scholarly journals ECM–Receptor Regulatory Network and Its Prognostic Role in Colorectal Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Stepan Nersisyan ◽  
Victor Novosad ◽  
Narek Engibaryan ◽  
Yuri Ushkaryov ◽  
Sergey Nikulin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regulatory Network ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction ◽  
Survival Prediction ◽  
Concordance Index ◽  
Logrank Test ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Interactions of the extracellular matrix (ECM) and cellular receptors constitute one of the crucial pathways involved in colorectal cancer progression and metastasis. With the use of bioinformatics analysis, we comprehensively evaluated the prognostic information concentrated in the genes from this pathway. First, we constructed a ECM–receptor regulatory network by integrating the transcription factor (TF) and 5’-isomiR interaction databases with mRNA/miRNA-seq data from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD). Notably, one-third of interactions mediated by 5’-isomiRs was represented by noncanonical isomiRs (isomiRs, whose 5’-end sequence did not match with the canonical miRBase version). Then, exhaustive search-based feature selection was used to fit prognostic signatures composed of nodes from the network for overall survival prediction. Two reliable prognostic signatures were identified and validated on the independent The Cancer Genome Atlas Rectum Adenocarcinoma (TCGA-READ) cohort. The first signature was made up by six genes, directly involved in ECM–receptor interaction: AGRN, DAG1, FN1, ITGA5, THBS3, and TNC (concordance index 0.61, logrank test p = 0.0164, 3-years ROC AUC = 0.68). The second hybrid signature was composed of three regulators: hsa-miR-32-5p, NR1H2, and SNAI1 (concordance index 0.64, logrank test p = 0.0229, 3-years ROC AUC = 0.71). While hsa-miR-32-5p exclusively regulated ECM-related genes (COL1A2 and ITGA5), NR1H2 and SNAI1 also targeted other pathways (adhesion, cell cycle, and cell division). Concordant distributions of the respective risk scores across four stages of colorectal cancer and adjacent normal mucosa additionally confirmed reliability of the models.

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 Using The Cancer Genome Atlas data to refine the 8th edition of the American Joint Committee on Cancer staging for papillary thyroid carcinoma

Endocrine ◽  
2020 ◽  
Author(s):  
Anello Marcello Poma ◽  
Elisabetta Macerola ◽  
Liborio Torregrossa ◽  
Rossella Elisei ◽  
Ferruccio Santini ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Molecular Features ◽  
American Joint Committee ◽  
Cancer Genome Atlas ◽  
Ajcc Staging ◽  
8Th Edition ◽  
Genome Atlas

Abstract Purpose The 8th edition of the American Joint Committee on Cancer (AJCC) staging led to a significant downstaging of well differentiated thyroid cancer patients. However, some patients who had been downstaged still experienced death. By using data from the thyroid cancer dataset of The Cancer Genome Atlas (TCGA), we aimed to find molecular features that could improve survival prediction. Methods TCGA data were downloaded from cBioPortal. Restaging of cases was performed according to the pathological reports. Results Out of 496 cases, 204 (41.1%) were downstaged, and the proportion of deaths increased in stages III and IV. TERT promoter mutations were no longer enriched in stage IV only, but significantly redistributed also in stages II and III. TERT mutation was the only alteration predictive of poor survival; however, in this series it was not independent from the AJCC staging. Five proteins (4E-BP1_pT70, Chk1_pS345, Snail, STAT5 alpha and PAI-1) were significantly associated with survival, and their use as a panel refined the risk stratification independently from the AJCC staging, with a hazard ratio for a positive result of 21.2 (95%CI 3.7–122.2, P = 0.0006). Conclusions In the TCGA series, the proportion of deaths is in line with the expected survival of the latest AJCC staging, with a neat separation of risk among stages. Nevertheless, the use of protein expression can be useful in refining the stratification. Finally, after the restaging, a considerable number of tumors with TERT mutations will be allocated in lower stages; hence, dedicated studies should define the prognostic usefulness of these mutations in low-stage diseases.

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.

scholarly journals Association Between Obesity and Incident Colorectal Cancer: An Analysis Based on Colorectal Cancer Database in the Cancer Genome Atlas

2021 ◽  
Author(s):  
Su Yongxian ◽  
Chen Tonghua
Keyword(s):  
Colorectal Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Obese Group ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Significant Difference ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Background To investigate gene factors of colorectal cancer (CRC) in obesity and potential molecular markers. Methods Clinical data and mRNA expression data from The Cancer Genome Atlas (TCGA) was collected and divided into obese group and non-obese group according to BMI. The differential expressed genes (DEGs) were screened out by “Limma” package of R software based on (|log2(fold change)|>2 and p < 0.05). The functions of DEGs were revealed with Gene Ontology and Kyoto Encyclopedia Genes and Genomes pathway enrichment analysis using the DAVID database. Then STRING database and Cytoscape were used to construct a protein-protein interaction (PPI) network and identify hub genes. Kaplan-Meier analysis was used to assess the potential prognostic genes for CRC patients. Results It has revealed 2055 DEGs in obese group with CRC, 7615 DEGs in non-obese group and 9046 DEGs in total group. MS4A12, TMIGD1, CA2, GBA3 and SLC51B were the top five downregulated genes in obese group. A PPI network consisted of 1042 nodes and 4073 edges, and top ten hub genes SST, PYY, GNG12, CCL13, MCHR2, CCL28, ADCY9, SSTR1, CXCL12 and ADRA2A were identified in obese group. PDCD11 may well predict overall survivals of CRC patients in non-obese group. The survival time of obese group was shorter than that of non-obese group, but there was no significant difference. Conclusions PDCD11 may be a potential molecular marker for non-obese patients with CRC.

scholarly journals The construction and analysis of ceRNA networks in invasive breast cancer: a study based on The Cancer Genome Atlas

2018 ◽  
Vol Volume 11 ◽  
pp. 1-11 ◽  
Author(s):  
Chundi Gao ◽  
Huayao Li ◽  
Jing Zhuang ◽  
HongXiu Zhang ◽  
Kejia Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Invasive Breast Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas
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