Identification of a 24-gene panel and a novel marker of PODXL2 essential for the pathological diagnosis of early prostate cancer

TRPM4 contributes to cell death in prostate cancer tumor spheroids, and to extravasation and metastasis in a zebrafish xenograft model system

Transient receptor potential melastatin-4 (TRPM4) ion channel expression is upregulated in prostate cancer (PCa), contributing to increased cell proliferation, migration, adhesion, epithelial-to-mesenchymal transition, cell cycle shift, and alterations of intracellular Ca2+ signaling. GEO2R platform analysis of messenger RNA (mRNA) expression of ~ 6350 genes in normal and malignant prostate tissue samples from 15 PCa patients demonstrates that TRPM4 expression is upregulated sixfold and is among the most significantly upregulated genes in PCa. We find that absence of TRPM4 reduced PCa tumor spheroid size and decreased PCa tumor spheroid outgrowth. In addition, lack of TRPM4 increased cell death in PCa tumor spheroids, a phenotype that is absent in two-dimensional (2D) cancer cell systems. Lastly, absence of TRPM4 in PCa cells reduced extravasation and metastatic burden in a preclinical zebrafish cancer model. Taken together, our findings show that TRPM4 is an attractive therapeutic target in PCa and highlights the need for future development of pharmacological tools.

Silencing of PODXL2 Modulates Cell Viability and Tumor Immune Microenvironment of Prostate Cancer and Involves PI3K/AKT Pathway Inactivation

Prostate cancer (PCa) is one of the malignant tumors affecting men and is an important reason for the increase in male mortality worldwide. The pathogenesis of PCa is not fully understood. Thus, there is an urgent need to discover novel therapeutic targets to facilitate the development of effective anti-PCa strategies. Quantitative real-time PCR and Western blot were applied to detect the PODXL2 expressions in PCa tissues and cells. Progression-free survival of PCa patients was assessed using Kaplan-Meier survival analysis. The relevance between PODXL2 expressions and PCa clinical index was assessed with a Chi-square test. Cell infection, cell coculture system, Cell Counting Kit-8 assay, TUNEL staining, Transwell, analysis of PCa cell epithelial-mesenchymal transition (EMT) morphological changes, flow cytometry, and enzyme-linked immunosorbent assay were used for the analysis of PODXL2 functions in PCa. Meanwhile, the PODXL2 mechanism in PCa was dissected via Western blot, immunofluorescence analysis, Cell Counting Kit-8 assay, Transwell, and flow cytometry. Furthermore, PODXL2 impacts in PCa growth were examined in vivo using TUNEL staining, immunohistochemistry, and Western blot. PODXL2 expressions were raised in PCa tissues and cells, and PCa patients with high PODXL2 expressions owned poorer progression-free survival, and PODXL2 was interrelated to the TNM stage and distant metastasis of PCa. Interference with PODXL2 weakened PCa cell proliferation, invasion, EMT, and immune escape, while promoting PCa cell apoptosis. Furthermore, silencing PODXL2 reduced PCa cell proliferation, invasion, EMT, immune escape, and boosted cell apoptosis, which involved PI3K/AKT pathway inactivation. Meanwhile, PODXL2 knockdown reduced the tumor weight of PCa and promoted apoptosis in vivo. Interference with PODXL2 inhibited PCa cell proliferation, invasion, EMT, immune escape, enhanced cell apoptosis, and involved PI3K/AKT pathway inactivation.

Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading

Artificial intelligence (AI) holds significant promise in transforming medical imaging, enhancing diagnostics, and refining treatment strategies. However, the reliance on extensive multicenter datasets for training AI models poses challenges due to privacy concerns. Federated learning provides a solution by facilitating collaborative model training across multiple centers without sharing raw data. This study introduces a federated attention-consistent learning (FACL) framework to address challenges associated with large-scale pathological images and data heterogeneity. FACL enhances model generalization by maximizing attention consistency between local clients and the server model. To ensure privacy and validate robustness, we incorporated differential privacy by introducing noise during parameter transfer. We assessed the effectiveness of FACL in cancer diagnosis and Gleason grading tasks using 19,461 whole-slide images of prostate cancer from multiple centers. In the diagnosis task, FACL achieved an area under the curve (AUC) of 0.9718, outperforming seven centers with an average AUC of 0.9499 when categories are relatively balanced. For the Gleason grading task, FACL attained a Kappa score of 0.8463, surpassing the average Kappa score of 0.7379 from six centers. In conclusion, FACL offers a robust, accurate, and cost-effective AI training model for prostate cancer pathology while maintaining effective data safeguards.

Metastatic hormone-naïve prostate cancer: a distinct biological entity

Metastatic hormone-naïve prostate cancer (mHNPC) is often the initial form of presentation for metastatic prostate cancer and encompasses a heterogeneous patient population with high inter-patient heterogeneity in prognosis and response to therapy. A more precise treatment of mHNPC, guided by evidence-based biomarkers, remains an unmet medical need. In addition, the limited number of representative laboratory models of mHNPC hampers the translation of basic research into clinical applications. We provide a comprehensive overview of the clinical and biological features that characterize mHNPC, highlight molecular data that could explain the unique prognostic characteristics of mHNPC, and identify key open questions.