Études multiparamétriques de biomarqueurs par immunofluorescence pour mieux suivre la progression du cancer de la prostate

Prostate cancer is the most frequently diagnosed cancer and the third leading cause of cancer-related death in men in Canada. A quarter of patients will develop a more aggressive form of this cancer. While there are several clinical prognostic variables for localized prostate cancer (Gleason score, prostate specific antigen (PSA) levels, stage, etc.), these are insufficient to adequately distinguish between low and high-risk of progression cases. As a result, clinicians need new, more effective tools to stratify this cancer and to ensure that treatments are best tailored to each patient. To date, no prognostic biomarker has yet been used clinically. Based on the literature and preliminary studies of small cohorts (less than 65 patients), we hypothesize that the protein expression of PUMA-NOXA and ERBB family members could help with the prediction of prostate cancer progression. The objectives of this thesis are: 1) to identify and validate antibodies for each biomarker of interest, 2) to define the expression levels of each biomarker on a 285 patient cohort, 3) to evaluate the correlation between marker expression levels and patient clinical data. For clinical use, monoclonal-type antibodies were chosen to identify the biomarkers of interest. These antibodies were validated for specificity by western blot and immunofluorescence techniques. The localization of the protein of interest was further identified within samples of patient tissues and additional optimization involving combinatorial staining for epithelial and basal cells. After refining the imaging and statistical analysis of PUMA and NOXA in benign glands, we found that extreme (weak or strong) PUMA expression coupled with high NOXA expression was associated with biochemical relapse. In addition, these proteins have significant potential for predicting disease evolution based on the initial radical prostatectomy sample. The presence of these proteins in benign glands would allow the identification of patients less suitable for active surveillance. Additionally, statistical analysis of ERBB family receptors in tumor glands, when used alone, allow stratification of prostate cancer patients for the prediction of biochemical relapse, development of metastases and also specific death from prostate cancer. Moreover, patients expressing a combination of high EGFR expression and low ERBB3 expression are at high risk of biochemical relapse and are at higher risk of prostate cancer specific mortality. In addition, coupling this high EGFR – low ERBB3 combination to a low ERBB2 expression helps classify patients at high risk of developing metastases. My doctoral research project will have made it possible to identify and validate biomarkers of interest for predicting the progression of prostate cancer and demonstrating the interest of combining these biomarkers in order to achieve better stratification of patients with prostate cancer. In the context of clinical utility, these results need to be validated on an independent and multicenter cohort in order to confirm these findings. This would eventually provide clinicians with a greater number of tools at their disposal to correctly anticipate patient trajectories and possibly identify new therapeutic targets for the control of the disease.

Keyphrases: PUMA, NOXA, EGFR, ERBB2, ERBB3, ERBB4, Immunofluorescence, Prostate cancer, Tissue micro-array