Gene expression analysis of invasive breast carcinoma yields differential patterns in luminal subtypes of breast cancer.

Breast cancer is a heterogeneous disease, and new biomarkers are needed for more accurate classification and prediction of prognosis. The goal of this study is to assess the expression of breast cancer classification genes, to identify new molecular signatures in different intrinsic subtypes of breast cancer and to correlate their expression with different clinical variables. The study included 84 female patients newly diagnosed with non-metastatic breast cancer at the outpatient clinic at the National Cancer Institute, Cairo University, Egypt. Detection of 17 breast cancer classification genes was done using RT-PCR in tumor and normal tissues. Estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 expression were assessed using IHC assay for intrinsic subtyping. Combined expression of FOXA1 and GATA3 was statistically higher in luminal subtypes in comparison to non-luminal subtypes. In Luminal A subtype; GRB7, EGFR, PTGS2, ID1, and KRT5 were significantly downregulated. FOXA1 and GATA3 were significantly upregulated in luminal B subtype, where EGFR and PTGS2 were significantly downregulated. While ESR1, EGFR, KRT5 and PTGS2 showed significantly low expression in tumor tissue in Her2 enriched subtype, TFF3 was significantly downregulated in triple negative subtype. GATA3 and FOXA1 expression exhibited significant correlation with tumor grade. Furthermore, GATA3, FOXA1, ESR1, and ID1 were also correlated significantly with staging of the tumor. Combined expression of ESR1, FOXA1 and GATA3 represents a molecular signature of luminal subtypes. Long term follow-up is needed to investigate the prognostic effect of breast cancer classification genes found in this study.

Effect of seasonal variation in ambient temperature on RNA quality of breast cancer tissue in a remote biobank setting.

Studies involving oncology especially diagnosis, prognosis and therapeutic monitoring are increasingly relying on molecular analyses. These analyses require high quality biomolecules to get accurate and precise results and this requires among others, monitoring for pre-analytical variables. The purpose of our study was to validate the SOPs of the newly established Egyptian National Cancer Institute (ENCI) biobank. We used a panel of 91 fresh frozen breast cancer tissue samples and their matched normal tissues and have investigated the overall quality (integrity and yield) of RNA extracted from fresh frozen breast tumor tissues and matched normal breast tissues. We investigated the effect of several factors including seasonal temperature variation, cold ischemia time, transportation method, and RNA extraction method. The RNA yield and quality were significantly increased with tumor samples collected in winter, transported on wet ice and using an automated RNA extraction platform. No significant effect was observed due to increased cold ischemia time >30 min. The effect of delay in time to cryopreservation on RNA degradation in fresh tissue samples may vary according to the type of tissue, temperature during tissue collection and transportation, and the use of stabilizing agents as RNA later.