Strategies for patient stratification and early intervention are required to improve clinical benefits for patients with prostate cancer. Here, we found that active DHEA utilization in the prostate gland correlated with tumor aggressiveness at early disease stages, and 3βHSD1 inhibitors were promising for early intervention. [³H]-labeled DHEA consumption was traced in fresh prostatic biopsies ex vivo. Active DHEA utilization was more frequently found in patients with metastatic disease or therapy-resistant disease. Genetic and transcriptomic features associated with the potency of prostatic DHEA utilization were analyzed to generate clinically accessible approaches for patient stratification. UBE3D, by regulating 3βHSD1 homeostasis, was discovered to be a regulator of patient metabolic heterogeneity. Equilin suppressed DHEA utilization and inhibited tumor growth as a potent 3βHSD1 antagonist, providing a promising strategy for the early treatment of aggressive prostate cancer. Overall, our findings indicate that patients with active prostatic DHEA utilization might benefit from 3βHSD1 inhibitors as early intervention.

Photoacoustic spectroscopy can generate abundant chemical and physical information about biological tissues. However, this abundance of information makes it difficult to compare these tissues directly. Data mining methods can circumvent this problem. We describe the application of machine-learning methods (including unsupervised hierarchical clustering and supervised classification) to the diagnosis of prostate cancer by photoacoustic spectrum analysis. We focus on the content and distribution of hemoglobin, collagen, and lipids, because these molecules change during the development of prostate cancer. A higher correlation among the ultrasonic power spectra of these chemical components is observed in cancerous than in normal tissues, indicating that the microstructural distributions in cancerous tissues are more consistent. Different classifiers applied in cancer-tissue diagnoses achieved an accuracy of 82 % (better than that of standard clinical methods). The technique thus exhibits great potential for painless early diagnosis of aggressive prostate cancer.

Novel strategies for prostate cancer therapy are required to overcome resistance to abiraterone and enzalutamide. Here, we show that increasing 3βHSD1 after abiraterone and enzalutamide treatment is essential for drug resistance, and biochanin A (BCA), as an inhibitor of 3βHSD1, overcomes drug resistance. 3βHSD1 activity increases in cell lines, biopsy samples, and patients after long-term treatment with enzalutamide or abiraterone. Enhanced steroidogenesis, mediated by 3βHSD1, is sufficient to impair enzalutamide function. In patients, accelerated abiraterone metabolism results in a decline of plasma abiraterone as disease progresses. BCA inhibits 3βHSD1 and suppresses prostate cancer development alone or together with abiraterone and enzalutamide. Daidzein, a BCA analog of dietary origin, is associated with higher plasma abiraterone concentrations and prevented prostate-specific antigen (PSA) increases in abiraterone-resistant patients. Overall, our results show that 3βHSD1 is a promising target to overcome drug resistance, and BCA suppresses disease progression as a 3βHSD1 inhibitor even after abiraterone and enzalutamide resistance.

Strategies beyond hormone-related therapy need to be developed to improve prostate cancer mortality. Here, we show that FUBP1 and its methylation were essential for prostate cancer progression, and a competitive peptide interfering with FUBP1 methylation suppressed the development of prostate cancer. FUBP1 accelerated prostate cancer development in various preclinical models. PRMT5-mediated FUBP1 methylation, regulated by BRD4, was crucial for its oncogenic effect and correlated with earlier biochemical recurrence in our patient cohort. Suppressed prostate cancer progression was observed in various genetic mouse models expressing the FUBP1 mutant deficient in PRMT5-mediated methylation. A competitive peptide, which was delivered through nanocomplexes, disrupted the interaction of FUBP1 with PRMT5, blocked FUBP1 methylation, and inhibited prostate cancer development in various preclinical models. Overall, our findings suggest that targeting FUBP1 methylation provides a potential therapeutic strategy for prostate cancer management.

Pathology is currently the gold standard for grading prostate cancer (PCa). However, pathology takes considerable time to provide a final result and is significantly dependent on subjective judgment. In this study, wavelet transform-based photoacoustic power spectrum analysis (WT-PASA) was used for grading PCa with different Gleason scores (GSs). The tumor region was accurately identified via wavelet transform time-frequency analysis. Then, a linear fitting was conducted on the photoacoustic power spectrum curve of the tumor region to obtain the quantified spectral parameter slope. The results showed that high GSs have small glandular cavity structures and higher heterogeneity, and consequently, the slopes at both 1210 nm and 1310 nm were high (p < 0.01). The classification accuracy of the PA time frequency spectrum (PA-TFS) of tumor region using ResNet-18 was 89% at 1210 nm and 92.7% at 1310 nm. Further, the testing time was less than 7 mins. The results demonstrated that identification of PCa can be rapidly and objectively realized using WT-PASA.