Single-cell analysis supports a luminal-neuroendocrine transdifferentiation in human prostate cancer

Genetically Engineered Membrane-Coated Nanoparticles for Enhanced Prostate-Specific Membrane Antigen Targeting and Ferroptosis Treatment of Castration-Resistant Prostate Cancer

Conventional androgen deprivation therapy (ADT) targets the androgen receptor (AR) inhibiting prostate cancer (PCa) progression; however, it can eventually lead to recurrence as castration-resistant PCa (CRPC), which has high mortality rates and lacks effective treatment modalities. The study confirms the presence of high glutathione peroxidase 4 (GPX4) expression, a key regulator of ferroptosis (i.e., iron-dependent program cell death) in CRPC cells. Therefore, inducing ferroptosis in CRPC cells might be an effective therapeutic modality for CRPC. However, nonspecific uptake of ferroptosis inducers can result in undesirable cytotoxicity in major organs. Thus, to precisely induce ferroptosis in CRPC cells, a genetic engineering strategy is proposed to embed a prostate-specific membrane antigen (PSMA)-targeting antibody fragment (gy1) in the macrophage membrane, which is then coated onto mesoporous polydopamine (MPDA) nanoparticles to produce a biomimetic nanoplatform. The results indicate that the membrane-coated nanoparticles (MNPs) exhibit high specificity and affinity toward CRPC cells. On further encapsulation with the ferroptosis inducers RSL3 and iron ions, MPDA/Fe/RSL3@M-gy1 demonstrates superior synergistic effects in highly targeted ferroptosis therapy eliciting significant therapeutic efficacy against CRPC tumor growth and bone metastasis without increased cytotoxicity. In conclusion, a new therapeutic strategy is reported for the PSMA-specific, CRPC-targeting platform for ferroptosis induction with increased efficacy and safety.

ONECUT2 acts as a lineage plasticity driver in adenocarcinoma as well as neuroendocrine variants of prostate cancer

Androgen receptor- (AR-) indifference is a mechanism of resistance to hormonal therapy in prostate cancer (PC). Here we demonstrate that ONECUT2 (OC2) activates resistance through multiple drivers associated with adenocarcinoma, stem-like and neuroendocrine (NE) variants. Direct OC2 gene targets include the glucocorticoid receptor (GR; NR3C1) and the NE splicing factor SRRM4, which are key drivers of lineage plasticity. Thus, OC2, despite its previously described NEPC driver function, can indirectly activate a portion of the AR cistrome through epigenetic activation of GR. Mechanisms by which OC2 regulates gene expression include promoter binding, enhancement of genome-wide chromatin accessibility, and super-enhancer reprogramming. Pharmacologic inhibition of OC2 suppresses lineage plasticity reprogramming induced by the AR signaling inhibitor enzalutamide. These results demonstrate that OC2 activation promotes a range of drug resistance mechanisms associated with treatment-emergent lineage variation in PC and support enhanced efforts to therapeutically target OC2 as a means of suppressing treatment-resistant disease.

PROX1 drives neuroendocrine plasticity and liver metastases in prostate cancer

With the widespread use of anti-androgen therapy, such as abiraterone and enzalutamide, the incidence of neuroendocrine prostate cancer (NEPC) is increasing. NEPC is a lethal form of prostate cancer (PCa), with a median overall survival of less than one year after diagnosis. In addition to the common bone metastases seen in PCa, NEPC exhibits characteristics of visceral metastases, notably liver metastasis, which serves as an indicator of a poor prognosis clinically. Key factors driving the neuroendocrine plasticity of PCa have been identified, yet the underlying mechanism behind liver metastasis remains unclear. In this study, we identified PROX1 as a driver of neuroendocrine plasticity in PCa, responsible for promoting liver metastases. Mechanistically, anti-androgen therapy alleviates transcriptional inhibition of PROX1. Subsequently, elevated PROX1 levels drive both neuroendocrine plasticity and liver-specific transcriptional reprogramming, promoting liver metastases. Moreover, liver metastases in PCa induced by PROX1 depend on reprogrammed lipid metabolism, a disruption that effectively reduces the formation of liver metastases.

A developmental constraint model of cancer cell states and tumor heterogeneity

Cancer is a disease that stems from a fundamental liability inherent to multicellular life forms in which an individual cell is capable of reneging on the interests of the collective organism. Although cancer is commonly described as an evolutionary process, a less appreciated aspect of tumorigenesis may be the constraints imposed by the organism's developmental programs. Recent work from single-cell transcriptomic analyses across a range of cancer types has revealed the recurrence, plasticity, and co-option of distinct cellular states among cancer cell populations. Here, we note that across diverse cancer types, the observed cell states are proximate within the developmental hierarchy of the cell of origin. We thus posit a model by which cancer cell states are directly constrained by the organism's "developmental map." According to this model, a population of cancer cells traverses the developmental map, thereby generating a heterogeneous set of states whose interactions underpin emergent tumor behavior.

Zeb1-controlled metabolic plasticity enables remodeling of chromatin accessibility in the development of neuroendocrine prostate cancer

Cell plasticity has been found to play a critical role in tumor progression and therapy resistance. However, our understanding of the characteristics and markers of plastic cellular states during cancer cell lineage transition remains limited. In this study, multi-omics analyses show that prostate cancer cells undergo an intermediate state marked by Zeb1 expression with epithelial-mesenchymal transition (EMT), stemness, and neuroendocrine features during the development of neuroendocrine prostate cancer (NEPC). Organoid-formation assays and in vivo lineage tracing experiments demonstrate that Zeb1+ epithelioid cells are putative cells of origin for NEPC. Mechanistically, Zeb1 transcriptionally regulates the expression of several key glycolytic enzymes, thereby predisposing tumor cells to utilize glycolysis for energy metabolism. During this process, lactate accumulation-mediated histone lactylation enhances chromatin accessibility and cellular plasticity including induction of neuro-gene expression, which promotes NEPC development. Collectively, Zeb1-driven metabolic rewiring enables the epigenetic reprogramming of prostate cancer cells to license the adeno-to-neuroendocrine lineage transition.

Single-cell sequencing revealed metabolic reprogramming and its transcription factor regulatory network in prostate cancer

BACKGROUND/AIMS

Prostate cancer is the most frequently diagnosed cancer among men in the United States and is the second leading cause of cancer-related deaths in men. The incidence of prostate cancer is gradually rising due to factors such as aging demographics and changes in dietary habits. The objective of this study is to investigate the metabolic reprogramming changes occurring in prostate cancer and identify potential therapeutic targets.

METHODS

In this study, we utilized single-cell sequencing to comprehensively characterize the alterations in metabolism and the regulatory role of transcription factors in various subtypes of prostate cancer.

RESULTS

In comparison to benign prostate tissue, prostate cancer displayed substantial metabolic variations, notably exhibiting heightened activity in fatty acid metabolism and cholesterol metabolism. This metabolic reprogramming not only influenced cellular energy utilization but also potentially impacted the activity of the androgen receptor (AR) pathway through the synthesis of endogenous steroid hormones. Through our analysis of transcription factor activity, we identified the crucial role of SREBPs, which are transcription factors associated with lipid metabolism, in prostate cancer. Encouragingly, the inhibitor Betulin effectively suppresses prostate cancer growth, highlighting its potential as a therapeutic agent for prostate cancer treatment.

PAX6 promotes neuroendocrine phenotypes of prostate cancer via enhancing MET/STAT5A-mediated chromatin accessibility

BACKGROUND

Neuroendocrine prostate cancer (NEPC) is a lethal subset of prostate cancer which is characterized by neuroendocrine differentiation and loss of androgen receptor (AR) signaling. Growing evidence reveals that cell lineage plasticity is crucial in the failure of NEPC therapies. Although studies suggest the involvement of the neural transcription factor PAX6 in drug resistance, its specific role in NEPC remains unclear.

METHODS

The expression of PAX6 in NEPC was identified via bioinformatics and immunohistochemistry. CCK8 assay, colony formation assay, tumorsphere formation assay and apoptosis assay were used to illustrate the key role of PAX6 in the progression of in vitro. ChIP and Dual-luciferase reporter assays were conducted to confirm the binding sequences of AR in the promoter region of PAX6, as well as the binding sequences of PAX6 in the promoter regions of STAT5A and MET. For in vivo validation, the xenograft model representing NEPC subtype underwent pathological analysis to verify the significant role of PAX6 in disease progression. Complementary diagnoses were established through public clinical datasets and transcriptome sequencing of specific cell lines. ATAC-seq was used to detect the chromatin accessibility of specific cell lines.

RESULTS

PAX6 expression was significantly elevated in NEPC and negatively regulated by AR signaling. Activation of PAX6 in non-NEPC cells led to NE trans-differentiation, while knock-down of PAX6 in NEPC cells inhibited the development and progression of NEPC. Importantly, loss of AR resulted in an enhanced expression of PAX6, which reprogramed the lineage plasticity of prostate cancer cells to develop NE phenotypes through the MET/STAT5A signaling pathway. Through ATAC-seq, we found that a high expression level of PAX6 elicited enhanced chromatin accessibility, mainly through attenuation of H4K20me3, which typically causes chromatin silence in cancer cells.

CONCLUSION

This study reveals a novel neural transcription factor PAX6 could drive NEPC progression and suggest that it might serve as a potential therapeutic target for the management of NEPC.

The lncRNA TPT1-AS1 promotes the survival of neuroendocrine prostate cancer cells by facilitating autophagy

The lncRNA tumor protein translationally controlled 1-antisense RNA 1 (TPT1-AS1) is known for its oncogenic role in various cancers, but its impact on the pathological progression of prostate cancer remains unclear. Our previous study demonstrated that the RE1-silencing transcription factor (REST) regulates neuroendocrine differentiation (NED) in prostate cancer (PCA) by derepressing specific long non-coding RNAs (lncRNAs), including TPT1-AS1. In this study, we revealed that TPT1-AS1 is overexpressed in LNCaP and C4-2B cells after IL-6 and enzalutamide treatment. By analyzing The Cancer Genome Atlas (TCGA) prostate adenocarcinoma dataset, we detected upregulated TPT1-AS1 expression in neuroendocrine-associated PCA but not in prostate adenocarcinoma. Single-cell RNA sequencing data further confirmed the increased TPT1-AS1 levels in neuroendocrine prostate cancer (NEPC) cells. Surprisingly, functional experiments indicated that TPT1-AS1 overexpression had no stimulatory effect on NED in LNCaP cells and that TPT1-AS1 knockdown did not inhibit IL-6-induced NED. Transcriptomic analysis revealed the essential role of TPT1-AS1 in synaptogenesis and autophagy activation in neuroendocrine differentiated PCA cells induced by IL-6 and enzalutamide treatment. TPT1-AS1 was found to regulate the expression of autophagy-related genes that maintain neuroendocrine cell survival through autophagy activation. In conclusion, our data expand the current knowledge of REST-repressed lncRNAs in NED in PCA and highlight the contribution of TPT1-AS1 to protect neuroendocrine cells from cell death rather than inducing NED. Our study suggested that TPT1-AS1 plays a cytoprotective role in NEPC cells; thus, targeting TPT1-AS1 is a potential therapeutic strategy.

Unveiling Novel Double-Negative Prostate Cancer Subtypes Through Single-Cell RNA Sequencing Analysis

Recent advancements in single-cell RNA sequencing (scRNAseq) have facilitated the discovery of previously unrecognized subtypes within prostate cancer (PCa), offering new insights into disease heterogeneity and progression. In this study, we integrated scRNAseq data from multiple studies, comprising both publicly available cohorts and data generated by our research team, and established the HuPSA (Human Prostate Single cell Atlas) and the MoPSA (Mouse Prostate Single cell Atlas) datasets. Through comprehensive analysis, we identified two novel double-negative PCa populations: KRT7 cells characterized by elevated KRT7 expression, and progenitor-like cells marked by SOX2 and FOXA2 expression, distinct from NEPCa, and displaying stem/progenitor features. Furthermore, HuPSA-based deconvolution allowed for the re-classification of human PCa specimens, validating the presence of these novel subtypes. Leveraging these findings, we developed a user-friendly web application, "HuPSA-MoPSA" (https://pcatools.shinyapps.io/HuPSA-MoPSA/), for visualizing gene expression across all newly-established datasets. Our study provides comprehensive tools for PCa research and uncovers novel cancer subtypes that can inform clinical diagnosis and treatment strategies.

Single-cell analysis revealing the metabolic landscape of prostate cancer

Tumor metabolic reprogramming is a hallmark of cancer development, and targeting metabolic vulnerabilities has been proven to be an effective approach for castration-resistant prostate cancer (CRPC) treatment. Nevertheless, treatment failure inevitably occurs, largely due to cellular heterogeneity, which cannot be deciphered by traditional bulk sequencing techniques. By employing computational pipelines for single-cell RNA sequencing, we demonstrated that epithelial cells within the prostate are more metabolically active and plastic than stromal cells. Moreover, we identified that neuroendocrine (NE) cells tend to have high metabolic rates, which might explain the high demand for nutrients and energy exhibited by neuroendocrine prostate cancer (NEPC), one of the most lethal variants of prostate cancer (PCa). Additionally, we demonstrated through computational and experimental approaches that variation in mitochondrial activity is the greatest contributor to metabolic heterogeneity among both tumor cells and nontumor cells. These results establish a detailed metabolic landscape of PCa, highlight a potential mechanism of disease progression, and emphasize the importance of future studies on tumor heterogeneity and the tumor microenvironment from a metabolic perspective.

Single-Cell Informatics for Tumor Microenvironment and Immunotherapy

Cancer comprises malignant cells surrounded by the tumor microenvironment (TME), a dynamic ecosystem composed of heterogeneous cell populations that exert unique influences on tumor development. The immune community within the TME plays a substantial role in tumorigenesis and tumor evolution. The innate and adaptive immune cells "talk" to the tumor through ligand-receptor interactions and signaling molecules, forming a complex communication network to influence the cellular and molecular basis of cancer. Such intricate intratumoral immune composition and interactions foster the application of immunotherapies, which empower the immune system against cancer to elicit durable long-term responses in cancer patients. Single-cell technologies have allowed for the dissection and characterization of the TME to an unprecedented level, while recent advancements in bioinformatics tools have expanded the horizon and depth of high-dimensional single-cell data analysis. This review will unravel the intertwined networks between malignancy and immunity, explore the utilization of computational tools for a deeper understanding of tumor-immune communications, and discuss the application of these approaches to aid in diagnosis or treatment decision making in the clinical setting, as well as the current challenges faced by the researchers with their potential future improvements.

Regulation of Molecular Biomarkers Associated with the Progression of Prostate Cancer

Androgen receptor signaling regulates the normal and pathological growth of the prostate. In particular, the growth and survival of prostate cancer cells is initially dependent on androgen receptor signaling. Exposure to androgen deprivation therapy leads to the development of castration-resistant prostate cancer. There is a multitude of molecular and cellular changes that occur in prostate tumor cells, including the expression of neuroendocrine features and various biomarkers, which promotes the switch of cancer cells to androgen-independent growth. These biomarkers include transcription factors (TP53, REST, BRN2, INSM1, c-Myc), signaling molecules (PTEN, Aurora kinases, retinoblastoma tumor suppressor, calcium-binding proteins), and receptors (glucocorticoid, androgen receptor-variant 7), among others. It is believed that genetic modifications, therapeutic treatments, and changes in the tumor microenvironment are contributing factors to the progression of prostate cancers with significant heterogeneity in their phenotypic characteristics. However, it is not well understood how these phenotypic characteristics and molecular modifications arise under specific treatment conditions. In this work, we summarize some of the most important molecular changes associated with the progression of prostate cancers and we describe some of the factors involved in these cellular processes.

Identification of an anaplastic subtype of prostate cancer amenable to therapies targeting SP1 or translation elongation

Histopathological heterogeneity is a hallmark of prostate cancer (PCa). Using spatial and parallel single-nucleus transcriptomics, we report an androgen receptor (AR)-positive but neuroendocrine-null primary PCa subtype with morphologic and molecular characteristics of small cell carcinoma. Such small cell-like PCa (SCLPC) is clinically aggressive with low AR, but high stemness and proliferation, activity. Molecular characterization prioritizes protein translation, represented by up-regulation of many ribosomal protein genes, and SP1, a transcriptional factor that drives SCLPC phenotype and overexpresses in castration-resistant PCa (CRPC), as two potential therapeutic targets in AR-indifferent CRPC. An SP1-specific inhibitor, plicamycin, effectively suppresses CRPC growth in vivo. Homoharringtonine, a Food And Drug Administration-approved translation elongation inhibitor, impedes CRPC progression in preclinical models and patients with CRPC. We construct an SCLPC-specific signature capable of stratifying patients for drug selectivity. Our studies reveal the existence of SCLPC in admixed PCa pathology, which may mediate tumor relapse, and establish SP1 and translation elongation as actionable therapeutic targets for CRPC.

Bioinformatics in urology - molecular characterization of pathophysiology and response to treatment

The application of bioinformatics has revolutionized the practice of medicine in the past 20 years. From early studies that uncovered subtypes of cancer to broad efforts spearheaded by the Cancer Genome Atlas initiative, the use of bioinformatics strategies to analyse high-dimensional data has provided unprecedented insights into the molecular basis of disease. In addition to the identification of disease subtypes - which enables risk stratification - informatics analysis has facilitated the identification of novel risk factors and drivers of disease, biomarkers of progression and treatment response, as well as possibilities for drug repurposing or repositioning; moreover, bioinformatics has guided research towards precision and personalized medicine. Implementation of specific computational approaches such as artificial intelligence, machine learning and molecular subtyping has yet to become widespread in urology clinical practice for reasons of cost, disruption of clinical workflow and need for prospective validation of informatics approaches in independent patient cohorts. Solving these challenges might accelerate routine integration of bioinformatics into clinical settings.

CDHu40: a novel marker gene set of neuroendocrine prostate cancer (NEPC)

Prostate cancer (PCa) is the most prevalent cancer affecting American men. Castration-resistant prostate cancer (CRPC) can emerge during hormone therapy for PCa, manifesting with elevated serum prostate-specific antigen (PSA) levels, continued disease progression, and/or metastasis to the new sites, resulting in a poor prognosis. A subset of CRPC patients shows a neuroendocrine (NE) phenotype, signifying reduced or no reliance on androgen receptor (AR) signaling and a particularly unfavorable prognosis. In this study, we incorporated computational approaches based on both gene expression profiles and protein-protein interaction (PPI) networks. We identified 500 potential marker genes, which are significantly enriched in cell cycle and neuronal processes. The top 40 candidates, collectively named as CDHu40, demonstrated superior performance in distinguishing NE prostate cancer (NEPC) and non-NEPC samples based on gene expression profiles compared to other published marker sets. Notably, some novel marker genes in CDHu40, absent in the other marker sets, have been reported to be associated with NEPC in the literature, such as DDC, FOLH1, BEX1, MAST1, and CACNA1A. Importantly, elevated CDHu40 scores derived from our predictive model showed a robust correlation with unfavorable survival outcomes in patients, indicating the potential of the CDHu40 score as a promising indicator for predicting the survival prognosis of those patients with the NE phenotype. Motif enrichment analysis on the top candidates suggests that REST and E2F6 may serve as key regulators in the NEPC progression.

Significance

our study integrates gene expression variances in multiple NEPC studies and protein-protein interaction network to pinpoint a specific set of NEPC maker genes namely CDHu40. These genes and scores based on their gene expression levels effectively distinguish NEPC samples and underscore the clinical prognostic significance and potential mechanism.

Treatment-related Neuroendocrine Prostate Carcinoma-Diagnostic and Molecular Correlates

Treatment-related neuroendocrine prostate cancer is a distinctive category of prostate cancer that arises after intensive suppression of the androgen receptor by next-generation therapeutic inhibition of androgen receptor signaling. The biological processes that set in motion the series of events resulting in transformation of adenocarcinoma to neuroendocrine carcinoma include genomic (loss of tumor suppressors TP53 and RB1, amplification of oncogenes N-MYC and Aurora Kinase A, dysregulation of transcription factors SOX2, achaete-scute-homolog 1, and others) as well as epigenomic (DNA methylation, EZH2 overexpression, and others). Pathologic diagnosis is key to effective therapy for this disease, and this is aided by localizing metastatic lesions for biopsy using radioligand imaging in the appropriate clinical context. As our understanding of biology evolves, there has been increased morphologic recognition and characterization of tumor phenotypes that are present in this advanced post-treatment setting. New and promising biomarkers (delta-like ligand 3 and others) have been discovered, which opens up novel therapeutic avenues including immunotherapy and antibody-drug conjugates for this lethal disease with currently limited treatment options.

Subtype Transdifferentiation in Human Cancer: The Power of Tissue Plasticity in Tumor Progression

The classification of tumors into subtypes, characterized by phenotypes determined by specific differentiation pathways, aids diagnosis and directs therapy towards targeted approaches. However, with the advent and explosion of next-generation sequencing, cancer phenotypes are turning out to be far more heterogenous than initially thought, and the classification is continually being updated to include more subtypes. Tumors are indeed highly dynamic, and they can evolve and undergo various changes in their characteristics during disease progression. The picture becomes even more complex when the tumor responds to a therapy. In all these cases, cancer cells acquire the ability to transdifferentiate, changing subtype, and adapt to changing microenvironments. These modifications affect the tumor's growth rate, invasiveness, response to treatment, and overall clinical behavior. Studying tumor subtype transitions is crucial for understanding tumor evolution, predicting disease outcomes, and developing personalized treatment strategies. We discuss this emerging hallmark of cancer and the molecular mechanisms involved at the crossroads between tumor cells and their microenvironment, focusing on four different human cancers in which tissue plasticity causes a subtype switch: breast cancer, prostate cancer, glioblastoma, and pancreatic adenocarcinoma.

Individualized detection of TMPRSS2-ERG fusion status in prostate cancer: a rank-based qualitative transcriptome signature

BACKGROUND

TMPRSS2-ERG (T2E) fusion is highly related to aggressive clinical features in prostate cancer (PC), which guides individual therapy. However, current fusion prediction tools lacked enough accuracy and biomarkers were unable to be applied to individuals across different platforms due to their quantitative nature. This study aims to identify a transcriptome signature to detect the T2E fusion status of PC at the individual level.

METHODS

Based on 272 high-throughput mRNA expression profiles from the Sboner dataset, we developed a rank-based algorithm to identify a qualitative signature to detect T2E fusion in PC. The signature was validated in 1223 samples from three external datasets (Setlur, Clarissa, and TCGA).

RESULTS

A signature, composed of five mRNAs coupled to ERG (five ERG-mRNA pairs, 5-ERG-mRPs), was developed to distinguish T2E fusion status in PC. 5-ERG-mRPs reached 84.56% accuracy in Sboner dataset, which was verified in Setlur dataset (n = 455, accuracy = 82.20%) and Clarissa dataset (n = 118, accuracy = 81.36%). Besides, for 495 samples from TCGA, two subtypes classified by 5-ERG-mRPs showed a higher level of significance in various T2E fusion features than subtypes obtained through current fusion prediction tools, such as STAR-Fusion.

CONCLUSIONS

Overall, 5-ERG-mRPs can robustly detect T2E fusion in PC at the individual level, which can be used on any gene measurement platform without specific normalization procedures. Hence, 5-ERG-mRPs may serve as an auxiliary tool for PC patient management.

Single-cell multi-omics reveals insights into differentiation of rare cell types in mucinous colorectal cancer

Neuroendocrine cells have been implicated in therapeutic resistance and worse overall survival in many cancer types. Mucinous colorectal cancer (mCRC) is uniquely enriched for enteroendocrine cells (EECs), the neuroendocrine cell of the normal colon epithelium, as compared to non-mucinous CRC. Therefore, targeting EEC differentiation may have clinical value in mCRC. Here, single cell multi-omics was used to uncover epigenetic alterations that accompany EEC differentiation, identify STAT3 as a novel regulator of EEC specification, and discover a rare cancer-specific cell type with enteric neuron-like characteristics. Further experiments demonstrated that lysine-specific demethylase 1 (LSD1) and CoREST2 mediate STAT3 demethylation and regulate STAT3 chromatin binding. Knockdown of CoREST2 in an orthotopic xenograft mouse model resulted in decreased primary tumor growth and lung metastases. In culmination, these results provide rationale for new LSD1 inhibitors that target the interaction between LSD1 with STAT3 or CoREST2, which may improve clinical outcomes for patients with mCRC.

SEVtras delineates small extracellular vesicles at droplet resolution from single-cell transcriptomes

Small extracellular vesicles (sEVs) are emerging as pivotal players in a wide range of physiological and pathological processes. However, a pressing challenge has been the lack of high-throughput techniques capable of unraveling the intricate heterogeneity of sEVs and decoding the underlying cellular behaviors governing sEV secretion. Here we leverage droplet-based single-cell RNA sequencing (scRNA-seq) and introduce an algorithm, SEVtras, to identify sEV-containing droplets and estimate the sEV secretion activity (ESAI) of individual cells. Through extensive validations on both simulated and real datasets, we demonstrate SEVtras' efficacy in capturing sEV-containing droplets and characterizing the secretion activity of specific cell types. By applying SEVtras to four tumor scRNA-seq datasets, we further illustrate that the ESAI can serve as a potent indicator of tumor progression, particularly in the early stages. With the increasing importance and availability of scRNA-seq datasets, SEVtras holds promise in offering valuable extracellular insights into the cell heterogeneity.

A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer

BACKGROUND

Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics.

METHODS

All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments.

RESULTS

Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies.

CONCLUSIONS

We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.

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.

Integrated analysis of single-cell and bulk transcriptomics develops a robust neuroendocrine cell-intrinsic signature to predict prostate cancer progression

Neuroendocrine prostate cancer (NEPC) typically implies severe lethality and limited treatment options. The precise identification of NEPC cells holds paramount significance for both research and clinical applications, yet valid NEPC biomarker remains to be defined. Methods: Leveraging 11 published NE-related gene sets, 11 single-cell RNA-sequencing (scRNA-seq) cohorts, 15 bulk transcriptomic cohorts, and 13 experimental models of prostate cancer (PCa), we employed multiple advanced algorithms to construct and validate a robust NEPC risk prediction model. Results: Through the compilation of a comprehensive scRNA-seq reference atlas (comprising a total of 210,879 single cells, including 66 tumor samples) from 9 multicenter datasets of PCa, we observed inconsistent and inefficient performance among the 11 published NE gene sets. Therefore, we developed an integrative analysis pipeline, identifying 762 high-quality NE markers. Subsequently, we derived the NE cell-intrinsic gene signature, and developed an R package named NEPAL, to predict NEPC risk scores. By applying to multiple independent validation datasets, NEPAL consistently and accurately assigned NE feature and delineated PCa progression. Intriguingly, NEPAL demonstrated predictive capabilities for prognosis and therapy responsiveness, as well as the identification of potential epigenetic drivers of NEPC. Conclusion: The present study furnishes a valuable tool for the identification of NEPC and the monitoring of PCa progression through transcriptomic profiles obtained from both bulk and single-cell sources.

Understanding the role of Pax5 in development of taxane-resistant neuroendocrine like prostate cancers

Resistance to the current Androgen Receptor Signaling Inhibitor (ARSI) therapies has led to higher incidences of therapy-induced neuroendocrine-like prostate cancer (t-NEPC). This highly aggressive subtype with predominant small cell-like characteristics is resistant to taxane chemotherapies and has a dismal overall survival. t-NEPCs are mostly treated with platinum-based drugs with a combination of etoposide or taxane and have less selectivity and high systemic toxicity, which often limit their clinical potential. During t-NEPC transformation, adenocarcinomas lose their luminal features and adopt neuro-basal characteristics. Whether the adaptive neuronal characteristics of t-NEPC are responsible for such taxane resistance remains unknown. Pathway analysis from patient gene-expression databases indicates that t-NEPC upregulates various neuronal pathways associated with enhanced cellular networks. To identify transcription factor(s) (TF) that could be important for promoting the gene expression for neuronal characters in t-NEPC, we performed ATAC-Seq, acetylated-histone ChIP-seq, and RNA-seq in our NE-like cell line models and analyzed the promoters of transcriptionally active and significantly enriched neuroendocrine-like (NE-like) cancer-specific genes. Our results indicate that Pax5 could be an important transcription factor for neuronal gene expression and specific to t-NEPC. Pathway analysis revealed that Pax5 expression is involved in axonal guidance, neurotransmitter regulation, and neuronal adhesion, which are critical for strong cellular communications. Further results suggest that depletion of Pax5 disrupts cellular interaction in NE-like cells and reduces surface growth factor receptor activation, thereby, sensitizing them to taxane therapies. Moreover, t-NEPC specific hydroxymethylation of Pax5 promoter CpG islands favors Pbx1 binding to induce Pax5 expression. Based on our study, we concluded that continuous exposure to ARSI therapies leads to epigenetic modifications and Pax5 activation in t-NEPC, which promotes the expression of genes necessary to adopt taxane-resistant NE-like cancer. Thus, targeting the Pax5 axis can be beneficial for reverting their taxane sensitivity.

Temporal evolution reveals bifurcated lineages in aggressive neuroendocrine small cell prostate cancer trans-differentiation

Trans-differentiation from an adenocarcinoma to a small cell neuroendocrine state is associated with therapy resistance in multiple cancer types. To gain insight into the underlying molecular events of the trans-differentiation, we perform a multi-omics time course analysis of a pan-small cell neuroendocrine cancer model (termed PARCB), a forward genetic transformation using human prostate basal cells and identify a shared developmental, arc-like, and entropy-high trajectory among all transformation model replicates. Further mapping with single cell resolution reveals two distinct lineages defined by mutually exclusive expression of ASCL1 or ASCL2. Temporal regulation by groups of transcription factors across developmental stages reveals that cellular reprogramming precedes the induction of neuronal programs. TFAP4 and ASCL1/2 feedback are identified as potential regulators of ASCL1 and ASCL2 expression. Our study provides temporal transcriptional patterns and uncovers pan-tissue parallels between prostate and lung cancers, as well as connections to normal neuroendocrine cell states.

The ELAVL3/MYCN positive feedback loop provides a therapeutic target for neuroendocrine prostate cancer

Neuroendocrine prostate cancer is a rapidly progressive and lethal disease characterized by early visceral metastasis, poor prognosis, and limited treatment options. Uncovering the oncogenic mechanisms could lead to the discovery of potential therapeutic avenues. Here, we demonstrate that the RNA-binding protein ELAVL3 is specifically upregulated in neuroendocrine prostate cancer and that overexpression of ELAVL3 alone is sufficient to induce the neuroendocrine phenotype in prostate adenocarcinoma. Mechanistically, ELAVL3 is transcriptionally regulated by MYCN and subsequently binds to and stabilizes MYCN and RICTOR mRNA. Moreover, ELAVL3 is shown to be released in extracellular vesicles and induce neuroendocrine differentiation of adenocarcinoma cells via an intercellular mechanism. Pharmacological inhibition of ELAVL3 with pyrvinium pamoate, an FDA-approved drug, effectively suppresses tumor growth, reduces metastatic risk, and improves survival in neuroendocrine prostate cancer mouse models. Our results identify ELAVL3 as a critical regulator of neuroendocrine differentiation in prostate cancer and propose a drug repurposing strategy for targeted therapies.

Inflammation in Prostate Cancer: Exploring the Promising Role of Phenolic Compounds as an Innovative Therapeutic Approach

Prostate cancer (PCa) remains a significant global health concern, being a major cause of cancer morbidity and mortality worldwide. Furthermore, profound understanding of the disease is needed. Prostate inflammation caused by external or genetic factors is a central player in prostate carcinogenesis. However, the mechanisms underlying inflammation-driven PCa remain poorly understood. This review dissects the diagnosis methods for PCa and the pathophysiological mechanisms underlying the disease, clarifying the dynamic interplay between inflammation and leukocytes in promoting tumour development and spread. It provides updates on recent advances in elucidating and treating prostate carcinogenesis, and opens new insights for the use of bioactive compounds in PCa. Polyphenols, with their noteworthy antioxidant and anti-inflammatory properties, along with their synergistic potential when combined with conventional treatments, offer promising prospects for innovative therapeutic strategies. Evidence from the use of polyphenols and polyphenol-based nanoparticles in PCa revealed their positive effects in controlling tumour growth, proliferation, and metastasis. By consolidating the diverse features of PCa research, this review aims to contribute to increased understanding of the disease and stimulate further research into the role of polyphenols and polyphenol-based nanoparticles in its management.

Anti-PD-1 immunotherapy with androgen deprivation therapy induces robust immune infiltration in metastatic castration-sensitive prostate cancer

When compared to other malignancies, the tumor microenvironment (TME) of primary and castration-resistant prostate cancer (CRPC) is relatively devoid of immune infiltrates. While androgen deprivation therapy (ADT) induces a complex immune infiltrate in localized prostate cancer, the composition of the TME in metastatic castration-sensitive prostate cancer (mCSPC), and the effects of ADT and other treatments in this context are poorly understood. Here, we perform a comprehensive single-cell RNA sequencing (scRNA-seq) profiling of metastatic sites from patients participating in a phase 2 clinical trial (NCT03951831) that evaluated standard-of-care chemo-hormonal therapy combined with anti-PD-1 immunotherapy. We perform a longitudinal, protein activity-based analysis of TME subpopulations, revealing immune subpopulations conserved across multiple metastatic sites. We also observe dynamic changes in these immune subpopulations in response to treatment and a correlation with clinical outcomes. Our study uncovers a therapy-resistant, transcriptionally distinct tumor subpopulation that expands in cell number in treatment-refractory patients.

Single-cell analysis of castration-resistant prostate cancers to identify potential biomarkers for diagnosis and prognosis of neuroendocrine prostate cancer

The high heterogeneity and low percentage of neuroendocrine cells in prostate cancer limit the utility of traditional bulk RNA sequencing and even single-cell RNA sequencing to find better biomarkers for early diagnosis and stratification. Re-clustering of specific cell-type holds great promise for identification of intra-cell-type heterogeneity. However, this has not yet been used in studying neuroendocrine prostate cancer heterogeneity. Neuroendocrine cluster(s) were individually identified in each castration-resistant prostate cancer specimen and combined for trajectory analysis. Three neuroendocrine states were identified. Neuroendocrine state 2 with the highest AR score was considered the initial starting state of neuroendocrine transdifferentiation. State 1 and state 3 with distinct high neuroendocrine scores and marker genes enriched in N-Myc and REST target genes, respectively, were considered as two different types of neuroendocrine differentiated cancer cells. These two states contained distinct groups of prostate cancer biomarkers and a strong distinguishing ability of normal versus cancerous prostate across different pathological grading was found in the N-Myc-associated state. Our data highlight the central role of N-Myc and REST in mediating lineage plasticity and classifying neuroendocrine phenotypes.

ONECUT2 Activates Diverse Resistance Drivers of Androgen Receptor-Independent Heterogeneity in Prostate Cancer

Androgen receptor- (AR-) indifference is a mechanism of resistance to hormonal therapy in prostate cancer (PC). Here we demonstrate that the HOX/CUT transcription factor ONECUT2 (OC2) activates resistance through multiple drivers associated with adenocarcinoma, stem-like and neuroendocrine (NE) variants. Direct OC2 targets include the glucocorticoid receptor and the NE splicing factor SRRM4, among others. OC2 regulates gene expression by promoter binding, enhancement of chromatin accessibility, and formation of novel super-enhancers. OC2 also activates glucuronidation genes that irreversibly disable androgen, thereby evoking phenotypic heterogeneity indirectly by hormone depletion. Pharmacologic inhibition of OC2 suppresses lineage plasticity reprogramming induced by the AR signaling inhibitor enzalutamide. These results demonstrate that OC2 activation promotes a range of drug resistance mechanisms associated with treatment-emergent lineage variation in PC. Our findings support enhanced efforts to therapeutically target this protein as a means of suppressing treatment-resistant disease.

A 12-gene panel in estimating hormone-treatment responses of castration-resistant prostate cancer patients generated using a combined analysis of bulk and single-cell sequencing data

BACKGROUND

Castration-resistant prostate cancer (CRPC) represents one type of advanced prostate cancer (PCa) with a median survival time of 1-2 years. Currently, there is a lack of reliable gene panels in predicting hormone treatment (HT) responses due to limited knowledge of CRPC-specific tumor-microenvironment (TME) characteristics.

METHODS

In this study, we first screened for up-regulated genes in CRPC samples using bulk-sequencing data retrieved from TCGA online database, and further investigated the expression status of these genes in four sets of downloaded single-cell RNA sequencing (scRNAseq) data: GSE117403 containing 16 normal human prostate samples; GSE141445 containing 13 PCa samples; GSE176031 containing 11 PCa samples and GSE137829 containing 6 CRPC samples.

RESULTS

We identified a series of CRPC-specific TME characteristics including an enriched number of PEG10+ neuroendocrine cells, elevated expression of PPIB/CCDC74A/GAPDH/AR genes in tumor cells, increased expression of FAP/TGFB1 in cancer-associated fibroblasts (CAFs), suppressed immune environment featured by enhanced M2 macrophage polarization, T cell exhaustion and increased number of regulatory B cells. We further established a 12-gene panel using these characteristics and showed that this panel could separate CRPC samples from PCa samples (AUC of 0.78), and CRPC patients with higher panel scores tended to have treatment failure or progression (R = -0.47, p = 0.019).

CONCLUSIONS

Based on these unique TME characteristics of CRPC, we established a prediction tool for estimating the duration of HT responses in PCa treatment. Our results suggest mechanisms by which prostate cancer becomes castrate resistant. Further study of PEG10 (and/or others) to evaluate therapeutic efficacy should be considered.

Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated "Omics" Approaches to Explore Measurable Metrics

Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.

Grade Progression and Intrapatient Tumor Heterogeneity as Potential Contributors to Resistance in Gastroenteropancreatic Neuroendocrine Tumors

Gastroenteropancreatic neuroendocrine neoplasms (NENs) are a heterogenous group of tumors that are incurable when metastatic, regardless of grade. The aim of this article is to understand tumor heterogeneity and grade progression as possible contributors to drug resistance in gastroentropancreatic neuroendocrine tumors (GEP-NETs). Heterogeneity has been observed in the genetic, pathological, and imaging features of these tumors at baseline. Diagnostic challenges related to tumor sampling and the potential for changes in grade over time further confound our ability to optimize therapy for patients. A better understanding of NEN biology and tumor heterogeneity at baseline and over time could lead to the development of new therapeutic avenues.

Single-cell RNA sequencing reveals that HSD17B2 in cancer-associated fibroblasts promotes the development and progression of castration-resistant prostate cancer

Castration-resistant prostate cancer (CRPC) responds poorly to existing therapy and appears as the lethal consequence of prostate cancer (PCa) progression. The tumour microenvironment (TME) has been thought to play a crucial role in CRPC progression. Here, we conducted single-cell RNA sequencing analysis on two CRPC and two hormone-sensitive prostate cancer (HSPC) samples to reveal potential leading roles in castration resistance. We described the single-cell transcriptional landscape of PCa. Higher cancer heterogeneity was explored in CRPC, with stronger cell cycling status and heavier copy number variant burden of luminal cells. Cancer-associated fibroblasts (CAFs), which are one of the most critical components of TME, demonstrated unique expression and cell-cell communication features in CRPC. A CAFs subtype with high expression of HSD17B2 in CRPC was identified with inflammatory features. HSD17B2 catalyses the conversion of testosterone and dihydrotestosterone to their less active forms, which was associated with steroid hormone metabolism in PCa tumour cells. However, the characteristics of HSD17B2 in PCa fibroblasts remained unknown. We found that HSD17B2 knockdown in CRPC-CAFs could inhibit migration, invasion, and castration resistance of PCa cells in vitro. Further study showed that HSD17B2 could regulate CAFs functions and promote PCa migration through the AR/ITGBL1 axis. Overall, our study revealed the important role of CAFs in the formation of CRPC. HSD17B2 in CAFs regulated AR activation and subsequent ITGBL1 secretion to promote the malignant behaviour of PCa cells. HSD17B2 in CAFs could serve as a promising therapeutic target for CRPC.

Appearance of tuft cells during prostate cancer progression

Tuft cells are chemosensory epithelial cells that increase in number following infection or injury to robustly activate the innate immune response to alleviate or promote disease. Recent studies of castration resistant prostate cancer and its subtype, neuroendocrine prostate cancer, revealed Pou2f3+ populations in mouse models. The transcription factor Pou2f3 is a master regulator of the tuft cell lineage. We show that tuft cells are upregulated early during prostate cancer development, and their numbers increase with progression. Cancer-associated tuft cells in the mouse prostate express DCLK1, COX1, COX2, while human tuft cells express COX1. Mouse and human tuft cells exhibit strong activation of signaling pathways including EGFR and SRC-family kinases. While DCLK1 is a mouse tuft cell marker, it is not present in human prostate tuft cells. Tuft cells that appear in mouse models of prostate cancer display genotype-specific tuft cell gene expression signatures. Using bioinformatic analysis tools and publicly available datasets, we characterized prostate tuft cells in aggressive disease and highlighted differences between tuft cell populations. Our findings indicate that tuft cells contribute to the prostate cancer microenvironment and may promote development of more advanced disease. Further research is needed to understand contributions of tuft cells to prostate cancer progression.

Minor intron splicing is critical for survival of lethal prostate cancer

The evolutionarily conserved minor spliceosome (MiS) is required for protein expression of ∼714 minor intron-containing genes (MIGs) crucial for cell-cycle regulation, DNA repair, and MAP-kinase signaling. We explored the role of MIGs and MiS in cancer, taking prostate cancer (PCa) as an exemplar. Both androgen receptor signaling and elevated levels of U6atac, a MiS small nuclear RNA, regulate MiS activity, which is highest in advanced metastatic PCa. siU6atac-mediated MiS inhibition in PCa in vitro model systems resulted in aberrant minor intron splicing leading to cell-cycle G1 arrest. Small interfering RNA knocking down U6atac was ∼50% more efficient in lowering tumor burden in models of advanced therapy-resistant PCa compared with standard antiandrogen therapy. In lethal PCa, siU6atac disrupted the splicing of a crucial lineage dependency factor, the RE1-silencing factor (REST). Taken together, we have nominated MiS as a vulnerability for lethal PCa and potentially other cancers.

Oncofetal protein glypican-3 is a biomarker and critical regulator of function for neuroendocrine cells in prostate cancer

Neuroendocrine (NE) cells comprise ~1% of epithelial cells in benign prostate and prostatic adenocarcinoma (PCa). However, they become enriched in hormonally treated and castration-resistant PCa (CRPC). In addition, close to 20% of hormonally treated tumors recur as small cell NE carcinoma (SCNC), composed entirely of NE cells, which may be the result of clonal expansion or lineage plasticity. Since NE cells do not express androgen receptors (ARs), they are resistant to hormonal therapy and contribute to therapy failure. Here, we describe the identification of glypican-3 (GPC3) as an oncofetal cell surface protein specific to NE cells in prostate cancer. Functional studies revealed that GPC3 is critical to the viability of NE tumor cells and tumors displaying NE differentiation and that it regulates calcium homeostasis and signaling. Since our results demonstrate that GPC3 is specifically expressed by NE cells, patients with confirmed SCNC may qualify for GPC3-targeted therapy which has been developed in the context of liver cancer and displays minimal toxicity due to its tumor-specific expression. © 2023 The Pathological Society of Great Britain and Ireland.

IL-1β Is an Androgen-Responsive Target in Macrophages for Immunotherapy of Prostate Cancer

Great attention is paid to the role of androgen receptor (AR) as a central transcriptional factor in driving the growth of prostate cancer (PCa) epithelial cells. However, the understanding of the role of androgen in PCa-infiltrated immune cells and the impact of androgen deprivation therapy (ADT), the first-line treatment for advanced PCa, on the PCa immune microenvironment remains limited. On the other hand, immune checkpoint blockade has revolutionized the treatment of certain cancer types, but fails to achieve any benefit in advanced PCa, due to an immune suppressive environment. In this study, it is reported that AR signaling pathway is evidently activated in tumor-associated macrophages (TAMs) of PCa both in mice and humans. AR acts as a transcriptional repressor for IL1B in TAMs. ADT releases the restraint of AR on IL1B and therefore leads to an excessive expression and secretion of IL-1β in TAMs. IL-1β induces myeloid-derived suppressor cells (MDSCs) accumulation that inhibits the activation of cytotoxic T cells, leading to the immune suppressive microenvironment. Critically, anti-IL-1β antibody coupled with ADT and the immune checkpoint inhibitor anti-PD-1 antibody exerts a stronger anticancer effect on PCa following castration. Together, IL-1β is an important androgen-responsive immunotherapeutic target for advanced PCa.

Cancer-cell-intrinsic mechanisms shaping the immunosuppressive landscape of prostate cancer

Although immunotherapy has revolutionized cancer treatment and achieved remarkable success across many different cancer types, only a subset of patients shows meaningful clinical responses. In particular, advanced prostate cancer exhibits overwhelming de novo resistance to immune checkpoint blockade therapy. This is primarily due to the immunosuppressive tumor microenvironment of prostate cancer. Therefore, it is paramount to understand how prostate cancer cell-intrinsic mechanisms promote immune evasion and foster an immunosuppressive microenvironment. Here, we review recent findings that reveal the roles of the genetic alterations, androgen receptor signaling, cancer cell plasticity, and oncogenic pathways in shaping the immunosuppressive microenvironment and thereby driving immunotherapy resistance. Based on preclinical and clinical observations, a variety of therapeutic strategies are being developed that may illuminate new paths to enhance immunotherapy efficacy in prostate cancer.

Numb/Parkin-directed mitochondrial fitness governs cancer cell fate via metabolic regulation of histone lactylation

Cell plasticity and neuroendocrine differentiation in prostate and lung adenocarcinomas are one of the major reasons for therapeutic resistance to targeted therapy. Whether and how metabolic changes contribute to this adenocarcinoma-to-neuroendocrine cell fate transition remains largely unclear. Here we show that neuroendocrine prostate or lung cancer cells possess mostly fragmented mitochondria with low membrane potential and rely on glycolysis for energy metabolism. We further show an important role of the cell fate determinant Numb in mitochondrial quality control via binding to Parkin and facilitating Parkin-mediated mitophagy. Deficiency in the Numb/Parkin pathway in prostate or lung adenocarcinomas causes a metabolic reprogramming featured with a significant increase in production of lactate acid, which subsequently leads to an upregulation of histone lactylation and transcription of neuroendocrine-associated genes. Collectively, the Numb/Parkin-directed mitochondrial fitness is a key metabolic switch and a promising therapeutic target on cancer cell plasticity through the regulation of histone lactylation.

Dissecting the immune suppressive human prostate tumor microenvironment via integrated single-cell and spatial transcriptomic analyses

The treatment of low-risk primary prostate cancer entails active surveillance only, while high-risk disease requires multimodal treatment including surgery, radiation therapy, and hormonal therapy. Recurrence and development of metastatic disease remains a clinical problem, without a clear understanding of what drives immune escape and tumor progression. Here, we comprehensively describe the tumor microenvironment of localized prostate cancer in comparison with adjacent normal samples and healthy controls. Single-cell RNA sequencing and high-resolution spatial transcriptomic analyses reveal tumor context dependent changes in gene expression. Our data indicate that an immune suppressive tumor microenvironment associates with suppressive myeloid populations and exhausted T-cells, in addition to high stromal angiogenic activity. We infer cell-to-cell relationships from high throughput ligand-receptor interaction measurements within undissociated tissue sections. Our work thus provides a highly detailed and comprehensive resource of the prostate tumor microenvironment as well as tumor-stromal cell interactions.

Clinical and molecular significance of the RNA m6A methyltransferase complex in prostate cancer

N⁶-methyladenosine (m⁶A) is the most abundant internal mRNA modification and is dynamically regulated through distinct protein complexes that methylate, demethylate, and/or interpret the m⁶A modification. These proteins, and the m⁶A modification, are involved in the regulation of gene expression, RNA stability, splicing and translation. Given its role in these crucial processes, m⁶A has been implicated in many diseases, including in cancer development and progression. Prostate cancer (PCa) is the most commonly diagnosed non-cutaneous cancer in men and recent studies support a role for m⁶A in PCa. Despite this, the literature currently lacks an integrated analysis of the expression of key components of the m⁶A RNA methyltransferase complex, both in PCa patients and in well-established cell line models. For this reason, this study used immunohistochemistry and functional studies to investigate the mechanistic and clinical significance of the METTL3, METTL14, WTAP and CBLL1 components of the m⁶A methyltransferase complex in PCa specimens and cell lines. Expression of METTL3 and CBLL1, but not METTL14 and WTAP, was associated with poorer PCa patient outcomes. Expression of METTL3, METTL14, WTAP and CBLL1 was higher in PCa cells compared with non-malignant prostate cells, with the highest expression seen in castrate-sensitive, androgen-responsive PCa cells. Moreover, in PCa cell lines, expression of METTL3 and WTAP was found to be androgen-regulated. To investigate the mechanistic role(s) of the m⁶A methyltransferase complex in PCa cells, short hairpin RNA (shRNA)-mediated knockdown coupled with next generation sequencing was used to determine the transcriptome-wide roles of METTL3, the catalytic subunit of the m⁶A methyltransferase complex. Functional depletion of METTL3 resulted in upregulation of the androgen receptor (AR), together with 134 AR-regulated genes. METTL3 knockdown also resulted in altered splicing, and enrichment of cell cycle, DNA repair and metabolic pathways. Collectively, this study identified the functional and clinical significance of four essential m⁶A complex components in PCa patient specimens and cell lines for the first time. Further studies are now warranted to determine the potential therapeutic relevance of METTL3 inhibitors in development to treat leukaemia to benefit patients with PCa.

IP-score correlated to endogenous tumour antigen peptide processing: A candidate clinical response score algorithm of immune checkpoint inhibitors therapy in multiple cohorts

The processing of endogenous tumour antigen peptides was essential for anti-tumour immunity in the tumour microenvironment. A high degree of Endogenous tumour antigen peptide processing has been demonstrated to improve the prognosis of carcinoma patients. However, there is insufficient evidence to prove its effect on the clinical response to immune checkpoint inhibitor therapy. To undertake a more in-depth analysis of the effects of the aforementioned genes on immunotherapy, we constructed a gene set evaluation score system relevant to tumour endogenous antigen peptide therapy using the GSVA approach. This rating mechanism is known as IP score (IPs). Immediately afterwards, we used the TCGA pan-cancer cohorts to conduct a comprehensive analysis of 6 genes in the IPs, and the analysis results showed that these six genes were related to the proportion of CD8⁺ T lymphocytes in a variety of solid tumours. As a prognostic protective factor for solid tumours, patients had better prognosis outcomes in the group with high expression levels of the above genes. We analysed the differential expression of six genes between immune checkpoint inhibitor treatment response and disease progression groups using several treatment cohorts. The results revealed that after treatment with PD-1 or CTLA4 inhibitors, the expression levels of the above six genes were comparatively high in the effective group, but the expression of the signature genes was dramatically downregulated in the ICI-insensitive groups. This indicates that the 6 genes are related to the clinical response to ICI treatment. Finally, we used the GSVA method to evaluate the above signatures, and the results showed that PDCD1, CTAL4, CD274 and LAG3 were significantly higher expressed in the IPs high-expression group; therefore, based on the processing of endogenous antigenic peptides in tumours, a predictive score of clinical response to immune checkpoint inhibitor therapy composed of 6 genes(PSMB8/PSMB9/PSMB10/PSME1/PSME2/IRF1) was constructed, and the role of each independent variable in the signature in the solid tumour microenvironment and the impact on ICI treatment were comprehensively analysed. This study provides a candidate evaluation score for predicting clinical response to immune checkpoint inhibitor therapy.

Novel biomarkers predict prognosis and drug-induced neuroendocrine differentiation in patients with prostate cancer

Background

A huge focus is being placed on the development of novel signatures in the form of new combinatorial regimens to distinguish the neuroendocrine (NE) characteristics from castration resistant prostate cancer (CRPC) timely and accurately, as well as predict the disease-free survival (DFS) and progression-free survival (PFS) of prostate cancer (PCa) patients.

Methods

Single cell data of 4 normal samples, 3 CRPC samples and 3 CRPC-NE samples were obtained from GEO database, and CellChatDB was used for potential intercellular communication, Secondly, using the "limma" package (v3.52.0), we obtained the differential expressed genes between CRPC and CRPC-NE both in single-cell RNA seq and bulk RNA seq samples, and discovered 12 differential genes characterized by CRPC-NE. Then, on the one hand, the diagnosis model of CRPC-NE is developed by random forest algorithm and artificial neural network (ANN) through Cbioportal database; On the other hand, using the data in Cbioportal and GEO database, the DFS and PFS prognostic model of PCa was established and verified through univariate Cox analysis, least absolute shrinkage and selection operator (Lasso) regression and multivariate Cox regression in R software. Finally, somatic mutation and immune infiltration were also discussed.

Results

Our research shows that there exists specific intercellular communication in classified clusters. Secondly, a CRPC-NE diagnostic model of six genes (HMGN2, MLLT11, SOX4, PCSK1N, RGS16 and PTMA) has been established and verified, the area under the ROC curve (AUC) is as high as 0.952 (95% CI: 0.882-0.994). The mutation landscape shows that these six genes are rarely mutated in the CRPC and NEPC samples. In addition, NE-DFS signature (STMN1 and PCSK1N) and NE-PFS signature (STMN1, UBE2S and HMGN2) are good predictors of DFS and PFS in PCa patients and better than other clinical features. Lastly, the infiltration levels of plasma cells, T cells CD4 naive, Eosinophils and Monocytes were significantly different between the CRPC and NEPC groups.

Conclusions

This study revealed the heterogeneity between CRPC and CRPC-NE from different perspectives, and developed a reliable diagnostic model of CRPC-NE and robust prognostic models for PCa.

Identification of cancer-associated fibroblasts subtypes in prostate cancer

Introduction

Cancer-associated fibroblasts (CAFs) are one of the most abundant cell types in tumor microenvironment. However, the phenotypic and functional heterogeneities among CAFs have not been sufficiently investigated in prostate cancer.

Methods

We obtained and analyzed the single-cell RNA-sequencing data from 26 hormone-sensitive prostate cancer samples and 8 castration-resistant prostate cancer samples, along with the analysis of bulk-sequencing datasets. Furthermore, we performed multicolor immunofluorescence staining to verify the findings from the data analysis.

Results

We identified two major CAFs subtypes with distinct molecular characteristics and biological functions in prostate cancer microenvironment, namely αSMA+ CAV1+ CAFs-C0 and FN1+ FAP+ CAFs-C1. Another single-cell RNA-sequencing dataset containing 7 bone metastatic prostate cancer samples demonstrated that osteoblasts in the bone metastatic lesions comprised two subtypes with molecular characteristics and biological functions similar to CAFs-C0 and CAFs-C1 in the primary tumor sites. In addition, we discovered a transcriptional factor regulatory network depending on CAFs-C1. CAFs-C1, but not CAFs-C0, was associated with castration resistance and poor prognosis. We also found that CAFs-C1 signature was involved in treatment resistance to immune checkpoint inhibitors.

Discussion

In summary, our results identified the presence of heterogeneous CAFs subtypes in prostate cancer microenvironment and the potential of specific CAFs subtype as therapeutic target for castration-resistant prostate cancer.

Defining cellular population dynamics at single-cell resolution during prostate cancer progression

Advanced prostate malignancies are a leading cause of cancer-related deaths in men, in large part due to our incomplete understanding of cellular drivers of disease progression. We investigate prostate cancer cell dynamics at single-cell resolution from disease onset to the development of androgen independence in an in vivo murine model. We observe an expansion of a castration-resistant intermediate luminal cell type that correlates with treatment resistance and poor prognosis in human patients. Moreover, transformed epithelial cells and associated fibroblasts create a microenvironment conducive to pro-tumorigenic immune infiltration, which is partially androgen responsive. Androgen-independent prostate cancer leads to significant diversification of intermediate luminal cell populations characterized by a range of androgen signaling activity, which is inversely correlated with proliferation and mRNA translation. Accordingly, distinct epithelial populations are exquisitely sensitive to translation inhibition, which leads to epithelial cell death, loss of pro-tumorigenic signaling, and decreased tumor heterogeneity. Our findings reveal a complex tumor environment largely dominated by castration-resistant luminal cells and immunosuppressive infiltrates.

FOXA2 drives lineage plasticity and KIT pathway activation in neuroendocrine prostate cancer

Prostate cancer adeno-to-neuroendocrine lineage transition has emerged as a mechanism of targeted therapeutic resistance. Identifying the direct molecular drivers and developing pharmacological strategies using clinical-grade inhibitors to overcome lineage transition-induced therapeutic resistance are imperative. Here, using single-cell multiomics analyses, we investigate the dynamics of cellular heterogeneity, transcriptome regulation, and microenvironmental factors in 107,201 cells from genetically engineered mouse prostate cancer samples with complete time series of tumor evolution seen in patients. We identify that FOXA2 orchestrates prostate cancer adeno-to-neuroendocrine lineage transition and that Foxa2 expression is significantly induced by androgen deprivation. Moreover, Foxa2 knockdown induces the reversal of adeno-to-neuroendocrine transition. The KIT pathway is directly regulated by FOXA2 and specifically activated in neuroendocrine prostate cancer (NEPC). Pharmacologic inhibition of KIT pathway significantly suppresses mouse and human NEPC tumor growth. These findings reveal that FOXA2 drives adeno-to-neuroendocrine lineage plasticity in prostate cancer and provides a potential pharmacological strategy for castration-resistant NEPC.

Developmental Deconvolution for Classification of Cancer Origin

Cancer is partly a developmental disease, with malignancies named based on cell or tissue of origin. However, a systematic atlas of tumor origins is lacking. Here we map the single-cell organogenesis of 56 developmental trajectories to the transcriptomes of over 10,000 tumors across 33 cancer types. We deconvolute tumor transcriptomes into signals for individual developmental trajectories. Using these signals as inputs, we construct a developmental multilayer perceptron (D-MLP) classifier that outputs cancer origin. D-MLP (ROC-AUC: 0.974 for top prediction) outperforms benchmark classifiers. We analyze tumors from patients with cancer of unknown primary (CUP), selecting the most difficult cases in which extensive multimodal workup yielded no definitive tumor type. Interestingly, CUPs form groups distinguished by developmental trajectories, and classification reveals diagnosis for patient tumors. Our results provide an atlas of tumor developmental origins, provide a tool for diagnostic pathology, and suggest developmental classification may be a useful approach for patient tumors.

SIGNIFICANCE

Here we map the developmental trajectories of tumors. We deconvolute tumor transcriptomes into signals for mammalian developmental programs and use this information to construct a deep learning classifier that outputs tumor type. We apply the classifier to CUP and reveal the developmental origins of patient tumors. See related commentary by Wang, p. 2498. This article is highlighted in the In This Issue feature, p. 2483.

Molecular mechanisms underlying the development of neuroendocrine prostate cancer

Prostate cancer is the most common non-cutaneous cancer and the second leading cause of cancer-associated deaths among men in the United States. Androgen deprivation therapy (ADT) is the standard of care for advanced prostate cancer. While patients with advanced prostate cancer initially respond to ADT, the disease frequently progresses to a lethal metastatic form, defined as castration-resistant prostate cancer (CRPC). After multiple rounds of anti-androgen therapies, 20-25% of metastatic CRPCs develop a neuroendocrine (NE) phenotype. These tumors are classified as neuroendocrine prostate cancer (NEPC). De novo NEPC is rare and accounts for less than 2% of all prostate cancers at diagnosis. NEPC is commonly characterized by the expression of NE markers and the absence of androgen receptor (AR) expression. NEPC is usually associated with tumor aggressiveness, hormone therapy resistance, and poor clinical outcome. Here, we review the molecular mechanisms underlying the emergence of NEPC and provide insights into the future perspectives on potential therapeutic strategies for NEPC.