Genome‑scale analysis to identify potential prognostic microRNA biomarkers for predicting overall survival in patients with colon adenocarcinoma

Wei, Haotang; Guo, Erna; Liao, Xiwen; Chen, Lisheng; Wang, Jia‐Lei; Ni, Min; Liang, Chaozhao

doi:10.3892/or.2018.6607

Cited by 19 publications

(19 citation statements)

References 69 publications

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“…At present, the diagnosis of COAD has many problems, such as poor specificity and low time efficiency (Benson et al, 2017;Sun et al, 2019). (Li et al, 2018b;Wei et al, 2018). For this reason, it is critical to find prognostic biomarkers for the treatment of COAD.…”

Section: Discussionmentioning

confidence: 99%

MicroRNAs Associated With Colon Cancer: New Potential Prognostic Markers and Targets for Therapy

Zhu

Xü

Liu

et al. 2020

Front. Bioeng. Biotechnol.

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MicroRNAs (miRNAs) are a kind of non-coding RNA (ncRNA) that regulate the expression of target genes and play a role in the occurrence and development of cancers. Colon cancer (COAD) is the second most common cause of cancer-related mortality. However, the prognostic value of miRNAs in COAD is still confusing. In this study, we obtain miRNAs and messenger RNAs (mRNAs) expression profiles of COAD from the Cancer Genome Atlas (TCGA) database. After preliminary data screening and preprocessing, we acquire the expression data of 894 miRNAs and 17,019 mRNAs. Then, compared with the normal samples, 39 upregulated miRNAs and 54 downregulated miRNAs are identified by differential expression analysis. Furthermore, we obtain 1,487 upregulated mRNAs and 2,847 downregulated mRNAs. We confirm nine key miRNAs related to the survival rate of COAD patients. Moreover, by using bioinformatics methods, we get 461 common genes from both the target genes of these nine key miRNAs and differentially expressed mRNAs. Through analyzing the protein-protein interaction (PPI) network of these 461 common genes and survival analysis, we confirm five hub genes as promising biomarkers for COAD prognosis. It is worth mentioning that no previous reports have found that PGR and KCNB1 are related to COAD. We expect these key miRNAs and hub genes will provide a new way for the study of COAD.

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Section: Discussionmentioning

confidence: 99%

MicroRNAs Associated With Colon Cancer: New Potential Prognostic Markers and Targets for Therapy

Zhu

Xü

Liu

et al. 2020

Front. Bioeng. Biotechnol.

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“…A study revealed that hsa-mir-486-1 may serve as a potential diagnostic biomarker of lung adenocarcinoma ( Ren et al, 2019 ). Hsa-mir-6854 was reported as a potential prognostic miRNA biomarker for colon adenocarcinoma ( Wei et al, 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Prognostic lncRNA, miRNA, and mRNA Signatures in Papillary Thyroid Carcinoma

Wang

Zhao

et al. 2020

Front. Genet.

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The current focus in the treatment of papillary thyroid carcinoma (PTC) is tumor progression. The aim of this study was to build RNA-based classifiers and develop a comprehensive model to provide progression-free interval (PFI) risk prediction for PTC. The RNAseq data, miRNAseq data, and clinical information of PTC were downloaded from The Cancer Genome Atlas database. Based on the differently expressed RNAs, the least absolute shrinkage and selection operator (LASSO) Cox regression model was utilized to build the RNA-based classifiers for PFI of the patients with PTC. A 6messenger RNA (mRNA)-based classifier, a 5-long non-coding RNA (lncRNA)-based classifier, and a 4-microRNA (miRNA)-based classifier were constructed to predict the PFI. Patients with high risk based on the constructed RNA-based classifiers had worse prognosis in Kaplan-Meier curve analysis with log-rank test. The areas under the curves of the first, third, and fifth years in the training and testing set were 0.83, 0.82, and 0.82 and 0.67, 0.72, and 0.73 for the 6-mRNA-based classifier, respectively; 0.75, 0.84, and 0.85 and 0.71, 0.67, and 0.71 for the 5-lncRNA-based classifier, respectively; and 0.70, 0.77, and 0.79 and 0.74, 0.67, and 0.66 for the 4-miRNA-based classifier, respectively. The prediction capability of the three RNA-based classifiers was superior to the TNM stage system. Furthermore, a nomogram based on the verified independent prognostic factors was established for the prognostic prediction. The C-index and calibration plots indicated good predictive accuracy of the nomogram. In summary, the 6-mRNA-based classifier and 5-lncRNA-based classifier constructed in this study were independent prognostic factors for PTC.

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“…The data analyzed in this study were all obtained from public databases. The training cohort datasets were downloaded from TCGA ( https: // tcga - data.nci.nih.gov / tcga ) [ 23 ], and the validation datasets were obtained from GEO ( https://www.ncbi.nlm.nih.gov/geo/ ). The training cohort datasets included clinical datasets ( n = 452), transcriptome datasets ( n = 449), and verification datasets from GSE39582 ( n = 585) [ 24 ] and GSE17538 ( n = 244) [ 25 ].…”

Section: Methodsmentioning

confidence: 99%

Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis

et al. 2020

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Background Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma (COAD) is the main pathological type of colon cancer, and much evidence has supported the correlation between the prognosis of COAD and the immune system. The current study aimed to develop a robust prognostic immune-related gene pair (IRGP) model to estimate the overall survival of patients with COAD. Methods The gene expression profiles and clinical information of patients with colon adenocarcinoma were obtained from the TCGA and GEO databases and were divided into training and validation cohorts. Immune genes were selected that showed a significant association with prognosis. Results Among 1647 immune genes, a model with 17 IRGPs was built that was significantly associated with OS in the training cohort. In the training and validation datasets, the IRGP model divided patients into the high-risk group and low-risk group, and the prognosis of the high-risk group was significantly worse (P<0.001). Univariate and multivariate Cox proportional hazard analyses confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways were upregulated in the high-risk groups. Regulatory T cells and macrophages M0 were significantly highly expressed in the high-risk group. Conclusion We successfully constructed an IRGP model that can predict the prognosis of COAD, providing new insights into the treatment strategy of COAD.

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Genome‑scale analysis to identify potential prognostic microRNA biomarkers for predicting overall survival in patients with colon adenocarcinoma

Cited by 19 publications

References 69 publications

MicroRNAs Associated With Colon Cancer: New Potential Prognostic Markers and Targets for Therapy

MicroRNAs Associated With Colon Cancer: New Potential Prognostic Markers and Targets for Therapy

Prognostic lncRNA, miRNA, and mRNA Signatures in Papillary Thyroid Carcinoma

Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis

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