Identification of survival-related predictors in hepatocellular carcinoma through integrated genomic, transcriptomic, and proteomic analyses

Patient survival time generally reflects the tumor progression and represents a key clinical parameter. In this study, we aimed to comprehensively characterize the prognosis-associated molecular alterations in hepatocellular carcinoma (HCC). In this study, copy-number changes, gene mutations, mRNA expression, and reverse phase protein arrays data in HCC samples profiled by The Cancer Genome Atlas (TCGA) were obtained. Tumors were then stratified into two groups based on the clinical outcome and identified genomic, transcriptomic, and proteomic traits associated to HCC prognosis. We found that several copy number amplifications and deletions can discriminate HCC patients with poor prognosis from those with better prognosis. Mutated DNAH8 showed a worse prognosis-specific pattern and correlated with a reduced disease-free survival in HCC. By integrating RNA sequencing data, we found that HCC samples with poor prognosis are consistently associated with the up-regulation of cell cycle process, such as chromosome separation, DNA replication, cytokinesis, and etc. At the proteomic level, seven proteins were significantly enriched in samples with poor prognosis, including acetylated alpha-Tubulin, p62-LCK-ligand, ARID1 A, MSH6, B-Raf, Cyclin B1, and PEA15. Acetylated alpha-Tubulin was frequently expressed in HCC tissues and acted as a promising prognostic factor for HCC. These alterations lay a foundation for developing relevant therapeutic strategies and improve our knowledge of the pathogenesis of HCC.