RFC4

Abstract: Liver cancer (LC) is one of the most fatal cancers throughout the world. More efficient and sensitive gene signatures that could accurately predict survival in LC patients are vitally needed to promote a better individualized and effective treatment. 422 LC and adjacent normal tissues with both RNA-Seq and clinical data in TCGA were embedded in our study. Gene set enrichment analysis (GSEA) was applied to identify genes and hallmark gene sets that are more valuable for liver cancer therapy. Cox regression analysis was used to identify genes related to overall survival (OS) and build the prediction model. cBioPortal database was used to examine the alterations of the panel mRNA signature. ROC curves and Kaplan–Meier curves were used to validate the prediction model. Besides, the expression of the genes in the model were validated using quantitative real-time PCR in clinical tissue specimens. The panel of DNA repair-related mRNA signature consisted of seven mRNAs: RFC4 (replication factor C subunit 4), ZWINT (ZW10 interacting kinetochore protein), UPF3B (UPF3B regulator of nonsense mediated mRNA decay), NCBP2 (nuclear cap binding protein subunit 2), ADA (adenosine deaminase), SF3A3 (splicing factor 3a subunit 3) and GTF2H1 (general transcription factor IIH subunit 1). On-line analysis of cBioPortal database found that the expression of the panel mRNA has a wide variation ranging from 7 to 10%. All the mRNAs were significantly upregulated in LC tissues compared to normal tissues (P < 0.05). The risk model is closely related to the OS of LC patients. The hazard ratio (HR) is 2.184 [95% CI (confidence interval) 1.523–3.132] and log-rank P-value < 0.0001. For clinical specimen validation, we found that all of the genes in the model upregulated in liver cancer tissues versus normal liver tissues, which was consistent with the results predicted. Our study demonstrated a mRNA signature including seven mRNA for prognosis prediction of LC. This panel gene signature provides a new criterion for accurate diagnosis and therapeutic target of LC.

Abstract: We performed a gene co-expression analysis on Lung Squamous Cell Carcinoma data to find modules (groups) of genes that may highly impact the growth of these type of tumors. Additionally, we used cancer survival data to relate modules to prognostic significance in terms of survival time. Analysis on RNA-seq data revealed modules which are significant in gene enrichment analysis. Specifically, two genes - RFC4 and ECT2 - have been found to be significant in terms of survival time. We also performed a second gene co-expression analysis on a second dataset of microarray data, and many significant genes found in this analysis could also be found in the RNA-seq data implying that these genes might indeed play a crucial role in Lung Squamous Cancer. All the R code for the analysis can be found at: \url{this https URL}

Abstract: Replication factor C (RFC) family is a complex comprised of the RFC1, RFC2, RFC3, RFC4, and RFC5 subunits, which acts as a primer recognition factor for DNA polymerase. It is reported that RFC, biologically active in various malignant tumors, may play an important role in the proliferation, progression, invasion, and metastasis of cancer cells. It could act as an oncogene or tumor suppressor gene based on the cellular and histological characteristics of the tumor. In this review, we summarized the updated researches on the structure, physiological function, and expression pattern of RFC in a variety of tumors, the underlying mechanisms on carcinogenesis, and the potentials of RFC family members in the diagnosis and prognosis prediction.

Abstract: Hepatocellular carcinoma (HCC) is one of the common cancers with a high incidence and mortality. The human replication factor C (RFC) family contains 5 subunits that play an important role in DNA replication and DNA damage repair. RFCs are abnormally expressed in a variety of cancers; some of them are differentially expressed in HCC tissues and related to tumor growth. However, the expression, prognostic value, and effect targets of the whole RFC family in HCC are still unclear. To address these issues, we performed a multidimensional analysis of RFCs in HCC patients by Oncomine, UALCAN, GEPIA, Human protein atlas, Kaplan-Meier plotter, cBioPortal, GeneMANIA, String, and LinkedOmics. mRNA expression of RFCs was significantly increased in HCC tissues. There was a significant correlation between the expression of RFC2/3/4/5 and tumor stage of HCC patients. Besides, high mRNA expression of RFC2/4 was associated with worse overall survival (OS). Moreover, genetic alterations of RFCs were associated with worse OS in HCC patients. We found that genes co-expressed with RFC2/4 were mainly involved in biological processes, such as chromosome segregation, mitotic cell cycle phase transition, and telomere organization and they activated the cell cycle and spliceosome pathways. The gene set is mainly enriched in cancer-related kinases AURKA, ATR, CDK1, PLK1, and CHEK1. E2F family members were the key transcription factors for RFCs. Our results suggest that differentially expressed RFC2 and RFC4 are potential prognostic biomarkers in HCC and may act on E2F transcription factors and some kinase targets to dysregulate the cell cycle pathway. These efforts may provide new research directions for prognostic biomarkers and therapeutic targets in HCC.