scholarly journals Comparative and multimodal analysis of the EGFR, HER2, c-MYC, and MET copy number alteration using in situ hybridization in Korean colorectal cancer patients with integration of array-based copy number data from The Cancer Genome Atlas

2017 ◽  
Vol 28 ◽  
pp. v187
Author(s):  
Y. Kwak ◽  
S. Yun ◽  
S.K. Nam ◽  
A.N. Seo ◽  
K.S. Lee ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Copy Number ◽  
Copy Number Alteration ◽  
The Cancer Genome Atlas ◽  
Copy Number Data ◽  
Multimodal Analysis ◽  
Cancer Genome Atlas ◽  
Colorectal Cancer Patients ◽  
Genome Atlas

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 CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression

2019 ◽  
Author(s):  
Quanhua Mu ◽  
Jiguang Wang
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Copy Number ◽  
Copy Number Alteration ◽  
The Cancer Genome Atlas ◽  
Detection Methods ◽  
Dna Arrays ◽  
Machine Learning Model ◽  
Cancer Genome Atlas ◽  
Genomic Regions

AbstractCopy number alteration (CNA), the abnormal number of copies of genomic regions, plays a key role in cancer initiation and progression. Current high-throughput CNA detection methods, including DNA arrays and genomic sequencing, are relatively expensive and require DNA samples at a microgram level, which are not achievable in certain occasions such as clinical biopsies or single-cell genomes. Here we proposed an alternative method—CNAPE to computationally infer CNA using gene expression data. A prior knowledge-aided machine learning model was proposed, trained and tested on the transcriptomic profiles with matched CNA data of 9,740 cancers from The Cancer Genome Atlas. Using brain tumors as a proof-of-concept study, CNAPE achieved over 90% accuracy in the prediction of arm-level CNAs. Prediction performance for 12 gene-level CNAs (commonly altered genes in glioma) was also evaluated, and CNAPE achieved reasonable accuracy. CNAPE is developed as an easy-to-use tool at http://wang-lab.ust.hk/software/Software.html.

scholarly journals A Timely Update of Immunohistochemistry and Molecular Classification in the Diagnosis and Risk Assessment of Endometrial Carcinomas

2021 ◽  
Vol 145 (11) ◽  
pp. 1367-1378
Author(s):  
Minhua Wang ◽  
Pei Hui
Keyword(s):  
Copy Number ◽  
Treatment Strategies ◽  
The United States ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Molecular Profile ◽  
Cancer Genome Atlas ◽  
Endometrial Carcinomas ◽  
Genome Atlas

Context.— Endometrial carcinoma is the most common gynecologic malignancy in the United States and has been traditionally classified based on histology. However, the distinction of certain histologic subtypes based on morphology is not uncommonly problematic, and as such, immunohistochemical study is often needed. Advances in comprehensive tumor sequencing have provided novel molecular profiles of endometrial carcinomas. Four distinct molecular subtypes with different prognostic values have been proposed by The Cancer Genome Atlas program: polymerase epsilon ultramutated, microsatellite instability hypermutated, copy number low (microsatellite stable or no specific molecular profile), and copy number high (serouslike, p53 mutant). Objective.— To discuss the utilities of commonly used immunohistochemical markers for the classification of endometrial carcinomas and to review the recent advancements of The Cancer Genome Atlas molecular reclassification and their potential impact on treatment strategies. Data Sources.— Literature review and authors' personal practice experience. Conclusions.— The current practice of classifying endometrial cancers is predominantly based on morphology. The use of ancillary testing, including immunohistochemistry, is helpful in the identification, differential diagnosis, and classification of these cancers. New developments such as molecular subtyping have provided insightful prognostic values for endometrial carcinomas. The proposed The Cancer Genome Atlas classification is poised to gain further prominence in guiding the prognostic evaluation for tailored treatment strategies in the near future.

Analysis of TGCA data reveals genetic and epigenetic changes and biological function of MUC family genes in colorectal cancer

2019 ◽  
Vol 15 (35) ◽  
pp. 4031-4043 ◽  
Author(s):  
Zhipeng Jiang ◽  
Huashe Wang ◽  
Liang Li ◽  
Zehui Hou ◽  
Wei Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Copy Number Variation ◽  
Copy Number ◽  
Regulatory Networks ◽  
The Cancer Genome Atlas ◽  
Epigenetic Changes ◽  
Copy Number Variation Analysis ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Drug Influence

Aim: Few studies focused on functions and regulatory networks of MUC family members in colorectal cancer based on comprehensive analysis of online database. Materials & methods: Copy number variation, methylation, pathway analysis and drug influence on MUC expression were analyzed based on The Cancer Genome Atlas and GTEx database. Results: Copy number variation analysis showed MUC heterozygous amplification and heterozygous deletion predominate. Methylation of MUC17, MUC12 and MUC4 were found related to gene expression. Function of MUC family genes mainly affects pathways such as apoptosis, cell cycle, DNA damage and EMT pathways. PLX4720, dabrafenib, gefitinib, afatinib and austocystin D can alter the expression of MUC gene. Conclusion: The genetic and epigenetic changes of MUC are related to the level of MUC expression in colorectal cancer.

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 Molecular and phenotypic profiling of colorectal cancer patients in West Africa reveals biological insights

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Olusegun Isaac Alatise ◽  
Gregory C. Knapp ◽  
Avinash Sharma ◽  
Walid K. Chatila ◽  
Olukayode A. Arowolo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
West Africa ◽  
The Cancer Genome Atlas ◽  
Cancer Center ◽  
Rectal Disease ◽  
Ras Pathway ◽  
Phenotypic Profile ◽  
Cancer Genome Atlas ◽  
Colorectal Cancer Patients ◽  
Generation Sequencing

AbstractUnderstanding the molecular and phenotypic profile of colorectal cancer (CRC) in West Africa is vital to addressing the regions rising burden of disease. Tissue from unselected Nigerian patients was analyzed with a multigene, next-generation sequencing assay. The rate of microsatellite instability is significantly higher among Nigerian CRC patients (28.1%) than patients from The Cancer Genome Atlas (TCGA, 14.2%) and Memorial Sloan Kettering Cancer Center (MSKCC, 8.5%, P < 0.001). In microsatellite-stable cases, tumors from Nigerian patients are less likely to have APC mutations (39.1% vs. 76.0% MSKCC P < 0.001) and WNT pathway alterations (47.8% vs. 81.9% MSKCC, P < 0.001); whereas RAS pathway alteration is more prevalent (76.1% vs. 59.6%, P = 0.03). Nigerian CRC patients are also younger and more likely to present with rectal disease (50.8% vs. 33.7% MSKCC, P < 0.001). The findings suggest a unique biology of CRC in Nigeria, which emphasizes the need for regional data to guide diagnostic and treatment approaches for patients in West Africa.

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 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.

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