ERG Tumor Type is Less Frequent in High Grade and High Stage Prostate Cancers of Chinese Men

AI-based prediction of androgen receptor expression and its prognostic significance in prostate cancer

Biochemical recurrence (BCR) of prostate cancer (PCa) negatively impacts patients' post-surgery quality of life, and the traditional predictive models have shown limited accuracy. This study develops an AI-based prognostic model using deep learning that incorporates androgen receptor (AR) regional features from whole-slide images (WSIs). Data from 545 patients across two centres are used for training and validation. The model showed strong performances, with high accuracy in identifying regions with high AR expression and BCR prediction. This AI model may help identify high-risk patients, aiding in better treatment strategies, particularly in underdeveloped areas.

Metabolic pathways enriched according to ERG status are associated with biochemical recurrence in Hispanic/Latino patients with prostate cancer

BACKGROUND

The role of ERG-status molecular subtyping in prognosis of prostate cancer (PCa) is still under debate. In this study, we identified differentially expressed genes (DEGs) according to ERG-status to explore their enriched pathways and implications in prognosis in Hispanic/Latino PCa patients.

METHODS

RNA from 78 Hispanic PCa tissues from radical prostatectomies (RP) were used for RNA-sequencing. ERG_high /ERG_low tumor groups were determined based on the 1.5-fold change median expression in non-tumor samples. DEGs with a False Discovery Rate (FDR) < 0.01 and a fold change >2 were identified between ERG_high and ERG_low tumors and submitted to enrichment analysis in MetaCore. Survival and association analyses were performed to evaluate biochemical recurrence (BCR)-free survival.

RESULTS

The identification of 150 DEGs between ERG_high and ERG_low tumors revealed clustering of most of the non-BCR cases (60%) into de ERG_high group and most of the BCR cases (60.8%) in ERG_low group. Kaplan-Meier survival curves showed a worst BCR-free survival for ERG_low patients, and a significant reduced risk of BCR was observed for ERG_high cases (OR = 0.29 (95%CI, 0.10-0.8)). Enrichment pathway analysis identified metabolic-related pathways, such as the renin-angiotensin system and angiotensin maturation system, the linoleic acid metabolism, and polyamines metabolism in these ERG groups.

CONCLUSIONS

ERG_low tumor cases were associated with poor BCR-free survival in our Hispanic/Latino patients, with metabolism-related pathways altered in the BCR progression.

IMPACT

Our findings suggest the need to dissect the role of diet, metabolism, and lifestyle as risk factors for more aggressive PCa subtypes.