Establishing a three-miRNA signature as a prognostic model for colorectal cancer through bioinformatics analysis

Abstract Background LINC00963 is high-expressed in various carcinomas, but its expression and function in colorectal cancer (CRC) have not been explored. This study explored the role and mechanism of LINC00963 in CRC. Methods The expression of LINC00963 in CRC and its relationship with prognosis were examined by starBase and survival analysis. The effects of LINC00963, miR-532-3p and HMGA2 on the biological characteristics and EMT-related genes of CRC cells were studied by RT-qPCR, CCK-8, clone formation experiments, flow cytometry, scratch test, Transwell, and Western blot. Xenograft assay and immunohistochemistry were performed to verify the effect of LINC00963 on tumor growth. The correlation among LINC00963, miR-532-3p, and HMGA2 was analyzed by bioinformatics analysis, luciferase assay, and Pearson test. Results LINC00963 was high-expressed in CRC, and this was associated with poor prognosis of CRC. Silencing LINC00963 inhibited the activity, proliferation, migration, and invasion of CRC cells, MMP-3 and MMP-9 expressions, moreover, it also blocked cell cycle progression, and inhibited tumor growth and Ki67 expression. However, overexpression of LINC00963 showed the opposite effects to silencing LINC00963. LINC00963 targeted miR-532-3p to regulate HMGA2 expression. Down-regulation of miR-532-3p promoted cell proliferation, migration and invasion, and expressions of MMP-3 and MMP-9, and knockdown of HMGA2 reversed the effect of miR-532-3p inhibitor. Up-regulation of miR-532-3p inhibited the biological functions of CRC cells, and overexpression of HMGA2 reversed the miR-532-3p mimic effect. Conclusion LINC00963 affects the development of CRC through the miR-532-3p/HMGA2 axis.

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Prediction of Prognostic Biomarkers and Construction of an Autophagy Prognostic Model for Colorectal Cancer Using Bioinformatics

Technology in Cancer Research & Treatment ◽

10.1177/1533033820984177 ◽

2020 ◽

Vol 19 ◽

pp. 153303382098417

Author(s):

Ting-ting Liu ◽

Shu-min Liu

Keyword(s):

Colorectal Cancer ◽

Regression Analysis ◽

Prognostic Model ◽

Cox Regression ◽

Small Gtpase ◽

Functional Enrichment ◽

Clinical Correlation ◽

Cox Regression Analysis ◽

Prognostic Analysis ◽

Key Genes

Objective: The incidence of colorectal cancer is increasing every year, and autophagy may be related closely to the pathogenesis of colorectal cancer. Autophagy is a natural catabolic mechanism that allows the degradation of cellular components in eukaryotic cells. However, autophagy plays a dual role in tumorigenesis. It not only promotes normal cell survival and tumor growth but also induces cell death and suppresses tumors survival. In addition, the pathogenesis of various conditions, including inflammation, neurodegenerative diseases, or tumors, is associated with abnormal autophagy. The present work aimed to examine the significance of autophagy-related genes (ARGs) in prognosis prediction, to construct an autophagy prognostic model, and to identify independent prognostic factors for colorectal cancer (CRC). Methods: This study discovered a total of 36 ARGs in CRC cases using The Cancer Genome Atlas (TCGA) and Human Autophagy-dedicated (HADd) databases along with functional enrichment analysis. Then, an autophagy prognostic model was constructed using univariate Cox regression analysis, and the key prognostic genes were screened. Finally, independent prognostic markers were determined through independent prognostic analysis and clinical correlation analysis of key genes. Results: Of the 36 differentially expressed ARGs, 13 were related to prognosis, as determined by univariate Cox regression analysis. A total of 6 key genes were obtained by a multivariate Cox regression analysis. Independent prognostic values were shown by 3 genes, namely, microtubule-associated protein 1 light chain 3 (MAP1LC3C), small GTPase superfamily and Rab family (RAB7A), and WD-repeat domain phosphoinositide-interacting protein 2 (WIPI2) by independent prognostic analysis and clinical correlation. Conclusions: In this study, molecular bioinformatics technology was employed to determine and construct a prognostic model of autophagy for colon cancer patients, which revealed 3 autophagy-related features, namely, MAP1LC3C, WIPI2, and RAB7A.

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Four targeted genes for predicting the prognosis of colorectal cancer: A bioinformatics analysis case

Oncology Letters ◽

10.3892/ol.2019.10866 ◽

2019 ◽

Cited By ~ 3

Author(s):

Qinglai Bian ◽

Jiaxu Chen ◽

Wenqi Qiu ◽

Chenxi Peng ◽

Meifang Song ◽

...

Keyword(s):

Colorectal Cancer ◽

Bioinformatics Analysis

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Development and Validation of A Seven-microRNA Signature as a Novel Prognostic Biomarker for Bladder Cancer

10.21203/rs.3.rs-70359/v1 ◽

2020 ◽

Author(s):

Jin-Xing Lv ◽

Fei Lin ◽

Zhi-Bin Ke ◽

Yun-Zhi Lin ◽

Peng-Fei Zhuang ◽

...

Keyword(s):

Bladder Cancer ◽

Cancer Patients ◽

Mirna Expression ◽

Prognostic Model ◽

Cox Regression ◽

Expression Profiles ◽

Univariate Analysis ◽

Test Group ◽

Differential Analysis ◽

Mirna Signature

Abstract Background The differential expression of miRNAs has played a significant role in bladder tumors. The aim of our study was to screen new biomarkers . Methods Through differential analysis of bladder cancer mRNA and miRNA expression data in the TCGA, differential genes and miRNAs were screened. Furthermore, Cox univariate analysis and multifactor analysis were used to establish a prognostic prediction model . The predictive ability of the prognostic model was then verified on the patient. The action mechanism of these miRNAs was analyzed.Results By the differential analysis and standardization of miRNA expression profiles. Differentially expressed miRNAs were screened, then all the patients were then randomly divided into train group and the test group. 23 miRNAs were revealed , then a Seven-miRNA signature prognostic biomarkers was constituting.Univariate cox regression and multivariate cox regression considering other clinical factors displayed that the seven-miRNA signature could serve as an independent prognostic factor.Target genes of these seven miRNAs were analyzed by KEGG signaling pathway and GO enrichment analysis. . Conclusion The prognostic model constructed by seven miRNAs has possessed certain degree of sensitivity and specificity for the prediction of the survival of bladder cancer patients, which can be used as a potential new clinical marker for bladder cancer patients.

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