scholarly journals Identification of a Novel Ferroptosis-Related Gene Prediction Model for Clinical Prognosis and Immunotherapy of Colorectal Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ya-bing Yang ◽  
Jia-xin Zhou ◽  
Sheng-hui Qiu ◽  
Jia-shuai He ◽  
Jing-hua Pan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Model ◽  
Gene Prediction ◽  
Predictive Performance ◽  
High Accuracy ◽  
Functional Enrichment ◽  
Clinical Prognosis ◽  
Cerna Network ◽  
Potential Biomarker ◽  
Dependent Cell

Background. Colorectal cancer (CRC) is the third most common malignancies worldwide. Ferroptosis is a programmed, iron-dependent cell death observed in cancer cells. However, the prognostic potential and immunotherapy biomarker potential of ferroptosis-related genes (FRGs) in CRC patients remains to be clarified. Methods. At first, we comprehensively analysed the different expression and prognosis of related FRGs in CRC patients based on TCGA cohort. The relationship between functional enrichment of these genes and immune microenvironment in CRC was investigated using the TCGA database. Prognostic model was constructed to determine the association between FRGs and the prognosis of CRC. Relative verification was done based on the GEO database. Meanwhile, the ceRNA network of FRGs in the model was also performed to explore the regulatory mechanisms. Results. Eight differentially expressed FRGs were associated with the prognosis of CRC patients. Patients from the TCGA database were classified into the A, B, and C FRG clusters with different features. And FRG scores were constructed to quantify the FRG pattern of individual patients with colorectal cancer. The CRC patients with higher FRG score showed worse survival outcomes, higher immune dysfunction, and lower response to immunotherapy. The prognostic model showed a high accuracy for predicting the OS of CRC. Finally, a ceRNA network was analysed to show the concrete regulation mechanisms of critical FRGs in CRC. Conclusions. The FRG risk score prognostic model based on 8 FRGs exhibit superior predictive performance, providing a novel prognostic model with a high accuracy for CRC patients. Moreover, FRG score can be the potential biomarker of the response of immunotherapy for CRC.

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

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.

scholarly journals Construction of ceRNA Coexpression Network and Screening of Molecular Targets in Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Zhao Hui ◽  
Wang Zhanwei ◽  
Yang Xi ◽  
Liu Jin ◽  
Zhuang Jing ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Normal Tissues ◽  
Cerna Network ◽  
Cancer Tissues

Objective. To screen some RNAs that correlated with colorectal cancer (CRC). Methods. Differentially expressed miRNAs, lncRNAs, and mRNAs between cancer tissues and normal tissues in CRC were identified using data from the Gene Expression Omnibus (GEO) database. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interactions (PPIs) were performed to do the functional enrichment analysis. And a lncRNA-miRNA-mRNA network was constructed which correlated with CRC. RNAs in this network were subjected to analyze the relationship with the patient prognosis. Results. A total of 688, 241, and 103 differentially expressed genes (diff-mRNA), diff-lncRNA, and diff-miRNA were obtained between cancer tissues and normal tissues. A total of 315 edges were obtained in the ceRNA network. lncRNA RP11-108K3.2 and mRNA ONECUT2 correlated with prognosis. Conclusion. The identified RNAs and constructed ceRNA network could provide great sources for the researches of therapy of the CRC. And the lncRNA RP11-108K3.2 and mRNA ONECUT2 may serve as a novel prognostic predictor of CRC.

scholarly journals Identification of Hub Gene TIMP1 and Relative ceRNAs Regulatory Network in Colorectal Cancer

2020 ◽  
Author(s):  
De-jun Kong ◽  
Ya-fei Qin ◽  
Guang-ming Li ◽  
Hong-da Wang ◽  
Yi-ming Zhao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Target Therapy ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Survival Prediction ◽  
Ppi Network ◽  
Gene Expressions ◽  
R Software ◽  
Hub Gene ◽  
Potential Biomarker

Abstract Objectives This study aimed to discover the ceRNAs network in pathophysiological development of human colorectal cancer (CRC) and to screen biomarkers for target therapy and prognosis by using integrated bioinformatics analysis.Methods Data on gene expressions of mRNAs, circRNAs, and miRNAs and clinical information were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus database respectively. Differentially expressed mRNAs (DEGs) were identified by using DESeq2 package of R software. Functional enrichment analysis was conducted by ClusterProfiler package of R software. Protein-protein interaction (PPI) network was shown by STRING website. Survival analysis of hub genes was performed by survival package in R software. Interactions among hub gene, DEmiRNAs and DEcircRNAs were used to construct ceRNAs network.Results A total of 412 DEGs (including 82 upregulated and 330 downregulated) were screened out between 473 CRC and 41 normal samples. 260 DEcircRNAs (including 253 upregulated and 7 downregulated) were altered. A ceRNAs and PPI network was successfully constructed and TIMP1 associated with prognosis were employed.Conclusion The present study identifies a novel ceRNAs network, which imply that TIMP1 is a potential biomarker underlying the development of CRC, providing new insights for survival prediction and therapeutic target.

scholarly journals A Novel Ferroptosis-Related Gene Risk Signature for Predicting Prognosis and Immunotherapy Response in Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Shi-jin Liu ◽  
Ya-bing Yang ◽  
Jia-xin Zhou ◽  
Yu-jian Lin ◽  
Yun-long Pan ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Gastric Carcinoma ◽  
Differentially Expressed Genes ◽  
Prognostic Model ◽  
Survival Outcome ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Related Gene ◽  
Value Analysis ◽  
Cerna Network

Background. Gastric cancer (GC) is the third leading cause of cancer death worldwide with complicated molecular and cellular heterogeneity. Iron metabolism and ferroptosis play crucial roles in the pathogenesis of GC. However, the prognostic role and immunotherapy biomarker potential of ferroptosis-related genes (FRGs) in GC still remains to be clarified. Methods. We comprehensively analyzed the prognosis of different expression FRGs, based on gastric carcinoma patients in the TCGA cohort. The functional enrichment and immune microenvironment associated with these genes in gastric cancer were investigated. The prognostic model was constructed to clarify the relation between FRGs and the prognosis of GC. Meanwhile, the ceRNA network of FRGs in the prognostic model was performed to explore the regulatory mechanisms. Results. Gastric carcinoma patients were classified into the A, B, and C FRGClusters with different features based on 19 prognostic ferroptosis-related differentially expressed genes in the TCGA database. To quantify the FRG characteristics of individual patients, FRGScore was constructed. And the research shows the GC patients with higher FRGScore had worse survival outcome. Moreover, thirteen prognostic ferroptosis-related differentially expressed genes (DEGs) were selected to construct a prognostic model for GC survival outcome with a superior accuracy in this research. And we also found that FRG RiskScore can be an independent biomarker for the prognosis of GC patients. Interestingly, GC patients with lower RiskScore had less immune dysfunction and were more likely to respond to immunotherapy according to TIDE value analysis. Finally, a ceRNA network based on FRGs in the prognostic model was analyzed to show the concrete regulation mechanisms. Conclusions. The ferroptosis-related gene risk signature has a superior potent in predicting GC prognosis and acts as the biomarkers for immunotherapy, which may provide a reference in clinic.

scholarly journals Identification of the 3-lncRNA Signature as a Prognostic Biomarker for Colorectal Cancer

2020 ◽  
Vol 21 (24) ◽  
pp. 9359
Author(s):  
Shuzhen Liu ◽  
Qing Cao ◽  
Guoyan An ◽  
Bianbian Yan ◽  
Lei Lei
Keyword(s):  
Colorectal Cancer ◽  
Noncoding Rna ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Cell Counting ◽  
Luciferase Assay ◽  
Clinical Feature ◽  
Cox Regression Analysis ◽  
Cerna Network

Colorectal cancer (CRC) is one of the most common malignant carcinomas in the world, and metastasis is the main cause of CRC-related death. However, the molecular network involved in CRC metastasis remains poorly understood. Long noncoding RNA (lncRNA) plays a vital role in tumorigenesis and may act as a competing endogenous RNA (ceRNA) to affect the expression of mRNA by suppressing miRNA function. In this study, we identified 628 mRNAs, 144 lncRNAs, and 25 miRNAs that are differentially expressed (DE) in metastatic CRC patients compared with nonmetastatic CRC patients from the Cancer Genome Atlas (TCGA) database. Functional enrichment analyses confirmed that the identified DE mRNAs are extensively involved in CRC tumorigenesis and migration. By bioinformatics analysis, we constructed a metastasis-associated ceRNA network for CRC that includes 28 mRNAs, 12 lncRNAs, and 15 miRNAs. We then performed multivariate Cox regression analysis on the ceRNA-related DE lncRNAs and identified a 3-lncRNA signature (LINC00114, LINC00261, and HOTAIR) with the greatest prognostic value for CRC. Clinical feature analysis and functional enrichment analysis further proved that these three lncRNAs are involved in CRC tumorigenesis. Finally, we used Transwell, Cell Counting Kit (CCK)-8, and colony formation assays to clarify that the inhibition of LINC00114 promotes the migratory, invasive, and proliferative abilities of CRC cells. The results of the luciferase assay suggest that LINC00114 is the direct target of miR-135a, which also verified the ceRNA network. In summary, this study provides a metastasis-associated ceRNA network for CRC and suggests that the 3-lncRNA signature may be a useful candidate for the diagnosis and prognosis of CRC.

scholarly journals Loss of ZNF677 expression is a predictive biomarker for lymph node metastasis in Middle Eastern Colorectal Cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Abdul K. Siraj ◽  
Sandeep Kumar Parvathareddy ◽  
Nabil Siraj ◽  
Khadija Al-Obaisi ◽  
Saud M. Aldughaither ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Lymph Node ◽  
Protein Expression ◽  
Zinc Finger ◽  
Zinc Finger Protein ◽  
Middle Eastern ◽  
Clinical Prognosis ◽  
Mesenchymal Transition ◽  
Finger Protein ◽  
Potential Biomarker

AbstractZinc-finger proteins are transcription factors with a “finger-like” domain that are widely involved in many biological processes. The zinc-finger protein 677 (ZNF677) belongs to the zinc-finger protein family. Previous reports have highlighted the tumor suppressive role of ZNF677 in thyroid and lung cancer. However, its role in colorectal cancer (CRC) has not been explored. ZNF677 protein expression was analyzed by immunohistochemistry in a large cohort of 1158 CRC patients. ZNF677 loss of expression was more frequent in CRC tissues (45.3%, 525/1158), when compared to that of normal tissue (5.1%, 11/214) (p < 0.0001) and was associated with mucinous histology (p = 0.0311), advanced pathological stage (p < 0.0001) and lymph node (LN) metastasis (p = 0.0374). Further analysis showed ZNF677 loss to be significantly enriched in LN metastatic CRC compared to overall cohort (p = 0.0258). More importantly, multivariate logistic regression analysis showed that ZNF677 loss is an independent predictor of LN metastasis in CRC (Odds ratio = 1.41; 95% confidence interval 1.05–1.87; p = 0.0203).The gain- and loss-of-function studies in CRC cell lines demonstrated that loss of ZNF677 protein expression prominently increased cell proliferation, progression of epithelial-mesenchymal transition and conferred chemoresistance, whereas its overexpression reversed the effect. In conclusion, loss of ZNF677 protein expression is common in Middle Eastern CRC and contributes to the prediction of biological aggressiveness of CRC. Therefore, ZNF677 could not only serve as a marker in predicting clinical prognosis in patient with CRC but also as a potential biomarker for personalized targeted therapy.

scholarly journals Construction and validation of an RNA-binding protein-associated prognostic model for colorectal cancer

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11219
Author(s):  
Yandong Miao ◽  
Hongling Zhang ◽  
Bin Su ◽  
Jiangtao Wang ◽  
Wuxia Quan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Model ◽  
Rna Binding ◽  
Cox Regression ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Cox Regression Analysis ◽  
Diagnosis And Prognosis

Colorectal cancer (CRC) is one of the most prevalent and fatal malignancies, and novel biomarkers for the diagnosis and prognosis of CRC must be identified. RNA-binding proteins (RBPs) are essential modulators of transcription and translation. They are frequently dysregulated in various cancers and are related to tumorigenesis and development. The mechanisms by which RBPs regulate CRC progression are poorly understood and no clinical prognostic model using RBPs has been reported in CRC. We sought to identify the hub prognosis-related RBPs and to construct a prognostic model for clinical use. mRNA sequencing and clinical data for CRC were obtained from The Cancer Genome Atlas database (TCGA). Gene expression profiles were analyzed to identify differentially expressed RBPs using R and Perl software. Hub RBPs were filtered out using univariate Cox and multivariate Cox regression analysis. We used functional enrichment analysis, including Gene Ontology and Gene Set Enrichment Analysis, to perform the function and mechanisms of the identified RBPs. The nomogram predicted overall survival (OS). Calibration curves were used to evaluate the consistency between the predicted and actual survival rate, the consistency index (c-index) was calculated, and the prognostic effect of the model was evaluated. Finally, we identified 178 differently expressed RBPs, including 121 up-regulated and 57 down-regulated proteins. Our prognostic model was based on nine RBPs (PNLDC1, RRS1, HEXIM1, PPARGC1A, PPARGC1B, BRCA1, CELF4, AEN and NOVA1). Survival analysis showed that patients in the high-risk subgroup had a worse OS than those in the low-risk subgroup. The area under the curve value of the receiver operating characteristic curve of the prognostic model is 0.712 in the TCGA cohort and 0.638 in the GEO cohort. These results show that the model has a moderate diagnostic ability. The c-index of the nomogram is 0.77 in the TCGA cohort and 0.73 in the GEO cohort. We showed that the risk score is an independent prognostic biomarker and that some RBPs may be potential biomarkers for the diagnosis and prognosis of CRC.

scholarly journals Comprehensive Analysis of N6-Methyladenosine-Related lncRNA Signature for Predicting Prognosis and Immune Cell Infiltration in Patients with Colorectal Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Zhan Zhao ◽  
Ya-bing Yang ◽  
Xin-yuan Li ◽  
Xu-Guang Li ◽  
Xiao-dong Chu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
Critical Role ◽  
R Package ◽  
Low Risk ◽  
Functional Enrichment ◽  
The Relationship

Background. Colorectal cancer (CRC) is the third most common tumor worldwide. Aberrant N6-methyladenosine (m6A) modification can influence the progress of the CRC. Additionally, long noncoding RNA (lncRNA) plays a critical role in CRC and has a close relationship with m6A modification. However, the prognostic potential of m6A-related lncRNAs in CRC patients still remains to be clarified. Methods. We use “limma” R package, “glmnet” R package, and “survival” R package to screen m6A-related-lncRNAs with prognostic potential. Then, we comprehensively analysed and integrated the related lncRNAs in different TNM stages from TCGA database using the LASSO Cox regression. Meanwhile, the relationship between functional enrichment of m6A-related lncRNAs and immune microenvironment in CRC was also investigated using the TCGA database. A prognostic model was constructed and validated to determine the association between m6A-related lncRNAs in different TNM stages and the prognosis of CRC. Result. We demonstrated that three related m6A lncRNAs in different TNM stages were associated with the prognosis of CRC patients. Patients from the TCGA database were classified into the low-risk and the high-risk groups based on the expression of these lncRNAs. The patients in the low-risk group had longer overall survival than the patients in the high-risk group ( P < 0.001 ). We further constructed and validated a prognostic nomogram based on these genes with a C-index of 0.80. The receiver operating characteristic curves confirmed the predictive capacity of the model. Meanwhile, we also found that the low-risk group has the correlation with the dendritic cell (DC). Finally, we discovered the relationship between the m6A regulators and the three lncRNAs. Conclusion. The prognostic model based on three m6A-related lncRNAs exhibits superior predictive performance, providing a novel prognostic model for the clinical evaluation of CRC patients.

scholarly journals CARD11 is a prognostic biomarker and correlated with immune infiltrates in uveal melanoma

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255293
Author(s):  
Xueying Shi ◽  
Shilin Xia ◽  
Yingming Chu ◽  
Nan Yang ◽  
Jingyuan Zheng ◽  
...  
Keyword(s):  
Uveal Melanoma ◽  
T Cell Activation ◽  
Cell Activation ◽  
Sequence Data ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Cerna Network ◽  
Potential Biomarker

Uveal melanoma (UVM), the most common primary intraocular malignancy, has a high mortality because of a high propensity to metastasize. Our study analyzed prognostic value and immune-related characteristics of CARD11 in UVM, hoping to provide a potential management and research direction. The RNA-sequence data of 80 UVM patients were downloaded from The Cancer Genome Atlas database and divided them into high- and low-expression groups. We analyzed the differentially expressed genes, enrichment analyses and the infiltration of immune cells using the R package and Gene-Set Enrichment Analysis. A clinical prediction nomogram and protein-protein interaction network were constructed and the first 8 genes were considered as the hub-genes. Finally, we constructed a competing endogenous RNA (ceRNA) network by Cytoscape and analyzed the statistical data via the R software. Here we found that CARD11 expression had notable correlation with UVM clinicopathological features, which was also an independent predictor for overall survival (OS). Intriguingly, CARD11 had a positively correlation to autophagy, cellular senescence and apoptosis. Infiltration of monocytes was significantly higher in low CARD11 expression group, and infiltration of T cells regulatory was lower in the same group. Functional enrichment analyses revealed that CARD11 was positively related to T cell activation pathways and cell adhesion molecules. The expressions of hub-genes were all increased in the high CARD11 expression group and the ceRNA network showed the interaction among mRNA, miRNA and lncRNA. These findings show that high CARD11 expression in UVM is associated with poor OS, indicating that CARD11 may serve as a potential biomarker for the diagnosis and prognosis of the UVM.

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