Heterogeneity Of Prostate Cancer Research Articles

Harnessing the Heterogeneity of Prostate Cancer for Target Discovery Using Patient-Derived Explants.

Simple SummaryThere is a widespread push toward more biologically relevant pre-clinical models of prostate cancer that can improve the discovery and translation of new drugs and biomarkers for this disease. Patient-derived explant culture is an innovative pre-clinical model that utilizes surgical prostate cancer specimens in a way that retains the architecture, microenvironment and heterogeneity of prostate tumors—factors that critically influence cell behavior and response to therapy. With increasing tissue complexity comes increasing complexity of analysis. The aim of this study was to provide critical information for the successful application and analysis of the patient-derived prostate cancer explant model.Prostate cancer is a complex and heterogeneous disease, but a small number of cell lines have dominated basic prostate cancer research, representing a major obstacle in the field of drug and biomarker discovery. A growing lack of confidence in cell lines has seen a shift toward more sophisticated pre-clinical cancer models that incorporate patient-derived tumors as xenografts or explants, to more accurately reflect clinical disease. Not only do these models retain critical features of the original tumor, and account for the molecular diversity and cellular heterogeneity of prostate cancer, but they provide a unique opportunity to conduct research in matched tumor samples. The challenge that accompanies these complex tissue models is increased complexity of analysis. With over 10 years of experience working with patient-derived explants (PDEs) of prostate cancer, this study provides guidance on the PDE method, its limitations, and considerations for addressing the heterogeneity of prostate cancer PDEs that are based on statistical modeling. Using inhibitors of the molecular chaperone heat shock protein 90 (Hsp90) as an example of a drug that induces robust proliferative response, we demonstrate how multi-omics analysis in prostate cancer PDEs is both feasible and essential for identification of key biological pathways, with significant potential for novel drug target and biomarker discovery.

Unravelling Prostate Cancer Heterogeneity Using Spatial Approaches to Lipidomics and Transcriptomics.

Simple SummaryProstate cancer is a heterogenous disease in terms of disease aggressiveness and therapy response, leading to dilemmas in treatment decisions. This heterogeneity reflects the multifocal nature of prostate cancer and its diversity in cellular and molecular composition, necessitating spatial molecular approaches. Here in view of the emerging importance of rewired lipid metabolism as a source of biomarkers and therapeutic targets for prostate cancer, we highlight recent advancements in technologies that enable the spatial mapping of lipids and related metabolic pathways associated with prostate cancer development and progression. We also evaluate their potential for future implementation in treatment decision-making in the clinical management of prostate cancer. Due to advances in the detection and management of prostate cancer over the past 20 years, most cases of localised disease are now potentially curable by surgery or radiotherapy, or amenable to active surveillance without treatment. However, this has given rise to a new dilemma for disease management; the inability to distinguish indolent from lethal, aggressive forms of prostate cancer, leading to substantial overtreatment of some patients and delayed intervention for others. Driving this uncertainty is the critical deficit of novel targets for systemic therapy and of validated biomarkers that can inform treatment decision-making and to select and monitor therapy. In part, this lack of progress reflects the inherent challenge of undertaking target and biomarker discovery in clinical prostate tumours, which are cellularly heterogeneous and multifocal, necessitating the use of spatial analytical approaches. In this review, the principles of mass spectrometry-based lipid imaging and complementary gene-based spatial omics technologies, their application to prostate cancer and recent advancements in these technologies are considered. We put in perspective studies that describe spatially-resolved lipid maps and metabolic genes that are associated with prostate tumours compared to benign tissue and increased risk of disease progression, with the aim of evaluating the future implementation of spatial lipidomics and complementary transcriptomics for prognostication, target identification and treatment decision-making for prostate cancer.

Cellular landscape of tumour microenvironment in prostate cancer.

Prostate cancer is still a public health priority in men and the impact of this disease will be more pronounced with the ageing of the world's population. Clinical heterogeneity of prostate cancer is reflected in spatial and clonal genomic diversity. Accumulating evidence demonstrates that the malignant behaviour of cancer is not only attributed to cancer cells but also fundamentally affected by stromal activity and controlled by various mechanisms of the tumour microenvironment. Data on prostate cancer in this study was derived from seven GEO datasets and the TCGA database. We analyzed the tumour microenvironment of prostate cancer in terms of clinical process, T stage and Gleason score using EPIC and xCell algorithms. We also analyzed the common immune checkpoints. In this study, we confirmed remarkable tumour tissue remodelling in the development of prostate cancer and further demonstrated the importance of cancer-related fibroblasts in the biochemical recurrence and metastasis for patients with prostate cancer undergoing radical radiotherapy or prostatectomy. In addition, we found that NRP1, CD200, TNFSF18 and CD80might be the potential targets for prostate cancer.

Expressed prognostic biomarkers for primary prostate cancer independent of multifocality and transcriptome heterogeneity.

The majority of prostate cancer patients are diagnosed with multiple primary malignant foci. The distinct foci are exceptionally heterogeneous with regard to DNA mutations, but whether this is recapitulated at the transcriptome level remains unknown. In this study, inter- and intrafocal heterogeneity has been assessed by whole-transcriptome sequencing of 87 tissue samples from 23 patients with localized prostate cancer treated with radical prostatectomy. From each patient, multiple samples were taken from one or more malignant foci, in addition to one sample from benign prostate tissue. Transcriptomic profiles of different malignant foci from the same patient showed a similar level of heterogeneity as tumors from different patients. This applies to expression of genes, fusion genes, and somatic mutations. Within-patient pair-wise analyses identified expression patterns linked to ETS status and extraprostatic extension. A set of 62 genes were found with low intrapatient heterogeneity and high interpatient heterogeneity, retaining stable expression profiles across foci within the same patient. Among these, 16 genes are associated with biochemical recurrence in a separately published study and are therefore nominated as biomarkers with prognostic value regardless of which malignant focus is sampled. In conclusion, an extensive heterogeneity in multifocal prostate cancer is confirmed at the gene expression level. Diagnostic biomarkers were identified for ETS positive samples and samples from extraprostatic extensions. Finally, prognostic biomarkers independent of multifocal heterogeneity were found.

Angiogenesis as Therapeutic Target in Metastatic Prostate Cancer - Narrowing the Gap Between Bench and Bedside.

Angiogenesis in metastatic castration-resistant prostate cancer (mCRPC) has been extensively investigated as a promising druggable biological process. Nonetheless, targeting angiogenesis has failed to impact overall survival (OS) in patients with mCRPC despite promising preclinical and early clinical data. This discrepancy prompted a literature review highlighting the tumor heterogeneity and biological context of Prostate Cancer (PCa). Narrowing the gap between the bench and bedside appears critical for developing novel therapeutic strategies. Searching clinicaltrials.gov for studies examining angiogenesis inhibition in patients with PCa resulted in n=20 trials with specific angiogenesis inhibitors currently recruiting (as of September 2021). Moreover, several other compounds with known anti-angiogenic properties – such as Metformin or Curcumin – are currently investigated. In general, angiogenesis-targeting strategies in PCa include biomarker-guided treatment stratification – as well as combinatorial approaches. Beyond established angiogenesis inhibitors, PCa therapies aiming at PSMA (Prostate Specific Membrane Antigen) hold the promise to have a substantial anti-angiogenic effect – due to PSMA´s abundant expression in tumor vasculature.

ONECUT2 as a key mediator of androgen receptor-independent cell growth and neuroendocrine differentiation in castration-resistant prostate cancer.

Despite androgen dependence in a majority of castration-resistant prostate cancers, some cancer cells are independent of androgen receptor (AR) function, a feature of heterogeneity in prostate cancer. One of the aggressive variants of prostate cancer that are AR independent is neuroendocrine prostate cancer (NEPC). This manuscript will focus on the new finding of human one cut domain family member 2 (ONECUT2) transcription factor and its role in castration resistance, especially in NEPC.

Hidden clues in prostate cancer - Lessons learned from clinical and pre-clinical approaches on diagnosis and risk stratification.

The heterogeneity of prostate cancer is evident at clinical, morphological and molecular levels. To aid clinical decision making, a three-tiered system for risk stratification is used to designate low-, intermediate-, and high-risk of disease progression. Intermediate-risk prostate cancers are the most frequently diagnosed, and even with common diagnostic features, can exhibit vastly different clinical progression. Thus, improved risk stratification methods are needed to better predict patient outcomes. Here, we provide an overview of the improvements in diagnosis/prognosis arising from advances in pathology reporting of prostate cancer, which can improve risk stratification, especially for patients with intermediate-risk disease. This review discusses updates to pathology reporting of morphological growth patterns, and proposes the utility of integrating prognostic biomarkers or innovative imaging techniques to enhance clinical decision-making. To complement clinical studies, experimental approaches using patient-derived tumors have highlighted important cellular and morphological features associated with aggressive disease that may impact treatment response. The intersection of urology, pathology and scientific disciplines is required to work towards a common goal of understanding disease pathogenesis, improving the stratification of patients with intermediate-risk disease and subsequently defining optimal treatment strategies using precision-based approaches.

Abstract PO-102: Multifocal analysis of the ETS (-) subtypes, mutated SPOP and overexpression of SPINK-1, in prostate cancer from Colombian patients as a process of understanding the carcinogenesis model of the disease

Abstract The Cancer Genome Atlas (TCGA) Research Network defined the SPOP-mutant subset of prostate cancers (PCa) had frequent overexpression of SPINK1 mRNA, which suggests a relationship in these subtypes that had not been evaluated simultaneously in other studies on ETS(-) subtypes as a key feature in the molecular taxonomy of prostate cancer. However, this analysis was performed on the index tumors and it is suggested that a better knowledge of the different molecular profiles of different neoplastic foci, in the same prostate, could be affecting the relationship of the molecular subtypes and prognosis of the disease. With an approximate 50% prevalence of ETS family gene fusions, attempts to molecularly characterize PCa often begin with the division into ETS(-) and ETS (+). To represent the molecular heterogeneity of PCa, which could improve medical decision-making, we aim to study it through the expression of SPINK-1 and mutations in SPOP; as well as the TMPRSS2-ERG fusion status, in order to assess the clonality of the foci in each patient and also the possible association of this alteration with different degrees of differentiation and lymph node metastasis. FFPE samples of different foci with different lesion degrees: High-Grade Prostatic Intraepithelial Neoplasia (n=17), PCa foci with different Gleason scores (n= 53; GL3: (n=23); GL4: (n=23) and GL5: (n=7)), and positive lymph node (LN) (n=13) from radical prostatectomy from twenty patients were used to analyse the presence of TMPRSS2-ERG fusion and expression levels of ERG and SPINK-1 using RT-PCR. Sanger sequencing was used in exon 6 and 7 to analyze mutations in SPOP. The molecular concordance between the different prostatic foci of the same patient was determined, taking into account subclonal events. The LN were compared with prostatic foci to try to establish its clonal origin. The results indicate that multifocal PCa may have monoclonal or multiclonal origin. SPINK-1 overexpression was the predominant pattern in the LN, while the opposite was the most frequent in the HGPIN samples. None of the thirteen analyzed LN showed the same pattern of other PCa foci from each patient. Metastasis have less molecular heterogeneity than pre-neoplastic lesions. The ERG(+) subtype was found in 54.7% of the foci and 70% of the patients. No mutations were found in SPOP. The frequency of overexpressed SPINK-1 in the 20 patients was 60%. In this study, the frequency of SPINK-1 cases overexpressed in ERG(-) taking into account all the samples analyzed as independent, even if they were from the same patient, due to the high heterogeneity in PCa, coincides with that expected (11%), but it should be taken into account that the foci that tested positive did not show total exclusivity with ERG(+), and in fact, there were more associated with it (74%), which does not agree with what was found in other studies that had not taken into account samples of patients from our country, which highlights the importance of personalized medicine and of not extrapolating results from other populations in our population. Citation Format: Yenifer Y. Segura Moreno, María C. Sanabria Salas, Jorge A. Mesa López De Mesa, Rodolfo Varela Ramirez, Natalia L. Acosta Vega, Martha L. Serrano López. Multifocal analysis of the ETS (-) subtypes, mutated SPOP and overexpression of SPINK-1, in prostate cancer from Colombian patients as a process of understanding the carcinogenesis model of the disease [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-102.

GENOMICS OF PROSTATE CANCER: CLINICAL UTILITY AND CHALLENGES.

The studying of prostate cancer genomics is important for understanding prostate cancer biology, it can provide clinically relevant stratification into subtypes, the development of new prognostic and predictive markers in the context of precision medicine, and the development of new targeted therapies. Recent studies have provided detailed insight into genomics, epigenomics and proteomics of prostate cancer, both primary and metastatic castration-resistant (mCRPC). Many mutations have been discovered, both those that occur early in the carcinogenesis and progression as well as those responsible for the resistance to therapy occurring later under the influence of treatment. A large number of characteristic mutated signaling pathways has been identified, e.g. the mutations in DNA repair pathway were found in 23% of mCRPC, which suggests potential response to PARP inhibitors. Multifocality and intralesional genomic heterogeneity of prostate cancer make the clinical application of genomics complicated. Although a great progress was made in understanding prostate cancer genomic, and clinical studies related to its routine application are ongoing, prostate cancer genomics still needs to find its standard wide routine application in patients with prostate cancer.

Experimental challenges to modeling prostate cancer heterogeneity.

Tumor heterogeneity plays a key role in prostate cancer prognosis, therapy selection, relapse, and acquisition of treatment resistance. Prostate cancer presents a heterogeneous diversity at inter- and intra-tumor and inter-patient levels which are influenced by multiple intrinsic and/or extrinsic factors. Recent studies have started to characterize the complexity of prostate tumors and these different tiers of heterogeneity. In this review, we discuss the most common factors that contribute to tumoral diversity. Moreover, we focus on the description of the in vitro and in vivo approaches, as well as high-throughput technologies, that help to model intra-tumoral diversity. Further understanding tumor heterogeneities and the challenges they present will guide enhanced patient risk stratification, aid the design of more precise therapies, and ultimately help beat this chameleon-like disease.

Multigene Profiling of Circulating Tumor Cells (CTCs) for Prognostic Assessment in Treatment-Naïve Metastatic Hormone-Sensitive Prostate Cancer (mHSPC).

The substantial biological heterogeneity of metastatic prostate cancer has hindered the development of personalized therapeutic approaches. Therefore, it is difficult to predict the course of metastatic hormone-sensitive prostate cancer (mHSPC), with some men remaining on first-line androgen deprivation therapy (ADT) for several years while others progress more rapidly. Improving our ability to risk-stratify patients would allow for the optimization of systemic therapies and support the development of stratified prospective clinical trials focused on patients likely to have the greatest potential benefit. Here, we applied a liquid biopsy approach to identify clinically relevant, blood-based prognostic biomarkers in patients with mHSPC. Gene expression indicating the presence of CTCs was greater in CHAARTED high-volume (HV) patients (52% CTChigh) than in low-volume (LV) patients (23% CTChigh; * p = 0.03). HV disease (p = 0.005, q = 0.033) and CTC presence at baseline prior to treatment initiation (p = 0.008, q = 0.033) were found to be independently associated with the risk of nonresponse at 7 months. The pooled gene expression from CTCs of pre-ADT samples found AR, DSG2, KLK3, MDK, and PCA3 as genes predictive of nonresponse. These observations support the utility of liquid biomarker approaches to identify patients with poor initial response. This approach could facilitate more precise treatment intensification in the highest risk patients.

CD8-positive T cells and CD204-positive M2-like macrophages predict postoperative prognosis of very high-risk prostate cancer

To stratify the heterogeneity of prostate cancer (PCa) with seminal vesicle invasion (SVI) immunologically after radical prostatectomy focusing on the tumor microenvironment. We retrospectively reviewed the clinicopathological data of 71 PCa patients with SVI, which is known as a factor of very high-risk PCa. Preoperative clinical variables and postoperative pathological variables were evaluated as predictors of biochemical recurrence (BCR) with a multivariate logistic regression. Immune cell infiltration including the CD8-positive cell (CD8+ cell) and CD204-positive M2-like macrophage (CD204+ cell) was investigated by immunohistochemistry. The cumulative incidence and risk of BCR were assessed with a Kaplan–Meier analysis and competing risks regression. A higher CD8+ cell count in the SVI area significantly indicated a favorable prognosis for cancers with SVI (p = 0.004). A lower CD204+ cell count in the SVI area also significantly indicated a favorable prognosis for cancers with SVI (p = 0.004). Furthermore, the combination of the CD8+ and CD204+ cell infiltration ratio of the SVI area to the main tumor area was a significant factor for BCR in the patients with the PCa with SVI (p = 0.001). In PCa patients with SVI, the combination of CD8+ and CD204+ cell infiltration is useful to predict the prognosis.

Androgen receptor (AR) heterogeneity in prostate cancer and therapy resistance.

Androgen receptor (AR), a ligand-dependent nuclear transcription factor and a member of steroid hormone receptor family, plays an important role in prostate organogenesis by regulating epithelial differentiation and restricting cell proliferation. Although rarely mutated or amplified in treatment-naïve prostate cancer (PCa), AR signaling drives tumor growth and as a result, therapies that aim to inhibit AR signaling, called ARSIs (AR signaling inhibitors), have been in clinical use for >70 years. Unfortunately, the clinical efficacy of ARSIs is short-lived and the majority of treated patients develop castration-resistant PCa (CRPC). Numerous molecular mechanisms have been proposed for castration resistance; however, the cellular basis for CRPC emergence has remained obscure. One under-appreciated cellular mechanism for CRPC development is the AR heterogeneity that pre-exists in treatment-naive primary tumors, i.e., although most PCa cells express AR (i.e., AR+), there is always a population of PCa cells that express no/low AR (i.e., AR-/lo). Importantly, this AR heterogeneity becomes accentuated during ARSI treatment and highly prominent in established CRPC. Here, we provide a succinct summary of AR heterogeneity across the PCa continuum and discuss its impact on PCa response to treatments. While AR+ PCa cells/clones exhibit exquisite sensitivities to ARSIs, AR-/lo PCa cells/clones, which are greatly enriched in stem cell signaling pathways, display de novo resistance to ARSIs. Finally, we offer several potential combinatorial strategies, e.g., ARSIs with stem cell targeting therapeutics, to co-target both AR+ and AR-/lo PCa cells and metastatic clones.

Subtype heterogeneity and epigenetic convergence in neuroendocrine prostate cancer

Neuroendocrine carcinomas (NEC) are tumors expressing markers of neuronal differentiation that can arise at different anatomic sites but have strong histological and clinical similarities. Here we report the chromatin landscapes of a range of human NECs and show convergence to the activation of a common epigenetic program. With a particular focus on treatment emergent neuroendocrine prostate cancer (NEPC), we analyze cell lines, patient-derived xenograft (PDX) models and human clinical samples to show the existence of two distinct NEPC subtypes based on the expression of the neuronal transcription factors ASCL1 and NEUROD1. While in cell lines and PDX models these subtypes are mutually exclusive, single-cell analysis of human clinical samples exhibits a more complex tumor structure with subtypes coexisting as separate sub-populations within the same tumor. These tumor sub-populations differ genetically and epigenetically contributing to intra- and inter-tumoral heterogeneity in human metastases. Overall, our results provide a deeper understanding of the shared clinicopathological characteristics shown by NECs. Furthermore, the intratumoral heterogeneity of human NEPCs suggests the requirement of simultaneous targeting of coexisting tumor populations as a therapeutic strategy.

Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes

Simple SummaryRecent methodological developments have enabled studying proteins on a large scale in a quantitative fashion, which helps in building comprehensive views of specific molecular settings. These proteomics approaches, and combining their information to genomics and transcriptomics, have revealed that not all genetic and transcriptomic aberrations in prostate cancer are translated to the proteome. This makes it important to understand which ones are translated. Here, we review recent large-scale proteomics studies on clinical prostate cancer and prostate cancer models which help us understand how prostate cancer develops and evades current drug treatments.Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.

Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization.

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.

AR gene rearrangement analysis in liquid biopsies reveals heterogeneity in lethal prostate cancer.

Castration-resistant prostate cancer (CRPC) is driven by AR gene aberrations that arise during androgen receptor (AR)-targeted therapy. AR amplification and mutations have been profiled in circulating tumor cells (CTCs), but whether AR gene rearrangements can be assessed in CTCs is unknown. In this study, we leveraged CRPC cell lines with defined AR gene rearrangements to develop and validate a CTC DNA analysis approach that utilized whole genome amplification and targeted DNA-sequencing of AR and other genes important in CRPC. We tested the utility of this approach by analyzing matched CTC DNA and plasma cell-free DNA (cfDNA) from a case series of ten CRPC patients. One of ten CTC samples and two of ten cfDNA samples were positive for AR gene rearrangements. All AR gene rearrangements were discordant between matched liquid biopsy samples. One patient harbored separate AR gene rearrangements in CTC DNA and cfDNA, but concordant AR amplification and AR T878A mutation. This patient also displayed concordant loss of TP53 and PTEN, but the loss of RB1 in cfDNA only. The overall frequency of discordant alterations in these genes between matched CTC DNA and cfDNA was high. This study establishes the technical feasibility of analyzing structural rearrangements, mutations, and copy number variants in AR and other CRPC genes using two different sources of DNA from a single blood sample. Paired CTC DNA and cfDNA analysis may have utility for capturing the heterogeneity of genetic alterations in CRPC patients.

Circulating tumor cell heterogeneity in neuroendocrine prostate cancer by single cell copy number analysis

Neuroendocrine prostate cancer is an aggressive variant of prostate cancer that may arise de novo or develop from pre-existing prostate adenocarcinoma as a mechanism of treatment resistance. The combined loss of tumor suppressors RB1, TP53, and PTEN are frequent in NEPC but also present in a subset of prostate adenocarcinomas. Most clinical and preclinical studies support a trans-differentiation process, whereby NEPC arises clonally from a prostate adenocarcinoma precursor during the course of treatment resistance. Here we highlight a case of NEPC with significant intra-patient heterogeneity observed across metastases. We further demonstrate how single-cell genomic analysis of circulating tumor cells combined with a phenotypic evaluation of cellular diversity can be considered as a window into tumor heterogeneity in patients with advanced prostate cancer.

SP-0698 The biological basis of heterogeneity in prostate cancer

SP-0698 The biological basis of heterogeneity in prostate cancer

The heterogeneity of prostate cancers lacking AR activity will require diverse treatment approaches.

The use of androgen deprivation therapy and second-line anti-androgens in prostate cancer has led to the emergence of tumors employing multiple androgen receptor (AR)-dependent and AR-independent mechanisms to resist AR-targeted therapies in castration-resistant prostate cancer (CRPC). While the AR signaling axis remains the cornerstone for therapeutic development in CRPC, a clearer understanding of the heterogeneous biology of CRPC tumors is needed for innovative treatment strategies. In this review, we discuss the characteristics of CRPC tumors that lack AR activity and the temporal and spatial considerations for the conversion of an AR-dependent to an AR-independent tumor type. We describe the more prevalent treatment-emergent phenotypes arising in the CRPC disease continuum, including amphicrine, AR-low, double-negative, neuroendocrine and small cell phenotypes. We discuss the association between the loss of AR activity and tumor plasticity with a focus on the roles of transcription factors like SOX2, DNA methylation, alternative splicing, and the activity of epigenetic modifiers like EZH2, BRD4, LSD1, and the nBAF complex in conversion to a neuroendocrine or small cell phenotype in CRPC. We hypothesize that only a subset of CRPC tumors have the propensity for tumor plasticity and conversion to the neuroendocrine phenotype and outline how we might target these plastic and emergent phenotypes in CRPC. In conclusion, we assess the current and future avenues for treatment and determine that the heterogeneity of CRPCs lacking AR activity will require diverse treatment approaches.