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Identification of miRNAs differentially expressed in clinical stages of human colorectal carcinoma-an investigation in Guangzhou, China.

ABSTRACT: Aberrant expression of microRNAs (miRNAs) has been implicated in human cancer, including colorectal cancer (CRC). Such dysregulated miRNAs may have potential as diagnostic markers or therapeutic targets. However, the nature of an association between these miRNAs and clinical stages of CRC is still not clear. To this end, we performed a miRNA profiling of 1547 distinct human miRNAs using 31 samples of tumor and paired normal mucosa obtained from 31 CRC patients. Based on statistical analyses of profiling data, we identified 569 miRNAs that were significantly dysregulated in CRC relative to normal tissues (P<0.05). Among the 569 dysregulated miRNAs, downregulation of 17 was associated with stages II, III, and IV colon and rectal cancers (separate or combined), according to our criteria. We also assessed the potential of these dysregulated miRNAs as diagnostic biomarkers for CRC patients who were without metastasis, and the value of the dysregulated miRNAs for predicting metastasis, lymph node and distant. Their distinct expression patterns in colon and rectal cancers were also examined. Although our findings cannot be immediately applied toward clinical diagnosis, our new study model for determining and assessing the biomarker potential of dysregulated miRNAs should be useful in further research in detection of human CRC.

SUBMITTER: Xu XH

PROVIDER: S-EPMC3990568 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Identification of miRNAs differentially expressed in clinical stages of human colorectal carcinoma-an investigation in Guangzhou, China.

Xu Xue-Hu XH Wu Xiao-Bing XB Wu Shang-Biao SB Liu Hai-Bo HB Chen Rong R Li Yong Y

PloS one 20140417 4

Aberrant expression of microRNAs (miRNAs) has been implicated in human cancer, including colorectal cancer (CRC). Such dysregulated miRNAs may have potential as diagnostic markers or therapeutic targets. However, the nature of an association between these miRNAs and clinical stages of CRC is still not clear. To this end, we performed a miRNA profiling of 1547 distinct human miRNAs using 31 samples of tumor and paired normal mucosa obtained from 31 CRC patients. Based on statistical analyses of p ...[more]

PMID: 24743265

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Project description:BACKGROUND: The miRNAs, a class of short approximately 22-nucleotide non-coding RNAs, often act post-transcriptionally to inhibit mRNA expression. In effect, they control gene expression by targeting mRNA. They also help in carrying out normal functioning of a cell as they play an important role in various cellular processes. However, dysregulation of miRNAs is found to be a major cause of a disease. It has been demonstrated that miRNA expression is altered in many human cancers, suggesting that they may play an important role as disease biomarkers. Multiple reports have also noted the utility of miRNAs for the diagnosis of cancer. Among the large number of miRNAs present in a microarray data, a modest number might be sufficient to classify human cancers. Hence, the identification of differentially expressed miRNAs is an important problem particularly for the data sets with large number of miRNAs and small number of samples. RESULTS: In this regard, a new miRNA selection algorithm, called ?HEM, is presented based on rough hypercuboid approach. It selects a set of miRNAs from a microarray data by maximizing both relevance and significance of the selected miRNAs. The degree of dependency of sample categories on miRNAs is defined, based on the concept of hypercuboid equivalence partition matrix, to measure both relevance and significance of miRNAs. The effectiveness of the new approach is demonstrated on six publicly available miRNA expression data sets using support vector machine. The.632+ bootstrap error estimate is used to minimize the variability and biasedness of the derived results. CONCLUSIONS: An important finding is that the ?HEM algorithm achieves lowest B.632+ error rate of support vector machine with a reduced set of differentially expressed miRNAs on four expression data sets compare to some existing machine learning and statistical methods, while for other two data sets, the error rate of the ?HEM algorithm is comparable with the existing techniques. The results on several microarray data sets demonstrate that the proposed method can bring a remarkable improvement on miRNA selection problem. The method is a potentially useful tool for exploration of miRNA expression data and identification of differentially expressed miRNAs worth further investigation.

Project description:To identify candidate key genes and miRNAs associated with esophageal squamous cell carcinoma (ESCC) development and prognosis, the gene expression profiles and miRNA microarray data including GSE20347, GSE38129, GSE23400, and GSE55856 were downloaded from the Gene Expression Omnibus (GEO) database. Clinical and survival data were retrieved from The Cancer Genome Atlas (TCGA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) was analyzed via DAVID, while the DEG-associated protein-protein interaction network (PPI) was constructed using the STRING database. Additionally, the miRNA target gene regulatory network and miRNA coregulatory network were constructed, using the Cytoscape software. Survival analysis and prognostic model construction were performed via the survival (version 2.42-6) and rbsurv R packages, respectively. The results showed a total of 2575, 2111, and 1205 DEGs, and 226 differentially expressed miRNAs (DEMs) were identified. Pathway enrichment analyses revealed that DEGs were mainly enriched in 36 pathways, such as the proteasome, p53, and beta-alanine metabolism pathways. Furthermore, 448 nodes and 1144 interactions were identified in the PPI network, with MYC having the highest random walk score. In addition, 7 DEMs in the microarray data, including miR-196a, miR-21, miR-205, miR-194, miR-103, miR-223, and miR-375, were found in the regulatory network. Moreover, several reported disease-related miRNAs, including miR-198a, miR-103, miR-223, miR-21, miR-194, and miR-375, were found to have common target genes with other DEMs. Survival analysis revealed that 85 DEMs were related to prognosis, among which hsa-miR-1248, hsa-miR-1291, hsa-miR-421, and hsa-miR-7-5p were used for a prognostic survival model. Taken together, this study revealed the important roles of DEGs and DEMs in ESCC development, as well as DEMs in the prognosis of ESCC. This will provide potential therapeutic targets and prognostic predictors for ESCC.

Dataset Information

Identification of miRNAs differentially expressed in clinical stages of human colorectal carcinoma-an investigation in Guangzhou, China.

Publications

Identification of miRNAs differentially expressed in clinical stages of human colorectal carcinoma-an investigation in Guangzhou, China.

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