Dataset Information

Integration analysis for novel lncRNA markers predicting tumor recurrence in human colon adenocarcinoma.

ABSTRACT:

Background

Numerous evidence has suggested that long non-coding RNA (lncRNA) acts an important role in tumor biology. This study focuses on the identification of novel prognostic lncRNA biomarkers predicting tumor recurrence in human colon adenocarcinoma.

Methods

We obtained the research data from The Cancer Genome Atlas (TCGA) database. The interaction among different expressed lncRNA, miRNA and mRNA markers between colon adenocarcinoma patients with and without tumor recurrence were verified with miRcode, starBase and miRTarBase databases. We established the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network based on the verified association between the selected markers. We performed the functional enrichment analysis to obtain better understanding of the selected lncRNAs. Then we use multivariate logistic regression to identify the prognostic lncRNA markers with covariates. We also generated a nomogram predicting tumor recurrence risk based on the identified lncRNA biomarkers and clinical covariates.

Results

We included 12,727 lncRNA, 1881 miRNA and 47,761 mRNA profiling and clinical features for 113 colon adenocarcinoma patients obtained from the TCGA database. After filtration, we used 37 specific lncRNAs, 60 miRNAs and 148 mRNAs in the ceRNA network analysis. We identified five lncRNAs as prognostic lncRNA markers predicting tumor recurrence in colon adenocarcinoma, in which four of them were identified for the first time. Finally, we generated a nomogram illustrating the association between the identified lncRNAs and the tumor recurrence risk in colon adenocarcinoma.

Conclusions

The four newly identified lncRNA biomarkers might be potential prognostic biomarkers predicting tumor recurrence in colon adenocarcinoma. We recommend that further clinical and fundamental researches be conducted on the identified lncRNA markers.

SUBMITTER: Chen F

PROVIDER: S-EPMC6717325 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Integration analysis for novel lncRNA markers predicting tumor recurrence in human colon adenocarcinoma.

Chen Fangyao F Li Zhe Z Deng Changyu C Yan Hong H

Journal of translational medicine 20190830 1

<h4>Background</h4>Numerous evidence has suggested that long non-coding RNA (lncRNA) acts an important role in tumor biology. This study focuses on the identification of novel prognostic lncRNA biomarkers predicting tumor recurrence in human colon adenocarcinoma.<h4>Methods</h4>We obtained the research data from The Cancer Genome Atlas (TCGA) database. The interaction among different expressed lncRNA, miRNA and mRNA markers between colon adenocarcinoma patients with and without tumor recurrence ...[more]

PMID: 31470869

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Project description:BACKGROUND: Several in vitro assays have been used to identify “cancer stem cells” (CSC), including expression of cell surface markers and Hoechst dye efflux properties. However, each of these methods has potential pitfalls that complicate interpretation of the results. Focusing on colon cancers (CC), the CD133 antigen has been proposed as a marker of colon CSC. However, conflicting results have been reported in the literature indicating the need of a systematic analysis of CSC within CC and a complete validation of markers for the isolation of these cells. AIMS: Aim of this study was to confirm that CD133 expression is a valid method for isolating CSC in CC and verify if other antigens can increase the specificity of this marker for isolating CSC in CC. METHODS: CD133+ and CD133- cells were isolated from different human CC lines (CaCo-2, HT29, LOVO, HCT-116) by FACS sorter and the tumor-initiating potential of CD133+ cells was assessed in vitro, by soft-agar colony formation assay, and in vivo, upon transplantation into nude mice. Furthermore, the gene expression profile of CD133+ versus CD133- CaCo-2 cells was compared by the means of microarray analysis. Then, in the effort to identify a common “tumor stem cell” signature for CC, the most relevant transcripts resulting from gene expression profiling on CD133+ cells was assessed by real-time PCR on SP-fraction isolated by FACS sorter from the same CC cell lines. Finally, we deplete CD133 expression in the CaCo-2 cell line by the means of siRNA and verified by Western Blot analysis whether there was a functional correlation between CD133 and the target genes. Moreover, CaCo-2 and HCT116 cells were exposed to sodium butyrate (NaBu) for 72h. Colon cells differentiation was assessed by Alkaline phosphatase activity and expression of CD133 and target genes was tested by western blot. RESULTS: We confirmed that only CD133+ cells have a tumor-initiating potential in vitro and in vivo. Furthermore, microarray analysis of CD133+ versus CD133- CaCo-2 cells revealed a significant overexpression of various transcripts involved in cell proliferation, invasion and stemness in CD133+ cell fraction. Comparison of the transcripts by real-time PCR revealed that the genes of Endothelin-1 (END-1) and NR4A2 are highly expressed in both CD133 + cells and in SP fractions. Finally, when we deplete CD133 expression in Caco-2cells by siRNA, we observed a significant attenuation of END-1 and NR4A2 expression, thus demonstrating that CD133 is involved in the transcriptional regulation of these genes. Interestingly, we also showed that the expression of all three genes was inversely correlated with cell differentiation status as demonstrated by the fact that their expression decreases in a time- and dose-dependent manner after differentiation induced by NaBu. CONCLUSION: Overall, this study confirms the role of CD133antigen as CSC marker and showed for the first time the existence of a functional relationship between CD133, END-1 and NR4A2 expression, hypothesizing that CD133 is involved in the transcriptional regulation of these gene. Microarray analysis was performed on CD133+ and CD133- sorted CACO-2 cells. For both fractions, cells were sorted three independent times. Sample preparation was performed according to Affymetrix recommendations. A total of 6 arrays were hybridized, including 3 CD133+ replicates and 3 CD133- replicates.

Dataset Information

Integration analysis for novel lncRNA markers predicting tumor recurrence in human colon adenocarcinoma.

Background

Methods

Results

Conclusions

Publications

Integration analysis for novel lncRNA markers predicting tumor recurrence in human colon adenocarcinoma.

Similar Datasets

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