Donor polymorphisms of Rap1A rs494453 contribute to a higher risk of hepatocellular carcinoma recurrence following liver transplantation

A comprehensive transcriptomic landscape of cholangiocarcinoma based on bioinformatics analysis from large cohort of patients

Cholangiocarcinoma (CCA) is a group of malignancies emerging in the biliary tree and is associated with a poor patient prognosis. Although the anatomical location is the only worldwide accepted classification basis, it still has bias. The current study integrates the whole-genome expression data from several big cohorts in the literature, to screen and provide a comprehensive bioinformatic analysis, in order to better classify molecular subtypes and explore an underlying cluster mechanism related to anatomy and geographical regions. Differentially expressed protein-coding genes (DEGs) were identified for CCA as well as subtypes. Biological function enrichment analysis-Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis-was applied and identified different DEGs enriched signaling pathways in CCA subtypes. A co-expression network was presented by Weighted gene co-expression network analysis package and modules related to specific phenotypes were identified. Combined with DEGs, hub genes in the given module were demonstrated through protein-protein interaction network analysis. Finally, DEGs which significantly related to patient overall survival and disease-free survival time were selected, including ARHGAP21, SCP2, UBIAD1, TJP2, RAP1A and HDAC9.

Molecular Associations and Clinical Significance of RAPs in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is an aggressive gastrointestinal malignancy with a high rate of mortality. Multiple studies have individually recognized members of RAP gene family as critical regulators of tumor progression in several cancers, including hepatocellular carcinoma. These studies suffer numerous limitations including a small sample size and lack of analysis of various clinicopathological and molecular features. In the current study, we utilized authoritative multi-omics databases to determine the association of RAP gene family expression and detailed molecular and clinicopathological features in hepatocellular carcinoma (HCC). All five RAP genes were observed to harbor dysregulated expression in HCC compared to normal liver tissues. RAP2A exhibited strongest ability to differentiate tumors from the normal tissues. RAP2A expression was associated with progressive tumor grade, TP53 and CTNNB1 mutation status. Additionally, RAP2A expression was associated with the alteration of its copy numbers and DNA methylation. RAP2A also emerged as an independent marker for patient prognosis. Further, pathway analysis revealed that RAP2A expression is correlated with tumor-infiltrating immune cell composition and oncogenic molecular pathways, such as cell cycle and cellular metabolism.

Three Genes Predict Prognosis in Microenvironment of Ovarian Cancer

Ovarian cancer (OC) is the deadliest gynecological cancer in women. Immune cell infiltration has a critical role in regulating carcinogenesis and prognosis in OC. To identify prognostic genes relevant to the tumor microenvironment in OC, we investigated the association between OC and gene expression profiles. Results obtained with the ESTIMATE R tool showed that immune score and stromal score were correlated with lymphatic invasion, and high immune score predicted a favorable prognosis. A total of 342 common differentially expressed genes were identified according to the two scores; these genes were mainly involved in immune response, extracellular region, and serine-type endopeptidase activity. Three immune-related prognostic genes were selected by univariate and multivariate Cox regression analysis. We further established a prognostic model and validated the prognostic value of three hub genes in different databases; our results showed that this model could accurately predict survival and evaluate prognosis independent of clinical characteristics. Three hub genes have prognostic value in OC. TIMER analysis revealed that the three genes were correlated with different immune cells. Low levels of macrophage infiltration and high levels of CD4+ T cell infiltration were associated with favorable survival outcomes. Arm-level gain of GYPC was correlated with neutrophils and dendritic cells. These findings indicate that CXCR4, GYPC, and MMP12 modulate prognosis via effects on the infiltration of immune cells. Thus, these genes represent potential targets for immune therapy in OC.