepatocellular Carcinoma gene expression dataset. Results: We included 196 HCC patients in our analytic samples. Included patients were mostly male (66%), median age was 62 years, and 60% were non-Hispanic white. Male gender was associated with poorer survival (Figure 1B). In a multivariable model adjusting for stage, DNA hypermethylation clusters, male gender was associated with a 60% increased risk of all-cause mortality (aHR=1.59; 95% confidence interval [CI]: 1.02–2.48, P=0.04). Furthermore, within the top 2 submodules, namely Module 1 and Module 2, we identified 10 and 8 genes, respectively, that demonstrated a significant association with adverse prognosis specifically in males (Table 1). Conclusion: Our findings reveal distinct gene modules that contribute to the differential survival observed between males and females. These findings highlight the importance of gender-specific considerations in HCC prognosis and provide insights into potential molecular mechanisms driving the observed disparities. Future studies should aim to explore the underlying molecular mechanisms driving these gene modules.Figure 1.: A) Cytoscape network of liver cancer switch genes (blue), known liver cancer disease genes (red), and disease genes extracted from DIAMOnD algorithm (green). Network was generated using protein interactions from STRING-DB with turquoise nodes representing non DIAMoND genes with StringR interactions. B) Kaplan-Meier Survival analysis of HCC. Table 1. - Cox regression summary results showing the hazard ratios and statistical significance of selected genes in relation to survival outcomes in males Gene HR HR lower 95% HR upper 95% P-value Module 1 FCGR3B 1.42 1.03 1.95 3.13E-02 ENTPD1 19.32 4.18 89.18 1.49E-04 CD2 36.25 5.52 238.02 1.84E-04 CD163 5.18 2.15 12.44 2.38E-04 ITGAL 2.47 1.17 5.19 1.75E-02 CD247 9.97 2.18 45.51 2.99E-03 IL1B 2.62 1.39 4.96 3E-03 CCL2 2.32 1.33 4.04 2.98E-03 HAVCR2 4.60 1.28 16.51 1.93E-02 CD80 4.36 1.83 10.43 9.2E-04 Module 2 STAT5A 3.67 1.01 13.27 4.77E-02 LCK 26.62 2.40 294.59 7.46E-03 PECAM1 4.07 1.21 13.63 2.29E-02 CTSS 3.16 1.31 7.64 1.07E-02 CSF1 21.34 5.62 80.99 6.88E-06 CD3E 20.49 2.09 200.81 9.49E-03 CD53 120.47 2.67 5427.94 1.37E-02 LILRB2 32.20 6.05 171.46 4.72E-05