Gene expression analysis in colorectal cancer using practical DNA array filter

2001 ◽  
Vol 44 (2) ◽  
pp. 295-299 ◽  
Author(s):  
Kiyotaka Okuno ◽  
Masayuki Yasutomi ◽  
Norihiro Nishimura ◽  
Taku Arakawa ◽  
Mikio Shiomi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Dna Array

Gene Expression Analysis with DNA Array Technology in Legumes

2008 ◽  
pp. 467-476
Author(s):  
Tohru Tsuchiya ◽  
Hirokazu Hakozaki ◽  
Hiromi Masuko ◽  
Masao Watanabe ◽  
Jong-In Park ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Dna Array ◽  
Array Technology

scholarly journals Gene Expression Analysis of Peripheral Blood Cells Reveals Toll-Like Receptor Pathway Deregulation in Colorectal Cancer

PLoS ONE ◽  
2013 ◽  
Vol 8 (5) ◽  
pp. e62870 ◽  
Author(s):  
Ye Xu ◽  
Qinghua Xu ◽  
Li Yang ◽  
Fang Liu ◽  
Xun Ye ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Expression Analysis ◽  
Peripheral Blood ◽  
Blood Cells ◽  
Gene Expression Analysis ◽  
Peripheral Blood Cells ◽  
Toll Like Receptor ◽  
Pathway Deregulation

Glycolysis gene expression analysis and selective metabolic advantage in the clinical progression of colorectal cancer

2016 ◽  
Vol 17 (3) ◽  
pp. 258-264 ◽  
Author(s):  
F Graziano ◽  
A Ruzzo ◽  
E Giacomini ◽  
T Ricciardi ◽  
G Aprile ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Clinical Progression ◽  
Metabolic Advantage ◽  
Glycolysis Gene

scholarly journals ETV4 plays a role on the primary events during the adenoma-adenocarcinoma progression in colorectal cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Aline Simoneti Fonseca ◽  
Anelisa Ramão ◽  
Matheus Carvalho Bürger ◽  
Jorge Estefano Santana de Souza ◽  
Dalila Lucíola Zanette ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Dna Sequencing ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Epithelial Mesenchymal Transition ◽  
Sequencing Analysis ◽  
Microarray Gene Expression ◽  
Mesenchymal Transition ◽  
Paired Samples

Abstract Background Colorectal cancer (CRC) is one of the most common cancers worldwide; it is the fourth leading cause of death in the world and the third in Brazil. Mutations in the APC, DCC, KRAS and TP53 genes have been associated with the progression of sporadic CRC, occurring at defined pathological stages of the tumor progression and consequently modulating several genes in the corresponding signaling pathways. Therefore, the identification of gene signatures that occur at each stage during the CRC progression is critical and can present an impact on the diagnosis and prognosis of the patient. In this study, our main goal was to determine these signatures, by evaluating the gene expression of paired colorectal adenoma and adenocarcinoma samples to identify novel genetic markers in association to the adenoma-adenocarcinoma stage transition. Methods Ten paired adenoma and adenocarcinoma colorectal samples were subjected to microarray gene expression analysis. In addition, mutations in APC, KRAS and TP53 genes were investigated by DNA sequencing in paired samples of adenoma, adenocarcinoma, normal tissue, and peripheral blood from ten patients. Results Gene expression analysis revealed a signature of 689 differentially expressed genes (DEG) (fold-change> 2, p< 0.05), between the adenoma and adenocarcinoma paired samples analyzed. Gene pathway analysis using the 689 DEG identified important cancer pathways such as remodeling of the extracellular matrix and epithelial-mesenchymal transition. Among these DEG, the ETV4 stood out as one of the most expressed in the adenocarcinoma samples, further confirmed in the adenocarcinoma set of samples from the TCGA database. Subsequent in vitro siRNA assays against ETV4 resulted in the decrease of cell proliferation, colony formation and cell migration in the HT29 and SW480 colorectal cell lines. DNA sequencing analysis revealed KRAS and TP53 gene pathogenic mutations, exclusively in the adenocarcinomas samples. Conclusion Our study identified a set of genes with high potential to be used as biomarkers in CRC, with a special emphasis on the ETV4 gene, which demonstrated involvement in proliferation and migration.

scholarly journals Gene-expression analysis of a colorectal cancer-specific discriminatory transcript set on formalin-fixed, paraffin-embedded (FFPE) tissue samples

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Alexandra Kalmár ◽  
Barnabás Wichmann ◽  
Orsolya Galamb ◽  
Sándor Spisák ◽  
Kinga Tóth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Ffpe Tissue ◽  
Tissue Samples ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Formalin Fixed

scholarly journals Prediction of Metastasis and Recurrence in Colorectal Cancer Based on Gene Expression Analysis: Ready for the Clinic?

Cancers ◽  
2011 ◽  
Vol 3 (3) ◽  
pp. 2858-2869 ◽  
Author(s):  
Masaki Shibayama ◽  
Matthias Maak ◽  
Ulrich Nitsche ◽  
Kengo Gotoh ◽  
Robert Rosenberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Prediction Of Metastasis

scholarly journals Mechanisms Associated With Acquisition Of Resistance To Butyrate-induced Apoptosis In Colorectal Cancer Cells Using Gene Expression Analysis

2014 ◽  
Vol 1 (4) ◽  
pp. 16-30
Author(s):  
Kim YC Fung ◽  
Caroline Kerr ◽  
Steven Henderson ◽  
Ilka Priebe ◽  
Jan Shaw ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Cancer Cells ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Colorectal Cancer Cells ◽  
Induced Apoptosis

scholarly journals Clinical Omics Analysis of Colorectal Cancer Incorporating Copy Number Aberrations and Gene Expression Data

2010 ◽  
Vol 9 ◽  
pp. CIN.S3851 ◽  
Author(s):  
Tsuyoshi Yoshida ◽  
Takumi Kobayashi ◽  
Masaya Itoda ◽  
Taika Muto ◽  
Ken Miyaguchi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Gene Expression Data ◽  
Expression Analysis ◽  
Copy Number ◽  
Gene Expression Analysis ◽  
Cancer Drug ◽  
Expression Data ◽  
New Genes ◽  
Wide Range

Background Colorectal cancer (CRC) is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC) and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an “omics” study by integrating many kinds of analysis into a single comprehensive investigation. In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers. Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC. This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC. Materials and methods Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language. Result We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene expression analysis, together with the clinical information, suggested UGT2B28, LOC440995, CXCL6, SULT1B1, RALBP1, TYMS, RAB12, RNMT, ARHGDIB, S1000A2, ABHD2, OIT3 and ABHD12 as genes that are possibly associated with CRC. Some of these genes have already been reported as being related to CRC. TYMS has been reported as being associated with resistance to the anti-cancer drug 5-fluorouracil, and we observed a copy number increase for this gene. RALBP1, ARHGDIB and S100A2 have been reported as oncogenes, and we observed copy number increases in each. ARHGDIB has been reported as a metastasis-related gene, and our data also showed copy number increases of this gene in cases with metastasis. Conclusion The combination of CNA analysis and gene expression analysis was a more effective method for finding genes associated with the clinicopathological classification of CRC than either analysis alone. Using this combination of methods, we were able to detect genes that have already been associated with CRC. We also identified additional candidate genes that may be new markers or targets for this form of cancer.

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