Overexpression of TCERG1 as a prognostic marker in hepatocellular carcinoma: A TCGA data-based analysis

HIV-1-induced translocation of CPSF6 to biomolecular condensates

Cleavage and polyadenylation specificity factor subunit 6 (CPSF6, also known as CFIm68) is a 68 kDa component of the mammalian cleavage factor I (CFIm) complex that modulates mRNA alternative polyadenylation (APA) and determines 3' untranslated region (UTR) length, an important gene expression control mechanism. CPSF6 directly interacts with the HIV-1 core during infection, suggesting involvement in HIV-1 replication. Here, we review the contributions of CPSF6 to every stage of the HIV-1 replication cycle. Recently, several groups described the ability of HIV-1 infection to induce CPSF6 translocation to nuclear speckles, which are biomolecular condensates. We discuss the implications for CPSF6 localization in condensates and the potential role of condensate-localized CPSF6 in the ability of HIV-1 to control the protein expression pattern of the cell.

AP4M1 as a prognostic biomarker associated with cell proliferation, migration and immune regulation in hepatocellular carcinoma

BACKGROUND

AP4M1 is a protein-coding gene that plays a crucial role in transporter activity, recognition, and hereditary-associated diseases, but it's largely unknown in cancers.

METHODS

The expression level of AP4M1 in cancers was investigated by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and the correlation between AP4M1 and hepatocellular carcinoma (HCC) clinicopathological parameters were analyzed. Univariate and multifactorial COX regression analyses were performed to clarify the prognostic value of AP4M1 in HCC. The correlation between AP4M1 and immune cell infiltration was analyzed using single-sample Gene Set Enrichment Analysis (ssGSEA). Besides, we verified the biological function of AP4M1 by applying Cell Counting Kit-8 (CCK8), colony formation, and transwell assays.

RESULTS

The expression of AP4M1 was significantly elevated in HCC and was correlated with patients' pathological grades, AFP, and BMI. Kaplan-Meier survival curves indicated that patients with AP4M1 overexpression had worse overall survival. Univariate and multivariate COX regression analyses showed that AP4M1 was an independent risk factor affecting the prognosis of HCC. In addition, we observed that AP4M1 positively correlated with most immune checkpoint suppressor genes in HCC. Moreover, in vitro experiments further confirmed that AP4M1 could promote the proliferation and invasion of HCC.

CONCLUSIONS

AP4M1 is highly expressed and associated with poor prognosis in HCC. AP4M1 is closely related to cancer-immune regulation and could be a novel target for HCC, and guiding new strategies for the diagnosis and treatment of HCC patients.

Identification of oncogenes and tumor-suppressor genes with hepatocellular carcinoma: A comprehensive analysis based on TCGA and GEO datasets

Aim: Existing targeted therapies for hepatocellular carcinoma (HCC) are resistant and have limitations. It is crucial to find new HCC-related target genes. Methods: RNA-sequencing data of HCC were gathered from The Cancer Genome Atlas and Gene Expression Omnibus datasets. Initially, differentially expressed genes between normal and tumor tissues were identified from four Gene Expression Omnibus datasets, GSE36376, GSE102079, GSE54236, and GSE45267. GO terms and KEGG pathway enrichment analyses were performed to explore the potential biological functions of differentially expressed genes. A PPI network was constructed by using the STRING database, and up-regulated and down-regulated hub genes were defined through 12 topological approaches. Subsequently, the correlation bounded by up-regulated genes and down-regulated genes in the diagnosis, prognosis, and clinicopathological features of HCC was analyzed. Beyond a shadow of doubt, the key oncogene PBK and tumor suppressor gene F9 were screened out, and the specific mechanism was investigated through GSEA enrichment analysis and immune correlation analysis. The role of PBK in HCC was further verified by western blot, CCK8, transwell, and tube formation experiments. Results: CDCA5, CDC20, PBK, PRC1, TOP2A, and NCAPG are good indicators of HCC diagnosis and prognosis. The low expressions of F9, AFM, and C8B indicate malignant progression and poor prognosis of HCC. PBK was found to be closely related to VEGF, VEGFR, and PDGFR pathways. Experiments showed that PBK promotes HCC cell proliferation, migration, invasion, and tube formation in HUVEC cells. F9 was negatively correlated with the degree of immune infiltration, and low expression of F9 suggested a poor response to immunotherapy. Conclusion: The role of HCC-related oncogenes and tumor-suppressor genes in diagnosis and prognosis was identified. In addition, we have found that PBK may promote tumor proliferation through angiogenesis and F9 may be a predictor of tumor immunotherapy response.