Identification of protein expression signatures in gastric carcinomas using clustering analysis

Background and Aim: The identification of gastric carcinomas (GC) has traditionally been based on histomorphology. Recently, DNA microarrays have successfully been used to identify tumors through clustering of the expression profiles. Random forest clustering is widely used for tissue microarrays and other immunohistochemical data, because it handles highly-skewed tumor marker expressions well, and weighs the contribution of each marker according to its relatedness with other tumor markers. In the present study, we e identified biologically- and clinically-meaningful groups of GC by hierarchical clustering analysis of immunohistochemical protein expression. Methods: We selected 28 proteins (p16, p27, p21, cyclin D1, cyclin A, cyclin B1, pRb, p53, c-met, c-erbB-2, vascular endothelial growth factor, transforming growth factor [TGF]-beta I, TGF-beta II, MutS homolog-2, bcl-2, bax, bak, bcl-x, adenomatous polyposis coli, clathrin, E-cadherin, beta-catenin, mucin (MUC) 1, MUC2, MUC5AC, MUC6, matrix metalloproteinase [ MMP]-2, and MMP-9) to be investigated by immunohistochemistry in 482 GC. The analyses of the data were done using a random forest-clustering method. Results: Proteins related to cell cycle, growth factor, cell motility, cell adhesion, apoptosis, and matrix remodeling were highly expressed in GC. We identified protein expressions associated with poor survival in diffuse-type GC. Conclusions: Based on the expression analysis of 28 proteins, we identified two groups of GC that could not be explained by any clinicopathological variables, and a subgroup of long-surviving diffuse-type GC patients with a distinct molecular profile. These results provide not only a new molecular basis for understanding the biological properties of GC, but also better prediction of survival than the classic pathological grouping.

HER-2, p53, p21 and hormonal receptors proteins expression as predictive factors of response and prognosis in locally advanced breast cancer treated with neoadjuvant docetaxel plus epirubicin combination

Abstract Background Neoadjuvant chemotherapy has been considered the standard care in locally advanced breast cancer. However, about 20% of the patients do not benefit from this clinical treatment and, predictive factors of response were not defined yet. This study was designed to evaluate the importance of biological markers to predict response and prognosis in stage II and III breast cancer patients treated with taxane and anthracycline combination as neoadjuvant setting. Methods Sixty patients received preoperative docetaxel (75 mg/m2) in combination with epirubicin (50 mg/m2) in i.v. infusion in D1 every 3 weeks after incisional biopsy. They received adjuvant chemotherapy with CMF or FEC, attaining axillary status following definitive breast surgery. Clinical and pathologic response rates were measured after preoperative therapy. We evaluated the response rate to neoadjuvant chemotherapy and the prognostic significance of clinicopathological and immunohistochemical parameters (ER, PR, p51, p21 and HER-2 protein expression). The median patient age was 50.5 years with a median follow up time 48 months after the time of diagnosis. Results Preoperative treatment achieved clinical response in 76.6% of patients and complete pathologic response in 5%. The clinical, pathological and immunohistochemical parameters were not able to predict response to therapy and, only HER2 protein overexpression was associated with a decrease in disease free and overall survival (P = 0.0007 and P = 0.003) as shown by multivariate analysis. Conclusion Immunohistochemical phenotypes were not able to predict response to neoadjuvant chemotherapy. Clinical response is inversely correlated with a risk of death in patients submitted to neoadjuvant chemotherapy and HER2 overexpression is the major prognostic factor in stage II and III breast cancer patients treated with a neoadjuvant docetaxel and epirubicin combination.