Dataset Information

Integrated characterization and validation of the prognostic significance of microRNA-200s in colorectal cancer.

ABSTRACT: Background:Accumulating evidence has demonstrated that microRNA-200s (miR-200a, miR-200b and miR-200c) could serve as promising molecular biomarkers for cancer prognosis. Nevertheless, the associations between miR-200s expression and colorectal cancer (CRC) prognosis remain controversial. Methods:We applied two mainstream approaches combining meta-analysis and bioinformatics analysis to answer whether miR-200s were associated with the prognosis of CRC patients and why miR-200s could be used as prognostic biomarkers for CRC. Results:Consequently, low expression of miR-200s was associated with unfavorable overall survival (OS) in CRC patients (HR: 1.09; 95% CI 1.01-1.17; P?=?0.025). According to the subgroup analysis, the prognostic role of miR-200s was more significant for tissue samples, large samples, American patients and miR-200a subgroups. Then the target genes of miR-200s were predicted and applied for functional enrichment analyses. The results showed that the target genes of miR-200s were mainly enriched into some vital ontology subjects such as regulation ability, key cell structures and binding function. Moreover, a series of important signaling pathways were identified, which were significantly linked with the initiation and progression of CRC. Additionally, a protein?protein interaction (PPI) network of miR-200s targets was constructed to screen hub genes and modules. The identified hub genes and modules were validated to be highly involved in the occurrence and development of CRC. Conclusions:Current evidences revealed that miR-200s could be promising biomarkers for CRC prognosis. However, the findings still need to be validated with more larger-scale prospective studies and biological experiments before miR-200s could be applied into clinical application.

SUBMITTER: Peng Q

PROVIDER: S-EPMC7029504 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrated characterization and validation of the prognostic significance of microRNA-200s in colorectal cancer.

Peng Qiliang Q Cheng Ming M Li Ting T Chen Xiangying X Shen Yi Y Zhu Yaqun Y Xu Bo B

Cancer cell international 20200218

<h4>Background</h4>Accumulating evidence has demonstrated that microRNA-200s (miR-200a, miR-200b and miR-200c) could serve as promising molecular biomarkers for cancer prognosis. Nevertheless, the associations between miR-200s expression and colorectal cancer (CRC) prognosis remain controversial.<h4>Methods</h4>We applied two mainstream approaches combining meta-analysis and bioinformatics analysis to answer whether miR-200s were associated with the prognosis of CRC patients and why miR-200s cou ...[more]

PMID: 32099529

Similar Datasets

Project description:BackgroundGastric cancer (GC) is one of the common gastrointestinal malignancy worldwide and exhibits a poor prognosis. Increasing studies have indicated that microRNAs play critical roles in the cancer progression and have shown great potential as useful biomarkers. The search for potential diagnostic and prognostic biomarkers of gastric cancer (GC) with integrated bioinformatics analyses has been undertaken in previous studies.MethodsIn this study, the robust rank aggregation (RRA) method was used to perform an integrated analysis of differentially expressed miRNAs (DEMs) from five microarray datasets in the Gene Expression Omnibus (GEO) database to find robust biomarkers for GC. Ultimately, seven miRNAs were filtered from fourteen primary miRNAs using the validation set of The Cancer Genome Atlas (TCGA) database. Based on these results, diagnostic and survival analyses were performed, and logistic regression and Cox regression were used to determine the clinicopathological characteristics of the DEM expression and overall survival.ResultsNine eligible miRNA datasets related to GC were selected from the GEO database for integrated analysis in this study. Diagnostic analysis implied that these miRNAs could be regarded as promising candidate diagnostic biomarkers in GC tissues, but whether the results of the tissue analysis are consistent with those of peripheral blood analysis requires further validation. The logistic regression indicated that the ectopic expression of these DEMs was relevant to the histological type, anatomical region, and pathological grade of GC. However, the survival and Cox regression analyses suggested that the poor prognosis of GC patients was not strongly dependent on the ectopic expression of the seven miRNAs, but rather, a poor prognosis was associated with age, metastasis, and histological grade.ConclusionsBased on the results presented in this study it can be concluded that these miRNAs (miR-455-3p, miR-135b-5p, let-7a-3p, miR-195-5p, miR-204-5p, miR-149-5p, and miR-143-3p) might be potential biomarkers for the early diagnosis of GC patients, but this finding should be regarded with caution. A large-scale, prospective, and multicenter cohort study should be performed.

Project description:BackgroundColorectal cancer (CRC) is a common malignant solid tumor with an extremely low survival rate after relapse. Previous investigations have shown that autophagy possesses a crucial function in tumors. However, there is no consensus on the value of autophagy-associated genes in predicting the prognosis of CRC patients. This work screens autophagy-related markers and signaling pathways that may participate in the development of CRC, and establishes a prognostic model of CRC based on autophagy-associated genes.MethodsGene transcripts from the TCGA database and autophagy-associated gene data from the GeneCards database were used to obtain expression levels of autophagy-associated genes, followed by Wilcox tests to screen for autophagy-related differentially expressed genes. Then, 11 key autophagy-associated genes were identified through univariate and multivariate Cox proportional hazard regression analysis and used to establish prognostic models. Additionally, immunohistochemical and CRC cell line data were used to evaluate the results of our three autophagy-associated genes EPHB2, NOL3, and SNAI1 in TCGA. Based on the multivariate Cox analysis, risk scores were calculated and used to classify samples into high-risk and low-risk groups. Kaplan-Meier survival analysis, risk profiling, and independent prognosis analysis were carried out. Receiver operating characteristic analysis was performed to estimate the specificity and sensitivity of the prognostic model. Finally, GSEA, GO, and KEGG analysis were performed to identify the relevant signaling pathways.ResultsA total of 301 autophagy-related genes were differentially expressed in CRC. The areas under the 1-year, 3-year, and 5-year receiver operating characteristic curves of the autophagy-based prognostic model for CRC were 0.764, 0.751, and 0.729, respectively. GSEA analysis of the model showed significant enrichment in several tumor-relevant pathways and cellular protective biological processes. The expression of EPHB2, IL-13, MAP2, RPN2, and TRAF5 was correlated with microsatellite instability (MSI), while the expression of IL-13, RPN2, and TRAF5 was related to tumor mutation burden (TMB). GO analysis showed that the 11 target autophagy genes were chiefly enriched in mRNA processing, RNA splicing, and regulation of the mRNA metabolic process. KEGG analysis showed enrichment mainly in spliceosomes. We constructed a prognostic risk assessment model based on 11 autophagy-related genes in CRC.ConclusionA prognostic risk assessment model based on 11 autophagy-associated genes was constructed in CRC. The new model suggests directions and ideas for evaluating prognosis and provides guidance to choose better treatment strategies for CRC.

Dataset Information

Integrated characterization and validation of the prognostic significance of microRNA-200s in colorectal cancer.

Publications

Integrated characterization and validation of the prognostic significance of microRNA-200s in colorectal cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets