scholarly journals Development and Validation of a Unique Gignature of Cancer Stemness-related Genes for Predicting the Overall survival of Colorectal Cancer Patients

2020 ◽  
Author(s):  
Ran Wei ◽  
Jichuan Quan ◽  
Shuofeng Li ◽  
Zhao Lu ◽  
Xu Guan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Cancer Stemness ◽  
Poor Overall Survival ◽  
Tissue Samples ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC.Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB) and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients.Results: This study suggests that high mRNAsi scores are associated with poor overall survival in stage Ⅳ CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 2 key modules and 34 key genes as prognosis-related candidate biomarkers. Finally, a 3-gene prognostic signature (PARPBP, KNSTRN and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort. Conclusions: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.

scholarly journals Integrative Analysis of Biomarkers Through Machine Learning Identifies Stemness Features in Colorectal Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Ran Wei ◽  
Jichuan Quan ◽  
Shuofeng Li ◽  
Hengchang Liu ◽  
Xu Guan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cox Regression ◽  
Stage Iv ◽  
The Cancer Genome Atlas ◽  
Poor Overall Survival ◽  
Tissue Samples ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation ◽  
Highly Correlated

Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC.Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB), and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using the Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients.Results: This study suggests that high-mRNAsi scores are associated with poor overall survival in stage IV CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low-mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 34 key genes as candidate prognosis biomarkers. Finally, a three-gene prognostic signature (PARPBP, KNSTRN, and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort.Conclusion: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.

scholarly journals Molecular Characterization and Clinical Relevance of m6A RNA Methylation Regulators in Cervical Cancer

2020 ◽  
Author(s):  
Jin Chen ◽  
Ji He ◽  
Xiaolei Ma ◽  
Xia Guo
Keyword(s):  
Cervical Cancer ◽  
Clinical Relevance ◽  
Cox Regression ◽  
Critical Role ◽  
The Cancer Genome Atlas ◽  
Rna Modification ◽  
Lasso Regression ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background: RNA modification, such as methylation of N6 adenosine (m6A), plays a critical role in many biological processes. However, the role of m6A RNA modification in cervical cancer (CC) remains largely unknown. Methods: The present study systematically investigated the molecular signatures and clinical relevance of 20 m6A RNA methylation regulators (writers, erasers, readers) in CC. The mRNA expression and clinical significance of m6A-related genes were investigated using data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cervical cancer cohort. Mutations, copy number variation (CNV), differential expression, gene ontology analysis and the construction of a mRNA-microRNA regulatory network were performed to investigate the underlying mechanisms involved in the abnormal expression of m6A-related genes. Results: We found inclusive genetic information alterations among the m6A regulators and that their transcript expression levels were significantly associated with cancer hallmark-related pathways activity, such as the PI3K-AKT signaling pathway, microRNAs in cancer and the focal adhesion pathway, which were significantly enriched. Moreover, m6A regulators were found to be potentially useful for prognostic stratification and we identified FMR1 and ZC3H13 as potential prognostic risk oncogenes by LASSO regression. The ROC curves of 3, 5 and 10 years were 0.685, 0.726 and 0.741, respectively. The specificity for 3, 5 and 10 years were 0.598, 0.631 and 0.833, the sensitivity were 0.707, 0.752 and 0.811, respectively. Conclusions: Multivariable Cox regression analysis revealed that the risk score is an independent prognostic marker and can be used to predict the clinical and pathological features of CC.

scholarly journals The N6-Methyladenosine- (m6A-) Associated Genes Act as Strong Key Biomarkers for the Prognosis of Pancreatic Adenocarcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Fei Li ◽  
Ping Zhang
Keyword(s):  
Pancreatic Adenocarcinoma ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Pancreatic Tumors ◽  
Molecular Characteristics ◽  
Main Role ◽  
Consensus Clustering ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Background. Pancreatic adenocarcinoma (PAAD) has become the major cause of cancer-related deaths globally. The m6A (N6-methyladenosine) alteration plays a crucial function in carcinogenesis and tumor progression. The role of genes related to m6A and their expression level in pancreatic cancer is not identified yet. The objective of this research analysis is a demonstration of the m6A RNA methylation regulators based as biomarkers for the PAAD diagnosis. Methods. About 23 extensively reported m6A RNA methylation regulators were identified through the Cancer Genome Atlas (TCGA) database. This identification was based on consensus clustering analysis, protein-protein integration (PPI) analysis, risk prognostic model, Cox-regression analysis, String Spearman analysis, and LASSO Cox-regression. Results. Herein, we conclude that 23 m6A methylation regulators have a strong link with the clinical and molecular characteristics of PAAD. The three subgroups (1/2) of pancreatic adenocarcinoma were identified using the clustering of 23 m6A regulators. Subgroup cluster 2 had a lower survival rate than the subgroup of cluster 1, and the difference in grades between the two groups was substantial. An assessment was performed using the 23 reported m6A methylation regulators. Eight of these can be used as independent PAAD prognostic markers. The consequences of variable IGF2BP3 expression in PAAD were then investigated further. Conclusions. The key finding of this study was that the m6A methylation regulator gene has the main role in pancreatic tumors, and it may be used as a biomarker in the prognosis of the PAAD and for therapy purposes.

scholarly journals Identification of lnc RNAs Related to Prognosis of Patients With Colorectal Cancer

2020 ◽  
Vol 19 ◽  
pp. 153303382096212
Author(s):  
Yuqi Sun ◽  
Peng Peng ◽  
Lanlan He ◽  
Xueren Gao
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Cox Regression Analysis ◽  
Cancer Genome Atlas ◽  
Score Model ◽  
Prognostic Prediction

The purpose of this study was to identify long noncoding RNAs (lncRNAs) related to prognosis of patients with colorectal cancer (CRC) and develop a prognostic prediction model for CRC. Transcriptome data and survival information of CRC patients were downloaded from The Cancer Genome Atlas. The differentially expressed lncRNAs (DElncRNAs) between CRC and normal colorectal tissues were identified by the edgeR package. The association of DElncRNAs expression with prognosis of CRC patients was analyzed by the survival package. A nomogram predicting 3- and 5- year overall survival of CRC patients was drawn by the rms package. A total of 1046 DElncRNAs were identified, including 271 down-regulated and 775 up-regulated lncRNAs in CRC. Multivariate Cox regression analysis showed 10 lncRNAs related to the prognosis of CRC patients. Thereinto high expression of AC004009.1, LHX1-DT, ELFN1-AS1, AL136307.1, AC087379.2, RBAKDN and AC078820.1 was associated with poorer prognosis of CRC patients. High expression of LINC01055, AL590483.1 and AC008514.1 was associated with better prognosis of CRC patients. Furthermore, the risk score model developed based on the 10 lncRNAs could effectively predict overall survival of CRC patients. In conclusion, 10 prognostic biomarkers for CRC were identified, which would be helpful to understand the role of lncRNAs in CRC progression.

scholarly journals PGM5 is a promising biomarker and may predict the prognosis of colorectal cancer patients

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yifan Sun ◽  
Haihua Long ◽  
Lin Sun ◽  
Xiujuan Sun ◽  
Liping Pang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
Migration And Invasion ◽  
Rank Test ◽  
Poor Overall Survival ◽  
Tissue Samples ◽  
Invasion And Migration ◽  
Kaplan Meier ◽  
And Migration

Abstract Background Phosphoglucomutase (PGM), a key enzyme in the metabolism of glucose-1-phosphate and glucose-6-phosphate, has been found to be associated with proliferation, invasion, and metastasis of cancer. However, the expression and function of PGM5 in colorectal cancer (CRC) remains unknown. Methods We tested PGM5 mRNA and protein expression levels in 79 CRC tissue and their matched adjacent tissue samples by qRT-PCR and immunohistochemistry, respectively. Overall survival (OS) was estimated with the Kaplan–Meier method and compared between groups with the log-rank test. We performed multivariable Cox regression analyses to identify factors associated with CRC risk. The cell proliferation, migration and invasion abilities of CRC cells were detected by using CCK-8, Transwell migration and invasion assays, respectively. Results The PGM5 protein levels expression in CRC tissues were significantly lower than those in the adjacent tissues (t = 5.035, P < 0.001), and Kaplan–Meier analysis indicated that low PGM5 expression were significantly associated with poor overall survival (P = 0.0069). Univariate and multivariate analyses demonstrated that PGM5 was an independent risk factor for overall survival (hazard ratio = 0.3951, P = 0.014). PGM5 overexpression significantly inhibited the proliferation, invasion and migration abilities of CRC cells. On the contrary, knockdown of PGM5 promotes the invasion and migration of CRC cells. Conclusions PMG5 regulates proliferation, invasion, and migration in the CRC and decreased PGM5 is associated with poor prognosis. Therefore, PGM5 is a promising biomarker in CRC and decreased PGM5 may predict poor overall survival in patients with CRC.

scholarly journals Identification of a m6A RNA methylation regulators-based signature for predicting the prognosis of esophageal adenocarcinoma

2020 ◽  
Author(s):  
Yue Zhou ◽  
Shuyan Li ◽  
Liqing Zou ◽  
Tiantian Guo ◽  
Xi Yang ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Clustering Analysis ◽  
Cox Regression ◽  
Area Under The Curve ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract BackgroundN6-methyladenosine (m6A) is an abundant modification in RNAs that affects RNA metabolism, and it is reported to be closely related to cancer occurrence and metastasis. The aim of this study was to identify novel prognostic biomarkers by using m6A RNA methylation regulators capable of improving the risk-stratification criteria of survival for esophageal adenocarcinoma patients.MethodsThe gene expression data of 16 m6A methylation regulators and its relevant clinical information were extracted from The Cancer Genome Atlas (TCGA) database. The expression pattern of these m6A methylation regulators was evaluated. Consensus clustering analysis was conducted to identify clusters of esophageal adenocarcinoma patients with different prognosis. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were performed to construct multiple-gene risk signature. A survival analysis was carried out to determine the prognosis significance.ResultsTen m6A methylation regulators (HNRNPA2B1, HNRNPC, YTHDF1, METTL3, YTHDF2, RBM15, YTHDC1, WTAP, KIAA1429 and YTHDF3) showed significant up-regulation in tumor tissue. Consensus clustering analysis identified three clusters of esophageal adenocarcinoma patients with different overall survival. A five-gene signature, HNRNPA2B1, KIAA1429, WTAP, METTL16 and ALKBH5, was constructed to serve as a prognostic indicator for distinguish esophageal adenocarcinoma patients with different prognosis. The receiver operator characteristic (ROC) curve which indicated the area under the curve (AUC) were 0.803, demonstrated that the prognostic signature had preferable prediction efficiency.Conclusionsm6A methylation regulators exert as potential biomarkers for prognostic stratification of esophageal adenocarcinoma patients and might help clinicians make individualized therapy for this patient population.

scholarly journals The Development of Three-DNA Methylation Signature as a Novel Prognostic Biomarker in Patients with Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Shu Gong ◽  
Weijian Ye ◽  
Tiankai Liu ◽  
Shaofen Jian ◽  
Wenhua Liu
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Overall Survival ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Methylation Array ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
And Gender

Aims. The prognosis of colorectal cancer (CRC) remains poor. This study aimed to develop and validate DNA methylation-based signature model to predict overall survival of CRC patients. Methods. The methylation array data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) database. These patients were divided into training and validation datasets. A risk score model was established based on Kaplan-Meier and multivariate Cox regression analysis of training cohort and tested in validation cohort. Results. Among total 14,626 DNA methylation candidate markers, we found that a three-DNA methylation signature (NR1H2, SCRIB, and UACA) was significantly associated with overall survival of CRC patients. Subgroup analysis indicated that this signature could predict overall survival of CRC patients regardless of age and gender. Conclusions. We established a prognostic model consisted of 3-DNA methylation sites, which could be used as potential biomarker to evaluate the prognosis of CRC patients.

scholarly journals Prognostic Value of an m6A RNA Methylation Regulator-Based Signature in Patients with Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xiaomin Wu ◽  
Xiaojing Zhang ◽  
Leilei Tao ◽  
Xichao Dai ◽  
Ping Chen
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Cox Regression ◽  
Malignant Tumors ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation ◽  
Cluster 2

Purposes. Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. Recent researches have demonstrated that m6A methylation regulators play a key role in various cancers, such as gastric cancer and colon adenocarcinoma. Several m6A methylation regulators are reported to predict the prognosis of HCC. Therefore, there is a need to further identify the predictive value of m6A methylation regulators in HCC. Methods. We utilized The Cancer Genome Atlas (TCGA) database to obtain the gene expression profile of m6A RNA methylation regulators and clinical information for patients with HCC. Besides, we identified two clusters of HCC with various clinical factors by consensus clustering analysis. Then the least absolute shrinkage and selection operator (LASSO) and the Cox regression analysis were applied to construct a prognostic signature. Results. Except for ZC3H13 and METTL14, a majority of the thirteen m6A RNA methylation regulators were significantly overexpressed in HCC specimens. HCC patients were classified into two groups (cluster 1 and cluster 2). The cluster 1 was with a significantly worse prognosis than cluster 2, and most of the 13 known m6A RNA methylation regulators were upregulated in cluster 1. Besides, we developed a prognostic signature consisting of YTHDF2, YTHDF1, METTL3, KIAA1429, and ZC3H13, which could successfully differentiate high-risk patients. More importantly, univariate and multivariate Cox regression analysis indicated that the signature-based risk score was an independent prognostic factor for patients with HCC. Conclusions. Our study showed these five m6A RNA methylation regulators can be used as practical and reliable prognostic tools of HCC, which might have potential value for therapeutic strategies.

scholarly journals The functions and prognostic values of m6A RNA methylation regulators in thyroid carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhi-Hao Yu ◽  
Shao-Ting Feng ◽  
Di Zhang ◽  
Xu-Chen Cao ◽  
Yue Yu ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Thyroid Carcinoma ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Rna Modification ◽  
Sequencing Data ◽  
Aberrant Expression ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background N6-Methyladenosine (m6A) is the most common RNA modification and regulates RNA splicing, translation, translocation, and stability. Aberrant expression of m6A has been reported in various types of human cancers. m6A RNA modification is dynamically and reversibly mediated by different regulators, including methyltransferase, demethylases, and m6A binding proteins. However, the role of m6A RNA methylation regulators in thyroid cancer remains unknown. The aim of this study is to investigate the effect of the 13 main m6A RNA modification regulators in thyroid carcinoma. Methods We obtained clinical data and RNA sequencing data of 13 m6A RNA methylation regulators from The Cancer Genome Atlas (TCGA) THCA database. We performed consensus clustering to identify the clinical relevance of m6A RNA methylation regulators in thyroid carcinoma. Then we used LASSO Cox regression analysis to generate a prognostic signature based on m6A RNA modification regulator expression. Kyoto Encyclopedia of Genes and Genomes, Gene Ontology and Gene Set Enrichment Analyses were performed to explore differential cellular processes and signaling pathways between the two groups based on risk signature. Results We found that most of the m6A RNA modification regulators are down-regulated in 450 patients with thyroid carcinoma. We derived a three m6A RNA modification regulator genes-based risk signature (FTO, RBM15 and KIAA1429), that is an independent prognostic biomarker in patients with thyroid carcinoma. Moreover, we found that this risk signature could better predict outcome in male than female. Functional research in vitro demonstrated that the m6A RNA methylation regulators involved in the model acted significant role in the proliferation and migration of thyroid cancer cells. Conclusions Our study revealed the influence of m6A RNA methylation regulators on thyroid carcinoma through biological experiments and three-gene prognostic model.

scholarly journals A m6A-related lncRNA Signature as a Novel Prognostic Factor for Gastric Cancer

2020 ◽  
Author(s):  
Haixu Wang ◽  
Qingkai Meng ◽  
Bin Ma
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
Complete Dataset ◽  
M6a Rna Methylation

Abstract Background: N6-methyladenosine (m6A)isa common form of mRNA modification regulated by m6A RNA methylation regulators. However, studies have not explored the role of m6A-related lncRNA in gastric cancer (GC). This study aimed atexploring biological and prognostic roles of m6A-related lncRNA in GC. Methods: We identified 800 m6A-related lncRNAs through correlation analysis of 13 main m6A RNA methylation regulators and all lncRNAs expressed in GC. We further categorized patients into train group and testing group equally. Results: A total of 11 m6A-related lncRNA signature associated with prognosis of GC were identified through univariate cox regression analysis and LASSO analysis which was validated using the testing dataset and complete dataset, respectively. More deaths and shorter survival time were reported for patients in the high-risk group compared to low-risk group. lncRNA signature is an independent prognosis predictor as shown by cox regression analysis of the complete dataset. Moreover, genes involved in base excision repair were highly expressed in patients in the high-risk group as shown by gene set enrichment analysis (GSEA) result whereas ECM receptor interaction and focal adhesion pathway were enriched in low-risk group. A nomogram on independent factors showed clinical net benefit asan overall survival predictor of GC. In addition, we identified four subgroups of GC patients with significant differences in overall survival (OS).Subgroup C1 and C2 responded well to immunotherapy, compared to subgroup C3 and C4. Conclusions: m6A-related lncRNA signature and four molecular subgroups provide information on the underlying molecular mechanism of GC and provide for a basis for development ofpersonalized therapy.

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