Explore prognostic marker of colorectal cancer based on ceRNA network

Ke, Mujing; Ji, Liandong; Li, Yixiong

doi:10.1002/jcb.28860

Cited by 13 publications

(8 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MiRNAs are potential for amending tumor cells behaviors due to abnormal gene profiles for mature and precursor sequences compared to normal tissues [7,8]. Consisting of different tumor stromal cells, abundant ncRNA and other cytokines, tumor microenvironment (TME) is the pivotal concern of identifying prognosisrelated markers [9,10]. In the past dozen years, miRNAs have been demonstrated to be closely associated with the occurrence, development and prognosis of different tumors [11,12].…”

Section: Introductionmentioning

confidence: 99%

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

Wang

Huang

Shan

et al. 2021

Aging

View full text Add to dashboard Cite

Background: Identification of more promising microRNAs (miRNAs) are being extensively studied with respect to colorectal cancer (CRC), since CRC is the leading cause of cancer deaths and most common malignant tumors worldwide. A series of colon cancer (CCa) samples from The Cancer Genome Atlas (TCGA) were analyzed to provide a new perspective into this field. Methods: The expression of miRNAs, mRNAs and the clinical data of 437 CRC patients were downloaded from the TCGA database. The survival-related differentially expressed miRNAs (sDMIRs) and mRNAs were detected by COX regression analysis. The high-risk group and low-risk group were separated by the median risk score of the risk score model. The potential clinical characteristics of these sDMIRs were analyzed by R software. The potential molecular mechanisms of these sDMIRs were explored by computational biology. The expression levels of three sDMIRs were explored by qPCR in CRC samples. Results: Three DMIRs (hsa-miR-21-3p, hsa-miR-194-3p and hsa-miR-891a-5p) correlated with the most remarkable prognostic values of CRC patients were selected to establish the risk score model (RSM) by univariate and multivariate COX regression analysis and the survival probability of the low-risk group was longer than that in the high-risk group. We detected the target genes of three sDMIRs and the potential molecular mechanisms of these sDMIRs. We further verified the high expression levels of hsa-miR-21-3p and hsa-miR-194-3p were associated with the early T-stages, while hsa-miR-891a-5p illustrated the reversed result. Conclusion: Our study demonstrated three sDMIRs with significantly clinical values illustrated the potential predicting values in the prognosis of CRC patients. Our results may provide a new perspective for the diagnostic methods and treatment strategies in CRC patients.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Wang

Huang

Shan

et al. 2021

Aging

View full text Add to dashboard Cite

show abstract

“…Careful assessing sensitive and novel biomarkers could monitor the progress and prognosis of carcinoma outcomes [5][6][7][8][9][10][11]. Based on alterations in these molecular or pathways, different assessment of biomarkers that give novel insights into bladder urothelial carcinoma mechanism.…”

Section: Discussionmentioning

confidence: 99%

Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma

Luo

Zhang

2020

BioMed Research International

View full text Add to dashboard Cite

Background. Though there are several prognostic models, there is no protein-related prognostic model. The aim of this study is to identify possible prognostic-related proteins in bladder urothelial carcinoma and to try to predict the prognosis of bladder urothelial carcinoma based on these proteins. Methods. Profile data and corresponding clinical traits were obtained from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA) expression. Survival-associated protein in bladder urothelial carcinoma patients were estimated with Kaplan-Meier (KM) test and COX regression analysis. The potential molecular mechanisms and properties of these bladder urothelial carcinoma-specific proteins were also explored with the help of computational skills. The risk score model was validated in different clinical traits. Sankey diagram representation is for protein correlation. A new prognostic-related risk model based on proteins was developed by using multivariable COX analysis. Next, the alteration of the corresponding genes to the 6 prognostic-related proteins was analyzed. Finally, the relation between the corresponding genes and the immune infiltration was analyzed using the TIMER. Results. Six proteins were identified to be associated with the prognosis of bladder urothelial carcinoma. A prognostic signature based on proteins (BECLIN, EGFR, PKCALPHA, SRC, ANNEXIN1, and AXL) performed moderately in prognostic predictions. The alteration of corresponding genes was in 31(24%) sequenced cases. ANXA1, AXL, and EGFR were positively related to CD8+ T cell. Conclusion. Our results screened six proteins of clinical significance. The importance of a personalized protein signature model in the recognition, surveillance. The abnormal expression of six prognostic-related proteins may be caused by corresponding gene alteration. Furthermore, these proteins may affect survival via the immune infiltration.

show abstract

“…Among these genes, H3F3A, as a diagnostic biomarker in the present study, was also identified as a hub gene, and maybe as a promoter of CRC progression and metastasis. The ceRNA network played a critical role in the initiation and progression of CRC (Ke et al, 2019;Ma et al, 2020). In the present study, we further constructed ceRNA networks based on those key exosomal genes.…”

Section: Discussionmentioning

confidence: 93%

A Diagnostic Model Using Exosomal Genes for Colorectal Cancer

et al. 2022

View full text Add to dashboard Cite

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. Exosomes have great potential as liquid biopsy specimens due to their presence and stability in body fluids. However, the function and diagnostic values of exosomal genes in CRC are poorly understood. In the present study, exosomal data of CRC and healthy samples from the exoRBase 2.0 and Gene Expression Omnibus (GEO) databases were used, and 38 common exosomal genes were identified. Through the least absolute shrinkage and selection operator (Lasso) analysis, support vector machine recursive feature elimination (SVM-RFE) analysis, and logistic regression analysis, a diagnostic model of the training set was constructed based on 6 exosomal genes. The diagnostic model was internally validated in the test and exoRBase 2.0 database and externally validated in the GEO database. In addition, the co-expression analysis was used to cluster co-expression modules, and the enrichment analysis was performed on module genes. Then a protein–protein interaction and competing endogenous RNA network were constructed and 10 hub genes were identified using module genes. In conclusion, the results provided a comprehensive understanding of the functions of exosomal genes in CRC as well as a diagnostic model related to exosomal genes.

show abstract

Explore prognostic marker of colorectal cancer based on ceRNA network

Cited by 13 publications

References 55 publications

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

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

Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma

A Diagnostic Model Using Exosomal Genes for Colorectal Cancer

Contact Info

Product

Resources

About