Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis
- Haiyan Gao
- Mei Yang
- Xiaolan Zhang
Published online on: February 2, 2018
Copyright: © Gao et al.
This is an open access article distributed under the terms of Creative Commons Attribution License.
The present study aimed to investigate potential recurrence‑risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18‑gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18‑gene prognostic assay including the key genes, transcription factor 7‑like 2, anterior parietal cortex and lymphocyte enhancer factor‑1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.