Cancer-associated fibroblasts promote enzalutamide resistance and PD-L1 expression in prostate cancer through CCL5-CCR5 paracrine axis.

Cancer-associated fibroblasts (CAFs) have been shown to play a key role in prostate cancer treatment resistance, but the role of CAFs in the initial course of enzalutamide therapy for prostate cancer remains unclear. Our research revealed that CAFs secrete CCL5, which promotes the upregulation of androgen receptor (AR) expression in prostate cancer cells, leading to resistance to enzalutamide therapy. Furthermore, CCL5 also enhances the expression of tumor programmed death-ligand 1 (PD-L1), resulting in immune escape. Mechanistically, CCL5 binds to the receptor CCR5 on prostate cancer cells and activates the AKT signaling pathway, leading to the upregulation of AR and PD-L1. The CCR5 antagonist maraviroc to inhibit the CAFs mediated CCL5 signaling pathway can effectively reduce the expression of AR and PD-L1, and improve the efficacy of enzalutamide. This study highlights a promising therapeutic approach targeting the CCL5-CCR5 signaling pathway to improve the effectiveness of enzalutamide.

Delivery of gefitinib loaded nanoparticles for effectively inhibiting prostate cancer progression.

Androgen deprivation therapy is administered to suppress the growth of prostate cancer (PCa). However, some cells continue to proliferate independent of hormones, leading to the development of castration-resistant prostate cancer (CRPC). Overexpression of the epidermal growth factor receptor (EGFR) has been observed in CRPC and is associated with an unfavorable prognosis. Gefitinib (GEF) is an EGFR inhibitor used to treat patients with CRPC. Nevertheless, some clinical studies have reported that gefitinib does not result in prostate-specific antigen (PSA) or objectively measurable CRPC reactions. This lack of response may be attributed to the limited solubility in water, high side effects, low tumor aggregation, and insufficient tumor-specific reactions of GEF. In order to tackle these obstacles, we present a practical and efficient approach to administer GEF, encompassing the utilization of biocompatible nanostructures as a vehicle for drug delivery to augment its bioaccessibility and curative potency. Despite their small particle size, poly(D,L-lactide-co-glycolide) acid nanoparticles (PLGA NPs) exhibit a high drug-loading capacity, low toxicity, biocompatibility, biodegradability, and minimal immunogenicity. The drug delivery efficiency can be improved by employing GEF@PLGA NPs, which could also enhance drug cytotoxicity and impede the advancement of prostate cancer. Moreover, through experiments in vivo, it has been verified that GEF@PLGA NPs exhibit selective accumulation in the tumor and effectively restrain tumor growth. Therefore, the GEF@PLGA NPs hold great promise for the treatment of PCa.

Cuproptosis illustrates tumor micro-environment features and predicts prostate cancer therapeutic sensitivity and prognosis.

BACKGROUND: Prostate cancer (PCA) is a common malignant genitourinary tumor that significantly impacts patient survival. Cuproptosis, a copper-dependent programmed cell death mechanism, plays a vital role in tumor development, therapy resistance, and immune microenvironment regulation in PCA. However, research on cuproptosis in prostate cancer is still in its early stages. METHODS: Using the publicly available datasets TCGA and GEO, we first acquired the transcriptome and clinical information of PCA patients. The expression of cuprotosis-related genes (CRG) was identified and a prediction model was established based on LASSO-COX method. The predictive performance of this model was evaluated based on Kaplan-Meier method. Using GEO datasets, we further confirmed the critical genes level in the model. Tumor responses to immune checkpoint (ICP) inhibitors were predicted based on Tumor Immune Dysfunction and Exclusion (TIDE) score. The Genomics of Drug Sensitivity in Cancer (GDSC) was utilized to forecast drug sensitivity in cancer cells, whereas the GSVA was employed to analyze enriched pathways related to the cuproptosis signature. Subsequently, the function of PDHA1 gene in PCA was verified. RESULTS: A predictive risk model on basis of five cuproptosis-related genes (ATP7B, DBT, LIPT1, GCSH, PDHA1) were established. The progression free survival of low-risk group was obviously longer than the high-risk group, and exhibit better response to ICB therapy.Furthermore,PDHA1 is very important in the pathological process of PCA according to regressions analysis result, and the validation of external data sets were conducted. High PDHA1 expression patients with PCA not only had a shorter PFS and were less likely to benefit from ICB treatment, but they were also less responsive to multiple targeted therapeutic drugs. In preliminary research, PDHA1 knockdown significantly decreased the proliferation and invasion of PCA cells. CONCLUSION: This study established a novel cuproptosis-related gene-based prostate cancer prediction model that accurately predicts the prognosis of PCA patients. The model benefits individualized therapy and can assist clinicians in making clinical decisions for PCA patients. Furthermore, our data show that PDHA1 promotes PCA cell proliferation and invasion while modulating the susceptibility to immunotherapy and other targeted therapies. PDHA1 can be regarded as an important target for PCA therapy.