Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors

W. Ma, T.-F. Zhang, P. Lu, S.H. Lu

Oncology Department, the First Affiliated Hospital of Zhengzhou University, China. shihsin_l@126.com

---

• Oncology

BACKGROUND: Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients.

MATERIALS AND METHODS: With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis.

RESULTS: We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1.

CONCLUSIONS: Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.

Free PDF Download