BCL-2 BAX RATIO AS A PREDICTIVE MARKER FOR THERAPEUTIC RESPONSE TO RADIOTHERAPY IN PATIENTS WITH PROSTATE-CANCER/

Objectives. Markers predictive of therapeutic response of prostatic tu mors to radiotherapy may have major significance in optimizing effecti ve treatment of prostate cancer. Because inherent cellular radioresist ance plays a critical role in the failure of radiotherapy, in this stu dy, we investigated whether there is a correlation between the ratio o f two apoptosis regulators, bcl-2 (apoptosis suppressor) and bar (apop tosis inducer) in prostatic tumors and the clinical response to radiot herapy in patients with localized prostate cancer. Methods. A retrospe ctive review of records of 41 patients who underwent external beam rad iotherapy for prostate cancer was conducted. On the basis of post-trea tment prostate biopsy and prostate-specific antigen (PSA) criteria, th e cancers of 20 patients were classified as radiation nonresponders an d 21 as radiation responders. Immunohistochemical analysis was perform ed on paraffin-embedded prostate sections to determine the level of ex pression of the two apoptotic proteins, bcl-2 and bar, in tumor cells. Results. bcl-2 immunoreactivity was significantly higher in prostatic tumors not responsive to radiotherapy (38.6 +/- 4.1), compared with t he radiation responders (24.1 +/- 4.6) (P < 0.001). Expression of bar protein was lower in nonresponders, but values were not significantly different from the responders. The resulting significantly higher bcl- 2/bax ratio (P < 0.01) correlated with poor therapeutic responsiveness of prostate cancer to radiotherapy (1.12 +/- 0.12 and 0.56 +/- 0.13, for nonresponders and responders, respectively). This correlation (r = 0.67) was independent of age, PSA, and Gleason score. Conclusions. Th ese findings suggest that patients with an elevated bcl-2/bax ratio ar e at increased risk of their cancer failing to respond to radiotherapy . This study suggests a predictive value for the bcl-2/bax ratio as a potential molecular marker for predicting radioresistance of prostatic tumors. (C) 1998, Elsevier Science Inc. All rights reserved.