Dataset Information

Identification of RFC5 as a novel potential prognostic biomarker in lung cancer through bioinformatics analysis.

ABSTRACT: Lung cancer is the leading cause of mortalities among all types of cancer. Therefore, the screening of biomarkers that are related with the progression of lung cancer is crucial for early diagnosis and efficient therapy of lung cancer. In the present study, bioinformatic analysis identified replication factor C 5 (RFC5) as a potential novel oncogene in lung cancer. RFC5 functions as a clamp loader and is involved in DNA replication and repair. Analysis of public databases and reverse transcription-quantitative polymerase chain reaction indicated that RFC5 was significantly increased in tumor tissues compared with adjacent normal tissues. A high RFC5 expression was observed to be associated with more aggressive malignant clinicopathological features, including higher T stage, more advanced regional lymph node metastasis and a higher probability of relapse. Notably, there were notable differences in overall survival (OS), first progression and post-progression survival between the high RFC5 expression group and low RFC5 expression group. Univariate and multivariate Cox regression analyses indicated that RFC5 was an independent risk factor that was associated with poorer OS and disease-free survival. According to GSEA, several gene sets that are associated with cell cycle and DNA damage were enriched in the RFC5 overexpression group, which indicated that RFC5 might promote the proliferation of lung cancer cells. Our finding indicated that RFC5 might be a novel prognostic biomarker of lung cancer, and it might be serve as a potential diagnosis and therapy target for lung cancer in the future.

SUBMITTER: Wang M

PROVIDER: S-EPMC6126192 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of RFC5 as a novel potential prognostic biomarker in lung cancer through bioinformatics analysis.

Wang Meng M Xie Tian T Wu Yingjie Y Yin Qian Q Xie Songping S Yao Qingyu Q Xiong Jie J Zhang Qiuping Q

Oncology letters 20180726 4

Lung cancer is the leading cause of mortalities among all types of cancer. Therefore, the screening of biomarkers that are related with the progression of lung cancer is crucial for early diagnosis and efficient therapy of lung cancer. In the present study, bioinformatic analysis identified replication factor C 5 (RFC5) as a potential novel oncogene in lung cancer. RFC5 functions as a clamp loader and is involved in DNA replication and repair. Analysis of public databases and reverse transcripti ...[more]

PMID: 30214556

Similar Datasets

Project description:Lung cancer is one of the most common types of cancer worldwide. Understanding the molecular mechanisms underlying the development and progression of lung cancer may improve early diagnosis, treatment and prognosis. The aim of the present study was to examine the pathogenesis of lung cancer and to identify potentially novel biomarkers. Gene expression datasets of patients with lung cancer were obtained from the Gene Expression Omnibus. Genes which were most closely associated with lung cancer (core genes) were screened by weighted gene co‑expression network analysis. In vitro cell based experiments were further utilized to verify the effects of the core genes on the proliferation of lung cancer cells, adhesion between cells and the matrix, and the associated metabolic pathways. Based on WGCNA screening, two gene modules and five core genes closely associated with lung cancer, including immunoglobulin superfamily member 10 (IGSF10) from the turquoise module, and ribonucleotide reductase regulatory subunit M2, protein regulator of cytokinesis 1, kinesin family member (KIF)14 and KIF2C from the brown module were identified as relevant. Survival analysis and differential gene expression analysis showed that there were significant differences in IGSF10 expression levels between the healthy controls and patients with lung cancer. In patients with lung cancer, IGSF10 expression was decreased, and the overall survival time of patients with lung cancer was significantly shortened. An MTT and colony formation assay showed that IGSF10‑knockout significantly increased proliferation of lung cancer cells, and Transwell assays and adhesion experiments further suggested that the adhesion between cells and the matrix was significantly increased in IGSF10‑knockout cells. Gene Set Enrichment Analysis showed that the expression level of IGSF10 was significantly associated with the activation of the integrin‑β1/focal adhesion kinase (FAK) pathway. Western blotting revealed that knockout of IGSF10 resulted in the activation of the integrin‑β1/FAK pathway, as the protein expression levels of integrin‑β1, phosphorylated (p)‑FAK and p‑AKT were significantly upregulated. Activation of the integrin‑β1/FAK pathway, following knockout of IGSF10, affected the proliferation and adhesion of lung cancer cells. Therefore, IGSF10 my serve as a potential prognostic marker of lung cancer.

Project description:Colorectal cancer (CRC) is a major cause of cancer-related deaths worldwide. NDUFAL42 is an important mitochondrial respiratory chain subunit that plays a critical role in cellular energy metabolism. However, the role of NDUFA4L2 in CRC remains unclear. Therefore, we used the data obtained from The Cancer Genome Atlas (TCGA) database to prove the relationship between NDUFA4L2 and CRC. The expression levels of NDUFA4L2 in CRC tissues were analyzed by immunohistochemical staining of NDUFA4L2 from the HPA database. Wilcoxon rank sum test, Chi-square test, Fisher exact test and logistic regression were used to evaluate relationships between clinical-pathologic features and NDUFA4L2 expression. Receiver operating characteristic (ROC) curves were used to describe binary classifier value of NDUFA4L2 using area under curve (AUC) score. Kaplan-Meier method and Cox regression analysis were used to evaluate factors contributing to prognosis. Gene oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to predict the function of differentially expressed genes associated with NDUFA4L2. Gene set enrichment analysis (GSEA) was used to predict canonical pathways associated with NDUFA4L2.Immune infiltration analysis was performed to identify the significantly involved functions of NDUFA4L2. Protein-protein interaction (PPI) networks were established and 20 hub genes identified with Cytoscape software. Increased NDUFA4L2 expression in CRC was associated with T stage (P = .019), N stage (P < .001), Pathologic stage (P = .020), Residual tumor (P = .023), Perineural invasion (P = .039), Lymphatic invasion (P = .007), Histological type(P < .001), PFI event (P = .007) and DSS event (P = .004).ROC curve suggested the significant diagnostic and prognostic ability of NDUFA4L2 (AUC = 0.878). High NDUFA4L2 expression predicted a poorer Overall-survival (P = .021), poorer progression-free interval (P = .001), and poorer Disease Specific Survival (P = .002). GO, KEGG, GSEA and immune infiltration analysis showed that NDUFA4L2 expression was correlated with regulating the function of DNA and some types of immune infiltrating cells. NDUFA4L2 expression was significantly correlated with poor survival and immune infiltrations in CRC, and it may be a promising prognostic biomarker in CRC.

Project description:Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality, which makes the prognostic prediction challenging. Angiogenesis appears to be of critical importance in the progression and metastasis of HCC. Some of the angiogenesis-related genes promote this process, while other anti-angiogenesis genes suppress tumor growth and metastasis. Therefore, the comprehensive prognostic value of multiple angiogenesis-related genes in HCC needs to be further clarified. In this study, the mRNA expression profile of HCC patients and the corresponding clinical data were acquired from multiple public databases. Univariate Cox regression analysis was utilized to screen out differentially expressed angiogenesis-related genes with prognostic value. A multigene signature was established with the least absolute shrinkage and selection operator Cox regression in the Cancer Genome Atlas cohort, and validated through an independent cohort. The results suggested that a total of 16 differentially expressed genes (DEGs) were associated with overall survival (OS) and a 7-gene signature was constructed. The risk score of each patient was calculated using this signature, the median value of which was used to divide these patients into a high-risk group and a low-risk group. Compared with the low-risk group, the patients in the high-risk group had a poor prognosis. The risk score was an independent predictor for OS through multivariate Cox regression analysis. Then, unsupervised learning was used to verify the validity of this 7-gene signature. A nomogram by further integrating clinical information and the prognostic signature was utilized to predict prognostic risk and individual OS. Functional enrichment analyses demonstrated that these DEGs were enriched in the pathways of cell proliferation and mitosis, and the immune cell infiltration was significantly different between the two risk groups. In summary, a novel angiogenesis-related genes signature could be used to predict the prognosis of HCC and for targeted therapy.

Dataset Information

Identification of RFC5 as a novel potential prognostic biomarker in lung cancer through bioinformatics analysis.

Publications

Identification of RFC5 as a novel potential prognostic biomarker in lung cancer through bioinformatics analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets