Prognostic significance of the presence of intraductal carcinoma of the prostate and bone metastasis in needle biopsy for prostate carcinoma patients with Grade Group 5

Identification of recurrent BRAF non-V600 mutations in intraductal carcinoma of the prostate in Chinese populations

While BRAF alterations have been established as a driver in various solid malignancies, the characterization of BRAF alterations in prostate cancer (PCa) has not been thoroughly interrogated. By bioinformatics analysis, we first found that BRAF alterations were associated with advanced PCa and exhibited mutually exclusive pattern with ERG alteration across multiple cohorts. Of the most interest, recurrent non-V600 BRAF mutations were found in 3 of 21 (14.3 %) PCa patients demonstrating IDC-P morphology. Furthermore, experimental overexpression of BRAFK601E and BRAFL597R exhibited emergence of oncogenic phenotypes with intensified MAPK signaling in vitro, which could be targeted by MEK inhibitors. Comparison of the incidence of BRAF alterations in IDC-P between western and Chinese ancestry revealed an increased prevalence in the Chinese population. The BRAF mutation may represent important genetic alteration in a subset of IDC-P, highlighting the role of MAPK signaling pathway in this subtype of PCa. To the best of knowledge, this is the first description of non-V600 BRAF mutation in setting of IDC-P, which may in part explain the aggressive phenotype seen in IDC-P and could also bring more treatment options for PCa patients with IDC-P harboring such mutations.

Construction and validation of a clinical predictive nomogram for intraductal carcinoma of the prostate based on Chinese multicenter clinical data

Introduction

Intraductal carcinoma of the prostate (IDC-P) is a special pathological type of prostate cancer that is highly aggressive with poor prognostic outcomes.

Objective

To establish an effective predictive model for predicting IDC-P.

Methods

Data for 3185 patients diagnosed with prostate cancer at three medical centers in China from October 2012 to April 2022 were retrospectively analyzed. One cohort (G cohort) consisting of 2384 patients from Zhejiang Provincial People's Hospital was selected for construction (Ga cohort) and internal validate (Gb cohort)of the model. Another cohort (I cohort) with 344 patients from Quzhou People's Hospital and 430 patients from Jiaxing Second People's Hospital was used for external validation. Univariate and multivariate binary logistic regression analyses were performed to identify the independent predictors. Then, the selected predictors were then used to establish the predictive nomogram. The apparent performance of the model was evaluated via externally validated. Decision curve analysis was also performed to assess the clinical utility of the developed model.

Results

Univariate and multivariate logistic regression analyses showed that alkaline phosphatase (ALP), total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), prostate specific antigen (PSA) and lactate dehydrogenase were independent predictors of IDC-P. Therefore, a predictive nomogram of IDC-P was constructed. The nomogram had a good discriminatory power (AUC = 0.794). Internal validation (AUC = 0.819)and external validation (AUC = 0.903) also revealed a good predictive ability. Calibration curves showed good agreement between the predicted and observed incidences of IDC-P.

Conclusion

We developed a clinical predictive model composed of alkaline phosphatase (ALP), total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), prostate specific antigen (PSA) and lactate dehydrogenase (LDH) with a high precision and universality. This model provides a novel calculator for predicting the diagnosis of IDC-P and different treatment options for patients at an early stage.