Dataset Information

A miRNA Combination as Promising Biomarker for Hepatocellular Carcinoma Diagnosis: A Study Based on Bioinformatics Analysis.

ABSTRACT: Background: miRNAs dysregulate in hepatocellular carcinoma (HCC), showing promise for diagnostic biomarkers which may be found through exploration of differentially expressed miRNAs when comparing HCC and normal liver tissues. Materials and Methods: In the present research, candidate miRNAs were selected and verified using screening dataset GSE12717 and training dataset GSE10694, respectively. A miRNA combination was constructed using stepwise logistic regression analysis and validated using two datasets GSE74618 and TCGA. Target genes of miRNAs in the combination were obtained using a miRNA target gene prediction database. Functional analysis was conducted using an online tool DAVID. We also analyzed the mRNA-Seq data of project LIHC from TCGA to identify the hub target genes of the miRNAs. Results: A miRNA combination, which is composed of hsa-miR-221 and hsa-miR-29c was defined in this study. The miRNA combination is more effective in discriminating HCC patients from normal individuals than individual miRNAs. Additionally, the combined miRNAs showed a lower misdiagnosis rate than AFP in HCC diagnosis. In terms of the functional analysis, a total of 27 target genes of hsa-miR-221 and 96 target genes of hsa-miR-29c were obtained. Among which, INSIG1 was the common target of the two miRNAs. It was also found that both previously mentioned miRNAs played important roles in the regulation of transcription, cell proliferation, and involvement in cancer-related pathways. Lastly, 2 hub target genes of hsa-miR-221 and 16 hub target genes of hsa-miR-29c were obtained. Conclusion: We established a miRNA combination as a promising tool for HCC diagnosis, and the target genes we predicted provide possible points of penetration for researching these two miRNAs in HCC.

SUBMITTER: Ji J

PROVIDER: S-EPMC6171011 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Liver hepatocellular carcinoma (LIHC) is one of the major causes of cancer-related death worldwide with increasing incidences, however there are very few studies about the underlying mechanisms and pathways in the development of LIHC. We obtained LIHC samples from The Cancer Genome Atlas (TCGA) to screen differentially expressed mRNAs, lncRNAs, miRNAs and driver mutations. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses and protein-protein interaction (PPI) network were performed. Moreover, we constructed a competing endogenous lncRNAs-miRNAs-mRNAs network. Finally, cox proportional hazards regression analysis was used to identify important prognostic differentially expressed genes. Total of 1284 mRNAs, 123 lncRNAs, 47 miRNAs were identified within different tissues of LIHC patients. GO analysis indicated that upregulated and downregulated differentially expressed mRNAs (DEmRNAs) were mainly associated with cell division, DNA replication, mitotic sister chromatid segregation and complement activation respectively. Meanwhile, KEGG terms revealed that upregulated and downregulated DEmRNAs were primarily involved in DNA replication, Metabolic pathways, cell cycle and Metabolic pathways, chemical carcinogenesis, retinol metabolism pathway respectively. Among the DERNAs, 542 lncRNAs-miRNAs-mRNAs pairs were predicted to construct a ceRNA regulatory network including 35 DElncRNAs, 26 DEmiRNAs and 112 DEmRNAs. In the Kaplan-Meier analysis, total of 43 mRNAs, 14 lncRNAs and 3 miRNAs were screened out to be significantly correlated with overall survival of LIHC. The mutation signatures were analyzed and its correlation with immune infiltrates were evaluated using the TIMER in LIHC. Among the mutation genes, TTN mutation is often associated with poor immune infiltration and a worse prognosis in LIHC. This work conducted a novel lncRNAs-miRNAs-mRNAs network and mutation signatures for finding potential molecular mechanisms underlying the development of LIHC. The biomarkers also can be used for predicting prognosis of LIHC.

Project description:Purpose Liver cancer is the fifth most common type of cancer worldwide, and the ATP-binding cassette (ABC) transporter family has been widely accepted as a cause of multidrug resistance. This study was conducted to explore the potential value and mechanisms of the ABC transporter gene family in the liver hepatocellular carcinoma (LIHC). Materials and Methods Data were collected from different public databases. UALCAN, ONCOMINE, and GEPIA were used to retrieve a selection of differently expressed and pathological stage-related genes among the ABC family. Principal component analysis (PCA) was utilized for grouping, and its prognostic value was evaluated by univariate and multivariate Cox analyses. The co-expression pattern was constructed with UALCAN, and the functional analyses were carried out with DAVID. The correlation between the biomarker and immune infiltration, genetic alteration frequency, and drug sensitivity were explored with TIMER, cBioPortal, GDSC and CTRP, respectively. Finally, tSNE algorithm was used to explore the distribution of ABCC5 expressed cells. Results Among the ABC transporter family members, ABCC5 was differently expressed and strongly related to the pathological stage of LIHC. PCA divided patients of LIHC into two groups, and Cox analyses demonstrated that ABCC5 was an independent risk factor of LIHC. Functional analyses indicated that the genes were enriched in the pathways of transmembrane transporter, ATPase activity, and bile secretion. ABCC5 is also associated with immune infiltration of cells like macrophages, neutrophils, and dendritic cells. The genetic alteration frequency of ABCC5 confirmed its potential value in LIHC. In addition, several drugs were explored and found to be relevant to LIHC. The t-SNE showed that expression of ABCC5 was most concentrated in macrophages, followed by hepatocytes. Conclusion ABCC5 may facilitate LIHC progression through different mechanisms and be a potential biomarker and target for diagnosis, prognosis, and therapy of LIHC.

Dataset Information

A miRNA Combination as Promising Biomarker for Hepatocellular Carcinoma Diagnosis: A Study Based on Bioinformatics Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets