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Identifying reproducible cancer-associated highly expressed genes with important functional significances using
Haiyan Huang1, Xiangyu Li1, You Guo1,2
1Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, 350108.
Scientific Reports
|November 1, 2016
Summary
The pairwise difference (PD) algorithm identifies highly expressed differentially expressed (DE) genes missed by standard methods. This new approach enhances cancer gene expression analysis by revealing crucial genes in oncogenesis.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Biology
Background:
- Identifying differentially expressed (DE) genes between cancer and normal tissues is crucial for understanding cancer mechanisms.
- Existing methods like Significance Analysis of Microarrays (SAM) exhibit bias towards genes with low expression levels.
Purpose of the Study:
- To extend the pairwise difference (PD) algorithm for identifying DE genes between different tissue types (biological replicates).
- To evaluate the performance of the PD algorithm in detecting highly expressed DE genes often overlooked by conventional methods.
Main Methods:
- The pairwise difference (PD) algorithm was adapted to analyze multiple independent datasets of lung and esophageal cancers.
- Multiple paired average gene expression profiles were constructed for cancer versus normal tissue samples.
- The PD algorithm's performance was compared against the Significance Analysis of Microarrays (SAM) method.
Main Results:
- The PD algorithm successfully identified numerous highly expressed DE genes in both cancer and normal tissues that were missed by SAM.
- These identified genes included many housekeeping genes.
- Enrichment analysis revealed that these DE genes were significantly associated with conserved pathways like ribosome, proteasome, phagosome, and TNF signaling.
Conclusions:
- The extended PD algorithm is effective in identifying highly expressed DE genes between tissue types, overcoming limitations of existing methods.
- The identified DE genes, including housekeeping genes, play significant roles in oncogenesis and are enriched in critical cellular pathways.
- This approach offers a valuable tool for cancer research, particularly for uncovering genes involved in fundamental cellular processes relevant to cancer development.
