Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Modeling oncogenic signaling in colon tumors by multidirectional analyses of microarray data


ABSTRACT: Background. Most colorectal cancers (CRC) arise in a progression through adenoma to carcinoma phenotypes as a consequence of altered genetic information. Clinical progression of CRC may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence. Methodology/Principal Findings. Studies were performed on normal mucosa, adenoma, and CRC samples obtained during surgery or colonoscopy. Collections of cryostat sections prepared from the tissue samples were evaluated by a pathologist to control the relative cell type content. RNA was isolated from 105 macro- and 40 microdissected specimens. The measurements were done using Affymetrix GeneChip HG-U133plus2, and probe set data were generated using two normalization algorithms: MAS5 and GCRMA with LVS. The data were evaluated using pair-wise comparisons and data decomposition into SVD modes. The method selected for the functional analysis used the Kolmogorov-Smirnov test. Based on a consensus of the results obtained by two tissue handling procedures, two normalization algorithms, and two probe set sorting criteria, we identified six KEGG signaling and metabolic pathways (cell cycle, DNA replication, p53 signaling pathway, purine metabolism, pyrimidine metabolism, and RNA polymerase) that are significantly altered in both macro- and microdissected tumor samples compared to normal colon. On the other hand, pathways altered between benign and malignant tumors were identified only in the macrodissected tissues. Conclusion/Significance. Multidirectional analyses of microarray data allow the identification of essential signaling alterations underlying CRC development. Although the proposed strategy is computationally complex and labor–intensive, it may reduce the number of false results. Gene expression profiles of 40 tissue samples representing distant full-thickness normal colon, normal colon mucosa dissected from tumor, adenoma, and carcinoma. Gene expression profiles of 105 tissue samples representing colon carcinomas, adenocarcinomas, and normal colon samples.

ORGANISM(S): Homo sapiens

SUBMITTER: Krzysztof Goryca 

PROVIDER: E-GEOD-20916 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

altmetric image

Publications

Modeling oncogenic signaling in colon tumors by multidirectional analyses of microarray data directed for maximization of analytical reliability.

Skrzypczak Magdalena M   Goryca Krzysztof K   Rubel Tymon T   Paziewska Agnieszka A   Mikula Michal M   Jarosz Dorota D   Pachlewski Jacek J   Oledzki Janusz J   Ostrowski Jerzy J  

PloS one 20101001 10


<h4>Background</h4>Clinical progression of colorectal cancers (CRC) may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence.<h4>Methodology/principal findings</h4>Studies were performed on normal mucosa, adenoma, and carcinoma samples obtained during surgery or colonosc  ...[more]

Similar Datasets

2014-06-19 | E-GEOD-49479 | biostudies-arrayexpress
2019-02-28 | PXD012650 | Pride
2010-08-01 | GSE20916 | GEO
2019-12-31 | GSE132804 | GEO
2019-02-11 | GSE125472 | GEO
2019-02-11 | GSE125578 | GEO
2020-09-28 | GSE104364 | GEO
2013-04-19 | E-GEOD-46200 | biostudies-arrayexpress
2016-09-08 | E-GEOD-72820 | biostudies-arrayexpress
2014-05-20 | GSE56896 | GEO