Gene expression profiles define molecular subtypes of prostate cancer bone metastases with different outcomes and morphology traceable back to the primary tumor

Investigating Ras homolog gene family member C (RhoC) and Ki67 expression following external beam radiation therapy show increased RhoC expression in relapsing prostate cancer xenografts

Ras homolog gene family member C (RhoC) is a GTPase involved in cell migration, implicated in epithelial-mesenchymal transition and treatment resistance and metastasis of cancer. For example, RhoC has been shown to be involved in resistance to radiation in cervical carcinoma. Here, the effect of X-ray irradiation on RhoC expression in prostate cancer (PCa) xenografts was investigated in both xenografts in regression and relapse. Male BALB/cAnNRj-Foxn1nu/nu mice were inoculated with 4-6 million LNCaP-FGC cells and established xenografts were irradiated with X-rays (200 kV, 1 Gymin-1), 5, 10 or 15 Gy using a Gulmay Medical X-ray system. Expression of RhoC and Ki67, a known proliferation marker, was investigated in xenografts, given 15 Gy, 7 days (midst response as measured by size) or 3 weeks (relapse) post irradiation. Staining was quantified using the Halo software (v2.3.2089.34) with the Indica Labs - cytonuclear v1.6 algorithm. RhoC and Ki67 staining was divided into weak, medium, and strong staining and the percentage of cells stained, single and dual staining, was quantified. The HALO software was further used to classify the tissue in each section so that analysis of RhoC and Ki67 expression in cancer cells, stroma and necrotic areas could be done separately. The results showed that RhoC expression in cancer and stroma cells was significantly higher in relapsed xenografts than in those in regression. This was not seen for Ki67 staining, where the percentage of stained cells were the same in regressing and relapsing tumors. RhoC could be a useful biomarker to confirm relapse following external beam radiation therapy.

From biology to the clinic - exploring liver metastasis in prostate cancer

Liver metastases from prostate cancer are associated with an aggressive disease course and poor prognosis. Results from autopsy studies indicate a liver metastasis prevalence of up to 25% in patients with advanced prostate cancer. Population data estimate that ~3-10% of patients with metastatic castration-resistant prostate cancer harbour liver metastases at the baseline, rising to 20-30% in post-treatment cohorts, suggesting that selective pressure imposed by novel therapies might promote metastatic spread to the liver. Liver metastases are associated with more aggressive tumour biology than lung metastases. Molecular profiling of liver lesions showed an enrichment of low androgen receptor, neuroendocrine phenotypes and high genomic instability. Despite advancements in molecular imaging modalities such as prostate-specific membrane antigen PET-CT, and liquid biopsy markers such as circulating tumour DNA, early detection of liver metastases from prostate cancer remains challenging, as both approaches are hampered by false positive and false negative results, impeding the accurate identification of early liver lesions. Current therapeutic strategies showed limited efficacy in this patient population. Emerging targeted radionuclide therapies, metastasis-directed therapy, and novel systemic agents have shown preliminary activity against liver metastases, but require further validation. Treatment with various novel prostate cancer therapies might lead to an increase in the prevalence of liver metastasis, underscoring the urgent need for coordinated efforts across preclinical and clinical researchers to improve characterization, monitoring, and management of liver metastases from prostate cancer. Elucidating molecular drivers of liver tropism and interactions with the liver microenvironment might ultimately help to identify actionable targets to enhance survival in this high-risk patient group.

Ki67 and prostate specific antigen are prognostic in metastatic hormone naïve prostate cancer

BACKGROUND

For metastatic hormone naïve prostate cancer patients, androgen deprivation therapy (ADT) with escalation therapy including docetaxel and/or androgen targeting drugs is the standard therapy. However, de-escalation is preferable to avoid unnecessary side effects, especially from docetaxel, but markers to identify these patients are lacking. The purpose of the present study was to investigate the potential of PSA and Ki67 immunoreactive scores as prognostic and treatment-predictive markers.

MATERIAL AND METHODS

Prostate biopsies from 92 patients with metastatic hormone naïve PC (PSA > 80 ng/mL or clinical metastases) were immunohistochemically evaluated for PSA and Ki67. Gene expression analysis was performed with Clariom D microarrays to identify the phenotypic profile associated with the immunohistochemistry scores of biopsies. Cox regression analysis for progression free survival after ADT adjustment for age, ISUP, and serum PSA and Kaplan-Meier analyses were performed to assess prognostic values of Ki67, PSA, and the Ki67/PSA ratio.

RESULTS

The immunohistochemical score for PSA was the strongest prognostic factor for progression-free and overall survival after ADT. Consequently, the ratio between Ki67 and PSA displayed a stronger prognostic value than Ki67 itself. Further, mRNA expression data analysis showed an association between high Ki67/PSA ratio, cell-cycle regulation, and DNA damage repair. In an exploratory sub-analysis of 12 patients treated with early docetaxel as addition to ADT and matched controls, a high Ki67/PSA ratio showed potential to identify those who benefit from docetaxel.

CONCLUSION

PSA and Ki67 immunoreactive scores are prognostic in the metastatic hormone-sensitive setting, with PSA being superior. The combination of Ki67 and PSA did not give additional prognostic value. The results suggest immunohistochemical scoring of PSA to have potential to improve identification of patients responding well to ADT alone.

Metabolomic profiles of intact tissues reflect clinically relevant prostate cancer subtypes

BACKGROUND

Prostate cancer (PC) is a heterogenous multifocal disease ranging from indolent to lethal states. For improved treatment-stratification, reliable approaches are needed to faithfully differentiate between high- and low-risk tumors and to predict therapy response at diagnosis.

METHODS

A metabolomic approach based on high resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) analysis was applied on intact biopsies samples (n = 111) obtained from patients (n = 31) treated by prostatectomy, and combined with advanced multi- and univariate statistical analysis methods to identify metabolomic profiles reflecting tumor differentiation (Gleason scores and the International Society of Urological Pathology (ISUP) grade) and subtypes based on tumor immunoreactivity for Ki67 (cell proliferation) and prostate specific antigen (PSA, marker for androgen receptor activity).

RESULTS

Validated metabolic profiles were obtained that clearly distinguished cancer tissues from benign prostate tissues. Subsequently, metabolic signatures were identified that further divided cancer tissues into two clinically relevant groups, namely ISUP Grade 2 (n = 29) and ISUP Grade 3 (n = 17) tumors. Furthermore, metabolic profiles associated with different tumor subtypes were identified. Tumors with low Ki67 and high PSA (subtype A, n = 21) displayed metabolite patterns significantly different from tumors with high Ki67 and low PSA (subtype B, n = 28). In total, seven metabolites; choline, peak for combined phosphocholine/glycerophosphocholine metabolites (PC + GPC), glycine, creatine, combined signal of glutamate/glutamine (Glx), taurine and lactate, showed significant alterations between PC subtypes A and B.

CONCLUSIONS

The metabolic profiles of intact biopsies obtained by our non-invasive HR MAS NMR approach together with advanced chemometric tools reliably identified PC and specifically differentiated highly aggressive tumors from less aggressive ones. Thus, this approach has proven the potential of exploiting cancer-specific metabolites in clinical settings for obtaining personalized treatment strategies in PC.

Molecular classifications of prostate cancer: basis for individualized risk stratification and precision therapy

Tumour classifications play a pivotal role in prostate cancer (PCa) management. It can predict the clinical outcomes of PCa as early as the disease is diagnosed and then guide therapeutic schemes, such as active monitoring, standalone surgical intervention, or surgery supplemented with postoperative adjunctive therapy, thereby circumventing disease exacerbation and excessive treatment. Classifications based on clinicopathological features, such as prostate cancer-specific antigen, Gleason score, and TNM stage, are still the main risk stratification strategies and have played an essential role in standardized clinical decision-making. However, mounting evidence indicates that clinicopathological parameters in isolation fail to adequately capture the heterogeneity exhibited among distinct PCa patients, such as those sharing identical Gleason scores yet experiencing divergent prognoses. As a remedy, molecular classifications have been introduced. Currently, molecular studies have revealed the characteristic genomic alterations, epigenetic modulations, and tumour microenvironment associated with different types of PCa, which provide a chance for urologists to refine the PCa classification. In this context, numerous invaluable molecular classifications have been devised, employing disparate statistical methodologies and algorithmic approaches, encompassing self-organizing map clustering, unsupervised cluster analysis, and multifarious algorithms. Interestingly, the classifier PAM50 was used in a phase-2 multicentre open-label trial, NRG-GU-006, for further validation, which hints at the promise of molecular classification for clinical use. Consequently, this review examines the extant molecular classifications, delineates the prevailing panorama of clinically pertinent molecular signatures, and delves into eight emblematic molecular classifications, dissecting their methodological underpinnings and clinical utility.

Bone Metastases and Health in Prostate Cancer: From Pathophysiology to Clinical Implications

Clinically relevant bone metastases are a major cause of morbidity and mortality for prostate cancer patients. Distinct phenotypes are described: osteoblastic, the more common osteolytic and mixed. A molecular classification has been also proposed. Bone metastases start with the tropism of cancer cells to the bone through different multi-step tumor-host interactions, as described by the "metastatic cascade" model. Understanding these mechanisms, although far from being fully elucidated, could offer several potential targets for prevention and therapy. Moreover, the prognosis of patients is markedly influenced by skeletal-related events. They can be correlated not only with bone metastases, but also with "bad" bone health. There is a close correlation between osteoporosis-a skeletal disorder with decreased bone mass and qualitative alterations-and prostate cancer, in particular when treated with androgen deprivation therapy, a milestone in its treatment. Systemic treatments for prostate cancer, especially with the newest options, have improved the survival and quality of life of patients with respect to skeletal-related events; however, all patients should be evaluated for "bone health" and osteoporotic risk, both in the presence and in the absence of bone metastases. Treatment with bone-targeted therapies should be evaluated even in the absence of bone metastases, as described in special guidelines and according to a multidisciplinary evaluation.

A Novel Radiographic Pattern Related to Poor Prognosis in Patients with Prostate Cancer with Metastatic Spinal Cord Compression

Background

Prostate cancer spinal bone metastases can have a radiographic profile that mimics multiple myeloma.

Objective

To analyse the presence and prognostic value of myeloma-like prostate cancer bone metastases and its relation to known clinical, molecular, and morphological prognostic markers.

Design setting and participants

A cohort of 110 patients with prostate cancer who underwent surgery for metastatic spinal cord compression (MSCC) was analysed. Spinal bone metastases were classified as myeloma like (n = 20) or non-myeloma like (n = 90) based on magnetic resonance imaging prior to surgery. An immunohistochemical analysis of metastasis samples was performed to assess tumour cell proliferation (percentage of Ki67-positive cells) and the expression levels of prostate-specific antigen (PSA) and androgen receptor (AR). The metastasis subtypes MetA, MetB, and MetC were determined from transcriptomic profiling.

Outcome measurements and statistical analysis

Survival curves were compared with the log-rank test. Univariate and multivariate Cox proportional hazard models were used to assess the effects of prognostic variables. Groups were compared using the Mann-Whitney U test for continuous variables and the chi-square test for categorical variables.

Results and limitations

Patients with the myeloma-like metastatic pattern had median survival after surgery for MSCC of 1.7 (range 0.1-33) mo, while the median survival period of those with the non-myeloma-like pattern was 13 (range 0-140) mo (p < 0.001). The myeloma-like appearance had an independent prognostic value for the risk of death after MSCC surgery (adjusted hazard ratio 2.4, p = 0.012). Postoperative neurological function was significantly reduced in the myeloma-like group. No association was found between the myeloma-like pattern and morphological markers of known relevance for this patient group: the transcriptomic subtypes MetA, MetB, and MetC; tumour cell proliferation; and AR and PSA expression.

Conclusions

A myeloma-like metastatic pattern identifies an important subtype of metastatic prostate cancer associated with poor survival and neurological outcomes after surgery for MSCC.

Patient summary

This study describes a novel radiographic pattern of prostate cancer bone metastases and its relation to poor patient prognosis.

Epithelial and Stromal Characteristics of Primary Tumors Predict the Bone Metastatic Subtype of Prostate Cancer and Patient Survival after Androgen-Deprivation Therapy

Simple Summary

Metastatic prostate cancer is a lethal disease and metastasis-specific treatments need to be developed. Mechanisms driving metastases and primary tumor growth could be different, but this is largely unexplored. We previously discovered that bone metastases can be separated into transcriptomic-based subtypes, showing different responses to standard androgen-deprivation therapy for metastatic prostate cancer. One subtype, named MetB, is particularly aggressive and has the worst prognosis. Here, we describe similarities and differences between primary tumors and their metastases, and specifically examine if the development of specific subtype of bone metastases can be predicted by analyzing the primary tumor. Results show that many aspects of prostate cancer bone metastases morphology are related to those in the primary tumor, while others are not. Importantly, men with primary tumors with high cell proliferation and low cellular PSA expression tend to develop metastases enriched for the MetB subtype, have poor prognosis, and need complementary treatment to standard hormone treatment.

Abstract

Prostate cancer (PC) bone metastases can be divided into transcriptomic subtypes, by us termed MetA-C. The MetB subtype, constituting about 20% of the cases, is characterized by high cell cycle activity, low androgen receptor (AR) activity, and a limited response to standard androgen deprivation therapy (ADT). Complementary treatments should preferably be introduced early on if the risk of developing metastases of the MetB subtype is predicted to behigh. In this study, we therefore examined if the bone metastatic subtype and patient outcome after ADT could be predicted by immunohistochemical analysis of epithelial and stromal cell markers in primary tumor biopsies obtained at diagnosis (n = 98). In this advanced patient group, primary tumor International Society of Urological Pathology (ISUP) grade was not associated with outcome or metastasis subtype. In contrast, high tumor cell Ki67 labeling (proliferation) in combination with low tumor cell immunoreactivity for PSA, and a low fraction of AR positive stroma cells in the primary tumors were prognostic for poor survival after ADT. Accordingly, the same tissue markers were associated with developing metastases enriched for the aggressive MetB subtype. The development of the contrasting MetA subtype, showing the best response to ADT, could be predicted by the opposite staining pattern. We conclude that outcome after ADT and metastasis subtype can, at least to some extent, be predicted by analysis of primary tumor characteristics, such as tumor cell proliferation and PSA expression, and AR expression in stromal cells.

Clinical and biological relevance of the transcriptomic-based prostate cancer metastasis subtypes MetA-C

To improve treatment of metastatic prostate cancer, the biology of metastases needs to be understood. We recently described three subtypes of prostate cancer bone metastases (MetA-C), based on differential gene expression. The aim of this study was to verify the clinical relevance of these subtypes and to explore their biology and relations to genetic drivers. Freshly-frozen metastasis samples were obtained as hormone-naive (n = 17), short-term castrated (n = 21), or castration-resistant (n = 65) from a total of 67 patients. Previously published sequencing data from 573 metastasis samples were also analyzed. Through transcriptome profiling and sample classification based on a set of predefined MetA-C-differentiating genes, we found that most metastases were heterogeneous for the MetA-C subtypes. Overall, MetA was the most common subtype, while MetB was significantly enriched in castration-resistant samples and in liver metastases, and consistently associated with poor prognosis. By gene set enrichment analysis, the phenotype of MetA was described by high androgen response, protein secretion and adipogenesis, MetB by high cell cycle activity and DNA repair, and MetC by epithelial-to-mesenchymal transition and inflammation. The MetB subtype demonstrated single nucleotide variants of RB transcriptional corepressor 1 (RB1) and loss of 21 genes at chromosome 13, including RB1, but provided independent prognostic value to those genetic aberrations. In conclusion, a distinct set of gene transcripts can be used to classify prostate cancer metastases into the subtypes MetA-C. The MetA-C subtypes show diverse biology, organ tropism, and prognosis. The MetA-C classification may be used independently, or in combination with genetic markers, primarily to identify MetB patients in need of complementary therapy to conventional androgen receptor-targeting treatments.

Exosomes Derived from RM-1 Cells Promote the Recruitment of MDSCs into Tumor Microenvironment by Upregulating CXCR4 via TLR2/NF-κB Pathway

Myeloid-derived suppressor cells (MDSCs) play a critical role in tumor immune escape because of its remarkable immunosuppressive effect. However, the mechanism of MDSCs migrated into tumor microenvironment remains unclear. In this study, we demonstrated the recruitment of MDSCs can be promoted by exosomes derived from prostate cancer cells, which could upregulate chemokine (CXC motif) receptor 4 (CXCR4) via the TLR2/NF-κB signalling pathway. Flow cytometry detected that the percentage of MDSCs in the mice spleen and tumor tissue was significantly increased after injection with exosomes via mouse tail vein. Transwell chemotaxis assay showed the recruitment of MDSCs toward the lower chamber was enhanced after stimulation with exosomes, and the migration ability could be inhibited by AMD3100 (a CXCR4 specific inhibitor) both in vivo and in vitro. Additionally, Western blot and flow cytometry verified a remarkably increase of CXCR4 in MDSCs after incubation with exosomes; meanwhile, the protein level of TLR2 and activation of NF-κB were also strengthened obviously. Nevertheless, after blocking TLR2 by C29 (a TLR2-specific inhibitor), the expression of p-p65 and CXCR4, which were hypothesized as the downstream target of TLR2, was prominently reduced. In conclusion, prostate cancer-derived exosomes could reinforce CXCR4 expression in MDSCs through the TLR2/NF-κB signalling pathway, eventually promoting migration of MDSCs into tumor microenvironment in a CXCR4-CXCL12 axis-dependent manner.

Molecular Characterization of Prostate Cancers in the Precision Medicine Era

Prostate cancer (PCa) therapy has been recently revolutionized by the approval of new therapeutic agents in the metastatic setting. However, the optimal therapeutic strategy in such patients should be individualized in the light of prognostic and predictive molecular factors, which have been recently studied: androgen receptor (AR) alterations, PTEN-PI3K-AKT pathway deregulation, homologous recombination deficiency (HRD), mismatch repair deficiency (MMRd), and tumor microenvironment (TME) modifications. In this review, we highlighted the clinical impact of prognostic and predictive molecular factors in PCa patients' outcomes, identifying biologically distinct subtypes. We further analyzed the relevant methods to detect these factors, both on tissue, i.e., immunohistochemistry (IHC) and molecular tests, and blood, i.e., analysis of circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA). Moreover, we discussed the main pros and cons of such techniques, depicting their present and future roles in PCa management, throughout the precision medicine era.

A novel DNA methylation signature is associated with androgen receptor activity and patient prognosis in bone metastatic prostate cancer

BACKGROUND

Patients with metastatic prostate cancer (PC) are treated with androgen deprivation therapy (ADT) that initially reduces metastasis growth, but after some time lethal castration-resistant PC (CRPC) develops. A better understanding of the tumor biology in bone metastases is needed to guide further treatment developments. Subgroups of PC bone metastases based on transcriptome profiling have been previously identified by our research team, and specifically, heterogeneities related to androgen receptor (AR) activity have been described. Epigenetic alterations during PC progression remain elusive and this study aims to explore promoter gene methylation signatures in relation to gene expression and tumor AR activity.

MATERIALS AND METHODS

Genome-wide promoter-associated CpG methylation signatures of a total of 94 tumor samples, including paired non-malignant and malignant primary tumor areas originating from radical prostatectomy samples (n = 12), and bone metastasis samples of separate patients with hormone-naive (n = 14), short-term castrated (n = 4) or CRPC (n = 52) disease were analyzed using the Infinium Methylation EPIC arrays, along with gene expression analysis by Illumina Bead Chip arrays (n = 90). AR activity was defined from expression levels of genes associated with canonical AR activity.

RESULTS

Integrated epigenome and transcriptome analysis identified pronounced hypermethylation in malignant compared to non-malignant areas of localized prostate tumors. Metastases showed an overall hypomethylation in relation to primary PC, including CpGs in the AR promoter accompanied with induction of AR mRNA levels. We identified a Methylation Classifier for Androgen receptor activity (MCA) signature, which separated metastases into two clusters (MCA positive/negative) related to tumor characteristics and patient prognosis. The MCA positive metastases showed low methylation levels of genes associated with canonical AR signaling and patients had a more favorable prognosis after ADT. In contrast, MCA negative patients had low AR activity associated with hypermethylation of AR-associated genes, and a worse prognosis after ADT.

CONCLUSIONS

A promoter methylation signature classifies PC bone metastases into two groups and predicts tumor AR activity and patient prognosis after ADT. The explanation for the methylation diversities observed during PC progression and their biological and clinical relevance need further exploration.

Personal Medicine and Bone Metastases: Biomarkers, Micro-RNAs and Bone Metastases

Bone metastasis is a major cause of morbidity within solid tumours of the breast, prostate, lung and kidney. Metastasis to the skeleton is associated with a wide range of complications including bone fractures, spinal cord compression, hypercalcaemia and increased bone pain. Improved treatments for bone metastasis, such as the use of anti-bone resorptive bisphosphonate agents, within post-menopausal women have improved disease-free survival; however, these treatments are not without side effects. There is thus a need for biomarkers, which will predict the risk of developing the spread to bone within these cancers. The application of molecular profiling techniques, together with animal model systems and engineered cell-lines has enabled the identification of a series of potential bone-metastasis biomarker molecules predictive of bone metastasis risk. Some of these biomarker candidates have been validated within patient-derived samples providing a step towards clinical utility. Recent developments in multiplex biomarker quantification now enable the simultaneous measurement of up to 96 micro-RNA/protein molecules in a spatially defined manner with single-cell resolution, thus enabling the characterisation of the key molecules active at the sites of pre-metastatic niche formation as well as tumour-stroma signalling. These technologies have considerable potential to inform biomarker discovery. Additionally, a potential future extension of these discoveries could also be the identification of novel drug targets within cancer spread to bone. This chapter summarises recent findings in biomarker discovery within the key bone metastatic cancers (breast, prostate, lung and renal cell carcinoma). Tissue-based and circulating blood-based biomarkers are discussed from the fields of genomics, epigenetic regulation (micro-RNAs) and protein/cell-signalling together with a discussion of the potential future development of these markers towards clinical development.