scholarly journals Identification of intestinal flora-related key genes and therapeutic drugs in colorectal cancer

2020 ◽  
Author(s):  
Jiayu Zhang ◽  
Huaiyu Zhang ◽  
Faping Li ◽  
Zheyu Song ◽  
Yezhou Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Intestinal Flora ◽  
Interaction Network ◽  
Gene Interaction ◽  
The Cancer Genome Atlas ◽  
Interaction Database ◽  
Therapeutic Drugs ◽  
Cancer Genome Atlas ◽  
Key Genes ◽  
Genome Atlas

Abstract Background: Colorectal cancer (CRC) is a multifactorial tumor and a leading cause of cancer-specific deaths worldwide. Recent research has shown that the alteration of intestinal flora contributes to the development of CRC. However, the molecular mechanism by which intestinal flora influences the pathogenesis of CRC remains unclear. This study aims to explore the key genes underlying the effect of intestinal flora on CRC and therapeutic drugs for CRC.Methods: Intestinal flora-related genes were determined using text mining. Based on The Cancer Genome Atlas database, differentially expressed genes (DEGs) between CRC and normal samples were identified with the limma package of the R software. Then, the intersection of the two gene sets was selected for enrichment analyses using the tool Database for Annotation, Visualization and Integrated Discovery. Protein interaction network analysis was performed for identifying the key genes using STRING and Cytoscape. The correlation of the key genes with overall survival of CRC patients was analyzed. Finally, the key genes were queried against the Drug-Gene Interaction database to find drug candidates for treating CRC.Results: 518 genes associated with intestinal flora were determined by text mining. Based on The Cancer Genome Atlas database, we identified 48 DEGs associated with intestinal flora, including 25 up-regulated and 23 down-regulated DEGs in CRC. The enrichment analyses indicated that the selected genes were mainly involved in cell-cell signaling, immune response, cytokine-cytokine receptor interaction, and JAK-STAT signaling pathway. The protein-protein interaction network was constructed with 13 nodes and 35 edges. Moreover, 8 genes in the significant cluster were considered as the key genes and chemokine (C-X-C motif) ligand 8 (CXCL8) correlated positively with the overall survival of CRC patients. Finally, a total of 24 drugs were predicted as possible drugs for CRC treatment using the Drug-Gene Interaction database.Conclusions: These findings of this study may provide new insights into CRC pathogenesis and treatments. The prediction of drug-gene interaction is of great practical significance for exploring new drugs or novel targets for existing drugs.

scholarly journals Identification of intestinal flora-related key genes and therapeutic drugs in colorectal cancer

2020 ◽  
Author(s):  
Jiayu Zhang ◽  
Huaiyu Zhang ◽  
Faping Li ◽  
Zheyu Song ◽  
Yezhou Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Intestinal Flora ◽  
Interaction Network ◽  
Gene Interaction ◽  
The Cancer Genome Atlas ◽  
Interaction Database ◽  
Therapeutic Drugs ◽  
Cancer Genome Atlas ◽  
Key Genes ◽  
Genome Atlas

Abstract Background: Colorectal cancer (CRC) is a multifactorial tumor and a leading cause of cancer-specific deaths worldwide. Recent research has shown that the alteration of intestinal flora contributes to the development of CRC. However, the molecular mechanism by which intestinal flora influences the pathogenesis of CRC remains unclear. This study aims to explore the key genes underlying the effect of intestinal flora on CRC and therapeutic drugs for CRC.Methods: Intestinal flora-related genes were determined using text mining. Based on The Cancer Genome Atlas database, differentially expressed genes (DEGs) between CRC and normal samples were identified with the limma package of the R software. Then, the intersection of the two gene sets was selected for enrichment analyses using the tool Database for Annotation, Visualization and Integrated Discovery. Protein interaction network analysis was performed for identifying the key genes using STRING and Cytoscape. The correlation of the key genes with overall survival of CRC patients was analyzed. Finally, the key genes were queried against the Drug-Gene Interaction database to find drug candidates for treating CRC.Results: 518 genes associated with intestinal flora were determined by text mining. Based on The Cancer Genome Atlas database, we identified 48 DEGs associated with intestinal flora, including 25 up-regulated and 23 down-regulated DEGs in CRC. The enrichment analyses indicated that the selected genes were mainly involved in cell-cell signaling, immune response, cytokine-cytokine receptor interaction, and JAK-STAT signaling pathway. The protein-protein interaction network was constructed with 13 nodes and 35 edges. Moreover, 8 genes in the significant cluster were considered as the key genes and chemokine (C-X-C motif) ligand 8 (CXCL8) correlated positively with the overall survival of CRC patients. Finally, a total of 24 drugs were predicted as possible drugs for CRC treatment using the Drug-Gene Interaction database.Conclusions: These findings of this study may provide new insights into CRC pathogenesis and treatments. The prediction of drug-gene interaction is of great practical significance for exploring new drugs or novel targets for existing drugs.

scholarly journals Identification of intestinal flora-related key genes and therapeutic drugs in colorectal cancer

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Jiayu Zhang ◽  
Huaiyu Zhang ◽  
Faping Li ◽  
Zheyu Song ◽  
Yezhou Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Intestinal Flora ◽  
Interaction Network ◽  
Gene Interaction ◽  
The Cancer Genome Atlas ◽  
Interaction Database ◽  
Therapeutic Drugs ◽  
Cancer Genome Atlas ◽  
Key Genes ◽  
Genome Atlas

Abstract Background Colorectal cancer (CRC) is a multifactorial tumor and a leading cause of cancer-specific deaths worldwide. Recent research has shown that the alteration of intestinal flora contributes to the development of CRC. However, the molecular mechanism by which intestinal flora influences the pathogenesis of CRC remains unclear. This study aims to explore the key genes underlying the effect of intestinal flora on CRC and therapeutic drugs for CRC. Methods Intestinal flora-related genes were determined using text mining. Based on The Cancer Genome Atlas database, differentially expressed genes (DEGs) between CRC and normal samples were identified with the limma package of the R software. Then, the intersection of the two gene sets was selected for enrichment analyses using the tool Database for Annotation, Visualization and Integrated Discovery. Protein interaction network analysis was performed for identifying the key genes using STRING and Cytoscape. The correlation of the key genes with overall survival of CRC patients was analyzed. Finally, the key genes were queried against the Drug-Gene Interaction database to find drug candidates for treating CRC. Results 518 genes associated with intestinal flora were determined by text mining. Based on The Cancer Genome Atlas database, we identified 48 DEGs associated with intestinal flora, including 25 up-regulated and 23 down-regulated DEGs in CRC. The enrichment analyses indicated that the selected genes were mainly involved in cell–cell signaling, immune response, cytokine-cytokine receptor interaction, and JAK-STAT signaling pathway. The protein–protein interaction network was constructed with 13 nodes and 35 edges. Moreover, 8 genes in the significant cluster were considered as the key genes and chemokine (C-X-C motif) ligand 8 (CXCL8) correlated positively with the overall survival of CRC patients. Finally, a total of 24 drugs were predicted as possible drugs for CRC treatment using the Drug-Gene Interaction database. Conclusions These findings of this study may provide new insights into CRC pathogenesis and treatments. The prediction of drug-gene interaction is of great practical significance for exploring new drugs or novel targets for existing drugs.

scholarly journals Identification of Intestinal Flora-Related Key Genes and Therapeutic Drugs in Colorectal Cancer

2020 ◽  
Author(s):  
Jiayu Zhang ◽  
Huaiyu Zhang ◽  
Faping Li ◽  
Zheyu Song ◽  
Yezhou Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Intestinal Flora ◽  
Interaction Network ◽  
Gene Interaction ◽  
New Drugs ◽  
The Cancer Genome Atlas ◽  
Practical Significance ◽  
Receptor Interaction ◽  
Therapeutic Drugs ◽  
Key Genes

Abstract Colorectal cancer (CRC) is a multifactorial tumor and a leading cause of cancer-specific deaths worldwide. Recent research has shown that the alteration of intestinal flora contributes to the development of CRC. However, the molecular mechanism by which intestinal flora influences the pathogenesis of CRC remains unclear. This study aims to explore the key genes underlying the effect of intestinal flora on CRC and therapeutic drugs for CRC. 518 genes associated with intestinal flora were determined by text mining. Based on The Cancer Genome Atlas (TCGA) database, we identified 48 differentially expressed genes (DEGs) associated with intestinal flora, including 25 up-regulated and 23 down-regulated DEGs. The enrichment analyses indicated that the selected genes were mainly involved in cell-cell signaling, immune response, cytokine-cytokine receptor interaction, and JAK-STAT signaling pathway. The protein-protein interaction network was constructed with 13 nodes and 35 edges. Moreover, 8 genes in the significant cluster were considered as the key genes and chemokine (C-X-C motif) ligand 8 (CXCL8) correlated positively with the overall survival of CRC patients. Finally, a total of 24 drugs were predicted as possible drugs for CRC treatment using the Drug-Gene Interaction database. These findings of this study may provide new insights into CRC pathogenesis and treatments. The prediction of drug-gene interaction is of great practical significance for exploring new drugs or novel targets for existing drugs.

scholarly journals Exceptional Chemotherapy Response in Metastatic Colorectal Cancer Associated With Hyper-Indel–Hypermutated Cancer Genome and Comutation of POLD1 and MLH1

2017 ◽  
pp. 1-12
Author(s):  
Manish R. Sharma ◽  
James T. Auman ◽  
Nirali M. Patel ◽  
Juneko E. Grilley-Olson ◽  
Xiaobei Zhao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Somatic Mutation ◽  
Mutation Rate ◽  
Germ Line ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Response To Chemotherapy ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Purpose A 73-year-old woman with metastatic colon cancer experienced a complete response to chemotherapy with dose-intensified irinotecan that has been durable for 5 years. We sequenced her tumor and germ line DNA and looked for similar patterns in publicly available genomic data from patients with colorectal cancer. Patients and Methods Tumor DNA was obtained from a biopsy before therapy, and germ line DNA was obtained from blood. Tumor and germline DNA were sequenced using a commercial panel with approximately 250 genes. Whole-genome amplification and exome sequencing were performed for POLE and POLD1. A POLD1 mutation was confirmed by Sanger sequencing. The somatic mutation and clinical annotation data files from the colon (n = 461) and rectal (n = 171) adenocarcinoma data sets were downloaded from The Cancer Genome Atlas data portal and analyzed for patterns of mutations and clinical outcomes in patients with POLE- and/or POLD1-mutated tumors. Results The pattern of alterations included APC biallelic inactivation and microsatellite instability high (MSI-H) phenotype, with somatic inactivation of MLH1 and hypermutation (estimated mutation rate > 200 per megabase). The extremely high mutation rate led us to investigate additional mechanisms for hypermutation, including loss of function of POLE. POLE was unaltered, but a related gene not typically associated with somatic mutation in colon cancer, POLD1, had a somatic mutation c.2171G>A [p.Gly724Glu]. Additionally, we noted that the high mutation rate was largely composed of dinucleotide deletions. A similar pattern of hypermutation (dinucleotide deletions, POLD1 mutations, MSI-H) was found in tumors from The Cancer Genome Atlas. Conclusion POLD1 mutation with associated MSI-H and hyper-indel–hypermutated cancer genome characterizes a previously unrecognized variant of colon cancer that was found in this patient with an exceptional response to chemotherapy.

scholarly journals Evaluating the Prognostic Value of microRNA-203 in Solid Tumors Based on a Meta-Analysis and the Cancer Genome Atlas (TCGA) Datasets

2017 ◽  
Vol 41 (4) ◽  
pp. 1468-1480 ◽  
Author(s):  
Yingjie Shao ◽  
Wendong Gu ◽  
Zhonghua Ning ◽  
Xing Song ◽  
Honglei Pei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Colorectal Cancer ◽  
Pancreatic Cancer ◽  
Esophageal Cancer ◽  
Solid Tumors ◽  
Prognostic Value ◽  
Meta Analysis ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: It has been reported that miR-203 expression was aberrant in various types of cancers, and it could be used as a prognostic biomarker. Therefore, in this study, we aimed to evaluate the prognostic value of miR-203 expression in solid tumors by using meta-analysis and The Cancer Genome Atlas (TCGA) datasets. Methods: By doing a literature research in PubMed, Embase and the Cochrane Library (last update by December 2016), we were able to identify the studies assessing the prognostic role of miR-203 in various tumors. We then used TCGA datasets to validate the results of meta-analysis. Results:33 studies from 26 articles were qualified and enrolled in this meta-analysis. Pooled analyses showed that higher expression of miR-203 in tissues couldn’t predict poor overall survival (OS) and progression-free survival (PFS) in solid tumors. However, the results of subgroup analyses revealed that the upregulation of tissue miR-203 expression was associated with poor OS in colorectal cancer (hazard ratio (HR)=1.81, 95% confidence intervals (CI) 1.31-2.49; P<0.001), pancreatic cancer (HR=1.19, 95% CI 1.09-1.31; P<0.001) and ovarian cancer (HR=1.85, 95% CI 1.45-2.37; P<0.001); but it had opposite association in liver cancer (HR=0.52, 95% CI 0.28-0.97; P=0.040) and esophageal cancer (HR=0.41, 95% CI 0.25-0.66; P<0.001). Based on TCGA datasets, we found the same results for pancreatic cancer and esophageal cancer, but not for colorectal cancer and liver cancer. Moreover, patients with high circulating miR-203 in blood had significantly poor OS and PFS in colorectal cancer and breast cancer. Conclusion: Our study showed that the prognostic values of tissue miR-203 varied in different tumor types. In addition, the upregulation of circulating miR-203 in blood was associated with poor prognosis in colorectal cancer and breast cancer.

scholarly journals MLH1 Deficiency Down-Regulates TLR4 Expression in Sporadic Colorectal Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Melania Scarpa ◽  
Cesare Ruffolo ◽  
Andromachi Kotsafti ◽  
Fabio Canal ◽  
Francesca Erroi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
The Cancer Genome Atlas ◽  
Sporadic Colorectal Cancer ◽  
Tlr4 Expression ◽  
Mmr Genes ◽  
Favorable Prognosis ◽  
Cancer Genome Atlas ◽  
Myd88 Signaling ◽  
Genome Atlas

Patients with mismatch repair (MMR)-deficient colorectal cancer (CRC) have a more favorable prognosis than patients with tumors with intact MMR. In order to obtain further insights on the reasons for this different outcome, we investigated the interplay between MMR genes and TLR4/MyD88 signaling. The cancer genome atlas (TCGA) databases were selected to predict the differential expression of TLR4 in colon cancer and its correlation with MMR genes. Moreover, the expression of MMR genes and TLR4 was evaluated by immunohistochemistry in 113 CRC samples and a cohort of 63 patients was used to assess TLR4 mRNA expression and MLH1 epigenetic silencing status. In vitro, the effect of MLH1 knockdown on TLR4 expression was quantified by Real Time PCR. TLR4 expression resulted dependent on MMR status and directly correlated to MLH1 expression. In vitro, MLH1 silencing decreased TLR4 expression. These observations may reflect the better prognosis and the chemoresistance of patients with CRC and MMR defects.

scholarly journals CpG-methylation-based risk score predicts progression in colorectal cancer

Epigenomics ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 605-615 ◽  
Author(s):  
Yao Deng ◽  
Hao Wan ◽  
Jianbo Tian ◽  
Xiang Cheng ◽  
Meilin Rao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Score ◽  
Area Under The Curve ◽  
The Cancer Genome Atlas ◽  
Free Interval ◽  
Future Clinical Practice ◽  
Risk Of Progression ◽  
Precision Therapy ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aim: To identify patients with colorectal cancer (CRC) who are at a truly higher risk of progression, which is key for individualized approaches to precision therapy. Materials & methods: We developed a predictor associated with progression-free interval (PFI) using The Cancer Genome Atlas CRC methylation data. Results: The risk score was associated with PFI in the whole cohort (p < 0.001). A nomogram consisting of the risk score and other significant clinical features was generated to predict the 3- and 5-year PFI in the whole set (area under the curve: 0.79 and 0.71, respectively). Conclusion: The risk score based on 23 DNA-methylation sites may serve as the basis for improved prediction of progression in patients with CRC in future clinical practice.

Genome-wide methylation and expression profiling identify methylation-associated genes in colorectal cancer

Epigenomics ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 19-36 ◽  
Author(s):  
Xiaohui Sun ◽  
Diyu Chen ◽  
Ziqi Jin ◽  
Tianhui Chen ◽  
Aifen Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Expression Profiling ◽  
The Cancer Genome Atlas ◽  
Gene Overexpression ◽  
Normal Tissues ◽  
Atlas Data ◽  
Genome Wide ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aim: To identify methylation-associated genes in the carcinogenesis of colorectal cancer (CRC). Materials & methods: Genome-wide patterns of DNA methylation and gene expression in CRC tissues and adjacent normal tissues were determined and further validated in The Cancer Genome Atlas data and Chinese CRC patients, respectively. Gene overexpression and knockdown cells were constructed to investigate their biological roles in CRC. Results: After validations, hypermethylation of eight genes were found to be correlated with their reduced transcription, and hypomethyaltion of three genes were associated with their upregulation. CADM3, CNRIP1, GRHL2, GRIA4, GSTM2 and NRXN1 were associated with the overall survival of CRC patients. CNRIP1 and GSTM2 were mainly responsible for the proliferation in CRC cells. Conclusion: A total of 11 genes may be promising biomarkers for CRC.

Expression of DUSP4 transcript variants as a potential biomarker for colorectal cancer

2020 ◽  
Vol 14 (8) ◽  
pp. 639-650
Author(s):  
Tatiana Varela ◽  
Vincent Laizé ◽  
Natércia Conceição ◽  
Paulo Caldeira ◽  
Ana Marreiros ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Kras Mutations ◽  
Normal Tissues ◽  
Potential Biomarker ◽  
Tumor Stages ◽  
Cancer Genome Atlas ◽  
Poorly Differentiated ◽  
Genome Atlas

Aim: To provide novel data on the expression of DUSP4 transcripts in colorectal cancer (CRC) tissues and to explore their potential as biomarkers. Materials & methods: DUSP4 transcripts expression was determined by quantitative real-time PCR in tissues from 28 CRC patients. Their association with clinicopathological factors and survival analysis was performed. Data from 380 CRC patients available at The Cancer Genome Atlas project were also analyzed. Results: All transcripts were overexpressed in CRC tissues. Variant X1 was the most upregulated and associated with KRAS mutations and poorly differentiated tumor. Overexpression of DUSP4 transcripts could distinguish all tumor stages from normal tissues. Similar results were found in The Cancer Genome Atlas cohort. Conclusion: DUSP4 transcripts have the potential to serve as diagnostic biomarkers for CRC, particularly variant X1.

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