Prognostic impact of multidrug resistance gene expression on the management of breast cancer in the context of adjuvant therapy based on a series of 171 patients

Study of the prognostic impact of multidrug resistance gene expression in the management of breast cancer in the context of adjuvant therapy. This study involved 171 patients treated by surgery, adjuvant chemotherapy±radiotherapy±hormonal therapy (mean follow-up: 55 months). We studied the expression of multidrug resistance gene 1 (MDR1), multidrug resistance-associated protein (MRP1), and glutathione-S-transferase P1 (GSTP1) using a standardised, semiquantitative rt–PCR method performed on frozen samples of breast cancer tissue. Patients were classified as presenting low or high levels of expression of these three genes. rt-PCR values were correlated with T stage, N stage, Scarff–Bloom–Richardson (SBR) grade, age and hormonal status. The impact of gene expression levels on 5-year disease-free survival (DFS) and overall survival (OS) was studied by univariate and multivariate Cox analysis. No statistically significant correlation was demonstrated between MDR1, MRP1 and GSTP1 expressions. On univariate analysis, DFS was significantly decreased in a context of low GSTP1 expression (P=0.0005) and high SBR grade (P=0.003), size ⩾5 cm (P=0.038), high T stage (P=0.013), presence of intravascular embolus (P=0.034), and >3 N+ (P=0.05). On multivariate analysis, GSTP1 expression and the presence of ER remained independent prognostic factors for DFS. GSTP1 expression did not affect OS. The levels of MDR1 and MRP1 expression had no significant influence on DFS or OS. GSTP1 expression can be considered to be an independent prognostic factor for DFS in patients receiving adjuvant chemotherapy for breast cancer

Rapid and cost effective screening of breast and ovarian cancer genes using novel sequence capture method in clinical samples

BRCA1 and BRCA2 are two well-known genes in the background of hereditary breast and ovarian cancer. There is also evidence that several other genes play an important role in the pathogenesis of these two malignancies. Latest population-scaled studies showed that certain mutations in different genes could cause similar risk elevation like BRCA2 mutations. In this study we present a new method to analyse the risk assessment of women to breast and ovarian cancer. Using Haloplex, a novel sequence capture method combined with next-generation sequencing we were able to perform rapid and cost-effective screening of 16 genes that could be associated with an increased risk of breast and ovarian cancer. The rapid and cost effective analysis of this 16-gene cohort can reveal the genetic background of approximately 30 % of hereditary and familiar cases of breast and ovarian cancers. Thus, it opens up a new and high-throughput approach with fast turnaround time to the genetic diagnostics of these disorders and may be helpful to investigate other familial genetic disorders as well