Genomics Inform.  2017 Dec;15(4):156-161. 10.5808/GI.2017.15.4.156.

Classification of Genes Based on Age-Related Differential Expression in Breast Cancer

• Lee G
• Lee M

• KMID: 2404053
• DOI: http://doi.org/10.5808/GI.2017.15.4.156

Abstract

Transcriptome analysis has been widely used to make biomarker panels to diagnose cancers. In breast cancer, the age of the patient has been known to be associated with clinical features. As clinical transcriptome data have accumulated significantly, we classified all human genes based on age-specific differential expression between normal and breast cancer cells using public data. We retrieved the values for gene expression levels in breast cancer and matched normal cells from The Cancer Genome Atlas. We divided genes into two classes by paired t test without considering age in the first classification. We carried out a secondary classification of genes for each class into eight groups, based on the patterns of the p-values, which were calculated for each of the three age groups we defined. Through this two-step classification, gene expression was eventually grouped into 16 classes. We showed that this classification method could be applied to establish a more accurate prediction model to diagnose breast cancer by comparing the performance of prediction models with different combinations of genes. We expect that our scheme of classification could be used for other types of cancer data.

Keyword

biomarkers; breast cancer; differentially expressed genes; gene classification

MeSH Terms

Biomarkers
Breast Neoplasms*
Breast*
Classification*
Gene Expression
Gene Expression Profiling
Genome
Humans
Methods
Transcriptome
Biomarkers