Abstract 732: Potentials of some serum proteins and urinary molecular biomarkers for early diagnosis of prostate cancer in Nigeria patients

Abstract

Abstract Background: Prostate cancer (PCa) an adenocarcinoma is the most common cancer diagnosed in African men today. At present, the only widely accepted screening tools for prostate cancer are prostate specific antigen (PSA) and digital rectal examination. There is controversy regarding the appropriate level of serum PSA that should trigger a biopsy. This study is aimed at finding a better marker/panel of markers for prostate cancer. Methods: 150 consented patients requiring a prostate biopsy and 100 age matched controls were recruited for this study. Genetic materials were found in 132 (88%) of the samples. Serum Total PSA (TPSA) , and free PSA were assayed using ELISA method, % free/total PSA(%f/tpsa) was obtained statistically, prostatic volume was determined using TRUS. In addition, selected urinary RNA’s were assayed; transmembrane serine protease (TMPRSS2:ERG and TMPRSS2:ETS) fusion genes, PSA gene and PCA3 (prostate cancer antigen 3) , using standard polymerase chain reaction (PCR) protocols. Results: TMPRSS2:ERG was detected in 9 (7 %) of the samples and limited to biopsy positive for PCa. Similarly, TMPRSS2:ETS was found in only 4 (3%) of the samples and also restricted to biopsy positive for PCa. PCA3 score had the best discriminatory accuracy in diagnosing PCa amongst patients with serum Total PSA in the range of 4 - 10 ng/ml with AUC of 0.705 compared to Total PSA, f/t PSA ratio, and PSA Density which were 0.365, 0.695, and 0.541 respectively. At the cut off value of 24.6, PCA3 score yielded its best sensitivity of 0.615 and specificity of 0.630. At the cutoff of 18, free/total PSA ratio (0.615, 0.77), at the cutoff of 0.14 PSAD yielded its best (0.538, 0.704.) respectively. Direct logistic regression was performed to access the predictability of PCa using different models comprising of three (3) covariates, the model comprising PCA3 Score, f/t PSA ratio and PSAD had the best discriminating accuracy in the subgroup with TPSA range of 4 - 10ng/ml, with the sensitivity, specificity, positive predictive value, and negative predictive values of 0.59, 0.93, 71.4% and 75.8% respectively, over models comprising PCA3 Score ,TPSA and %f/t PSA, and PCA3 Score, TPSA and PSAD with these values (0.23, 0.85, 42.9 % and 70.1%), (0.39, 0.89, 62.5%, and 75 %) and ( 0.15, 0.85,66.7% and 67.6%) respectively. Conclusions: In predicting PCa amongst patients with serum total PSA in the grey area of 4 - 10 ng/ml, the model comprising PCA3 Score, f/t PSA ratio and PSAD had the best discriminating accuracy. Note: This abstract was not presented at the meeting. Citation Format: Oluyemi Akinloye, Aniebietabasi S. Obot, Taiwo A. Adewole. Potentials of some serum proteins and urinary molecular biomarkers for early diagnosis of prostate cancer in Nigeria patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 732. doi:10.1158/1538-7445.AM2017-732