Secretoglobin expression in ovarian carcinoma: lipophilin B gene upregulation as an independent marker of better prognosis.

BACKGROUND: The aim of the present study was to investigate within ovarian carcinoma and normal ovarian biopsies the gene expression of multiple secretoglobin family members relative to mammaglobin B, which we previously reported as a promising novel ovarian carcinoma prognostic marker. METHODS: Using quantitative real-time Reverse Transcription PCR we tested 53 ovarian carcinoma and 30 normal ovaries for the expression of 8 genes belonging to the secretoglobin family: mammaglobin A, lipophilin A, lipophilin B, uteroglobin, HIN-1, UGRP-1, RYD5 and IIS. Next, we decided to expand the LipB gene expression analysis to a further 48 ovarian carcinoma samples, for a total of 101 tumor tissues of various histologies and to study its protein expression by immunohistochemistry in formalin-fixed paraffin-embedded tumors and normal ovaries. Finally, we correlated lipophilin B gene and protein expression to conventional patient clinico-pathological features and outcome. RESULTS: We found significant mammaglobin A, lipophilin A, lipophilin B and RYD5 gene overexpression in ovarian carcinomas compared to normal ovaries. Lipophilin B mRNA showed a higher presence in tumors (75.4%) compared to normal ovaries (16.6%) and the most significant correlation with mammaglobin B mRNA (r(s) =0.77, p < 0.001). By immunohistochemical analysis, we showed higher lipophilin B expression in the cytoplasm of tumor cells compared to normal ovaries (p < 0.001). Moreover, lipophilin B gene overexpression was significantly associated with serous histology (serous vs clear cell p = 0.027; serous vs undifferentiated p = 0.007) and lower tumor grade (p = 0.02). Lower LipB mRNA levels (low versus high tertiles) were associated to a shorter progression-free (p = 0.03, HR = 2.2) and disease-free survival (p = 0.02, HR = 2.5) by univariate survival analysis and, importantly, they remain an independent prognostic marker for decreased disease-free (p = 0.001, HR = 3.9) and progression-free survival (p = 0.004, HR = 2.8) in multivariate Cox regression analysis. CONCLUSIONS: The present study represents the first quantitative evaluation of secretoglobin gene expression in normal and neoplastic ovarian tissues. Our results demonstrate lipophilin B gene and protein upregulation in ovarian carcinoma compared to normal ovary. Moreover, lipophilin B gene overexpression correlates with a less aggressive tumor phenotype and represents a novel ovarian carcinoma prognostic factor

Tyrosine Kinase inhibitors

Breast cancer is the most common cancer in women worldwide. Although various subgroups are defined according to the expression of hormones and ErbB family receptors, it is well known that this disease is more heterogeneous than its classification system suggests. As new effective therapeutic choices are developed and used clinically, resistance to these new agents is also being observed. The most promising new anti-HER therapies are T-DM1 and pertuzumab, which has been evaluated in trastuzumabresistant patients and also in a first-line setting with trastuzumab. The dual blockage of HER seems to be a favorable approach for these patients; however, the downstream signaling steps can be activated to overcome the tyrosine kinase inhibition. Because tumor cells can adapt themselves by using alternative pathways to maintain proliferation, providing a sufficient treatment approach also requires the consideration of possible escape mechanisms in tumor cells. By inhibiting tyrosine kinases combined with another agent that affects downstream factors of the PI3K/AKT/mTOR pathway, drug resistance in breast cancer can be overcome or delayed. In this chapter, we discuss the new tyrosine kinase inhibitors that inhibit more than only HER-2 and discuss some ongoing clinical trials in this area. In so doing, we hope to provide information for overcoming tyrosine kinase drug resistance and to identify the ideal settings for these treatment choices according to recent data. © Springer International Publishing Switzerland 2016