Expression of TGFβ1 and its receptors is associated with biological features of ovarian cancer and sensitivity to paclitaxel/carboplatin

It has been suggested that expression of TGF beta 1 and its receptors [TGF beta receptor type I (T beta RI) and TGF beta receptor type II (T beta RII)] may play a key role in the proliferation and progression of epithelial ovarian cancer. We investigated the biological significance of TGF beta 1 and its receptors, as well as their association with the tumor response to paclitaxel (PTX) and carboplatin (CBDCA). We studied 24 patients with ovarian cancer, primary peritoneal cancer, or fallopian tube cancer who had undergone surgery and chemotherapy with PTX and CBDCA. Tissues from the primary tumor were examined and the expression of TGF beta 1, T beta RI, and T beta RII mRNA was assessed by the RNase protection assay. It was found that TGF beta 1 mRNA expression was significantly lower in the tumors of patients who had optimal surgery than in the tumors of patients with suboptimal surgery. TGF beta 1 mRNA expression was also significantly lower in tumors with high sensitivity to PTX and CBDCA than in those with low sensitivity. T beta RI mRNA expression was not associated with any clinicopathological factors. Expression of T beta RII mRNA was significantly higher in clear cell adenocarcinoma and mucinous adenocarcinoma, while it was lower in serous adenocarcinoma and endometrioid adenocarcinoma. Moreover, it tended to be higher in early-stage tumors compared with advanced tumors. Among TGF beta 1, T beta RI, and T beta RII, expression of TGF beta 1 mRNA was most strongly associated with progression-free survival. When the prognosis of the patients with advanced cancer was compared on the basis of TGF beta 1 mRNA expression, those whose tumors showed low expression tended to have a better prognosis than those whose tumors showed high expression. It is suggested that TGF beta 1 mRNA expression is an indicator of tumor sensitivity to standard therapy with PTX and CBDCA, that it can identify biologically aggressive and highly malignant tumors and that it can predict the prognosis of patients with ovarian cancer.