Prostate最新文献

Background: The transcription factor Signal Transducer and Activator of Transcription 3 (STAT3) plays a role in carcinogenesis and is involved in processes, such as proliferation, differentiation, drug resistance and immunosuppression. STAT3 can be activated by phosphorylation of tyrosine at position 705 (pSTAT3^Tyr705) or serine at 727 (pSTAT3^Ser727). High expression levels of pSTAT3 are implicated in advanced stages of prostate cancer (PCa) and are known to interact with the androgen receptor signaling pathway. However, not much is known about how androgen deprivation therapy (ADT) in advanced disease affects pSTAT3 expression. The aim of this study was to determine the influence of ADT on pSTAT3 expression in PCa tissue.

Methods: The study cohort came from a PCa tissue microarray resource containing prostate specimens from patients before and post-initiation of ADT. Tissue samples from 111 patients were immunostained for pSTAT3^Tyr705 and pSTAT3^Ser727. H-score was used to evaluate the intensity and the percentage of pSTAT3 expression in malignant epithelial and stromal compartments. Univariate and multivariable Cox regression analyses were used to assess pSTAT3^Tyr705 and pSTAT3^Ser727 as biomarkers of oncological outcome in patients undergoing ADT.

Results: Post-ADT PCa samples demonstrated increased nuclear and cytoplasmic levels of pSTAT3^Ser727 in the stroma compared to pre-ADT samples, whereas pSTAT3^Tyr705 expression was increased significantly in both stromal and malignant epithelial compartments except for stromal cytoplasm. High cytoplasmic pSTAT3^Ser727 in stromal compartments correlated with reduced overall survival, shorter time to castration-resistant PCa development, and decreased metastasis-free survival. An increase in nuclear and cytoplasmic pSTAT3^Ser727 expression within the stromal compartment of post-ADT samples corresponded to a shorter time to CRPC development, which was not observed for pSTAT3^Tyr705. Multivariable survival analysis using Cox's regression identified that high cytoplasmic pSTAT3^Ser727 expression in the stroma of post-ADT samples and pT3 or pT4-stage were associated with worse overall survival and 5-year metastasis-free survival (MFS).

Conclusions: This study presents novel insights into the impact of ADT on the expression levels of pSTAT3^Tyr705 and pSTAT3^Ser727 in PCa. Cytoplasmic pSTAT3^Ser727 status of cancer-associated stromal cells in post-ADT samples may serve as an independent prognostic marker for OS and 5-year MFS, identifying prostate cancer patients prone to developing resistance to ADT.

Objectives: To compare the detection rates for clinically significant prostate cancer (csPCa; grade group 2 or higher disease) using MRI-targeted biopsy (MRI-TB) versus systematic biopsy (SB) or their combination, and identify risk factors for detecting csPCa in MRI-TB with systematic transrectal (TR)/transperineal (TP) biopsies (sTR/TP-bx) and MRI-TB with sTP-bx.

Methods: We retrospectively analyzed 216 patients who underwent MRI-TB with SB at our hospital between September 2020 and December 2023 and compared clinical characteristics for patients with and without prostate cancer.

Results: csPCa was detected in 132 (61.1%) patients by MRI-TB with sTR/TP-bx, in 121 (56.0%) patients using MRI-TB with sTP-bx, and in 101 (46.8%) patients using MRI-TB. Older age, higher PSA density (PSAD), smaller prostate volume, region of interest in the peripheral zone, higher Prostate Imaging-Reporting and Data System (PI-RADS), and administration of dutasteride were more common in csPCa cases. A scoring system was constructed based on odds ratios for PSAD, PI-RADS ≥ 4, and administration of dutasteride; accordingly, the detection rate of csPCa was 20.3% (14/69) in the low-risk group (RG) and 95.5% (42/44) in high RG for MRI-TB with sTR/TP-bx, and 16.7% (12/72) in the low RG and 97.8% (45/46) in high RG for MRI-TB with sTP-Bx.

Conclusions: The addition of SB increased the detection rate of csPCa compared with MRI-TB alone. PSAD, PI-RADS ≥ 4, and administration of dutasteride significantly affect the detection of csPCa using MRI-TB with SB and can be used for deciding whether to perform a biopsy or include sTR-bx with MRI-TB.

Background: Large language model (LLM) chatbots, a form of artificial intelligence (AI) that excels at prompt-based interactions and mimics human conversation, have emerged as a tool for providing patients with information about urologic conditions. We aimed to examine the quality of information related to benign prostatic hyperplasia surgery from four chatbots and how they would respond to sample patient messages.

Methods: We identified the top three queries in Google Trends related to "treatment for enlarged prostate." These were entered into ChatGPT (OpenAI), Bard (Google), Bing AI (Microsoft), and Doximity GPT (Doximity), both unprompted and prompted for specific criteria (optimized). The chatbot-provided answers to each query were evaluated for overall quality by three urologists using the DISCERN instrument. Readability was measured with the built-in Flesch-Kincaid reading level tool in Microsoft Word. To assess the ability of chatbots to answer patient questions, we prompted the chatbots with a clinical scenario related to holmium laser enucleation of the prostate, followed by 10 questions that the National Institutes of Health recommends patients ask before surgery. Accuracy and completeness of responses were graded with Likert scales.

Results: Without prompting, the quality of information was moderate across all chatbots but improved significantly with prompting (mean [SD], 3.3 [1.2] vs. 4.4 [0.7] out of 5; p < 0.001). When answering simulated patient messages, the chatbots were accurate (mean [SD], 5.6 [0.4] out of 6) and complete (mean [SD], 2.8 [0.3] out of 3). Additionally, 98% (39/40) had a median score of 5 or higher for accuracy, which corresponds to "nearly all correct." The readability was poor, with a mean (SD) Flesch-Kincaid reading level grade of 12.1 (1.3) (unprompted).

Conclusions: LLM chatbots hold promise for patient education, but their effectiveness is limited by the need for careful prompting from the user and by responding at a reading level higher than that of most Americans (grade 8). Educating patients and physicians on optimal LLM interaction is crucial to unlock the full potential of chatbots.

Objective: To compare the effects of carbon-ion radiation therapy (CIRT) and external beam radiotherapy (EBRT) on the prognosis of patients with prostate cancer.

Methods: The effects of initial prostate-specific antigen (iPSA), clinical Tumor (cT) stage, radiotherapy method, and other clinical factors on the prognosis of 577 patients with radiotherapy were analyzed.

Results: Cox regression analysis showed that CIRT (RR: 0.49, p = 0.0215), cT stage ≥ 3 (RR: 2.72, p = 0.0003), and iPSA ≥ 16 ng/mL (RR: 1.74, p = 0.0347) were independent predictors of biochemical recurrence (BCR). After propensity score matching (PSM), CIRT (RR: 0.42, p = 0.0147), cT stage ≥ 3 (RR: 2.55, p = 0.0092), and iPSA ≥ 16 ng/mL (RR: 2.12, p = 0.0366) were still the predictors of univariate analysis. In multivariate analysis, CIRT (RR: 0.42, p = 0.015) and cT stage≥ 3 (RR:2.21, p = 0.0332) were independent predictors of BCR. Among them, we used iPSA and cT stages to establish a new radiotherapy selection model based on BCR risk. Patients who met more than one factor (score ≥ 1) and underwent CIRT had significantly better BCR progression-free survival (PFS) than those who received EBRT (p ≤ 0.01). This was also confirmed by Kaplan-Meier analysis after PSM.

Conclusion: CIRT patients exhibited lower 5-year BCR rates compared to the EBRT group. Patients with a risk score of our model ≥ 1 undergoing CIRT were more likely to experience BCR benefits compared to those receiving EBRT.

Background: Multiple novel protein biomarkers have been shown to be associated with prostate cancer risk using genetic instruments. This study aimed to externally validate the associations of 30 genetically predicted candidate proteins with prostate cancer risk using aptamer-based levels in US Black and White men in the Atherosclerosis Risk in Communities (ARIC) study. Plasma protein levels were previously measured by SomaScan® using the blood collected in 1990-1992.

Methods: Among 4864 eligible participants, we ascertained 667 first primary prostate cancer cases through 2015. Hazard ratios (HRs) of prostate cancer and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression for tertiles of each protein. We adjusted for age, race, and other risk factors.

Results: Of the 30 proteins and considering a nominal p trend < 0.05, two were positively associated with prostate cancer risk-RF1ML (tertile 3 vs. 1: HR = 1.23; 95% CI 1.02-1.48; p trend = 0.037) and TPST1 (1.28, 95% CI 1.06-1.55; p trend = 0.0087); two were inversely associated-ATF6A (HR = 0.80, 95% CI 0.65-0.98; p trend = 0.028) and SPINT2 (HR = 0.74, 95% CI 0.61-0.90; p trend = 0.0025). One protein, KDEL2, which was nonlinearly associated (test-for-linearity: p < 0.01) showed a statistically significant lower risk in the second tertile (HR = 0.79, 95% CI 0.65-0.95). Of these five, four proteins-ATF6A, KDEL2, RF1ML, and TPST1-were consistent in the direction of association with the discovery studies.

Conclusion: This study validated some pre-diagnostic protein biomarkers of the risk of prostate cancer.