Molecular classification of prostate cancer using curated expression signatures. Proc Natl Acad Sci U S A. 2011;108:21276-21281. [PMID: 22123976 DOI: 10.1073/pnas.1117029108]

Nanomedicines in diagnosis and treatment of prostate cancers: an updated review

Prostate cancer (PC) is the third most common male cancer in the world, which occurs due to various mutations leading to the loss of chromatin structure. There are multiple treatments for this type of cancer, of which chemotherapy is one of the most important. Sometimes, a combination of different treatments, such as chemotherapy, radiotherapy, and surgery, are used to prevent tumor recurrence. Among other treatments, androgen deprivation therapy (ADT) can be mentioned, which has had promising results. One of the drawbacks of chemotherapy and ADT treatments is that they are not targeted to the tumor tissue. For this reason, their use can cause extensive side effects. Treatments based on nanomaterials, known as nanomedicine, have attracted much attention today. Nanoparticles (NPs) are one of the main branches of nanomedicine, and they can be made of different materials such as polymer, metal, and carbon, each of which has distinct characteristics. In addition to NPs, nanovesicles (NVs) also have therapeutic applications in PC. In treating PC, synthetic NVs (liposomes, micelles, and nanobubbles) or produced from cells (exosomes) can be used. In addition to the role that NPs and NVs have in treating PC, due to being targeted, they can be used to diagnose PC and check the treatment process. Knowing the characteristics of nanomedicine-based treatments can help design new treatments and improve researchers' understanding of tumor biology and its rapid diagnosis. In this study, we will discuss conventional and nanomedicine-based treatments. The results of these studies show that the use of NPs and NVs in combination with conventional treatments has higher efficacy in tumor treatment than the individual use of each of them.

Boosting predictive models and augmenting patient data with relevant genomic and pathway information

The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized care and patient outcomes heavily rely on early relapse identification, yet current predictive models, despite their potential, lack comprehensive genetic data. This inadequacy fuels our research focus-integrating specific genetic information, such as pathway scores, into clinical data. Our aim is to refine machine learning models for more precise relapse prediction in early-stage non-small cell lung cancer. To address the scarcity of genetic data, we employ imputation techniques, leveraging publicly available datasets such as The Cancer Genome Atlas (TCGA), integrating pathway scores into our patient cohort from the Cancer Long Survivor Artificial Intelligence Follow-up (CLARIFY) project. Through the integration of imputed pathway scores from the TCGA dataset with clinical data, our approach achieves notable strides in predicting relapse among a held-out test set of 200 patients. By training machine learning models on enriched knowledge graph data, inclusive of triples derived from pathway score imputation, we achieve a promising precision of 82% and specificity of 91%. These outcomes highlight the potential of our models as supplementary tools within tumour, node, and metastasis (TNM) classification systems, offering improved prognostic capabilities for lung cancer patients. In summary, our research underscores the significance of refining machine learning models for relapse prediction in early-stage non-small cell lung cancer. Our approach, centered on imputing pathway scores and integrating them with clinical data, not only enhances predictive performance but also demonstrates the promising role of machine learning in anticipating relapse and ultimately elevating patient outcomes.

Synergy between imputed genetic pathway and clinical information for predicting recurrence in early stage non-small cell lung cancer

OBJECTIVE

Lung cancer exhibits unpredictable recurrence in low-stage tumors and variable responses to different therapeutic interventions. Predicting relapse in early-stage lung cancer can facilitate precision medicine and improve patient survivability. While existing machine learning models rely on clinical data, incorporating genomic information could enhance their efficiency. This study aims to impute and integrate specific types of genomic data with clinical data to improve the accuracy of machine learning models for predicting relapse in early-stage, non-small cell lung cancer patients.

METHODS

The study utilized a publicly available TCGA lung cancer cohort and imputed genetic pathway scores into the Spanish Lung Cancer Group (SLCG) data, specifically in 1348 early-stage patients. Initially, tumor recurrence was predicted without imputed pathway scores. Subsequently, the SLCG data were augmented with pathway scores imputed from TCGA. The integrative approach aimed to enhance relapse risk prediction performance.

RESULTS

The integrative approach achieved improved relapse risk prediction with the following evaluation metrics: an area under the precision-recall curve (PR-AUC) score of 0.75, an area under the ROC (ROC-AUC) score of 0.80, an F1 score of 0.61, and a Precision of 0.80. The prediction explanation model SHAP (SHapley Additive exPlanations) was employed to explain the machine learning model's predictions.

CONCLUSION

We conclude that our explainable predictive model is a promising tool for oncologists that addresses an unmet clinical need of post-treatment patient stratification based on the relapse risk while also improving the predictive power by incorporating proxy genomic data not available for specific patients.

Current view of liver cancer cell-of-origin and proposed mechanisms precluding its proper determination

Hepatocellular carcinoma and intrahepatic cholangiocarcinoma are devastating primary liver cancers with increasing prevalence in many parts of the world. Despite intense investigation, many aspects of their biology are still largely obscure. For example, numerous studies have tackled the question of the cell-of-origin of primary liver cancers using different experimental approaches; they have not, however, provided a clear and undisputed answer. Here, we will review the evidence from animal models supporting the role of all major types of liver epithelial cells: hepatocytes, cholangiocytes, and their common progenitor as liver cancer cell-of-origin. Moreover, we will also propose mechanisms that promote liver cancer cell plasticity (dedifferentiation, transdifferentiation, and epithelial-to-mesenchymal transition) which may contribute to misinterpretation of the results and which make the issue of liver cancer cell-of-origin particularly complex.

Epigenetic regulation of pluripotency inducer genes NANOG and SOX2 in human prostate cancer

The cells of multicellular organisms are genetically homogeneous but heterogenous in structure and function by virtue of differential gene expression. During embryonic development, differential gene expression by modification of chromatin (DNA and histone complex) regulates the developmental proceedings before and after the germ layers are formed. Post-replicative DNA modification, where the fifth carbon atom of the cytosine gets methylated (hereafter, DNA methylation), does not incorporate mutations within the DNA. In the past few years, a boom has been observed in the field of research related to various epigenetic regulation models, which includes DNA methylation, post-translational modification of histone tails, control of chromatin structure by non-coding RNAs, and remodeling of nucleosome. Epigenetic effects like DNA methylation or histone modification play a cardinal role in development but also be able to arise stochastically, as observed during aging, in tumor development and cancer progression. Over the past few decades, researchers allured toward the involvement of pluripotency inducer genes in cancer progression and apparent for prostate cancer (PCa); also, PCa is the most diagnosed tumor worldwide and comes to the second position in causing mortality in men. The anomalous articulation of pluripotency-inducing transcription factor; SRY-related HMG box-containing transcription factor-2 (SOX2), Octamer-binding transcription factor 4 (OCT4) or POU domain, class 5, transcription factor 1 (POU5F1), and NANOG have been reported in different cancers which includes breast cancer, tongue cancer, and lung cancer, etc. Although there is a variety in gene expression signatures demonstrated by cancer cells, the epigenetic mode of regulation at the pluripotency-associated genes in PCa has been recently explored. This chapter focuses on the epigenetic control of NANOG and SOX2 genes in human PCa and the precise role thereof executed by the two transcription factors.

A Phase II Study of sEphB4-HSA in Metastatic Castration-Resistant Prostate Cancer

INTRODUCTION

Ephrin receptors and their membrane-localized ligands induce bidirectional signaling and facilitate tumor-stroma interactions. Blocking the EphB4-EphrinB2 pathway, which can be accomplished by soluble EphB4 conjugated to human serum albumin (sEphB4-HSA), promotes cell death in preclinical models of aggressive prostate cancer. We hypothesized that targeting the EphB4-EphrinB2 pathway may serve as a therapeutic target in the treatment of metastatic castration resistant prostate cancer (mCRPC).

PATIENTS AND METHODS

We conducted a single arm, phase II trial in patients with progressive mCRPC who had received no more than 3 prior therapies for mCRPC. sEphB4-HSA 1000 mg IV was administered every 2 weeks, extending to 3 weeks starting from cycle 7. The primary endpoint was confirmed prostate specific antigen (PSA) response rate. We employed a Simon 2-stage Minimax design with 15 patients in the first stage and 10 additional patients in the second stage.

RESULTS

Fourteen eligible patients enrolled in the study with median age of 73.5 years (range: 52-83) and median baseline PSA of 65.11 ng/mL (range: 7.77-2850 ng/mL). Most patients received 3 prior therapies for mCRPC. The median treatment duration with sEphB4-HSA was 6.5 weeks (range: 2-35 weeks). Three patients experienced a serious adverse event potentially related to therapy, including 1 patient with a grade 5 event (cerebral vascular accident) possibly related to the study drug. No patient had a confirmed PSA response, and the study was stopped for futility. Thirteen patients had PSA progression. The median time to PSA progression was 28 days (90% CI: 28-42 days), and median time to radiologic progression was 55 days (90% CI: 54-72 days). Of 3 patients with measurable disease, 2 had stable disease and one had progressive disease.

CONCLUSION

In patients with mCRPC who progressed on prior second generation AR-targeted therapy, sEphB4-HSA monotherapy had no discernable anti-tumor activity.

SR9009 inhibits lethal prostate cancer subtype 1 by regulating the LXRα/FOXM1 pathway independently of REV-ERBs

Perturbations of the circadian clock are linked to multiple diseases, including cancers. Pharmacological activation of REV-ERB nuclear receptors, the core components of the circadian clock, has antitumor effects on various malignancies, while the impact of SR9009 on prostate cancer (PCa) remains unknown. Here, we found that SR9009 was specifically lethal to PCa cell lines but had no cytotoxic effect on prostate cells. SR9009 significantly inhibited colony formation, the cell cycle, and cell migration and promoted apoptosis in PCa cells. SR9009 treatment markedly inhibited prostate cancer subtype 1 (PCS1), the most lethal and aggressive PCa subtype, through FOXM1 pathway blockade, while it had no impacts on PCS2 and PCS3. Seven representative genes, including FOXM1, CENPA, CENPF, CDK1, CCNB1, CCNB2, and BIRC5, were identified as the shared genes involved in the FOXM1 pathway and PCS1. All of these genes were upregulated in PCa tissues, associated with worse clinicopathological outcomes and downregulated after SR9009 treatment. Nevertheless, knockdown or knockout of REV-ERB could not rescue the anticancer effect of SR9009 in PCa. Further analysis confirmed that it was LXRα rather than REV-ERBs which has been activated by SR9009. The expression levels of these seven genes were changed correspondingly after LXRα knockdown and SR9009 treatment. An in vivo study validated that SR9009 restrained tumor growth in 22RV1 xenograft models and inhibited FOXM1 and its targeted gene expression. In summary, SR9009 can serve as an effective treatment option for highly aggressive and lethal PCS1 tumors through mediating the LXRα/FOXM1 pathway independently of REV-ERBs.

PTEN Protein Phosphatase Activity Is Not Required for Tumour Suppression in the Mouse Prostate

Loss PTEN function is one of the most common events driving aggressive prostate cancers and biochemically, PTEN is a lipid phosphatase which opposes the activation of the oncogenic PI3K-AKT signalling network. However, PTEN also has additional potential mechanisms of action, including protein phosphatase activity. Using a mutant enzyme, PTEN Y138L, which selectively lacks protein phosphatase activity, we characterised genetically modified mice lacking either the full function of PTEN in the prostate gland or only lacking protein phosphatase activity. The phenotypes of mice carrying a single allele of either wild-type Pten or Pten^Y138L in the prostate were similar, with common prostatic intraepithelial neoplasia (PIN) and similar gene expression profiles. However, the latter group, lacking PTEN protein phosphatase activity additionally showed lymphocyte infiltration around PIN and an increased immune cell gene expression signature. Prostate adenocarcinoma, elevated proliferation and AKT activation were only frequently observed when PTEN was fully deleted. We also identify a common gene expression signature of PTEN loss conserved in other studies (including Nkx3.1, Tnf and Cd44). We provide further insight into tumour development in the prostate driven by loss of PTEN function and show that PTEN protein phosphatase activity is not required for tumour suppression.

The genes controlling normal function of citrate and spermine secretion are lost in aggressive prostate cancer and prostate model systems

High secretion of the metabolites citrate and spermine is a unique hallmark for normal prostate epithelial cells, and is reduced in aggressive prostate cancer. However, the identity of the genes controlling this biological process is mostly unknown. In this study, we have created a gene signature of 150 genes connected to citrate and spermine secretion in the prostate. We have computationally integrated metabolic measurements with multiple transcriptomics datasets from the public domain, including 3826 tissue samples from prostate and prostate cancer. The accuracy of the signature is validated by its unique enrichment in prostate samples and prostate epithelial tissue compartments. The signature highlights genes AZGP1, ANPEP and metallothioneins with zinc-binding properties not previously studied in the prostate, and the expression of these genes are reduced in more aggressive cancer lesions. However, the absence of signature enrichment in common prostate model systems can make it challenging to study these genes mechanistically.

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Novel 150 gene signature reflecting prostatic citrate and spermine secretion

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Identified several zinc-binding proteins not previously investigated in the prostate

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The signature is absent in prostate model systems

Molecular classification of hormone-sensitive and castration-resistant prostate cancer, using nonnegative matrix factorization molecular subtyping of primary and metastatic specimens

BACKGROUND

Despite the rapidly evolving therapeutic landscape, immunotherapy has demonstrated limited activity in prostate cancer. A greater understanding of the molecular landscape, particularly the expression of immune-related pathways, will inform future immunotherapeutic strategies. Consensus nonnegative matrix factorization (cNMF) is a novel model of molecular classification analyzing gene expression data, focusing on biological interpretation of metagenes and selecting meaningful clusters.

OBJECTIVE

We aimed to identify molecular subtypes of prostate cancer using cNMF and correlate these with existing biomarkers to inform future immunotherapeutic strategies.

METHODS

A cohort of archival tumor specimens from hormone-sensitive and castration-resistant disease was studied. Whole transcriptomic profiles were generated using TruSeq RNA Access technology and subjected to cNMF. Comprehensive genomic profiling was performed with the FoundationOne assay. NMF subtypes were characterized by gene expression pathways, genomic alterations and correlated with clinical data, then applied to The Cancer Genome Atlas data set.

RESULTS

We studied 164 specimens, including 52 castration-resistant and 13 paired primary/metastatic specimens. cNMF identified four distinct subtypes. NMF1 (19%) is enriched for immune-related and stromal-related pathways with transforming growth factor β (TGFβ) signature. NMF2 (36%) is associated with FOXO-mediated transcription signature and AKT signaling, NMF3 (26%) is enriched for ribosomal RNA processing, while NMF4 (19%) is enriched for cell cycle and DNA-repair pathways. The most common gene alterations included TMPRSS22 (42%), TP53 (23%), and DNA-repair genes (19%), occurring across all subtypes. NMF4 is significantly enriched for MYC and Wnt-signaling gene alterations. TMB, CD8 density, and PD-L1 expression were low overall. NMF1 and NMF4 were NMF2 was associated with superior overall survival.

CONCLUSIONS

Using cNMF, we identified four molecularly distinct subtypes which may inform treatment selection. NMF1 demonstrates the most inflammatory signature with asuppressive TGFβ signature, suggesting potential benefit with immunotherapy combination strategies targeting TGFβ and PD-(L)1. Prospective studies are required to evaluate the use of this novel model to molecularly stratify patients for optimal treatment selection.

Genome-wide cross-cancer analysis illustrates the critical role of bimodal miRNA in patient survival and drug responses to PI3K inhibitors

Heterogeneity of cancer means many tumorigenic genes are only aberrantly expressed in a subset of patients and thus follow a bimodal distribution, having two modes of expression within a single population. Traditional statistical techniques that compare sample means between cancer patients and healthy controls fail to detect bimodally expressed genes. We utilize a mixture modeling approach to identify bimodal microRNA (miRNA) across cancers, find consistent sources of heterogeneity, and identify potential oncogenic miRNA that may be used to guide personalized therapies. Pathway analysis was conducted using target genes of the bimodal miRNA to identify potential functional implications in cancer. In vivo overexpression experiments were conducted to elucidate the clinical importance of bimodal miRNA in chemotherapy treatments. In nine types of cancer, tumors consistently displayed greater bimodality than normal tissue. Specifically, in liver and lung cancers, high expression of miR-105 and miR-767 was indicative of poor prognosis. Functional pathway analysis identified target genes of miR-105 and miR-767 enriched in the phosphoinositide-3-kinase (PI3K) pathway, and analysis of over 200 cancer drugs in vitro showed that drugs targeting the same pathway had greater efficacy in cell lines with high miR-105 and miR-767 levels. Overexpression of the two miRNA facilitated response to PI3K inhibitor treatment. We demonstrate that while cancer is marked by considerable genetic heterogeneity, there is between-cancer concordance regarding the particular miRNA that are more variable. Bimodal miRNA are ideal biomarkers that can be used to stratify patients for prognosis and drug response in certain types of cancer.

Bimodal genes can be defined as those having two modes of expression within the same population. A variety of statistical methodologies have been employed to assess bimodal gene expression, but current methods and their applications have been limited. Given the advances in next-generation sequencing as well as the extensive regulatory role of miRNA, assessing bimodality in miRNA-seq data can greatly broaden our understanding of factors underlying tumor progression. The goal of the current study was to utilize a novel mixture modeling approach to identify bimodal miRNA and then demonstrate their importance in cancer by evaluating their ability to predict overall survival and drug response. Our results showed that high levels of bimodal miRNA expression was characteristic of cancer. Additionally, several bimodal miRNA were common to multiple cancer types, suggesting that certain miRNA consistently account for tumor heterogeneity and may be involved in general oncogenic processes. Our study points to the potential of bimodal miRNA to facilitate precise prognostic evaluation and effective treatment strategies.

Clonal evolution after treatment pressure in multiple myeloma: heterogenous genomic aberrations and transcriptomic convergence

We investigated genomic and transcriptomic changes in paired tumor samples of 29 in-house multiple myeloma (MM) patients and 28 patients from the MMRF CoMMpass study before and after treatment. A change in clonal composition was found in 46/57 (82%) of patients, and single-nucleotide variants (SNVs) increased from median 67 to 86. The highest increase in prevalence of genetic aberrations was found in RAS genes (60% to 72%), amp1q21 (18% to 35%), and TP53 (9% to 18%). The SBS-MM1 mutation signature was detected both in patients receiving high and low dose melphalan. A total of 2589 genes were differentially expressed between early and late samples (FDR < 0.05). Gene set enrichment analysis (GSEA) showed increased expression of E2F, MYC, and glycolysis pathways and a decreased expression in TNF-NFkB and TGFbeta pathways in late compared to early stage. Single sample GSEA (ssGSEA) scores of differentially expressed pathways revealed that these changes were most evident in end-stage disease. Increased expression of several potentially targetable genes was found at late disease stages, including cancer-testis antigens, XPO1 and ABC transporters. Our study demonstrates a transcriptomic convergence of pathways supporting increased proliferation and metabolism during disease progression in MM.

A case of microsatellite instability-high clinically advanced castration-resistant prostate cancer showing a remarkable response to pembrolizumab sustained over at least 18 months

Defective DNA mismatch repair genes can lead to microsatellite instability (MSI)-high status in prostate cancer (PC). Accumulation of replication errors in DNA leads to the production of abundant neoantigens, which could be targets for immune checkpoint inhibitors (CPIs). However, the incidence of MSI-high PC is low, and not all patients show a satisfactory therapeutic response to CPIs. Here, we present the case of a patient with MSI-high castration-resistant PC who showed a remarkable and durable response to pembrolizumab. The patient was resistant to abiraterone, docetaxel, and cabazitaxel and was suffering from multiple tumor-associated or treatment-related complications, such as urinary tract infection, infective endocarditis, and uncontrollable prostatic hemorrhage. Soon after the start of pembrolizumab therapy, the patient showed a dramatic decrease in prostate-specific antigen from 35.67 ng/mL to an undetectable level and a remarkable reduction in the size of a massive prostate mass and lymph node metastases, with an absence of treatment-related complications. Specimens from the transurethral resection of prostate cancer during cabazitaxel treatment for control of prostate bleeding and also that from the prostate biopsy at initial diagnosis revealed MSI-high status. Immunohistochemistry showed loss of MSH2 and MSH6, and whole-exome sequencing revealed an approximate tumor mutation burden of 61 mutations/Mb as well as biallelic loss of MSH2. Pembrolizumab could show a significant effect even in a heavily treated patient with MSI-high advanced PC. Accumulation of detailed clinical and genomic information of cases of MSI-high PC treated with pembrolizumab is necessary for optimal patient selection.

SEPA: Signalling entropy-based algorithm to evaluate personalized pathway activation for survival analysis on pan-cancer data

MOTIVATION

Biomarkers with prognostic ability and biological interpretability can be used to support decision-making in the survival analysis. Genes usually form functional modules to play synergistic roles, such as pathways. Predicting significant features from the functional level can effectively reduce the adverse effects of heterogeneity and obtain more reproducible and interpretable biomarkers. Personalized pathway activation inference can quantify the dysregulation of essential pathways involved in the initiation and progression of cancers, and can contribute to the development of personalized medical treatments.

RESULTS

In this study, we propose a novel method to evaluate personalized pathway activation based on signalling entropy for survival analysis (SEPA), which is a new attempt to introduce the information-theoretic entropy in generating pathway representation for each patient. SEPA effectively integrates pathway-level information into gene expression data, converting the high-dimensional gene expression data into the low-dimensional biological pathway activation scores. SEPA shows its classification power on the prognostic pan-cancer genomic data, and the potential pathway markers identified based on SEPA have statistical significance in the discrimination of high-risk and low-risk cohorts and are likely to be associated with the initiation and progress of cancers. The results show that SEPA scores can be used as an indicator to precisely distinguish cancer patients with different clinical outcomes, and identify important pathway features with strong discriminative power and biological interpretability.

AVAILABILITY

The MATLAB-package for SEPA is freely available from https://github.com/xingyili/SEPA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A novel defined risk signature based on pyroptosis-related genes can predict the prognosis of prostate cancer

Background

Pyroptosis can not only inhibit the occurrence and development of tumors but also develop a microenvironment conducive to cancer growth. However, pyroptosis research in prostate cancer (PCa) has rarely been reported.

Methods

The expression profile and corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Patients were divided into different clusters using consensus clustering analysis, and differential genes were obtained. We developed and validated a prognostic biomarker for biochemical recurrence (BCR) of PCa using univariate Cox analysis, Lasso-Cox analysis, Kaplan–Meier (K–M) survival analysis, and time-dependent receiver operating characteristics (ROC) curves.

Results

The expression levels of most pyroptosis-related genes (PRGs) are different not only between normal and tumor tissues but also between different clusters. Cluster 2 patients have a better prognosis than cluster 1 patients, and there are significant differences in immune cell content and biological pathway between them. Based on the classification of different clusters, we constructed an eight genes signature that can independently predict the progression-free survival (PFS) rate of a patient, and this signature was validated using a GEO data set (GSE70769). Finally, we established a nomogram model with good accuracy.

Conclusions

In this study, PRGs were used as the starting point and based on the expression profile and clinical data, a prognostic signature with a high predictive value for biochemical recurrence (BCR) following radical prostatectomy (RP) was finally constructed, and the relationship between pyroptosis, immune microenvironment, and PCa was explored, providing important clues for future research on pyroptosis and immunity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01172-5.

Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches

Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In this context, a deeper understanding of metabolic reprogramming, an emerging hallmark of cancer, could provide novel opportunities for cancer diagnosis, prognosis, and treatment. In this setting, multi-omics data integration approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, and metabolomics, could offer unprecedented opportunities for uncovering the molecular changes underlying metabolic rewiring in complex diseases, such as PCa. Recent studies, focused on the integrated analysis of multi-omics data derived from PCa patients, have in fact revealed new insights into specific metabolic reprogramming events and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients. This review aims to provide an up-to-date summary of multi-omics studies focused on the characterization of the metabolomic phenotype of PCa, as well as an in-depth analysis of the correlation between changes identified in the multi-omics studies and the metabolic profile of PCa tumors.

A comparative study of PCS and PAM50 prostate cancer classification schemes

BACKGROUND

Two prostate cancer (PC) classification methods based on transcriptome profiles, a de novo method referred to as the "Prostate Cancer Classification System" (PCS) and a variation of the established PAM50 breast cancer algorithm, were recently proposed. Both studies concluded that most human PC can be assigned to one of three tumor subtypes, two categorized as luminal and one as basal, suggesting the two methods reflect consistency in underlying biology. Despite the similarity, differences and commonalities between the two classification methods have not yet been reported.

METHODS

Here, we describe a comparison of the PCS and PAM50 classification systems. PCS and PAM50 signatures consisting of 37 (PCS37) and 50 genes, respectively, were used to categorize 9,947 PC patients into PCS and PAM50 classes. Enrichment of hallmark gene sets and luminal and basal marker gene expression were assessed in the same datasets. Finally, survival analysis was performed to compare PCS and PAM50 subtypes in terms of clinical outcomes.

RESULTS

PCS and PAM50 subtypes show clear differential expression of PCS37 and PAM50 genes. While only three genes are shared in common between the two systems, there is some consensus between three subtype pairs (PCS1 versus Luminal B, PCS2 versus Luminal A, and PCS3 versus Basal) with respect to gene expression, cellular processes, and clinical outcomes. PCS categories displayed better separation of cellular processes and luminal and basal marker gene expression compared to PAM50. Although both PCS1 and Luminal B tumors exhibited the worst clinical outcomes, outcomes between aggressive and less aggressive subtypes were better defined in the PCS system, based on larger hazard ratios observed.

CONCLUSION

The PCS and PAM50 classification systems are similar in terms of molecular profiles and clinical outcomes. However, the PCS system exhibits greater separation in multiple clinical outcomes and provides better separation of prostate luminal and basal characteristics.

Fatty acid oxidation is required for embryonic stem cell survival during metabolic stress

Metabolic regulation is critical for the maintenance of pluripotency and the survival of embryonic stem cells (ESCs). The transcription factor Tfcp2l1 has emerged as a key factor for the naïve pluripotency of ESCs. Here, we report an unexpected role of Tfcp2l1 in metabolic regulation in ESCs-promoting the survival of ESCs through regulating fatty acid oxidation (FAO) under metabolic stress. Tfcp2l1 directly activates many metabolic genes in ESCs. Deletion of Tfcp2l1 leads to an FAO defect associated with upregulation of glucose uptake, the TCA cycle, and glutamine catabolism. Mechanistically, Tfcp2l1 activates FAO by inducing Cpt1a, a rate-limiting enzyme transporting free fatty acids into the mitochondria. ESCs with defective FAO are sensitive to cell death induced by glycolysis inhibition and glutamine deprivation. Moreover, the Tfcp2l1-Cpt1a-FAO axis promotes the survival of quiescent ESCs and diapause-like blastocysts induced by mTOR inhibition. Thus, our results reveal how ESCs orchestrate pluripotent and metabolic programs to ensure their survival in response to metabolic stress.

A risk prediction model of gene signatures in ovarian cancer through bagging of GA-XGBoost models

Introduction

Ovarian cancer (OC) is one of the most frequent gynecologic cancers among women, and high-accuracy risk prediction techniques are essential to effectively select the best intervention strategies and clinical management for OC patients at different risk levels. Current risk prediction models used in OC have low sensitivity, and few of them are able to identify OC patients at high risk of mortality, which would both optimize the treatment of high-risk patients and prevent unnecessary medical intervention in those at low risk.

Objectives

To this end, we have developed a bagging-based algorithm with GA-XGBoost models that predicts the risk of death from OC using gene expression profiles.

Methods

Four gene expression datasets from public sources were used as training (n = 1) or validation (n = 3) sets. The performance of our proposed algorithm was compared with fine-tuning and other existing methods. Moreover, the biological function of selected genetic features was further interpreted, and the response to a panel of approved drugs was predicted for different risk levels.

Results

The proposed algorithm showed good sensitivity (74-100%) in the validation sets, compared with two simple models whose sensitivity only reached 47% and 60%. The prognostic gene signature used in this study was highly connected to AKT, a key component of the PI3K/AKT/mTOR signaling pathway, which influences the tumorigenesis, proliferation, and progression of OC.

Conclusion

These findings demonstrated an improvement in the sensitivity of risk classification of OC patients with our risk prediction models compared with other methods. Ongoing effort is needed to validate the outcomes of this approach for precise clinical treatment.

Leveraging Single-Cell Approaches in Cancer Precision Medicine

Cancer precision medicine aims to improve patient outcomes by tailoring treatment to the unique genomic background of a tumor. However, efforts to develop prognostic and drug response biomarkers largely rely on bulk 'omic' data, which fails to capture intratumor heterogeneity (ITH) and deconvolve signals from normal versus tumor cells. These shortcomings in measuring clinically relevant features are being addressed with single-cell technologies, which provide a fine-resolution map of the genetic and phenotypic heterogeneity in tumors and their microenvironment, as well as an improved understanding of the patterns of subclonal tumor populations. Here we present recent advances in the application of single-cell technologies, towards gaining a deeper understanding of ITH and evolution, and potential applications in developing personalized therapeutic strategies.

p53 and Tumor Suppression: It Takes a Network

The TP53 tumor suppressor is the most frequently mutated gene in human cancer. p53 suppresses tumorigenesis by transcriptionally regulating a network of target genes that play roles in various cellular processes. Though originally characterized as a critical regulator for responses to acute DNA damage (activation of apoptosis and cell cycle arrest), recent studies have highlighted new pathways and transcriptional targets downstream of p53 regulating genomic integrity, metabolism, redox biology, stemness, and non-cell autonomous signaling in tumor suppression. Here, we summarize our current understanding of p53-mediated tumor suppression, situating recent findings from mouse models and unbiased screens in the context of previous studies and arguing for the importance of the pleiotropic effects of the p53 transcriptional network in inhibiting cancer.

CHD1 loss negatively influences metastasis-free survival in R0-resected prostate cancer patients and promotes spontaneous metastasis in vivo

The outcome of prostate cancer (PCa) patients is highly variable and depends on whether or not distant metastases occur. Multiple chromosomal deletions have been linked to early tumor marker PSA recurrence (biochemical relapse, BCR) after radical prostatectomy (RP), but their potential role for distant metastasis formation is largely unknown. Here, we specifically analyzed whether deletion of the tumor suppressor CHD1 (5q21) influences the post-surgical risk of distant metastasis and whether CHD1 loss directly contributes to metastasis formation in vivo. By considering >6800 patients we found that the CHD1 deletion negatively influences metastasis-free survival in R0 patients (HR: 2.32; 95% CI: 1.61, 3.33; p < 0.001) independent of preoperative PSA, pT stage, pN status, Gleason Score, and BCR. Moreover, CHD1 deletion predicts shortened BCR-free survival in pT2 patients and cancer-specific survival in all patients. In vivo, CHD1 loss increases spontaneous pulmonary metastasis formation in two distinct PCa models coupled with a higher number of multicellular colonies as compared to single-cell metastases. Transcriptome analyses revealed down-regulation of the PCa-specific metastasis suppressor and TGFβ signaling regulator PMEPA1 after CHD1 depletion in both tested PCa models. CHD1 loss increases the risk of postoperative metastasis in R0-resected PCa patients and promotes spontaneous metastasis formation in vivo.

PIM protein kinases regulate the level of the long noncoding RNA H19 to control stem cell gene transcription and modulate tumor growth

The proviral integration site for Moloney murine leukemia virus (PIM) serine/threonine kinases have an oncogenic and prosurvival role in hematological and solid cancers. However, the mechanism by which these kinases drive tumor growth has not been completely elucidated. To determine the genes controlled by these protein kinases, we carried out a microarray analysis in T-cell acute lymphoblastic leukemia (T-ALL) comparing early progenitor (ETP-ALL) cell lines whose growth is driven by PIM kinases to more mature T-ALL cells that have low PIM levels. This analysis demonstrated that the long noncoding RNA (lncRNA) H19 was associated with increased PIM levels in ETP-ALL. Overexpression or knockdown of PIM in these T-ALL cell lines controlled the level of H19 and regulated the methylation of the H19 promoter, suggesting a mechanism by which PIM controls H19 transcription. In these T-ALL cells, the expression of PIM1 induced stem cell gene expression (SOX2, OCT-4, and NANOG) through H19. Identical results were found in prostate cancer (PCa) cell lines where PIM kinases drive cancer growth, and both H19 and stem cell gene levels. Small molecule pan-PIM inhibitors (PIM-i) currently in clinical trials reduced H19 expression in both of these tumor types. Importantly, the knockdown of H19 blocked the ability of PIM to induce stem cell genes in T-ALL cells, suggesting a novel signal transduction cascade. In PCa, increases in SOX2 levels have been shown to cause both resistance to the androgen deprivation therapy (ADT) and the induction of neuroendocrine PCa, a highly metastatic form of this disease. Treatment of PCa cells with a small molecule pan-PIM-i reduced stem cell gene transcription and enhanced ADT, while overexpression of H19 suppressed the ability of pan-PIM-i to regulate hormone blockade. Together, these results demonstrate that the PIM kinases control the level of lncRNA H19, which in turn modifies stem cell gene transcription regulating tumor growth.

Molecular classification of breast cancer using the mRNA expression profiles of immune-related genes

Breast cancer is the most lethal cancer in women and displaying a broad range of heterogeneity in terms of clinical, molecular behavior and response to therapy. Increasing evidence demonstrated that immune-related genes were an important source of prognostic information for several types of tumors. In this study, the k-mean clustering was applied to gene expression data from the immune-related genes, two molecular clusters were identified for 1980 breast cancer patients. The prognostic significance of the immune-related genes based classification was confirmed in the log-rank test. These clusters were also associated with immune checkpoints, immune-related features and tumor infiltrating levels. In addition, we used the shrunken centroid algorithm to predict the cluster of a given breast cancer sample, and good predictive results were obtained by this algorithm. These results indicated that the proposed classification method is a promising method, and we hope that this method may improve the treatment stratification of breast cancer in the future.

The Role of Castration-Resistant Bmi1+Sox2+ Cells in Driving Recurrence in Prostate Cancer

BACKGROUND

Recurrence following androgen-deprivation therapy is associated with adverse clinical outcomes in prostate cancer, but the cellular origins and molecular mechanisms underlying this process are poorly defined. We previously identified a population of castration-resistant luminal progenitor cells expressing Bmi1 in the normal mouse prostate that can serve as a cancer cell-of-origin. Here, we investigate the potential of Bmi1-expressing tumor cells that survive castration to initiate recurrence in vivo.

METHODS

We employed lineage retracing in Bmi1-CreER; R26R-confetti; Ptenf/f transgenic mice to mark and follow the fate of emerging recurrent tumor clones after castration. A tissue recombination strategy was used to rescue transgenic mouse prostates by regeneration as grafts in immunodeficient hosts. We also used a small molecule Bmi1 inhibitor, PTC-209, to directly test the role of Bmi1 in recurrence.

RESULTS

Transgenic prostate tumors (n = 17) regressed upon castration but uniformly recurred within 3 months. Residual regressed tumor lesions exhibited a transient luminal-to-basal phenotypic switch and marked cellular heterogeneity. Additionally, in these lesions, a subpopulation of Bmi1-expressing castration-resistant tumor cells overexpressed the stem cell reprogramming factor Sox2 (mean [SD] = 41.1 [3.8]%, n = 10, P < .001). Bmi1+Sox2+ cells were quiescent (BrdU+Bmi1+Sox2+ at 3.4 [1.5]% vs BrdU+Bmi1+Sox2- at 18.8 [3.4]%, n = 10, P = .009), consistent with a cancer stem cell phenotype. By lineage retracing, we established that recurrence emerges from the Bmi1+ tumor cells in regressed tumors. Furthermore, treatment with the small molecule Bmi1 inhibitor PTC-209 reduced Bmi1+Sox2+ cells (6.1 [1.4]% PTC-209 vs 38.8 [2.3]% vehicle, n = 10, P < .001) and potently suppressed recurrence (retraced clone size = 2.6 [0.5] PTC-209 vs 15.7 [5.9] vehicle, n = 12, P = .04).

CONCLUSIONS

These results illustrate the utility of lineage retracing to define the cellular origins of recurrent prostate cancer and identify Bmi1+Sox2+ cells as a source of recurrence that could be targeted therapeutically.

Evaluation of Pathway Activation for a Single Sample Toward Inflammatory Bowel Disease Classification

Since similar complex diseases are much alike in clinical symptoms, patients are easily misdiagnosed and mistreated. It is crucial to accurately predict the disease status and identify markers with high sensitivity and specificity for classifying similar complex diseases. Many approaches incorporating network information have been put forward to predict outcomes, but they are not robust because of their low reproducibility. Several pathway-based methods are robust and functionally interpretable. However, few methods characterize the disease-specific states of single samples from the perspective of pathways. In this study, we propose a novel framework, Pathway Activation for Single Sample (PASS), which utilizes the pathway information in a single sample way to better recognize the differences between two similar complex diseases. PASS can mainly be divided into two parts: for each pathway, the extent of perturbation of edges and the statistic difference of genes caused by a single disease sample are quantified; then, a novel method, named as an AUCpath, is applied to evaluate the pathway activation for single samples from the perspective of genes and their interactions. We have applied PASS to two main types of inflammatory bowel disease (IBD) and widely verified the characteristics of PASS. For a new patient, PASS features can be used as the indicators or potential pathway biomarkers to precisely diagnose complex diseases, discover significant features with interpretability and explore changes in the biological mechanisms of diseases.

Cellular and Molecular Mechanisms Underlying Prostate Cancer Development: Therapeutic Implications

Prostate cancer is the most frequent nonskin cancer and second most common cause of cancer-related deaths in man. Prostate cancer is a clinically heterogeneous disease with many patients exhibiting an aggressive disease with progression, metastasis, and other patients showing an indolent disease with low tendency to progression. Three stages of development of human prostate tumors have been identified: intraepithelial neoplasia, adenocarcinoma androgen-dependent, and adenocarcinoma androgen-independent or castration-resistant. Advances in molecular technologies have provided a very rapid progress in our understanding of the genomic events responsible for the initial development and progression of prostate cancer. These studies have shown that prostate cancer genome displays a relatively low mutation rate compared with other cancers and few chromosomal loss or gains. The ensemble of these molecular studies has led to suggest the existence of two main molecular groups of prostate cancers: one characterized by the presence of ERG rearrangements (~50% of prostate cancers harbor recurrent gene fusions involving ETS transcription factors, fusing the 5' untranslated region of the androgen-regulated gene TMPRSS2 to nearly the coding sequence of the ETS family transcription factor ERG) and features of chemoplexy (complex gene rearrangements developing from a coordinated and simultaneous molecular event), and a second one characterized by the absence of ERG rearrangements and by the frequent mutations in the E3 ubiquitin ligase adapter SPOP and/or deletion of CDH1, a chromatin remodeling factor, and interchromosomal rearrangements and SPOP mutations are early events during prostate cancer development. During disease progression, genomic and epigenomic abnormalities accrued and converged on prostate cancer pathways, leading to a highly heterogeneous transcriptomic landscape, characterized by a hyperactive androgen receptor signaling axis.

Increased mediator complex subunit CDK19 expression associates with aggressive prostate cancer

The Mediator complex is a transcriptional regulator interacting with transcription factors and RNA-polymerase-II. Recently, we identified its subunit CDK19 to be specifically expressed in prostate cancer (PCa) and to be functionally implicated in PCa aggressiveness. Aim of our study was to comprehensively characterize the protein expression of CDK19 and its paralog CDK8 in PCa. We performed immunohistochemistry (IHC) for CDK19/CDK8 on a large cohort including needle biopsies from 202 patients, 799 primary tumor foci of radical prostatectomy specimens from 415 patients, 120 locally advanced tumor foci obtained by palliative transurethral resection, 140 lymph node metastases, 67 distant metastases and 82 benigns. Primary tumors were stained for the proliferation marker Ki67, androgen receptor (AR) and ERG. For 376 patients, clinic-pathologic data were available. Primary endpoint was disease-recurrence-free survival (DFS). Nuclear CDK19 and CDK8 expression increases during progression showing the highest intensity in metastatic and castration-resistant tumors. High CDK19 expression on primary tumors correlates with DFS independently from Gleason grade and PSA. Five-year-DFS rates of patients with primary tumors expressing no, moderate and high CDK19 are 73.7, 56.9 and 30.4%, respectively. CDK19 correlates with Gleason grade, T-stage, Ki67 proliferation-index, nuclear AR expression and ERG-status. Therapeutic options for metastatic and castration-resistant PCa remain limited. In the current study, we confirmed an important role of the Mediator subunit CDK19 in advanced PCa supporting current developments to target CDK19 and its paralog CDK8. Furthermore, CDK19 protein expression has the potential to predict disease recurrence independently from established biomarkers thus contributing to individual management for PCa patients.

Genetic and Epigenetic Determinants of Aggressiveness in Cribriform Carcinoma of the Prostate

Among prostate cancers containing Gleason pattern 4, cribriform morphology is associated with unfavorable clinicopathologic factors, but its genetic features and association with long-term outcomes are incompletely understood. In this study, genetic, transcriptional, and epigenetic features of invasive cribriform carcinoma (ICC) tumors were compared with non-cribriform Gleason 4 (NC4) in The Cancer Genome Atlas (TCGA) cohort. ICC (n = 164) had distinctive molecular features when compared with NC4 (n = 102). These include: (i) increased somatic copy number variations (SCNV), specifically deletions at 6q, 8p and 10q, which encompassed PTEN and MAP3K7 losses and gains at 3q; (ii) increased SPOP mut and ATMmut ; (iii) enrichment for mTORC1 and MYC pathways by gene expression; and (iv) increased methylation of selected genes. In addition, when compared with the metastatic prostate cancer, ICC clustered more closely to metastatic prostate cancer than NC4. Validation in clinical cohorts and genomically annotated murine models confirmed the association with SPOPmut (n = 38) and PTENloss (n = 818). The association of ICC with lethal disease was evaluated in the Health Professionals Follow-up Study (HPFS) and Physicians' Health Study (PHS) prospective prostate cancer cohorts (median follow-up, 13.4 years; n = 818). Patients with ICC were more likely to develop lethal cancer [HR, 1.62; 95% confidence interval (CI), 1.05-2.49], independent from Gleason score (GS). IMPLICATIONS: ICC has a distinct molecular phenotype that resembles metastatic prostate cancer and is associated with progression to lethal disease.

High-throughput screens identify HSP90 inhibitors as potent therapeutics that target inter-related growth and survival pathways in advanced prostate cancer

The development of new treatments for castrate resistant prostate cancer (CRPC) must address such challenges as intrinsic tumor heterogeneity and phenotypic plasticity. Combined PTEN/TP53 alterations represent a major genotype of CRPC (25–30%) and are associated with poor outcomes. Using tumor-derived, castration-resistant Pten/Tp53 null luminal prostate cells for comprehensive, high-throughput, mechanism-based screening, we identified several vulnerabilities among >1900 compounds, including inhibitors of: PI3K/AKT/mTOR, the proteasome, the cell cycle, heat shock proteins, DNA repair, NFκB, MAPK, and epigenetic modifiers. HSP90 inhibitors were one of the most active compound classes in the screen and have clinical potential for use in drug combinations to enhance efficacy and delay the development of resistance. To inform future design of rational drug combinations, we tested ganetespib, a potent second-generation HSP90 inhibitor, as a single agent in multiple CRPC genotypes and phenotypes. Ganetespib decreased growth of endogenous Pten/Tp53 null tumors, confirming therapeutic activity in situ. Fifteen human CRPC LuCaP PDX-derived organoid models were assayed for responses to 110 drugs, and HSP90 inhibitors (ganetespib and onalespib) were among the select group of drugs (<10%) that demonstrated broad activity (>75% of models) at high potency (IC50 <1 µM). Ganetespib inhibits multiple targets, including AR and PI3K pathways, which regulate mutually compensatory growth and survival signals in some forms of CRPC. Combined with castration, ganetespib displayed deeper PDX tumor regressions and delayed castration resistance relative to either monotherapy. In all, comprehensive data from near-patient models presents novel contexts for HSP90 inhibition in multiple CRPC genotypes and phenotypes, expands upon HSP90 inhibitors as simultaneous inhibitors of oncogenic signaling and resistance mechanisms, and suggests utility for combined HSP90/AR inhibition in CRPC.

Prostate cancer: updates on current strategies for screening, diagnosis and clinical implications of treatment modalities

Prostate cancer is the most common cancer in men by way of diagnosis and a leading cause of cancer-related deaths. Early detection and intervention remains key to its optimum clinical management. This review provides the most updated information on the recent methods of prostate cancer screening, imaging and treatment modalities. Wherever possible, clinical trial data has been supplemented to provide a comprehensive overview of current prostate cancer research and development. Considering the recent success of immunotherapy in prostate cancer, we discuss cell, DNA and viruses based, as well as combinatorial immunotherapeutic strategies in detail. Furthermore, the potential of nanotechnology is increasingly being realized, especially in prostate cancer research, and we provide an overview of nanotechnology-based strategies, with special emphasis on nanotheranostics and multifunctional nanoconstructs. Understanding these recent developments is critical to the design of future therapeutic strategies to counter prostate cancer.

A functional genomics screen reveals a strong synergistic effect between docetaxel and the mitotic gene DLGAP5 that is mediated by the androgen receptor

Based on a molecular classification of prostate cancer using gene expression pathway signatures, we derived a set of 48 genes in critical pathways that significantly predicts clinical outcome in all tested patient cohorts. We tested these genes in a functional genomics screen in a panel of three prostate cancer cell lines (LNCaP, PC3, DU145), using RNA interference. The screen revealed several genes whose knockdown caused strong growth inhibition in all cell lines. Additionally, we tested the gene set in the presence of docetaxel to see whether any gene exhibited additive or synergistic effects with the drug. We observed a strong synergistic effect between DLGAP5 knockdown and docetaxel in the androgen-sensitive line LNCaP, but not in the two other androgen-independent lines. We then tested whether this effect was connected to androgen pathways and found that knockdown of the androgen receptor by si-RNA attenuated the synergy significantly. Similarly, androgen desensitized LNCaP-AI cells had a higher IC50 to docetaxel and did not exhibit the synergistic interaction. Short-term exposure to enzalutamide did not significantly alter the behaviour of parental LNCaP cells. An immunofluorescence analysis in LNCaP cells suggests that under the double insult of DLGAP5 knockdown and docetaxel, cells predominantly arrest in metaphase. In contrast, the knockdown of the androgen receptor by siRNA appears to assist cells to progress through metaphase in to anaphase, even in the presence of docetaxel. Our data suggest that DLGAP5 has a unique function in stabilizing spindle formation and surviving microtubule assault from docetaxel, in an androgen-regulated cell cycle system.

Analysis of cell proliferation and tissue remodelling uncovers a KLF4 activity score associated with poor prognosis in colorectal cancer

BACKGROUND

Human cancers can be classified based on gene signatures quantifying the degree of cell proliferation and tissue remodelling (PR). However, the specific factors that drive the increased tissue remodelling in tumours are not fully understood. Here we address this question using colorectal cancer as a case study.

METHODS

We reanalysed a reported cohort of colorectal cancer patients. The patients were stratified based on gene signatures of cell proliferation and tissue remodelling. Putative transcription factors activity was inferred using gene expression profiles and annotations of transcription factor targets as input.

RESULTS

We demonstrate that the PR classification performs better than the currently adopted consensus molecular subtyping (CMS). Although CMS classification differentiates patients with a mesenchymal signature, it cannot distinguish the remaining patients based on survival. We demonstrate that the missing factor is cell proliferation, which is indicative of good prognosis. We also uncover a KLF4 transcription factor activity score associated with the tissue remodelling gene signature. We further show that the KLF4 activity score is significantly higher in colorectal tumours with predicted infiltration of cells from the myeloid lineage.

CONCLUSION

The KLF4 activity score is associated with tissue remodelling, myeloid cell infiltration and poor prognosis in colorectal cancer.

CD38 is methylated in prostate cancer and regulates extracellular NAD. Cancer Metab 2018;6:13. [PMID: 30258629 PMCID: PMC6150989 DOI: 10.1186/s40170-018-0186-3]

BACKGROUND

Cancer cell metabolism requires sustained pools of intracellular nicotinamide adenine dinucleotide (NAD+) which is maintained by a balance of NAD+ hydrolase activity and NAD+ salvage activity. We recently reported that human prostate cancer can be initiated following oncogene expression in progenitor-like luminal cells marked by low expression of the NAD+-consuming enzyme CD38. CD38 expression is reduced in prostate cancer compared to benign prostate, suggesting that tumor cells may reduce CD38 expression in order to enhance pools of NAD+. However, little is known about how CD38 expression is repressed in advanced prostate cancer and whether CD38 plays a role in regulating NAD+ levels in prostate epithelial cells.

METHODS

CD38 expression, its association with recurrence after prostatectomy for clinically localized prostate cancer, and DNA methylation of the CD38 promoter were evaluated in human prostate tissues representing various stages of disease progression. CD38 was inducibly over-expressed in benign and malignant human prostate cell lines in order to determine the effects on cell proliferation and levels of NAD+ and NADH. NAD+ and NADH were also measured in urogenital tissues from wild-type and CD38 knockout mice.

RESULTS

CD38 mRNA expression was reduced in metastatic castration-resistant prostate cancer compared to localized prostate cancer. In a large cohort of men undergoing radical prostatectomy, CD38 protein expression was inversely correlated with recurrence. We identified methylation of the CD38 promoter in primary and metastatic prostate cancer. Over-expression of wild-type CD38, but not an NAD+ hydrolase-deficient mutant, depleted extracellular NAD+ levels in benign and malignant prostate cell lines. However, expression of CD38 did not significantly alter intracellular NAD+ levels in human prostate cell lines grown in vitro and in urogenital tissues isolated from wild-type and CD38 knockout mice.

CONCLUSIONS

CD38 protein expression in prostate cancer is associated with risk of recurrence. Methylation results suggest that CD38 is epigenetically regulated in localized and metastatic prostate cancer tissues. Our study provides support for CD38 as a regulator of extracellular, but not intracellular, NAD+ in epithelial cells. These findings suggest that repression of CD38 by methylation may serve to increase the availability of extracellular NAD+ in prostate cancer tissues.

Translocations involving ETS family proteins in human cancer

The ETS transcription factors regulate expression of genes involved in normal cell development, proliferation, differentiation, angiogenesis, and apoptosis, consisting of 28 family members in humans. Dysregulation of these transcription factors facilitates cell proliferation in cancers, and several members participate in invasion and metastasis by activating certain gene transcriptions. ETS1 and ETS2 are the founding members of the ETS family and regulate transcription by binding to ETS sequences. Three chimeric genes involving ETS genes have been identified in human cancers, which are EWS-FLI1 in Ewing's sarcoma, TMPRSS2-ERG in prostate cancer, and ETV6-RUNX1 in acute lymphocytic leukemia. Although these fusion transcripts definitely contribute to the pathogenesis of the disease, the impact of these fusion transcripts on patients' prognosis is highly controversial. In the present review, the roles of ETS protein translocations in human carcinogenesis are discussed.

PTEN deletion in luminal cells of mature prostate induces replication stress and senescence in vivo

Genetic ablation of the tumor suppressor PTEN in prostatic epithelial cells (PECs) induces cell senescence. However, unlike oncogene-induced senescence, no hyperproliferation phase and no signs of DNA damage response (DDR) were observed in PTEN-deficient PECs; PTEN loss-induced senescence (PICS) was reported to be a novel type of cellular senescence. Our study reveals that PTEN ablation in prostatic luminal epithelial cells of adult mice stimulates PEC proliferation, followed by a progressive growth arrest with characteristics of cell senescence. Importantly, we also show that proliferating PTEN-deficient PECs undergo replication stress and mount a DDR leading to p53 stabilization, which is however delayed by Mdm2-mediated p53 down-regulation. Thus, even though PTEN-deficiency induces cellular senescence that restrains tumor progression, as it involves replication stress, strategies promoting PTEN loss-induced senescence are at risk for cancer prevention and therapy.

Cholesterol synthesis pathway genes in prostate cancer are transcriptionally downregulated when tissue confounding is minimized

BACKGROUND

The relationship between cholesterol and prostate cancer has been extensively studied for decades, where high levels of cellular cholesterol are generally associated with cancer progression and less favorable outcomes. However, the role of in vivo cellular cholesterol synthesis in this process is unclear, and data on the transcriptional activity of cholesterol synthesis pathway genes in tissue from prostate cancer patients are inconsistent.

METHODS

A common problem with cancer tissue data from patient cohorts is the presence of heterogeneous tissue which confounds molecular analysis of the samples. In this study we present a general method to minimize systematic confounding from stroma tissue in any prostate cancer cohort comparing prostate cancer and normal samples. In particular we use samples assessed by histopathology to identify genes enriched and depleted in prostate stroma. These genes are then used to assess stroma content in tissue samples from other prostate cancer cohorts where no histopathology is available. Differential expression analysis is performed by comparing cancer and normal samples where the average stroma content has been balanced between the sample groups. In total we analyzed seven patient cohorts with prostate cancer consisting of 1713 prostate cancer and 230 normal tissue samples.

RESULTS

When stroma confounding was minimized, differential gene expression analysis over all cohorts showed robust and consistent downregulation of nearly all genes in the cholesterol synthesis pathway. Additional Gene Ontology analysis also identified cholesterol synthesis as the most significantly altered metabolic pathway in prostate cancer at the transcriptional level.

CONCLUSION

The surprising observation that cholesterol synthesis genes are downregulated in prostate cancer is important for our understanding of how prostate cancer cells regulate cholesterol levels in vivo. Moreover, we show that tissue heterogeneity explains the lack of consistency in previous expression analysis of cholesterol synthesis genes in prostate cancer.

LSD1 activates a lethal prostate cancer gene network independently of its demethylase function

Medical castration that interferes with androgen receptor (AR) function is the principal treatment for advanced prostate cancer. However, clinical progression is universal, and tumors with AR-independent resistance mechanisms appear to be increasing in frequency. Consequently, there is an urgent need to develop new treatments targeting molecular pathways enriched in lethal prostate cancer. Lysine-specific demethylase 1 (LSD1) is a histone demethylase and an important regulator of gene expression. Here, we show that LSD1 promotes the survival of prostate cancer cells, including those that are castration-resistant, independently of its demethylase function and of the AR. Importantly, this effect is explained in part by activation of a lethal prostate cancer gene network in collaboration with LSD1's binding protein, ZNF217. Finally, that a small-molecule LSD1 inhibitor-SP-2509-blocks important demethylase-independent functions and suppresses castration-resistant prostate cancer cell viability demonstrates the potential of LSD1 inhibition in this disease.

A novel non-canonical Wnt signature for prostate cancer aggressiveness

Activation of the Canonical Wnt pathway (CWP) has been linked to advanced and metastatic prostate cancer, whereas the Wnt5a-induced non-canonical Wnt pathway (NCWP) has been associated with both good and poor prognosis. A newly discovered NCWP, Wnt5/Fzd2, has been shown to induce epithelial-to-mesenchymal transition (EMT) in cancers, but has not been investigated in prostate cancer. The aim of this study was to investigate if the CWP and NCWP, in combination with EMT, are associated with metabolic alterations, aggressive disease and biochemical recurrence in prostate cancer. An initial analysis was performed using integrated transcriptomics, ex vivo and in vivo metabolomics, and histopathology of prostatectomy samples (n=129), combined with at least five-year follow-up. This analysis detected increased activation of NCWP through Wnt5a/ Fzd2 as the most common mode of Wnt activation in prostate cancer. This activation was associated with increased expression of EMT markers and higher Gleason score. The transcriptional association between NCWP and EMT was confirmed in five other publicly available patient cohorts (1519 samples in total). A novel gene expression signature of concordant activation of NCWP and EMT (NCWP-EMT) was developed, and this signature was significantly associated with metastasis and shown to be a significant predictor of biochemical recurrence. The NCWP-EMT signature was also associated with decreased concentrations of the metabolites citrate and spermine, which have previously been linked to aggressive prostate cancer. Our results demonstrate the importance of NCWP and EMT in prostate cancer aggressiveness, suggest a novel gene signature for improved risk stratification, and give new molecular insight.

Estrogen and Androgen Blockade for Advanced Prostate Cancer in the Era of Precision Medicine

Androgen deprivation therapy (ADT) has been widely prescribed for patients with advanced prostate cancer (PC) to control key signaling pathways via androgen receptor (AR) and AR-collaborative transcriptional factors; however, PC gradually acquires a lethal phenotype and results in castration-resistant PC (CRPC) during ADT. Therefore, new therapeutic strategies are required in clinical practice. In addition, ARs; estrogen receptors (ERs; ERα and ERβ); and estrogen-related receptors (ERRs; ERRα, ERRβ, and ERRγ) have been reported to be involved in the development or regulation of PC. Recent investigations have revealed the role of associated molecules, such as KLF5, FOXO1, PDGFA, VEGF-A, WNT5A, TGFβ1, and micro-RNA 135a of PC, via ERs and ERRs. Selective ER modulators (SERMs) have been developed. Recently, estrogen and androgen blockade (EAB) using a combination of toremifene and ADT has been demonstrated to improve biochemical recurrence rate in treatment-naïve bone metastatic PC. In the future, the suitability of ADT alone or EAB for individuals may be evaluated by making clinical decisions on the basis of information obtained from RT-PCR, gene-panel, or liquid biopsy to create a “personalized medicine” or “precision medicine”. In this review, we summarize ER and ERR signaling pathways, molecular diagnosis, and SERMs as candidates for advanced PC treatment.

Presence of TMPRSS2-ERG is associated with alterations of the metabolic profile in human prostate cancer

TMPRSS2-ERG has been proposed to be a prognostic marker for prostate cancer. The aim of this study was to identify changes in metabolism, genes and biochemical recurrence related to TMPRSS2-ERG by using an integrated approach, combining metabolomics, transcriptomics, histopathology and clinical data in a cohort of 129 human prostate samples (41 patients). Metabolic analyses revealed lower concentrations of citrate and spermine comparing ERG_high to ERG_low samples, suggesting an increased cancer aggressiveness of ERG_high compared to ERG_low. These results could be validated in a separate cohort, consisting of 40 samples (40 patients), and magnetic resonance spectroscopy imaging (MRSI) indicated an in vivo translational potential. Alterations of gene expression levels associated with key enzymes in the metabolism of citrate and polyamines were in consistence with the metabolic results. Furthermore, the metabolic alterations between ERG_high and ERG_low were more pronounced in low Gleason samples than in high Gleason samples, suggesting it as a potential tool for risk stratification. However, no significant difference in biochemical recurrence was detected, although a trend towards significance was detected for low Gleason samples. Using an integrated approach, this study suggests TMPRSS2-ERG as a potential risk stratification tool for inclusion of active surveillance patients.

Modeling African American prostate adenocarcinoma by inducing defined genetic alterations in organoids

Genomic studies are rapidly identifying genetic alterations in human cancer, but functional validation of such alterations has been slow. Here, using human prostate cancer as a model, we have assessed the feasibility of engineering defined genetic alterations in well-known cancer driver genes to transform benign prostate epithelial organoids derived from African American men. Benign human prostate organoids were transduced with lentiviruses expressing MYC, shPTEN, shTP53 and AR, alone and in various combinations, to recapitulate prostate cancer development. Organoids expressing MYC, shPTEN, shTP53 and AR (denoted MPPA); MYC, shPTEN and shTP53 (MPP); or MYC (M) were significantly larger, had higher proliferation rates and demonstrated pathologically transformed morphology compared to organoids transduced with control lentivirus. Alterations in MYC, PTEN and TP53 also affected the rate of organoid basal-to-luminal differentiation in vitro. MPPA and MPP organoids expressed the clinical prostate cancer marker AMACR and developed prostate adenocarcinoma when grafted under the renal capsule in mice. These data indicate that genetic alterations commonly observed in human prostate cancer can be rapidly modeled in human organoid culture. Prostate cancer organoids provide a useful pre-clinical model for the evaluation of new candidate cancer genes, cancer disparities, and potentially for testing of novel therapeutic agents.

Molecular classification of prostate adenocarcinoma by the integrated somatic mutation profiles and molecular network

Prostate cancer is one of the most common cancers in men and a leading cause of cancer death worldwide, displaying a broad range of heterogeneity in terms of clinical and molecular behavior. Increasing evidence suggests that classifying prostate cancers into distinct molecular subtypes is critical to exploring the potential molecular variation underlying this heterogeneity and to better treat this cancer. In this study, the somatic mutation profiles of prostate cancer were downloaded from the TCGA database and used as the source nodes of the random walk with restart algorithm (RWRA) for generating smoothed mutation profiles in the STRING network. The smoothed mutation profiles were selected as the input matrix of the Graph-regularized Nonnegative Matrix Factorization (GNMF) for classifying patients into distinct molecular subtypes. The results were associated with most of the clinical and pathological outcomes. In addition, some bioinformatics analyses were performed for the robust subtyping, and good results were obtained. These results indicated that prostate cancers can be usefully classified according to their mutation profiles, and we hope that these subtypes will help improve the treatment stratification of this cancer in the future.

Androgen receptor in cancer-associated fibroblasts influences stemness in cancer cells

Androgen receptor (AR) regulation pathways are essential for supporting the growth and survival of prostate cancer cells. Recently, sub-populations of prostate cancer cells have been identified with stem cell features and are associated with the emergence of treatment-resistant prostate cancer. Here, we explored the function of AR in prostate cancer-associated fibroblasts (CAFs) relative to growth and stem cell-associated characteristics. CAFs were isolated from the murine cPten^-/-L prostate cancer model and cultured with human prostate cancer epithelial (hPCa) cells. A murine-specific AR antisense oligonucleotide (ASO) was used to suppress the expression of AR in the CAF cells. CAFs express low, but significant levels of AR relative to fibroblasts derived from non-malignant tissue. CAFs promoted growth and colony formation of hPCa cells, which was attenuated by the suppression of AR expression. Surprisingly, AR-depleted CAFs promoted increased stem cell marker expression in hPCa cells. Interferon gamma (IFN-γ) and macrophage colony-stimulating factor (M-CSF) were increased in AR-depleted CAF cells and exhibited similar effects on stem cell marker expression as seen in the CAF co-culture systems. Clinically, elevated IFN-γ expression was found to correlate with histologic grade in primary prostate cancer samples. In summary, AR and androgen-dependent signaling are active in CAFs and exert significant effects on prostate cancer cells. IFN-γ and M-CSF are AR-regulated factors secreted by CAF cells, which promote the expression of stem cell markers in prostate cancer epithelial cells. Understanding how CAFs and other constituents of stromal tissue react to anti-cancer therapies may provide insight into the development and progression of prostate cancer.

Distance in cancer gene expression from stem cells predicts patient survival

The degree of histologic cellular differentiation of a cancer has been associated with prognosis but is subjectively assessed. We hypothesized that information about tumor differentiation of individual cancers could be derived objectively from cancer gene expression data, and would allow creation of a cancer phylogenetic framework that would correlate with clinical, histologic and molecular characteristics of the cancers, as well as predict prognosis. Here we utilized mRNA expression data from 4,413 patient samples with 7 diverse cancer histologies to explore the utility of ordering samples by their distance in gene expression from that of stem cells. A differentiation baseline was obtained by including expression data of human embryonic stem cells (hESC) and human mesenchymal stem cells (hMSC) for solid tumors, and of hESC and CD34+ cells for liquid tumors. We found that the correlation distance (the degree of similarity) between the gene expression profile of a tumor sample and that of stem cells orients cancers in a clinically coherent fashion. For all histologies analyzed (including carcinomas, sarcomas, and hematologic malignancies), patients with cancers with gene expression patterns most similar to that of stem cells had poorer overall survival. We also found that the genes in all undifferentiated cancers of diverse histologies that were most differentially expressed were associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes. Thus, a stem cell-oriented phylogeny of cancers allows for the derivation of a novel cancer gene expression signature found in all undifferentiated forms of diverse cancer histologies, that is competitive in predicting overall survival in cancer patients compared to previously published prediction models, and is coherent in that gene expression was associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes associated with regulation of the multicellular state.

Micro-RNA-204 Participates in TMPRSS2/ERG Regulation and Androgen Receptor Reprogramming in Prostate Cancer

Cancer progression is driven by genome instability incurred rearrangements such as transmembrane protease, serine 2 (TMPRSS2)/v-ets erythroblastosis virus E26 oncogene (ERG) that could possibly turn some of the tumor suppressor micro-RNAs into pro-oncogenic ones. Previously, we found dualistic miR-204 effects, acting either as a tumor suppressor or as an oncomiR in ERG fusion-dependent manner. Here, we provided further evidence for an important role of miR-204 for TMPRSS2/ERG and androgen receptor (AR) signaling modulation and fine tuning that prevents TMPRSS2/ERG overexpression in prostate cancer. Based on proximity-based ligation assay, we designed a novel method for detection of TMPRSS2/ERG protein products. We found that miR-204 is TMPRSS2/ERG oncofusion negative regulator, and this was mediated by DNA methylation of TMPRSS2 promoter. Transcriptional factors runt-related transcription factor 2 (RUNX2) and ETS proto-oncogene 1 (ETS1) were positive regulators of TMPRSS2/ERG expression and promoter hypo-methylation. Clustering of patients' sera for fusion protein, transcript expression, and wild-type ERG transcript isoforms, demonstrated not all patients harboring fusion transcripts had fusion protein products, and only few fusion positive ones exhibited increased wild-type ERG transcripts. miR-204 upregulated AR through direct promoter hypo-methylation, potentiated by the presence of ERG fusion and RUNX2 and ETS1. Proteomics studies provided evidence that miR-204 has dualistic role in AR cancer-related reprogramming, promoting prostate cancer-related androgen-responsive genes and AR target genes, as well as AR co-regulatory molecules. miR-204 methylation regulation was supported by changes in molecules responsible for chromatin remodeling, DNA methylation, and its regulation. In summary, miR-204 is a mild regulator of the AR function during the phase of preserved AR sensitivity as the latter one is required for ERG-fusion translocation.

Anticancer Effects of the Marine Sponge Lipastrotethya sp. Extract on Wild-Type and p53 Knockout HCT116 Cells

Interest in marine bioresources is increasing in the drug development sector. In particular, marine sponges produce a wide range of unique metabolites that enable them to survive in challenging environments, which makes them attractive sources of candidate pharmaceuticals. In previous study, we investigated over 40 marine specimens collected in Micronesia and provided by the Korean Institute of Ocean Science and Technology, for their antiproliferative effects on various cancer cell lines, and Lipastrotethya sp. extract (LSSE) was found to have a marked antiproliferative effect. In the present study, we investigated the mechanism responsible for its anticancer effect on wild-type p53 (WT) or p53 knockout (KO) HCT116 cells. LSSE inhibited cell viability and induced apoptotic cell death more so in HCT116 p53 KO cells than the WT. HCT116 WT cells treated with LSSE underwent apoptosis associated with the induction of p53 and its target genes. On the other hand, in HCT116 p53 KO cells, LSSE reduced mTOR and Bcl-2 and increased Beclin-1 and LC3-II protein levels, suggesting autophagy induction. These results indicate that the mechanisms responsible for the anticancer effect of LSSE depend on p53 status.