Dataset Information

Mining, Validation, and Clinical Significance of Colorectal Cancer (CRC)-Associated lncRNAs.

ABSTRACT: Colorectal cancer (CRC) is one of the deadliest tumours, but its pathogenesis remains unclear. The involvement of differentially expressed long non-coding RNAs (lncRNAs) in CRC tumorigenesis makes them suitable tumour biomarkers.Here, we screened 150 cases of CRC and 85 cases of paracancerous tissues in the GEO database for differentially expressed lncRNAs. The levels of lncRNA candidates in 84 CRC and paracancerous tissue samples were validated by qRT-PCR and their clinical significance was analyzed. We identified 15 lncRNAs with differential expression in CRC tumours; among them, AK098081 was significantly up-regulated, whereas AK025209, BC040303, BC037331, AK026659, and CR749831 were down-regulated in CRC. In a receiver operating characteristic curve analysis, the area under the curve for the six lncRNAs was 0.914. High expression of AK098081 and low expression of BC040303, CR749831, and BC037331 indicated poor CRC differentiation. CRC patients with lymph node metastasis had lower expression of BC037331. In addition, the group with high AK098081 expression presented significantly lower overall survival and disease-free survival rates than the low-expression group, confirming AK098081 as an independent risk factor for CRC patients.In conclusion, we have identified multiple CRC-associated lncRNAs from microarray expression profiles that can serve as novel biomarkers for the diagnosis and prognosis of CRC.

SUBMITTER: Sun X

PROVIDER: S-EPMC5082825 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Mining, Validation, and Clinical Significance of Colorectal Cancer (CRC)-Associated lncRNAs.

Sun Xiangwei X Hu Yingying Y Zhang Liang L Hu Changyuan C Guo Gangqiang G Mao Chenchen C Xu Jianfeng J Ye Sisi S Huang Guanli G Xue Xiangyang X Guo Aizhen A Shen Xian X

PloS one 20161027 10

<h4>Background</h4>Colorectal cancer (CRC) is one of the deadliest tumours, but its pathogenesis remains unclear. The involvement of differentially expressed long non-coding RNAs (lncRNAs) in CRC tumorigenesis makes them suitable tumour biomarkers.<h4>Methods/findings</h4>Here, we screened 150 cases of CRC and 85 cases of paracancerous tissues in the GEO database for differentially expressed lncRNAs. The levels of lncRNA candidates in 84 CRC and paracancerous tissue samples were validated by qRT ...[more]

PMID: 27788162

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Project description:Purpose: This study aimed to identify a novel biomarker or a target of treatment for colorectal cancer (CRC). Experimental Design: The expression profiles of cancer cells in 104 patients with CRC were examined using laser microdissection and oligonucleotide microarray analysis. Overexpression in CRC cells especially in patients with distant metastasis was a prerequisite to select candidate genes. The mRNA expression of candidate gene was investigated by quantitative reversetranscription polymerase chain reaction (RT-PCR) in 77 patients as a validation study. We analyzed the protein expression and localization of the candidate gene by immunohistochemical study, and investigated the relationship between the expression and the clinicopathological feature in 274 CRC patients. Results: We identified 6 genes as candidates related to distant metastasis in CRC patients by microarray analysis. Among these genes, Osteoprotegerin (OPG) is known to have an association with aggressiveness in several cancers through inhibiting apoptosis by neutralizing the function of tumor necrosis factor related apoptosis inducing ligand (TRAIL). The mRNA expression of OPG in cancer tissues was significantly higher in patients with distant metastasis than those without metastasis. The overexpression of OPG protein was significantly associated with worse overall survival and relapse free survival (RFS). Moreover, the overexpression of OPG protein was an independent risk factor for recurrence of CRC. Conclusion: The overexpression of OPG would be a predictive biomarker of recurrence and a target of the treatment for CRC. Total of 148 microarray datasets obtained from LCM and homogenized tissues of colorectal cancer patients were normalized using robust multi-array average (RMA) method under R 2.6.2 statistical software with affy package from BioConductor. Normalization was separately performed for LCM dataset and homogenized tissue dataset. The normalized gene expression levels were presented as log2-transformed values by RMA.

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.

Dataset Information

Mining, Validation, and Clinical Significance of Colorectal Cancer (CRC)-Associated lncRNAs.

Publications

Mining, Validation, and Clinical Significance of Colorectal Cancer (CRC)-Associated lncRNAs.

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