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Web-based data warehouse on gene expression in human colorectal cancer
Emil Sagynaliev1, Ralf Steinert, Gerd Nestler
1Department of Surgery, Johanniter Krankenhaus, Stendal, Germany.
Proteomics
|July 26, 2005
Summary
Building a gene expression data warehouse for human colorectal cancer (CRC) revealed low reproducibility. Standardized data processes are crucial for advancing translational research in CRC.
Area of Science:
- Genomics
- Proteomics
- Bioinformatics
Background:
- Human colorectal cancer (CRC) gene expression data is fragmented across numerous studies using diverse technologies.
- Existing research lacks standardized data collection and analysis, hindering comprehensive understanding.
Purpose of the Study:
- To construct a preliminary gene expression data warehouse for human CRC.
- To assess the reproducibility of gene and protein expression findings in CRC.
Main Methods:
- Systematic review of published genome-wide transcriptomic and proteomic studies in human CRC.
- Data compilation from 12 transcriptomic and 8 proteomic studies.
- Analysis of gene and protein overlap and differential expression across studies.
Main Results:
- Low overlap was observed for differentially expressed genes (88% unique to one study) and proteins (83% unique to one study).
- Cross-platform confirmation rates were 25% from transcriptomics to proteomics and 67% from proteomics to transcriptomics.
- Significant discrepancies in findings highlight challenges in data integration.
Conclusions:
- Reproducibility of gene and protein expression data in human CRC is critically low.
- Standardized protocols for sample handling, data storage, and querying are essential for effective translational research in CRC.