Chromosome-specific segment size alterations are determinants of prognosis in prostate cancer.

Currently, risk stratification is the most difficult problem in prostate cancer (PCa) management. Gleason grading cannot adequately predict cancer progression. This study aimed to identify chromosome-specific segment size alterations that could aid risk stratification and predict metastasis using a retrospective cohort-study strategy. A binary logistic regression model was generated using 16 chromosome-specific segments with size alterations (deletions and amplifications) that showed associations with disease stage (primary versus metastatic). The regression model was trained with the MSKCC PIK3R1 PCa cohort (n = 1417), and validated with the TCGA Firehose Legacy (n = 500), MSKCC Prostate Oncogenome Project (n = 218), and the SU2C/PCF Dream Team (n = 150) PCa cohorts. Furthermore, the capacity of the model to predict metastasis between primary tumours with metastasis (n = 54) and primary tumours without metastasis (n = 54) was tested. The accuracy, sensitivity, and specificity of the model at disease stage stratification ranged from 69.02% to 88.55%, 72.8% to 86.00% and 66.30% to 89.50%, respectively. The model also showed good performance at metastasis prediction with accuracy, sensitivity, and specificity of 57.41%, 62.96% and 51.85%, respectively. The study conclusion was that chromosome-specific segment size alterations can aid risk stratification and metastasis prediction. The significance of the study findings is that in combinations with clinical, biochemical, and histopathological variables, chromosome-specific alterations could improve current risk stratification and prediction models for PCa.