Revisiting Immunotherapy: A Focus on Prostate Cancer

Stemness regulation in prostate cancer: prostate cancer stem cells and targeted therapy

BACKGROUND

Increasing evidence indicates that cancer stem cells (CSCs) and cancer stem-like cells form a special subpopulation of cells that are ubiquitous in tumors. These cells exhibit similar characteristics to those of normal stem cells in tissues; moreover, they are capable of self-renewal and differentiation, as well as high tumorigenicity and drug resistance. In prostate cancer (PCa), it is difficult to kill these cells using androgen signaling inhibitors and chemotherapy drugs. Consequently, the residual prostate cancer stem cells (PCSCs) mediate tumor recurrence and progression.

OBJECTIVE

This review aims to provide a comprehensive and up-to-date overview of PCSCs, with a particular emphasis on potential therapeutic strategies targeting these cells.

METHODS

After searching in PubMed and Embase databases using 'prostate cancer' and 'cancer stem cells' as keywords, studies related were compiled and examined.

RESULTS

In this review, we detail the origin and characteristics of PCSCs, introduce the regulatory pathways closely related to CSC survival and stemness maintenance, and discuss the link between epithelial-mesenchymal transition, tumor microenvironment and tumor stemness. Furthermore, we introduce the currently available therapeutic strategies targeting CSCs, including signaling pathway inhibitors, anti-apoptotic protein inhibitors, microRNAs, nanomedicine, and immunotherapy. Lastly, we summarize the limitations of current CSC research and mention future research directions.

CONCLUSION

A deeper understanding of the regulatory network and molecular markers of PCSCs could facilitate the development of novel therapeutic strategies targeting these cells. Previous preclinical studies have demonstrated the potential of this treatment approach. In the future, this may offer alternative treatment options for PCa patients.

Identification of neutrophil extracellular traps (NETs)-related molecular clusters in prostate cancer: Implications for predicting biochemical recurrence

OBJECTIVE

To identify neutrophil extracellular traps (NETs)-related molecular clusters and establish a novel gene signature for predicting biochemical recurrence in prostate cancer (PCa).

METHODS

The transcriptome and clinicaldata of PCa sampleswere obtained from The TCGA and GEO databases. To identify NET-related molecular clusters, consensus clustering analyses were performed. Using univariate Cox and Lasso regression analysis, a novel NETs-related prognostic model was formulated. To evaluate the validity of the model, both internal and external validations were carried out. At last, preliminary experimental validations were performed to verify the biological functions of ANXA3 in PCa cells.

RESULTS

After screening 75 NETs-related prognostic genes, two NET-related clusters with significantly different clinical features, immune cell infiltration, and biochemical recurrence were established. Next, a new NET-related model was constructed. In training, test, whole TCGA, and GEO cohorts, the biochemical recurrences free survival of the patients with high-risk scores was considerably lower. The AUCs for the four cohorts were 0.827, 0.696, 0.757, and 0.715, respectively. Subgroup analysis suggested that the novel NETs-related prognostic model has a strong clinical value in the identification of high-risk patients. Finally, we confirmed that chemotherapy might be more beneficial for patients at low risk. In preliminary experiments, the inhibition of ANXA3 could reduce the invasion, migration, and proliferation of PCa cells.

CONCLUSIONS

We have identified novel NETs-related clusters and developed a NETs-related model for PCa that has excellent predictive performance for predicting biochemical recurrences as well as chemotherapy efficacy.

UQCRB and LBH are correlated with Gleason score progression in prostate cancer: Spatial transcriptomics and experimental validation

Prostate cancer (PCa) is a multifocal disease characterized by genomic and phenotypic heterogeneity within a single gland. In this study, Visium spatial transcriptomics (ST) analysis was applied to PCa tissues with different histological structures to infer the molecular events involved in Gleason score (GS) progression. The spots in tissue sections were classified into various groups using Principal Component Analysis (PCA) and Louvain clustering analysis based on transcriptome data. Anotation of the spots according to GS revealed notable similarities between transcriptomic profiles and histologically identifiable structures. The accuracy of macroscopic GS determination was bioinformatically verified through malignancy-related feature analysis, specifically inferred copy number variation (inferCNV), as well as developmental trajectory analyses, such as diffusion pseudotime (DPT) and partition-based graph abstraction (PAGA). Genes related to GS progression were identified from the differentially expressed genes (DEGs) through pairwise comparisons of groups along a GS gradient. The proteins encoded by the representative oncogenes UQCRB and LBH were found to be highly expressed in advanced-stage PCa tissues. Knockdown of their mRNAs significantly suppressed PCa cell proliferation and invasion. These findings were validated using The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset, as well as through histological and cytological experiments. The results presented here establish a foundation for ST-based evaluation of GS progression and provide valuable insights into the GS progression-related genes UQCRB and LBH.

Disulfidptosis-related subtype and prognostic signature in prostate cancer

BACKGROUND

Disulfidptosis refers to cell death caused by the accumulation and bonding of disulfide in the cytoskeleton protein of SLC7A11-high level cells under glucose deprivation. However, the role of disulfidptosis-related genes (DRGs) in prostate cancer (PCa) classification and regulation of the tumor microenvironment remains unclear.

METHODS

Firstly, we analyzed the expression and mutation landscape of DRGs in PCa. We observed the expression levels of SLC7A11 in PCa cells through in vitro experiments and assessed the inhibitory effect of the glucose transporter inhibitor BAY-876 on SLC7A11-high cells using CCK-8 assay. Subsequently, we performed unsupervised clustering of the PCa population and analyzed the differentially expressed genes (DEGs) between clusters. Using machine learning techniques to select a minimal gene set and developed disulfidoptosis-related risk signatures for PCa. We analyzed the tumor immune microenvironment and the sensitivity to immunotherapy in different risk groups. Finally, we validated the accuracy of the prognostic signatures genes using single-cell sequencing, qPCR, and western blot.

RESULTS

Although SLC7A11 can increase the migration ability of tumor cells, BAY-876 effectively suppressed the viability of prostate cancer cells, particularly those with high SLC7A11 expression. Based on the DRGs, PCa patients were categorized into two clusters (A and B). The risk label, consisting of a minimal gene set derived from DEGs, included four genes. The expression levels of these genes in PCa were initially validated through in vitro experiments, and the accuracy of the risk label was confirmed in an external dataset. Cluster-B exhibited higher expression levels of DRG, representing lower risk, better prognosis, higher immune cell infiltration, and greater sensitivity to immune checkpoint blockade, whereas Cluster A showed the opposite results. These findings suggest that DRGs may serve as targets for PCa classification and treatment. Additionally, we constructed a nomogram that incorporates DRGs and clinical pathological features, providing clinicians with a quantitative method to assess the prognosis of PCa patients.

CONCLUSION

This study analyzed the potential connection between disulfidptosis and PCa, and established a prognostic model related to disulfidptosis, which holds promise as a valuable tool for the management and treatment of PCa patients.

Cancer cell-selective induction of mitochondrial stress and immunogenic cell death by PT-112 in human prostate cell lines

PT-112 is a novel immunogenic cell death (ICD)-inducing small molecule currently under Phase 2 clinical development, including in metastatic castration-resistant prostate cancer (mCRPC), an immunologically cold and heterogeneous disease state in need of novel therapeutic approaches. PT-112 has been shown to cause ribosome biogenesis inhibition and organelle stress followed by ICD in cancer cells, culminating in anticancer immunity. In addition, clinical evidence of PT-112-driven immune effects has been observed in patient immunoprofiling. Given the unmet need for immune-based therapies in prostate cancer, along with a Phase I study (NCT#02266745) showing PT-112 activity in mCRPC patients, we investigated PT-112 effects in a panel of human prostate cancer cell lines. PT-112 demonstrated cancer cell selectivity, inhibiting cell growth and leading to cell death in prostate cancer cells without affecting the non-tumorigenic epithelial prostate cell line RWPE-1 at the concentrations tested. PT-112 also caused caspase-3 activation, as well as stress features in mitochondria including ROS generation, compromised membrane integrity, altered respiration, and morphological changes. Moreover, PT-112 induced damage-associated molecular pattern (DAMP) release, the first demonstration of ICD in human cancer cell lines, in addition to autophagy initiation across the panel. Taken together, PT-112 caused selective stress, growth inhibition and death in human prostate cancer cell lines. Our data provide additional insight into mitochondrial stress and ICD in response to PT-112. PT-112 anticancer immunogenicity could have clinical applications and is currently under investigation in a Phase 2 mCRPC study.

The Immune Microenvironment in Prostate Cancer: A Comprehensive Review

BACKGROUND

Prostate cancer (PCa) is a malignancy with significant immunosuppressive properties and limited immune activation. This immunosuppression is linked to reduced cytotoxic T cell activity, impaired antigen presentation, and elevated levels of immunosuppressive cytokines and immune checkpoint molecules. Studies demonstrate that cytotoxic CD8+ T cell infiltration correlates with improved survival, while increased regulatory T cells (Tregs) and tumor-associated macrophages (TAMs) are associated with worse outcomes and therapeutic resistance. Th1 cells are beneficial, whereas Th17 cells, producing interleukin-17 (IL-17), contribute to tumor progression. Tumor-associated neutrophils (TANs) and immune checkpoint molecules, such as PD-1/PD-L1 and T cell immunoglobulin-3 (TIM-3) are also linked to advanced stages of PCa. Chemotherapy holds promise in converting the "cold" tumor microenvironment (TME) to a "hot" one by depleting immunosuppressive cells and enhancing tumor immunogenicity.

SUMMARY

This comprehensive review examines the immune microenvironment in PCa, focusing on the intricate interactions between immune and tumor cells in the TME. It highlights how TAMs, Tregs, cytotoxic T cells, and other immune cell types contribute to tumor progression or suppression and how PCa's low immunogenicity complicates immunotherapy.

KEY MESSAGES

The infiltration of cytotoxic CD8+ T cells and Th1 cells correlates with better outcomes, while elevated T regs and TAMs promote tumor growth, metastasis, and resistance. TANs and natural killer (NK) cells exhibit dual roles, with higher NK cell levels linked to better prognoses. Immune checkpoint molecules like PD-1, PD-L1, and TIM-3 are associated with advanced disease. Chemotherapy can improve tumor immunogenicity by depleting T regs and myeloid-derived suppressor cells, offering therapeutic promise.

Time-varying associations of patient and tumor characteristics with cancer survival: an analysis of SEER data across 14 cancer sites, 2004-2017

PURPOSE

Surveillance, Epidemiology, and End Results (SEER) cancer registries provides information about survival duration and cause of death for cancer patients. Baseline demographic and tumor characteristics such as age, sex, race, year of diagnosis, and tumor stage can inform the expected survival time of patients, but their associations with survival may not be constant over the post-diagnosis period.

METHODS

Using SEER data, we examined if there were time-varying associations of patient and tumor characteristics on survival, and we assessed how these relationships differed across 14 cancer sites. Standard Cox proportional hazards models were extended to allow for time-varying associations and incorporated into a competing-risks framework, separately modeling cancer-specific and other-cause deaths. For each cancer site and for each of the five factors, we estimated the relative hazard ratio and absolute hazard over time in the presence of competing risks.

RESULTS

Our comprehensive consideration of patient and tumor characteristics when estimating time-varying hazards showed that the associations of age, tumor stage at diagnosis, and race/ethnicity with risk of death (cancer-specific and other-cause) change over time for many cancers; characteristics of sex and year of diagnosis exhibit some time-varying patterns as well. Stage at diagnosis had the largest associations with survival.

CONCLUSION

These findings suggest that proportional hazards assumptions are often violated when examining patient characteristics on cancer survival post-diagnosis. We discuss several interesting results where the relative hazards are time-varying and suggest possible interpretations. Based on the time-varying associations of several important covariates on survival after cancer diagnosis using a pan-cancer approach, the likelihood of the proportional hazards assumption being met or corresponding interpretation should be considered in survival analyses, as flawed inference may have implications for cancer care and policy.

Exploring the interaction between immune cells in the prostate cancer microenvironment combining weighted correlation gene network analysis and single-cell sequencing: An integrated bioinformatics analysis

BACKGROUND

The rise of treatment resistance and variability across malignant profiles has made precision oncology an imperative in today's medical landscape. Prostate cancer is a prevalent form of cancer in males, characterized by significant diversity in both genomic and clinical characteristics. The tumor microenvironment consists of stroma, tumor cells, and various immune cells. The stromal components and tumor cells engage in mutual communication and facilitate the development of a low-oxygen and pro-cancer milieu by producing cytokines and activating pro-inflammatory signaling pathways.

METHODS

In order to discover new genes associated with tumor cells that interact and facilitate a hypoxic environment in prostate cancer, we conducted a cutting-edge bioinformatics investigation. This included analyzing high-throughput genomic datasets obtained from the cancer genome atlas (TCGA).

RESULTS

A combination of weighted gene co-expression network analysis and single-cell sequencing has identified nine dysregulated immune hub genes (AMACR, KCNN3, MME, EGFR, FLT1, GDF15, KDR, IGF1, and KRT7) that are believed to have significant involvement in the biological pathways involved with the advancement of prostate cancer enviriment. In the prostate cancer environment, we observed the overexpression of GDF15 and KRT7 genes, as well as the downregulation of other genes. Additionally, the cBioPortal platform was used to investigate the frequency of alterations in the genes and their effects on the survival of the patients. The Kaplan-Meier survival analysis indicated that the changes in the candidate genes were associated with a reduction in the overall survival of the patients.

CONCLUSIONS

In summary, the findings indicate that studying the genes and their genomic changes may be used to develop precise treatments for prostate cancer. This approach involves early detection and targeted therapy.

Identification and validation of diagnostic and prognostic biomarkers in prostate cancer based on WGCNA

BACKGROUND

Prostate cancer (PCa) represents a significant health challenge for men, and the advancement of the disease often results in a grave prognosis for patients. Therefore, the identification of biomarkers associated with the diagnosis and prognosis of PCa holds paramount importance in patient health management.

METHODS

The datasets pertaining to PCa were retrieved from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was conducted to investigate the modules specifically associated with the diagnosis of PCa. The hub genes were identified using the LASSO regression analysis. The expression levels of these hub genes were further validated by qRT-PCR experiments. Receiver operating characteristic (ROC) curves and nomograms were employed as evaluative measures for assessing the diagnostic value.

RESULTS

The blue module identified by WGCNA exhibited a strong association with PCa. Six hub genes (SLC14A1, COL4A6, MYOF, FLRT3, KRT15, and LAMB3) were identified by LASSO regression analysis. Further verification confirmed that these six genes were significantly downregulated in tumor tissues and cells. The six hub genes and the nomogram demonstrated substantial diagnostic value, with area under the curve (AUC) values ranging from 0.754 to 0.961. Moreover, patients with low expression levels of these six genes exhibited elevated T/N pathological stage and Gleason score, implying a more advanced disease state. Meanwhile, their progression-free survival (PFS) was observed to be potentially poorer. Finally, a significant association could be observed between the expression of these genes and the dysregulation of immune cells, along with drug sensitivity.

CONCLUSIONS

In summary, our study identified six hub genes, namely SLC14A1, COL4A6, MYOF, FLRT3, KRT15, and LAMB3, which can be utilized to establish a diagnostic model for PCa. The discovery may offer potential molecular targets for clinical diagnosis and treatment of PCa.

Machine learning based androgen receptor regulatory gene-related random forest survival model for precise treatment decision in prostate cancer

Background

It has been demonstrated that aberrant androgen receptor (AR) signaling contributes to the pathogenesis of prostate cancer (PCa). To date, the most efficacious strategy for the treatment of PCa remains to target the AR signaling axis. However, numerous PCa patients still face the issue of overtreatment or undertreatment. The establishment of a precise risk prediction model is urgently needed to distinguish patients with high-risk and select appropriate treatment modalities.

Methods

In this study, a consensus AR regulatory gene-related signature (ARS) was developed by integrating a total of 101 algorithm combinations of 10 machine learning algorithms. We evaluated the value of ARS in predicting patient prognosis and the therapeutic effects of the various treatments. Additionally, we conducted a screening of therapeutic targets and agents for high-risk patients, followed by the verification in vitro and in vivo.

Results

ARS was an independent risk factor for biochemical recurrence and distant metastasis in PCa patients. The enhanced and consistent prognostic predictive capability of ARS across various platforms was confirmed when compared with 44 previously published signatures. More importantly, PCa patients in the ARShigh group benefit more from PARP inhibitors and immunotherapy, while chemotherapy, radiotherapy, and AR-targeted therapy are more effective for ARSlow patients. The results of in silico screening suggest that AURKB could potentially serve as a promising therapeutic target for ARShigh patients.

Conclusions

Collectively, this prediction model based on AR regulatory genes holds great clinical translational potential to solve the dilemma of treatment choice and identify potential novel therapeutic targets in PCa.

Causality investigation among gut microbiota, immune cells, and prostate diseases: a Mendelian randomization study

Background

The gut microbiota has been demonstrated to have a significant role in the pathogenesis and progression of a variety of diseases, including prostate cancer, prostatitis, and benign prostatic hyperplasia. Potential links between prostate diseases, immune cells and the gut microbiota have not been adequately investigated.

Methods

MR studies were conducted to estimate the effects of instrumental variables obtained from genome-wide association studies (GWASs) of 196 gut microbial taxa and 731 immune cells on the risk of prostate diseases. The primary method for analysing causal relationships was inverse variance-weighted (IVW) analysis, and the MR results were validated through various sensitivity analyses.

Results

MR analysis revealed that 28 gut microbiome taxa and 75 immune cell types were significantly associated with prostate diseases. Furthermore, reverse MR analysis did not support a causal relationship between prostate diseases and the intestinal microbiota or immune cells. Finally, the results of the mediation analysis indicated that Secreting Treg % CD4 Treg, Activated & resting Treg % CD4 Treg, and Mo MDSC AC inhibited the role of the class Mollicutes in reducing the risk of PCa. In prostatitis, CD8+ T cells on EM CD8br hinder the increased risk associated with the genus Eubacterium nodatum group. Interestingly, in BPH, CD28- CD25++CD8br AC and CD16-CD56 on HLA DR+ NK promoted the role of the genus Dorea in reducing the risk of BPH.

Conclusion

This study highlights the complex relationships among the gut microbiota, immune cells and prostate diseases. The involvement of the gut microbiota in regulating immune cells to impact prostate diseases could provide novel methods and concepts for its therapy and management.

Identification of circadian clock-related immunological prognostic index and molecular subtypes in prostate cancer

BACKGROUND

Evidence suggests that the circadian clock (CIC) is among the important factors for tumorigenesis. We aimed to provide new insights into CIC-mediated molecular subtypes and gene prognostic indexes for prostate cancer (PCa) patients undergoing radical prostatectomy (RP) or radical radiotherapy (RT).

METHODS

PCa data from TCGA was analyzed to identify differentially expressed genes (DEGs) with significant fold changes and p-values. A prognostic index called CIC-related gene prognostic index (CICGPI) was developed through clustering methods and survival analysis and validated on multiple data sets. The diagnostic accuracy of CICGPI for resistance to chemotherapy and radiotherapy was confirmed. Additionally, the interaction between tumor immune environment and CICGPI score was explored, along with their correlation with prognosis.

RESULTS

TOP2A, APOE, and ALDH2 were used to classify the PCa patients into two subtypes. Cluster 2 had a higher risk of biochemical recurrence (BCR) than cluster 1 for PCa patients undergoing RP or RT. A CIC-related gene prognostic index (CICGPI) was constructed using the above three genes for PCa patents in the TCGA database. The CICGPI score showed good prognostic value in the TCGA database and was externally confirmed by PCa patients in GSE116918, MSKCC2010 and GSE46602. In addition, the CICGPI score had a certain and high diagnostic accuracy for tumor chemoresistance (AUC: 0.781) and radioresistance (AUC: 0.988). For gene set variation analysis, we observed that both beta alanine metabolism and limonene and pinene degradation were upregulated in cluster 1 for PCa patients undergoing RP or RT. For PCa patients undergoing RP, cell cycle, homologous recombination, mismatch repair, and DNA replication were upregulated in cluster 2. A strongly positive relationship between cancer-related fibroblasts and CICGPI score was observed in PCa patients undergoing RP or RT. Moreover, a high density of CAFs was highly closely associated with poorer BCR-free survival of PCa patients.

CONCLUSIONS

In this study, we established CIC-related immunological prognostic index and molecular subtypes, which might be useful for the clinical practice.

Identification of miRNA signature in cancer-associated fibroblast to predict recurrent prostate cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) are one of the major components of prostate stromal cells, which play a crucial part in tumor development and treatment resistance. This study aimed to establish a model of CAFs-related microRNAs (miRNAs) to assess prognostic differences, tumor microenvironments, and screening of anticancer drugs by integrating data from single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (buRNA-seq).

METHODS

scRNA-seq and buRNA-seq data of primary prostate cancer (PCa) were downloaded from Gene Expression Omnibus and The Cancer Genome Atlas databases. Statistical methods including Least absolute shrinkage and selection operator (Lasso), Lasso penalized, Random Forest, Random Forest Combination, and Support Vector Machine (SVM) were performed to select hub miRNAs. Pathway analyses and assessment of infiltrating immune cells were conducted using Gene Set Enrichment Analysis and the CIBERSORT algorithm. The expression of CAFs-related miRNAs in fibroblast cell lines were validated through quantitative real-time PCR. Cell Counting Kit 8 (CCK8), wound-healing, clone formation, and cell migration assays were used to explore cell proliferation, growth, and migration in vitro. A mouse xenograft model was established to investigate the effect of CAFs on tumor growth in vivo.

RESULTS

Through single-cell transcriptomics analysis in 34 PCa patients, 89 CAFs-related mRNAs were identified. A prognostic model based on 9 CAFs-related miRNAs (hsa-miR-1258, hsa-miR-133b, hsa-miR-222-3p, hsa-miR-145-3p, hsa-miR-493-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-106b-5p, and hsa-miR-191-5p) was established to predict biochemical recurrence (BCR). We have determined through two prediction methods that NVP-TAE684 may be the optimal targeted therapy drug for treating CAFs. Downregulation of hsa-miR-106b-5p in CAFs significantly suppressed cell proliferation, migration, and colony formation in vitro. In vivo studies using a xenograft model further confirmed that hsa-miR-106b-5p downregulation significantly reduced tumor growth.

CONCLUSION

Our findings conducted an integrated bioinformatic analysis to develop a CAFs-related miRNAs model that provides prognostic insights into individualized and precise treatment for prostate adenocarcinoma patients. Downregulation of miR-106b-5p in CAFs significantly suppressed tumor growth, suggesting a potential therapeutic target for cancer treatment.

Machine learning-driven mast cell gene signatures for prognostic and therapeutic prediction in prostate cancer

Background

The role of Mast cells has not been thoroughly explored in the context of prostate cancer's (PCA) unpredictable prognosis and mixed immunotherapy outcomes. Our research aims to employs a comprehensive computational methodology to evaluate Mast cell marker gene signatures (MCMGS) derived from a global cohort of 1091 PCA patients. This approach is designed to identify a robust biomarker to assist in prognosis and predicting responses to immunotherapy.

Methods

This study initially identified mast cell-associated biomarkers from prostate adenocarcinoma (PRAD) patients across six international cohorts. We employed a variety of machine learning techniques, including Random Forest, Support Vector Machine (SVM), Lasso regression, and the Cox Proportional Hazards Model, to develop an effective MCMGS from candidate genes. Subsequently, an immunological assessment of MCMGS was conducted to provide new insights into the evaluation of immunotherapy responses and prognostic assessments. Additionally, we utilized Gene Set Enrichment Analysis (GSEA) and pathway analysis to explore the biological pathways and mechanisms associated with MCMGS.

Results

MCMGS incorporated 13 marker genes and was successful in segregating patients into distinct high- and low-risk categories. Prognostic efficacy was confirmed by survival analysis incorporating MCMGS scores, alongside clinical parameters such as age, T stage, and Gleason scores. High MCMGS scores were correlated with upregulated pathways in fatty acid metabolism and β-alanine metabolism, while low scores correlated with DNA repair mechanisms, homologous recombination, and cell cycle progression. Patients classified as low-risk displayed increased sensitivity to drugs, indicating the utility of MCMGS in forecasting responses to immune checkpoint inhibitors.

Conclusion

The combination of MCMGS with a robust machine learning methodology demonstrates considerable promise in guiding personalized risk stratification and informing therapeutic decisions for patients with PCA.

Prostate cancer stem cells and their targeted therapies

Prostate cancer (PCa) is the most common malignancy among men worldwide. Through androgen receptor signaling inhibitor (ARSI) treatment, patients eventually succumb to castration-resistant prostate cancer (CRPC). For this, the prostate cancer stem cells (PCSCs), as a minor population of tumor cells that can promote tumor relapse, ARSI resistance, and disease progression, are gaining attention. Therefore, specific therapy targeting PCSCs has momentum. This study reviewed the identification and characterization of PCSCs and PCSC-based putative biomarkers and summarized their mechanisms of action. We further discussed clinical trials of novel therapeutic interventions focused on PCSC-related pathways, the PCSC microenvironment, cutting-edge miRNA therapy, and immunotherapy approaches from a mechanistic standpoint. This review provides updated insights into PCSC plasticity, identifying new PCSC biomarkers and optimized treatments for patients with advanced PCa.

Oncogene goosecoid is transcriptionally regulated by E2F1 and correlates with disease progression in prostate cancer

BACKGROUND

Although some well-established oncogenes are involved in cancer initiation and progression such as prostate cancer (PCa), the long tail of cancer genes remains to be defined. Goosecoid ( GSC ) has been implicated in cancer development. However, the comprehensive biological role of GSC in pan-cancer, specifically in PCa, remains unexplored. The aim of this study was to investigate the role of GSC in PCa development.

METHODS

We performed a systematic bioinformatics exploration of GSC using datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, Gene Expression Omnibus, German Cancer Research Center, and our in-house cohorts. First, we evaluated the expression of GSC and its association with patient prognosis, and identified GSC -relevant genetic alterations in cancers. Further, we focused on the clinical characterization and prognostic analysis of GSC in PCa. To understand the transcriptional regulation of GSC by E2F transcription factor 1 ( E2F1 ), we performed chromatin immunoprecipitation quantitative polymerase chain reaction (qPCR). Functional experiments were conducted to validate the effect of GSC on the tumor cellular phenotype and sensitivity to trametinib.

RESULTS

GSC expression was elevated in various tumors and significantly correlated with patient prognosis. The alterations of GSC contribute to the progression of various tumors especially in PCa. Patients with PCa and high GSC expression exhibited worse progression-free survival and biochemical recurrence outcomes. Further, GSC upregulation in patients with PCa was mostly accompanied with higher Gleason score, advanced tumor stage, lymph node metastasis, and elevated prostate-specific antigen (PSA) levels. Mechanistically, the transcription factor, E2F1 , stimulates GSC by binding to its promoter region. Detailed experiments further demonstrated that GSC acted as an oncogene and influenced the response of PCa cells to trametinib treatment.

CONCLUSIONS

GSC was highly overexpressed and strongly correlated with patient prognosis in PCa. We found that GSC , regulated by E2F1 , acted as an oncogene and impeded the therapeutic efficacy of trametinib in PCa.

Insights into immune microenvironment and therapeutic targeting in androgen-associated prostate cancer subtypes

Prostate cancer, one of the most prevalent malignancies among men worldwide, is intricately linked with androgen signaling, a key driver of its pathogenesis and progression. Understanding the diverse expression patterns of androgen-responsive genes holds paramount importance in unraveling the biological intricacies of this disease and prognosticating patient outcomes. In this study, utilizing consensus clustering analysis based on the expression profiles of androgen-responsive genes, prostate cancer patients from the TCGA database were stratified into two distinct subtypes, denoted as C1 and C2. Notably, the C1 subtype demonstrates a significant upregulation of certain genes, such as CGA and HSD17B12, along with a shorter progression-free survival duration, indicating a potentially unfavorable prognosis. Further analyses elucidated the immune infiltration disparities, mutation landscapes, and gene functional pathways characteristic of each subtype. Through integrated bioinformatics approaches and machine learning techniques, key genes such as BIRC5, CENPA, and MMP11 were identified as potential therapeutic targets, providing novel insights into tailored treatment strategies. Additionally, single-cell transcriptome analysis shed light on the heterogeneous expression patterns of these genes across different cell types within the tumor microenvironment. Furthermore, virtual screening identified candidate drugs targeting the BIRC5 receptor, offering promising avenues for drug development. Collectively, these findings deepen our understanding of prostate cancer biology, paving the way for personalized therapeutic interventions and advancing the quest for more effective treatments in prostate cancer management.

Single-cell and bulk RNA-sequencing reveals mitosis-involved gene HAUS1 is a promising indicator for predicting prognosis and immune responses in prostate adenocarcinoma (PRAD)

It was imperative to identify latent biomarkers pertinent to malignancies, given the pivotal role targeted molecular therapies play in tumor treatment investigations. This study aimed to assess the validity of HAUS1 as an indicator for survival prognosis and immune responses in prostate adenocarcinoma (PRAD) via single-cell and bulk RNA-sequencing. Related data on HAUS1 expression in PRAD were obtained from online databases, followed by comprehensive analyses to delineate its associations with survival prognosis, implicated pathways, and immune responses. Besides, the expression pattern of HAUS1 in PRAD was also verified in vitro, by using qRT-PCR, Western blot analysis, and immunohistochemistry. We found HAUS1 was downregulated in PRAD compared with normal tissues, as verified in vitro by qRT-PCR, Western blot, and immunohistochemistry (p < 0.05). Single-cell RNA-sequencing analysis indicated that HAUS1 had relatively higher expressions in B cells, Mono/Macro cells, and Endothelial cells compared with other cell types. Cox regression analysis revealed HAUS1 could serve as an independent indicator for the overall survival prognosis of PRAD (p < 0.05). Spearman correlation analyses revealed HAUS1 was closely related to the tumor microenvironment, immune cell infiltration levels, immune checkpoints, and immune cell pathways (p < 0.05). Furthermore, HAUS1 expression was found to be closely related to the immunotherapeutic response of patients receiving clinical intervention (p < 0.05). Collectively, our findings underscored the significant role of HAUS1 in PRAD prognosis and immune response, thereby presenting a novel and promising avenue for investigating the clinical utility of immunotherapy in PRAD.

Evaluating Immune Checkpoint Blockade in Metastatic Castration-Resistant Prostate Cancers with Deleterious CDK12 Alterations in the Phase 2 IMPACT Trial

PURPOSE

CDK12 inactivation in metastatic castration-resistant prostate cancer (mCRPC) may predict immunotherapy responses. This phase 2 trial evaluated the efficacy of immune checkpoint inhibitor (ICI) therapy in patients with CDK12-altered mCRPC.

PATIENTS AND METHODS

Eligible patients had mCRPC with deleterious CDK12 alterations and any prior therapies except ICI. Cohort A received ipilimumab (1 mg/kg) with nivolumab (3 mg/kg) every 3 weeks for up to four cycles, followed by nivolumab 480 mg every 4 weeks. Cohort C received nivolumab alone 480 mg every 4 weeks. Patients with CDK12-altered nonprostate tumors were enrolled in cohort B and not reported. The primary endpoint was a 50% reduction in PSA (PSA50). Key secondary endpoints included PSA progression-free survival, overall survival, objective response rate, and safety.

RESULTS

PSA was evaluable in 23 patients in cohort A and 14 in cohort C. Median lines of prior therapy were two in cohorts A and C, including any prior novel hormonal agent (74% and 79%) and chemotherapy (57% and 36%). The PSA50 rate was 9% [95% confidence interval (CI), 1%-28%] in cohort A with two responders; neither had microsatellite instability or a tumor mutational burden >10 mutations/megabase. No PSA50 responses occurred in cohort C. Median PSA progression-free survival was 7.0 months (95% CI, 3.6-11.4) in cohort A and 4.5 months (95% CI, 3.4-13.8) in cohort C. Median overall survival was 9.0 months (95% CI, 6.2-12.3) in cohort A and 13.8 months (95% CI, 3.6-not reached) in cohort C.

CONCLUSIONS

There was minimal activity with ICI therapy in patients with CDK12-altered mCRPC.

Characteristics, clinical significance, and cancer immune interactions of lipid metabolism in prostate cancer

Background

The relationship between lipid metabolism, immune response, and immunotherapy in prostate cancer (PCa) is closely intertwined, and targeted intervention in lipid metabolism may facilitate the success of anticancer immunotherapy. This research attempted to explore effective immunotherapy for PCa.

Methods

We obtained RNA sequencing (RNA-seq) data for PCa patients from the UCSC Xena platform. Data analysis of differentially expressed genes (DEGs) was performed using package limma in R. Then, DEGs were subjected to enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The Human Protein Atlas (HPA) database was conducted to validate the protein expression of the up-regulated lipid metabolism related genes (LMRGs) between PCa tissues and normal prostate tissues. And then we identified critical transcription factors (TFs), LMRGs and miRNA by constructing a regulatory network of TF-gene-miRNA. Furthermore, we determined the high and low groups based on the score of lipid metabolism enrichment. The hallmark gene sets were derived from gene expression profiles using the gene set variation analysis (GSVA) R package. Finally, we conducted immune infiltration analysis and drug sensitivity analysis.

Results

Immune response and lipid metabolism have undergone significant changes in PCa and paracancerous tissues compared to normal tissues. A total of 21 LMRGs were differentially up-regulated in PCa. The TF-gene-miRNA network showed that PLA2G7, TWIST1, and TRIB3 may be the key genes that elevated lipid metabolism in PCa. The high group had more infiltration of B cell memory, macrophage M0, macrophage M1, and myeloid dendritic cell resting, and the low group had more infiltration of B cell plasma, monocyte, myeloid dendritic cell activated, and mast cell resting. The majority of checkpoint genes exhibited high expression levels in the low group. Lipid metabolism was remarkedly correlated with drug sensitivity.

Conclusions

The analysis of lipid metabolism and related genes has revealed a complex regulatory mechanism that has a significant influence on immune response, immunotherapy, and medication guidance for patients with PCa.

Keywords

Prostate cancer (PCa); lipid metabolism; cancer immune; RNA sequencing (RNA-seq).

Dual immunotherapy alternating with anti-PD-1 antibody plus liposomal doxorubicin show good efficacy in prostate epithelioid hemangioendothelioma: a case report

Epithelioid hemangioendothelioma is a rare vascular malignancy, and currently, there is no standard treatment regimen for this disease and existing treatment options have limited efficacy. In this case report, we present a patient with lung and lymph node metastases from prostate epithelioid hemangioendothelioma who achieved a significant partial response. This was accomplished through alternating nivolumab therapy with ipilimumab and liposomal doxorubicin, resulting in a progression-free-survival more than 6 months to date. The treatment was well-tolerated throughout. Our report suggests that dual immunotherapy alternating with anti-PD-1antibody plus doxorubicin may be a potential treatment modality for epithelioid hemangioendothelioma. However, larger sample studies are necessary to ascertain the effectiveness of this treatment strategy and it is essential to continue monitoring this patient to sustain progression-free survival and overall survival.

Advancements in nanomedicine: Precision delivery strategies for male pelvic malignancies - Spotlight on prostate and colorectal cancer

BACKGROUND

Pelvic malignancies consistently pose significant global health challenges, adversely affecting the well-being of the male population. It is anticipated that clinicians will continue to confront these cancers in their practice. Nanomedicine offers promising strategies that revolutionize the treatment of male pelvic malignancies by providing precise delivery methods that aim to improve the efficacy of therapeutic outcomes while minimizing side effects. Nanoparticles are designed to encapsulate therapeutic agents and selectively target cancer cells. They can also be loaded with theragnostic agents, enabling multifunctional capabilities.

OBJECTIVE

This review aims to summarize the latest nanomedicine research into clinical applications, focusing on nanotechnology-based treatment strategies for male pelvic malignancies, encompassing chemotherapy, radiotherapy, immunotherapy, and other cutting-edge therapies. The review is structured to assist physicians, particularly those with limited knowledge of biochemistry and bioengineering, in comprehending the functionalities and applications of nanomaterials.

METHODS

Multiple databases, including PubMed, the National Library of Medicine, and Embase, were utilized to locate and review recently published articles on advancements in nano-drug delivery for prostate and colorectal cancers.

CONCLUSION

Nanomedicine possesses considerable potential in improving therapeutic outcomes and reducing adverse effects for male pelvic malignancies. Through precision delivery methods, this emerging field presents innovative treatment modalities to address these challenging diseases. Nevertheless, the majority of current studies are in the preclinical phase, with a lack of sufficient evidence to fully understand the precise mechanisms of action, absence of comprehensive pharmacotoxicity profiles, and uncertainty surrounding long-term consequences.

Sex differences in cancer and immunotherapy outcomes: the role of androgen receptor

Across the wide range of clinical conditions, there exists a sex imbalance where biological females are more prone to autoimmune diseases and males to some cancers. These discrepancies are the combinatory consequence of lifestyle and environmental factors such as smoking, alcohol consumption, obesity, and oncogenic viruses, as well as other intrinsic biological traits including sex chromosomes and sex hormones. While the emergence of immuno-oncology (I/O) has revolutionised cancer care, the efficacy across multiple cancers may be limited because of a complex, dynamic interplay between the tumour and its microenvironment (TME). Indeed, sex and gender can also influence the varying effectiveness of I/O. Androgen receptor (AR) plays an important role in tumorigenesis and in shaping the TME. Here, we lay out the epidemiological context of sex disparity in cancer and then review the current literature on how AR signalling contributes to such observation via altered tumour development and immunology. We offer insights into AR-mediated immunosuppressive mechanisms, with the hope of translating preclinical and clinical evidence in gender oncology into improved outcomes in personalised, I/O-based cancer care.

Icaritin-curcumol activates CD8+ T cells through regulation of gut microbiota and the DNMT1/IGFBP2 axis to suppress the development of prostate cancer

BACKGROUND

Prostate cancer (PCa) incidence and mortality rates are rising. Our previous research has shown that the combination of icariin (ICA) and curcumol (CUR) induced autophagy and ferroptosis in PCa cells, and altered lipid metabolism. We aimed to further explore the effects of the combination of ICA and CUR on gut microbiota, metabolism, and immunity in PCa.

METHODS

A mouse subcutaneous RM-1 cell tumor model was established. 16 S rRNA sequencing was performed to detect changes in fecal gut microbiota. SCFAs in mouse feces, and the effect of ICA-CUR on T-cell immunity, IGFBP2, and DNMT1 were examined. Fecal microbiota transplantation (FMT) was conducted to explore the mechanism of ICA-CUR. Si-IGFBP2 and si/oe-DNMT1 were transfected into RM-1 and DU145 cells, and the cells were treated with ICA-CUR to investigate the mechanism of ICA-CUR on PCa development.

RESULTS

After treatment with ICA-CUR, there was a decrease in tumor volume and weight, accompanied by changes in gut microbiota. ICA-CUR affected SCFAs and DNMT1/IGFBP2/EGFR/STAT3/PD-L1 pathway. ICA-CUR increased the positive rates of CD3+CD8+IFN-γ, CD3+CD8+Ki67 cells, and the levels of IFN-γ and IFN-α in the serum. After FMT (with donors from the ICA-CUR group), tumor volume and weight were decreased. SCFAs promote tumor development and the expression of IGFBP2. In vitro, DNMT1/IGFBP2 promotes cell migration and proliferation. ICA-CUR inhibits the expression of DNMT1/IGFBP2.

CONCLUSIONS

ICA-CUR mediates the interaction between gut microbiota and the DNMT1/IGFBP2 axis to inhibit the progression of PCa by regulating immune response and metabolism, suggesting a potential therapeutic strategy for PCa.

Comprehensive analysis of macrophage-related genes in prostate cancer by integrated analysis of single-cell and bulk RNA sequencing

Macrophages, as essential components of the tumor immune microenvironment (TIME), could promote growth and invasion in many cancers. However, the role of macrophages in tumor microenvironment (TME) and immunotherapy in PCa is largely unexplored at present. Here, we investigated the roles of macrophage-related genes in molecular stratification, prognosis, TME, and immunotherapeutic response in PCa. Public databases provided single-cell RNA sequencing (scRNA-seq) and bulk RNAseq data. Using the Seurat R package, scRNA-seq data was processed and macrophage clusters were identified automatically and manually. Using the CellChat R package, intercellular communication analysis revealed that tumor-associated macrophages (TAMs) interact with other cells in the PCa TME primarily through MIF - (CD74+CXCR4) and MIF - (CD74+CD44) ligand-receptor pairs. We constructed coexpression networks of macrophages using the WGCNA to identify macrophage-related genes. Using the R package ConsensusClusterPlus, unsupervised hierarchical clustering analysis identified two distinct macrophage-associated subtypes, which have significantly different pathway activation status, TIME, and immunotherapeutic efficacy. Next, an 8-gene macrophage-related risk signature (MRS) was established through the LASSO Cox regression analysis with 10-fold cross-validation, and the performance of the MRS was validated in eight external PCa cohorts. The high-risk group had more active immune-related functions, more infiltrating immune cells, higher HLA and immune checkpoint gene expression, higher immune scores, and lower TIDE scores. Finally, the NCF4 gene has been identified as the hub gene in MRS using the "mgeneSim" function.

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Causal relationship between immune cells and prostate cancer: a Mendelian randomization study

Introduction

Despite the abundance of research indicating the participation of immune cells in prostate cancer development, establishing a definitive cause-and-effect relationship has proven to be a difficult undertaking.

Methods

This study employs Mendelian randomization (MR), leveraging genetic variables related to immune cells from publicly available genome-wide association studies (GWAS), to investigate this association. The primary analytical method used in this study is inverse variance weighting (IVW) analysis. Comprehensive sensitivity analyses were conducted to assess the heterogeneity and horizontal pleiotropy of the results.

Results

The study identifies four immune cell traits as causally contributing to prostate cancer risk, including CD127- CD8+ T cell %CD8+ T cell (OR = 1.0042, 95%CI:1.0011-1.0073, p = 0.0077), CD45RA on CD39+ resting CD4 regulatory T cell (OR = 1.0029, 95%CI:1.0008-1.0050, p = 0.0065), CD62L- Dendritic Cell Absolute Count (OR = 1.0016; 95%CI:1.0005-1.0026; p = 0.0039), CX3CR1 on CD14+ CD16- monocyte (OR = 1.0024, 95%CI:1.0007-1.0040, p = 0.0060). Additionally, two immune cell traits are identified as causally protective factors: CD4 on monocyte (OR = 0.9975, 95%CI:0.9958-0.9992, p = 0.0047), FSC-A on plasmacytoid Dendritic Cell (OR = 0.9983, 95%CI:0.9970-0.9995, p = 0.0070). Sensitivity analyses indicated no horizontal pleiotropy.

Discussion

Our MR study provide evidence for a causal relationship between immune cells and prostate cancer, holding implications for clinical diagnosis and treatment.

Targeting the prostate tumor microenvironment by plant-derived natural products

Prostate cancer is among the most common malignancies for men, with limited therapy options for last stages of the tumor. There are some different options for treatment and control of prostate tumor growth. However, targeting some specific molecules and cells within tumors has been attracted interests in recent years. The tumor microenvironment (TME) has an important role in the initiation of various malignancies, which can also expand the progression of tumor and facilitate invasion of malignant cells. By regulating immune responses and distinct changes in the metabolism of cells in the tumor, TME has substantial effects in the resistance of cancer cells to therapy. TME in various solid cancers like prostate cancer includes various cells, including cancer cells, supportive stromal cells, immunosuppressive cells, and anticancer inflammatory cells. Natural products including herbal-derived agents and also other natural compounds have been well studied for their anti-tumor potentials. These compounds may modulate various signaling pathways involved in TME, such as immune responses, the metabolism of cells, epigenetics, angiogenesis, and extracellular matrix (ECM). This paper provides a review of the current knowledge of prostate TME and complex interactions in this environment. Additionally, the potential use of natural products and also nanoparticles loaded with natural products as therapeutic adjuvants on different cells and therapeutic targets within prostate TME will be discussed.

Natural Killer Cell Infiltration in Prostate Cancers Predict Improved Patient Outcomes

BACKGROUND

Natural killer (NK) cells are non-antigen specific innate immune cells that can be redirected to targets of interest using multiple strategies, although none are currently FDA-approved. We sought to evaluate NK cell infiltration into tumors to develop an improved understanding of which histologies may be most amenable to NK cell-based therapies currently in the developmental pipeline.

METHODS

DNA (targeted/whole-exome) and RNA (whole-transcriptome) sequencing was performed from tumors from 45 cancer types (N = 90,916 for all cancers and N = 3365 for prostate cancer) submitted to Caris Life Sciences. NK cell fractions and immune deconvolution were inferred from RNA-seq data using quanTIseq. Real-world overall survival (OS) and treatment status was determined and Kaplan-Meier estimates were calculated. Statistical significance was determined using X2 and Mann-Whitney U tests, with corrections for multiple comparisons where appropriate.

RESULTS

In both a pan-tumor and prostate cancer (PCa) -specific setting, we demonstrated that NK cells represent a substantial proportion of the total cellular infiltrate (median range 2-9% for all tumors). Higher NK cell infiltration was associated with improved OS in 28 of 45 cancer types, including (PCa). NK cell infiltration was negatively correlated with common driver mutations and androgen receptor variants (AR-V7) in primary prostate biopsies, while positively correlated with negative immune regulators. Higher levels of NK cell infiltration were associated with patterns consistent with a compensatory anti-inflammatory response.

CONCLUSIONS

Using the largest available dataset to date, we demonstrated that NK cells infiltrate a broad range of tumors, including both primary and metastatic PCa. NK cell infiltration is associated with improved PCa patient outcomes. This study demonstrates that NK cells are capable of trafficking to both primary and metastatic PCa and are a viable option for immunotherapy approaches moving forward. Future development of strategies to enhance tumor-infiltrating NK cell-mediated cytolytic activity and activation while limiting inhibitory pathways will be key.

Divergent immune microenvironments in two tumor nodules from a patient with mismatch repair-deficient prostate cancer

Patients with prostate cancer (PC) generally do not respond favorably to immune checkpoint inhibitors, which may be due to a low abundance of tumor-infiltrating lymphocytes even when mutational load is high. Here, we identified a patient who presented with high-grade primary prostate cancer with two adjacent tumor nodules. While both nodules were mismatch repair-deficient (MMRd), exhibited pathogenic MSH2 and MSH6 alterations, had a high tumor mutational burden (TMB), and demonstrated high microsatellite instability (MSI), they had markedly distinct immune phenotypes. The first displayed a dense infiltrate of lymphocytes ("hot nodule"), while the second displayed significantly fewer infiltrating lymphocytes ("cold nodule"). Whole-exome DNA analysis found that both nodules shared many identical mutations, indicating that they were derived from a single clone. However, the cold nodule appeared to be sub-clonal relative to the hot nodule, suggesting divergent evolution of the cold nodule from the hot nodule. Whole-transcriptome RNA analysis found that the cold nodule demonstrated lower expression of genes related to antigen presentation (HLA) and, paradoxically, classical tumor immune tolerance markers such as PD-L1 (CD274) and CTLA-4. Immune cell deconvolution suggested that the hot nodule was enriched not only in CD8+ and CD4 + T lymphocytes, but also in M1 macrophages, activated NK cells, and γδ T cells compared to the cold nodule. This case highlights that MMRd/TMB-high PC can evolve to minimize an anti-tumor immune response, and nominates downregulation of antigen presentation machinery (HLA loss) as a potential mechanism of adaptive immune evasion in PC.

Organoids: An Emerging Precision Medicine Model for Prostate Cancer Research

Prostate cancer (PCa) has been known as the most prevalent cancer disease and the second leading cause of cancer mortality in men almost all over the globe. There is an urgent need for establishment of PCa models that can recapitulate the progress of genomic landscapes and molecular alterations during development and progression of this disease. Notably, several organoid models have been developed for assessing the complex interaction between PCa and its surrounding microenvironment. In recent years, PCa organoids have been emerged as powerful in vitro 3D model systems that recapitulate the molecular features (such as genomic/epigenomic changes and tumor microenvironment) of PCa metastatic tumors. In addition, application of organoid technology in mechanistic studies (i.e., for understanding cellular/subcellular and molecular alterations) and translational medicine has been recognized as a promising approach for facilitating the development of potential biomarkers and novel therapeutic strategies. In this review, we summarize the application of PCa organoids in the high-throughput screening and establishment of relevant xenografts for developing novel therapeutics for metastatic, castration resistant, and neuroendocrine PCa. These organoid-based studies are expected to expand our knowledge from basic research to clinical applications for PCa diseases. Furthermore, we also highlight the optimization of PCa cultures and establishment of promising 3D organoid models for in vitro and in vivo investigations, ultimately facilitating mechanistic studies and development of novel clinical diagnosis/prognosis and therapies for PCa.

Tumor-associated macrophages and PD-L1 in prostate cancer: a possible key to unlocking immunotherapy efficacy

PURPOSE

Prostate cancer (PCa) is often considered as a "cold" tumor with low responsiveness to immunotherapy. Recent evidence suggests the activation of specific immune cells, such as tumor-associated macrophages (TAMs), could potentially influence the efficacy of immunotherapy in PCa. However, the relationship between TAMs and PD-L1, a significant regulator in immunotherapy, within PCa remains unexplored.

METHODS

In this study, we assessed TAM infiltration and PD-L1 expression levels in a local cohort of 95 PCa tissue samples and two publicly available PCa datasets. We employed a combination of bioinformatics and experimental techniques, including gene set enrichment analysis, CIBERSORTx, tissue microarray, immunohistochemistry staining, and analysis of single-cell sequencing datasets, to provide a comprehensive understanding of the association between PD-L1 and TAMs in the PCa microenvironment.

RESULTS

The study showed that CD68+ TAMs and CD163+ TAMs (M2-TAMs) were more abundant in the tumor microenvironment than in non-cancerous surrounding tissues. The infiltration of CD163+ TAMs was significantly associated with the Gleason score and risk stratification of PCa. Importantly, elevated PD-L1 expression correlated significantly with high infiltration of CD163+ TAMs. Furthermore, patients displaying high levels of CD163+ TAMs and PD-L1 expression exhibited shorter times to biochemical recurrence-free survival.

CONCLUSION

Our study suggests that CD163+ TAMs are closely associated with PD-L1 expression and can act as a valuable prognostic indicator for PCa. The high infiltration of M2-TAMs, coupled with the overexpression of PD-L1, may contribute to immune escape mechanisms in PCa, thereby influencing disease prognosis.

Expression and Clinical Significance of Non B Cell-Derived Immunoglobulins in the Urinary System and Male Reproductive System

The urinary system comprises kidneys, ureters, bladder, and urethra with its primary function being excretion, referring to the physiological process of transporting substances that are harmful or surplus out of the body. The male reproductive system consists of gonads (testis), vas deferens, and accessory glands such as the prostate. According to classical immunology theory, the tissues and organs mentioned above are not thought to produce immunoglobulins (Igs), and any Ig present in the relevant tissues under physiological and pathological conditions is believed to be derived from B cells. For instance, most renal diseases are associated with uncontrolled inflammation caused by pathogenic Ig deposited in the kidney. Generally, these pathological Igs are presumed to be produced by B cells. Recent studies have demonstrated that renal parenchymal cells can produce and secrete Igs, including IgA and IgG. Glomerular mesangial cells can express and secrete IgA, which is associated with cell survival and adhesion. Likewise, human podocytes demonstrate the ability to produce and secrete IgG, which is related to cell survival and adhesion. Furthermore, renal tubular epithelial cells also express IgG, potentially involved in the epithelial-mesenchymal transition (EMT). More significantly, renal cell carcinoma, bladder cancer, and prostate cancer have been revealed to express high levels of IgG, which promotes tumour progression. Given the widespread Ig expression in the urinary and male reproductive systems, continued efforts to elucidate the roles of Igs in renal physiological and pathological processes are necessary.

Cuproptosis Regulates Microenvironment and Affects Prognosis in Prostate Cancer

Current immunotherapy for prostate cancer is still in the stage of clinical trials. This delay is thought to be caused by an unclear regulatory mechanism of the immune microenvironment, which makes it impossible to distinguish patients suitable for immunotherapy. Cuprotosis may be related to the heterogeneity of immune microenvironment, which was regarded as a new copper-dependent cell death mode, was proposed, and gain attention. We explored for the first time the relationship between cuprotosis and the immune microenvironment of prostate cancer and constructed cuprotosis score. RNA sequencing data sets for prostate cancer were downloaded from public databases. Consensus clustering was applied to distinguish cuprotosis phenotype based on the expression of cuproptosis-related genes (CRGs) identified as prognostic factors. Genomic phenotypes of CRG clusters were depicted via consensus clustering. Cuprotosis score was established on the basis of differentially expressed genes (DEGs) identified as prognostic factors via principal component analysis. Cuprotosis score = the first principal component of prognostic factors + the second principal component of prognostic factors. The value of cuproptosis score in predicting prognosis and immunotherapy response was evaluated. PDHA1 (HR = 3.86, P < 0.001) and GLS (HR = 1.75, P = 0.018) were risk factors for prognosis of prostate cancer patients, while DBT (HR = 0.66, P = 0.048) was a favorable factor for prognosis of prostate cancer patients. CRG clusters had different prognosis and immune cell infiltration. So as gene clusters. Prostate cancer patients with low cuprotosis score showed better prognosis for biochemical relapse-free survival. Cuprotosis score is accompanied with high immune score and Gleason score. As cuprotosis genes, PDHA1, GLS, and DBT were identified as independent prognostic factors of prostate cancer. Cuprotosis score was established via principal component analysis of PDHA1, GLS, and DBT, which can be used as a predictor of prognosis and immunotherapy response of prostate cancer patients, and can characterize immune cells infiltration in tumors. Cuproptosis was involved in the regulation of immune microenvironment, which may depend on the effect of tricarboxylic acid cycle. Our study provided clues to reveal the relationship between copper death and immune microenvironment, highlighted the clinical significance of cuproptosis, and provided a reference for the development of personalized immunotherapy.

Hyperoside Inhibits RNF8-mediated Nuclear Translocation of β-catenin to Repress PD-L1 Expression and Prostate Cancer

BACKGROUND

Hyperoside is a flavonol glycoside isolated from Hypericum perforatum L. that has inhibitory effects on cancer cells; however, its effects on prostate cancer (PCa) remain unclear. Therefore, we studied the anti-PCa effects of hyperoside and its underlying mechanisms in vitro and in vivo.

AIM

This study aimed to explore the mechanism of hyperoside in anti-PCa.

METHODS

3-(4,5-Dimethyl-2-Thiazolyl)-2,5-Diphenyl Tetrazolium Bromide (MTT), transwell, and flow cytometry assays were used to detect PCa cell growth, invasion, and cell apoptosis. Immunoblot analysis, immunofluorescence, immunoprecipitation, and quantitative real-time PCR (qRT-PCR) were used to analyze the antitumor mechanism of hyperoside.

RESULTS

Hyperoside inhibited PCa cell growth, invasion, and cell cycle and induced cell apoptosis. Furthermore, RING finger protein 8 (RNF8), an E3 ligase that assembles K63 polyubiquitination chains, was predicted to be a direct target of hyperoside and was downregulated by hyperoside. Downregulation of RNF8 by hyperoside impeded the nuclear translocation of β-catenin and disrupted the Wnt/β-catenin pathway, which reduced the expression of the target genes c-myc, cyclin D1, and programmed death ligand 1 (PD-L1). Decreased PD-L1 levels contributed to induced immunity in Jurkat cells in vitro. Finally, in vivo studies demonstrated that hyperoside significantly reduced tumor size, inhibited PD-L1 and RNF8 expression, and induced apoptosis in tumor tissues of a subcutaneous mouse model.

CONCLUSION

Hyperoside exerts its anti-PCa effect by reducing RNF8 protein, inhibiting nuclear translocation of β-catenin, and disrupting the Wnt/β-catenin pathway, in turn reducing the expression of PD-L1 and improving Jurkat cell immunity.

Silencing HOXC13 exerts anti-prostate cancer effects by inducing DNA damage and activating cGAS/STING/IRF3 pathway

BACKGROUND

Advanced prostate cancer (PCa) will develop into castration-resistant prostate cancer (CRPC) and lead to poor prognosis. As the primary subtype of CRPC, CRPC-AR accounts for the major induction of PCa heterogeneity. CRPC-AR is mainly driven by 25 transcription factors (TFs), which we speculate may be the key factors driving PCa toward CRPC. Therefore, it is necessary to clarify the key regulator and its molecular mechanism mediating PCa progression.

METHODS

Firstly, we downloaded transcriptomic data and clinical information from TCGA-PRAD. The characteristic gene cluster was identified by PPI clustering, GO enrichment, co-expression correlation and clinical feature analyses for 25 TFs. Then, the effects of 25 TFs expression on prognosis of PCa patients was analyzed using univariate Cox regression, and the target gene was identified. The expression properties of the target gene in PCa tissues were verified using tissue microarray. Meanwhile, the related mechanistic pathway of the target gene was mined based on its function. Next, the target gene was silenced by small interfering RNAs (siRNAs) for cellular function and mechanistic pathway validation. Finally, CIBERSORT algorithm was used to analyze the infiltration levels of 22 immune cells in PCa patients with low and high expression of target gene, and validated by assaying the expression of related immunomodulatory factor.

RESULTS

We found that HOX family existed independently in 25 TFs, among which HOXC10, HOXC12 and HOXC13 had unique clinical features and the PCa patients with high HOXC13 expression had the worst prognosis. In addition, HOXC13 was highly expressed in tumor tissues and correlated with Gleason score and pathological grade. In vitro experiments demonstrated that silencing HOXC13 inhibited 22RV1 and DU145 cell function by inducing cellular DNA damage and activating cGAS/STING/IRF3 pathway. Immune infiltration analysis revealed that high HOXC13 expression suppressed infiltration of γδ T cells and plasma cells and recruited M2 macrophages. Consistent with these results, silencing HOXC13 up-regulated the transcriptional expression of IFN-β, CCL2, CCL5 and CXCL10.

CONCLUSION

HOXC13 regulates PCa progression by mediating the DNA damage-induced cGAS/STING/IRF3 pathway and remodels TIME through regulation of the transcription of the immune factors IFN-β, CCL2, CCL5 and CXCL10.

A Novel Signature Based on Anoikis Associated with BCR-Free Survival for Prostate Cancer

This study aimed to elucidate the role of anoikis in the progression of prostate cancer (PCa) and to develop a prognostic signature based on anoikis-related genes (ARGs). To achieve this, PCa cases were subjected to nonnegative matrix factorization (NMF) analysis, which allowed for the identification of distinct patterns of anoikis modification. Additionally, immune infiltration was evaluated using single-sample gene-set enrichment analysis (ssGSEA). Survival analysis was performed using the Kaplan-Meier method, and a risk score was generated based on the expression levels of ARGs to quantitatively assess the modification of anoikis in PCa. Using the Least Absolute Shrinkage and Selection Operator (LASSO) method, four hub-genes were identified, and patients were classified into different risk groups based on their individual scores. Importantly, the low-risk subtype was characterized by a significantly improved biochemical recurrence-free survival, underscoring the clinical relevance of the ARG-based prognostic signature. To further improve the prognostic accuracy of the signature, patient age, pathological T stage, Gleason score, and prostate-specific antigen level were incorporated into the analysis, yielding a comprehensive prognostic signature. The clinical relevance of this signature was illustrated through a nomogram, providing a visual representation of the prognostic implications of the ARG-based signature. Taken together, these findings highlight the potential of ARGs in predicting the clinical outcomes of PCa patients and provide a novel and clinically relevant prognostic signature based on the modification of anoikis in PCa.

A Prediction Model for Deciphering Intratumoral Heterogeneity Derived from the Microglia/Macrophages of Glioma Using Non-Invasive Radiogenomics

Microglia and macrophages play a major role in glioma immune responses within the glioma microenvironment. We aimed to construct a prognostic prediction model for glioma based on microglia/macrophage-correlated genes. Additionally, we sought to develop a non-invasive radiogenomics approach for risk stratification evaluation. Microglia/macrophage-correlated genes were identified from four single-cell datasets. Hub genes were selected via lasso-Cox regression, and risk scores were calculated. The immunological characteristics of different risk stratifications were assessed, and radiomics models were constructed using corresponding MRI imaging to predict risk stratification. We identified eight hub genes and developed a relevant risk score formula. The risk score emerged as a significant prognostic predictor correlated with immune checkpoints, and a relevant nomogram was drawn. High-risk groups displayed an active microenvironment associated with microglia/macrophages. Furthermore, differences in somatic mutation rates, such as IDH1 missense variant and TP53 missense variant, were observed between high- and low-risk groups. Lastly, a radiogenomics model utilizing five features from magnetic resonance imaging (MRI) T2 fluid-attenuated inversion recovery (Flair) effectively predicted the risk groups under a random forest model. Our findings demonstrate that risk stratification based on microglia/macrophages can effectively predict prognosis and immune functions in glioma. Moreover, we have shown that risk stratification can be non-invasively predicted using an MRI-T2 Flair-based radiogenomics model.

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

BACKGROUND

Prostate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy.

METHODS

An integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms.

RESULTS

We identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments.

CONCLUSIONS

The three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.

Integrated machine learning identifies epithelial cell marker genes for improving outcomes and immunotherapy in prostate cancer

BACKGROUND

Prostate cancer (PCa), a globally prevalent malignancy, displays intricate heterogeneity within its epithelial cells, closely linked with disease progression and immune modulation. However, the clinical significance of genes and biomarkers associated with these cells remains inadequately explored. To address this gap, this study aimed to comprehensively investigate the roles and clinical value of epithelial cell-related genes in PCa.

METHODS

Leveraging single-cell sequencing data from GSE176031, we conducted an extensive analysis to identify epithelial cell marker genes (ECMGs). Employing consensus clustering analysis, we evaluated the correlations between ECMGs, prognosis, and immune responses in PCa. Subsequently, we developed and validated an optimal prognostic signature, termed the epithelial cell marker gene prognostic signature (ECMGPS), through synergistic analysis from 101 models employing 10 machine learning algorithms across five independent cohorts. Additionally, we collected clinical features and previously published signatures from the literature for comparative analysis. Furthermore, we explored the clinical utility of ECMGPS in immunotherapy and drug selection using multi-omics analysis and the IMvigor cohort. Finally, we investigated the biological functions of the hub gene, transmembrane p24 trafficking protein 3 (TMED3), in PCa using public databases and experiments.

RESULTS

We identified a comprehensive set of 543 ECMGs and established a strong correlation between ECMGs and both the prognostic evaluation and immune classification in PCa. Notably, ECMGPS exhibited robust predictive capability, surpassing traditional clinical features and 80 published signatures in terms of both independence and accuracy across five cohorts. Significantly, ECMGPS demonstrated significant promise in identifying potential PCa patients who might benefit from immunotherapy and personalized medicine, thereby moving us nearer to tailored therapeutic approaches for individuals. Moreover, the role of TMED3 in promoting malignant proliferation of PCa cells was validated.

CONCLUSIONS

Our findings highlight ECMGPS as a powerful tool for improving PCa patient outcomes and supply a robust conceptual framework for in-depth examination of PCa complexities. Simultaneously, our study has the potential to develop a novel alternative for PCa diagnosis and prognostication.

In Situ Cocktail Nanovaccine for Cancer Immunotherapy

In situ vaccination is a desirable strategy for cancer immunotherapy due to its convenience and capacity to target tumor antigens. Here, an in situ nanovaccine based on a cationic peptide with cholesterol-modified, DP7-C, for cancer immunotherapy is rationally designed, and developed a cancer nanovaccine that is easy to preparate. The nanovaccine includes cocktail small interfering RNAs (siRNAs) and immunologic adjuvant CpG ODNs, has synergistic effect in the cancer treatment. This nanovaccine can induce tumor cell death, promote antigen presentation and relieve immune suppression in the tumor microenvironment (TME). Moreover, this nanovaccine is administered to CT26 (hot) and B16F10 (cold) tumor model mice, in which it targeted the primary tumors and induced systemic antitumor immunity to inhibit metastasis. It is validated that the nanovaccine can convert cold tumors into hot tumors. Furthermore, the nanovaccine increased the immune response to anti-PD-1 therapy by modulating the TME in both CT26- and B16F10-tumor-bearing mice. The siRNA cocktail/CpG ODN/self-assembling peptide nanovaccine is a simple and universal tool that can effectively generate specific tumor cell antigens and can be combined with immuno-oncology agents to enhance antitumor immune activity. The versatile methodology provides an alternative approach for developing cancer nanovaccines.

Efficacy and safety of immune checkpoint inhibitors for patients with prostate cancer: a systematic review and meta-analysis

Immunotherapy has revolutionized the treatment paradigm of many cancers, however, its effectiveness in prostate cancer patients is still under question. In the present systematic review and meta-analysis, we sought for assessing the efficacy and safety of Immune checkpoint inhibitors (ICIs) in patients with prostate cancer. PubMed, Scopus, Web of Science, and EMBASE databases were searched on Aguste 19, 2022. Thirty five studies met the eligibility criteria. The median overall survival (mOS) of all treatments was 14.1 months, with the longest and shortest mOS was seen among patients who received anti-CTLA-4 monotherapy and anti-PD-1/PD-L1+anti-CTLA-4 regimen at 24.9 and 9.2 months, respectively. Noteworthy, all types of adverse events had the lowest incidence in the anti-PD-1/PD-L1 monotherapy group. Considering the ICI monotherapy regimens, we found that fatigue, diarrhea, and infusion reaction had the highest incidence rates. Future studies evaluating the efficacy and safety of novel combination therapies with ICIs are warranted.

Remodeling Tumor Immune Microenvironment by Using Polymer-Lipid-Manganese Dioxide Nanoparticles with Radiation Therapy to Boost Immune Response of Castration-Resistant Prostate Cancer

Despite substantial progress in the treatment of castration-resistant prostate cancer (CRPC), including radiation therapy and immunotherapy alone or in combination, the response to treatment remains poor due to the hypoxic and immunosuppressive nature of the tumor microenvironment. Herein, we exploited the bioreactivity of novel polymer-lipid manganese dioxide nanoparticles (PLMDs) to remodel the tumor immune microenvironment (TIME) by increasing the local oxygen levels and extracellular pH and enhancing radiation-induced immunogenic cell death. This study demonstrated that PLMD treatment sensitized hypoxic human and murine CRPC cells to radiation, significantly increasing radiation-induced DNA double-strand breaks and ultimately cell death, which enhanced the secretion of damage-associated molecular patterns, attributable to the induction of autophagy and endoplasmic reticulum stress. Reoxygenation via PLMDs also polarized hypoxic murine RAW264.7 macrophages toward the M1 phenotype, enhancing tumor necrosis factor alpha release, and thus reducing the viability of murine CRPC TRAMP-C2 cells. In a syngeneic TRAMP-C2 tumor model, intravenous injection of PLMDs suppressed, while radiation alone enhanced recruitment of regulatory T cells and myeloid-derived suppressor cells. Pretreatment with PLMDs followed by radiation down-regulated programmed death-ligand 1 and promoted the infiltration of antitumor CD8+ T cells and M1 macrophages to tumor sites. Taken together, TIME modulation by PLMDs plus radiation profoundly delayed tumor growth and prolonged median survival compared with radiation alone. These results suggest that PLMDs plus radiation is a promising treatment modality for improving therapeutic efficacy in radioresistant and immunosuppressive solid tumors.

Unleashing novel horizons in advanced prostate cancer treatment: investigating the potential of prostate specific membrane antigen-targeted nanomedicine-based combination therapy

Prostate cancer (PCa) is a prevalent malignancy with increasing incidence in middle-aged and older men. Despite various treatment options, advanced metastatic PCa remains challenging with poor prognosis and limited effective therapies. Nanomedicine, with its targeted drug delivery capabilities, has emerged as a promising approach to enhance treatment efficacy and reduce adverse effects. Prostate-specific membrane antigen (PSMA) stands as one of the most distinctive and highly selective biomarkers for PCa, exhibiting robust expression in PCa cells. In this review, we explore the applications of PSMA-targeted nanomedicines in advanced PCa management. Our primary objective is to bridge the gap between cutting-edge nanomedicine research and clinical practice, making it accessible to the medical community. We discuss mainstream treatment strategies for advanced PCa, including chemotherapy, radiotherapy, and immunotherapy, in the context of PSMA-targeted nanomedicines. Additionally, we elucidate novel treatment concepts such as photodynamic and photothermal therapies, along with nano-theragnostics. We present the content in a clear and accessible manner, appealing to general physicians, including those with limited backgrounds in biochemistry and bioengineering. The review emphasizes the potential benefits of PSMA-targeted nanomedicines in enhancing treatment efficiency and improving patient outcomes. While the use of PSMA-targeted nano-drug delivery has demonstrated promising results, further investigation is required to comprehend the precise mechanisms of action, pharmacotoxicity, and long-term outcomes. By meticulous optimization of the combination of nanomedicines and PSMA ligands, a novel horizon of PSMA-targeted nanomedicine-based combination therapy could bring renewed hope for patients with advanced PCa.

Unleashing novel horizons in advanced prostate cancer treatment: investigating the potential of prostate specific membrane antigen-targeted nanomedicine-based combination therapy

Prostate cancer (PCa) is a prevalent malignancy with increasing incidence in middle-aged and older men. Despite various treatment options, advanced metastatic PCa remains challenging with poor prognosis and limited effective therapies. Nanomedicine, with its targeted drug delivery capabilities, has emerged as a promising approach to enhance treatment efficacy and reduce adverse effects. Prostate-specific membrane antigen (PSMA) stands as one of the most distinctive and highly selective biomarkers for PCa, exhibiting robust expression in PCa cells. In this review, we explore the applications of PSMA-targeted nanomedicines in advanced PCa management. Our primary objective is to bridge the gap between cutting-edge nanomedicine research and clinical practice, making it accessible to the medical community. We discuss mainstream treatment strategies for advanced PCa, including chemotherapy, radiotherapy, and immunotherapy, in the context of PSMA-targeted nanomedicines. Additionally, we elucidate novel treatment concepts such as photodynamic and photothermal therapies, along with nano-theragnostics. We present the content in a clear and accessible manner, appealing to general physicians, including those with limited backgrounds in biochemistry and bioengineering. The review emphasizes the potential benefits of PSMA-targeted nanomedicines in enhancing treatment efficiency and improving patient outcomes. While the use of PSMA-targeted nano-drug delivery has demonstrated promising results, further investigation is required to comprehend the precise mechanisms of action, pharmacotoxicity, and long-term outcomes. By meticulous optimization of the combination of nanomedicines and PSMA ligands, a novel horizon of PSMA-targeted nanomedicine-based combination therapy could bring renewed hope for patients with advanced PCa.

Construction of PANoptosis signature: Novel target discovery for prostate cancer immunotherapy

PANoptosis pathway gene sets encompassing pyroptosis, apoptosis, and necroptosis were identified from the MSigDB database. We analyzed the perturbations and crosstalk in the PANoptosis pathway in prostate adenocarcinoma (PRAD), including gene mutation, transcription, methylation, and clinical features. By constructing a PANoptosis signature, we accurately predicted the prognosis and immunotherapeutic response of PRAD patients. We further explored the molecular features and immunological roles of the signature, dividing patients into high- and low-score groups. Notably, the high-score group correlated with better survival outcomes and immunotherapeutic responses, as well as a higher mutation frequency and enrichment score in the PANoptosis and HALLMARK pathways. The PANoptosis signature also enhanced overall antitumor immunity, promoted immune cell infiltration, upregulated immune checkpoint regulators, and revealed the cold tumor characteristics of PRAD. We also identified potential drug targets based on the PANoptosis signature. These findings lead the way in identifying novel prognostic markers and therapeutic targets for patients with PRAD.

RNA m6A modification in prostate cancer: A new weapon for its diagnosis and therapy

Prostate cancer (PCa) is the most common malignant tumor and the second leading cause of cancer-related mortality in men worldwide. Despite significant advances in PCa therapy, the underlying molecular mechanisms have yet to be fully elucidated. Recently, epigenetic modification has emerged as a key player in tumor progression, and RNA-based N6-methyladenosine (m6A) epigenetic modification was found to be crucial. This review summarizes comprehensive state-of-art mechanisms underlying m6A modification, its implication in the pathogenesis, and advancement of PCa in protein-coding and non-coding RNA contexts, its relevance to PCa immunotherapy, and the ongoing clinical trials for PCa treatment. This review presents potential m6A-based targets and paves a new avenue for diagnosing and treating PCa, providing new guidelines for future related research through a systematic review of previous results.

Engineering prostate cancer in vitro: what does it take?

A key challenge in the clinical management and cause of treatment failure of prostate cancer (PCa) is its molecular, cellular and clinical heterogeneity. Modelling systems that fully recapitulate clinical diversity and resistant phenotypes are urgently required for the development of successful personalised PCa therapies. The advent of the three-dimensional (3D) organoid model has revolutionised preclinical cancer research through reflecting heterogeneity and offering genomic and environmental manipulation that has opened up unparalleled opportunities for applications in disease modelling, high-throughput drug screening and precision medicine. Despite these remarkable achievements of organoid technology, several shortcomings in emulating the complex tumor microenvironment and dynamic process of metastasis as well as the epigenome profile limit organoids achieving true in vivo functionality. Technological advances in tissue engineering have enabled the development of innovative tools to facilitate the design of improved 3D cancer models. In this review, we highlight the current in vitro 3D PCa models with a special focus on organoids and discuss engineering approaches to create more physiologically relevant PCa organoid models and maximise their translational relevance that ultimately will help to realise the transformational power of precision medicine.

Improving cancer immunotherapy via co-delivering checkpoint blockade and thrombospondin-1 downregulator

The use of checkpoint-blockade antibodies is still restricted in several malignancies due to the modest efficacy, despite considerable success in anti-tumor immunotherapy. The poor response of cancer cells to immune destruction is an essential contributor to the failure of checkpoint therapy. We hypothesized that combining checkpoint therapy with natural-product chemosensitizer could enhance immune response. Herein, a targeted diterpenoid derivative was integrated with the checkpoint blockade (anti-CTLA-4) to improve immunotherapy using thermosensitive liposomes as carriers. In vivo, the liposomes enabled the co-delivery of the two drug payloads into the tumor. Consequently, the regulatory T cell proliferation was restrained, the cytotoxic T cell infiltration was enhanced, and the profound immunotherapeutic effect was achieved. In addition, the immunotherapeutic effect of another clinically used checkpoint antibody, anti-PD-1, also benefited from the diterpenoid derivative. Of note, our mechanism study revealed that the targeted diterpenoid derivative increased the sensitivity of cancer cells to immune attack via THBS1 downregulation and the resultant destruction of THBS1-CD47 interaction. Collectively, co-delivering THBS1 inhibitor and checkpoint blockade is promising to boost cancer immunotherapy. We first time discovered that THBS1 suppression could strengthen checkpoint therapy.