TMPRSS2-ERG expression predicts prostate cancer survival and associates with stromal biomarkers

Semi-Supervised, Attention-Based Deep Learning for Predicting TMPRSS2:ERG Fusion Status in Prostate Cancer Using Whole Slide Images

IMPLICATIONS

Our study illuminates the potential of deep learning in effectively inferring key prostate cancer genetic alterations from the tissue morphology depicted in routinely available histology slides, offering a cost-effective method that could revolutionize diagnostic strategies in oncology.

Therapy With Metronomic Cyclophosphamide (mCyc) for Previously-Treated Metastatic Castrate-Resistant Prostate Cancer (mCRPC)

INTRODUCTION

Despite the introduction of various novel therapies for management of metastatic castrate resistant prostate cancer (mCRPC) in recent decades, available treatment options are finite and remain limited. Multiple historical studies have demonstrated activity and a favorable toxicity profile of oral metronomic cyclophosphamide (mCyc) in prostate cancer (PCa). Unlike the cytotoxic immunosuppressive effects of high-dose intravenously-administered cyclophosphamide, continuous low doses of oral mCyc have a unique immune-stimulatory mechanism of action.

MATERIALS AND METHODS

This is a retrospective, multi-institution study of men with 43 patients with mCRPC treated mCyc. Patient demographic information as well as clinical, pathologic, and genomic characteristics of their PCa were extracted. The primary endpoint was the rate of PSA decline by ≥ 50% (ie, PSA50). Additional efficacy and toxicity data as well as cost analysis compared to other commonly used agents in mCRPC was obtained.

RESULTS

PSA50 was noted in 20.9% of patients, while an additional 25.6% patients achieved < PSA50 and 6.9% reported improvement in prostate cancer-related symptoms without any PSA reduction. Meanwhile, 9.3% of patients required mCyc dose reduction, 11.6% needed dose interruption due to toxicity, and no treatment discontinuations due to toxicity were observed. mCyc was also cost effective compared to other agents commonly used in mCRPC.

CONCLUSIONS

Despite the small sample size and retrospective nature of this dataset, mCyc demonstrated promising rapid activity and a tolerable toxicity profile in a heavily pretreated mCRPC population with aggressive clinical, pathologic, and genomic disease features.

Prognostic utility of biopsy-based PTEN and ERG status on biochemical progression and overall survival after SBRT for localized prostate cancer

Introduction/background

Phosphatase and tensin homolog (PTEN) genomic deletions and transmembrane protease, serine 2/v-ets avian erthyroblastosis virus E26 oncogene homolog (ERG) rearrangements are two of the most common genetic abnormalities associated with prostate cancer. Prior studies have demonstrated these alterations portend worse clinical outcomes. Our objective is to evaluate the impact of biopsy-determined PTEN losses and TMPRSS2-ERG fusion on biochemical progression-free survival (bPFS) and overall survival (OS) in patients who receive SBRT for localized prostate cancer.

Methods/materials

Patients received SBRT for localized prostate cancer on a prospective quality-of-life (QoL) and cancer outcomes study. For each patient, the single biopsy core with the highest grade/volume of cancer was evaluated for PTEN and ERG abnormalities. Differences in baseline patient and disease characteristics between groups were analyzed using ANOVA for age and χ2 for categorical groupings. bPFS and OS were calculated using the Kaplan Meier (KM) method with Log-Rank test comparison between groups. Predictors of bPFS and OS were identified using the Cox proportional hazards method. For all analyses, p <0.05 was considered statistically significant.

Results

Ninety-nine consecutive patients were included in the analysis with a median follow-up of 72 months. A statistically significant improvement in bPFS (p = 0.018) was observed for wild type ERG patients with an estimated 5-year bPFS of 94.1% vs. 72.4%. Regarding PTEN mutational status, significant improvements in were observed in both bPFS (p = 0.006) and OS (p < 0.001), with estimated 5-year bPFS rates of 91.0% vs. 67.9% and 5-year OS rates of 96.4% vs. 79.4%. When including both ERG and PTEN mutational status in the analysis, there were statistically significant differences in both bPFS (p = 0.011) and OS (p < 0.001). The estimated 5-year bPFS rates were 100%, 76.6%, 72.9%, and 63.8% for patients with ERG+/PTEN+, ERG-/PTEN+, ERG+/PTEN-, and ERG-/PTEN- phenotypes respectively. The estimated 5-year OS rates were 93.9%, 100%, 80.0%, and 78.7% for patients with ERG+/PTEN+, ERG-/PTEN+, ERG+/PTEN-, and ERG-/PTEN- phenotypes respectively.

Conclusion

ERG rearrangements and PTEN deletions detected on biopsy samples are associated with poorer oncologic outcomes in prostate cancer patients treated with SBRT and merit further study in a dedicated prospective trial.

Evaluation of HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1 polymorphisms associated with prostate cancer in samples of patients from HUPE-UERJ

PURPOSE

Prostate cancer (PCa) is the leading cause of death among men in 48 countries. Genetic alterations play a significant role in PCa carcinogenesis. For the hypothesis of this research, five unique polymorphisms (SNP) were investigated in different genes that showed to be associated in different ways with PCa: rs4430796, rs2735839, rs4792311, rs12329760, and rs28931588, respectively for the genes HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1.

PATIENTS AND METHODS

Blood samples from 426 subjects were evaluated: 290 controls (161 females and 129 males) and 136 PCa patients. SNP were determined by real-time polymerase chain reaction. TaqMan SNP genotyping assay. In the control samples, the SNPs were defined in association with the self-reported ethnicity, and in 218 control samples with markers with ancestry indicators. The genes were in Hardy-Weinberg equilibrium. One hundred and seventy control samples were matched by ethnicity for comparison with the PCa samples.

RESULTS

The G allele at rs28931588 was monomorphic in both patients and controls studied. Significant differences were observed in allelic and genotypic frequencies between the control and Pca samples in rs2735839 (KLK3; p = 0.002 and χ2  = 8.73 and p = 0.01, respectively), by the global frequency and in the dominant model rs2735839_GG (odds ratio [OR] = 0.51, p = 0.02). AA and GA genotypes at rs4792311 (ELAC2) were more frequent in patients with Gleason 7(4 + 3), 8, and 9 (n = 37%-59.7%) compared to patients with Gleason 6 and 7(3 + 4) (n = 26%-40.0%) conferring a protective effect on the GG genotype (OR = 0.45, p = 0.02). The same genotype showed an OR = 2.71 (p = 0.01) for patients with low severity. The HNF1B-KLK3-ELAC2-TMPRSS2-ERG haplotypes: GAAT, AAAT, GAGT, and AAGT were more frequent in patients with Pca with OR ranging from 4.65 to 2.48.

CONCLUSIONS

Higher frequencies of risk alleles were confirmed in the SNPs, KLK3 rs2735839_A, ELAC2 rs4792311_A, and TMPRSS2 rs12329760_T in patients with Pca. Rs2735839_A was associated with risk of Pca and rs4792311_A with severity and Gleason score of 7(4 + 3) or greater. There is a need for careful observation of rs2735839 and rs4792311 in association with the prostatic biopsy due to the increased risk of Pca.

Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer

Prostate cancer (PCa) is a non-cutaneous malignancy in males with wide variation in incidence rates across the globe. It is the second most reported cause of cancer death. Its etiology may have been linked to genetic polymorphisms, which are not only dominating cause of malignancy casualties but also exerts significant effects on pharmacotherapy outcomes. Although many therapeutic options are available, but suitable candidates identified by useful biomarkers can exhibit maximum therapeutic efficacy. The single-nucleotide polymorphisms (SNPs) reported in androgen receptor signaling genes influence the effectiveness of androgen receptor pathway inhibitors and androgen deprivation therapy. Furthermore, SNPs located in genes involved in transport, drug metabolism, and efflux pumps also influence the efficacy of pharmacotherapy. Hence, SNPs biomarkers provide the basis for individualized pharmacotherapy. The pharmacotherapeutic options for PCa include hormonal therapy, chemotherapy (Docetaxel, Mitoxantrone, Cabazitaxel, and Estramustine, etc.), and radiotherapy. Here, we overview the impact of SNPs reported in various genes on the pharmacotherapy for PCa and evaluate current genetic biomarkers with an emphasis on early diagnosis and individualized treatment strategy in PCa.

Decoding Oncofusions: Unveiling Mechanisms, Clinical Impact, and Prospects for Personalized Cancer Therapies

Cancer-associated gene fusions, also known as oncofusions, have emerged as influential drivers of oncogenesis across a diverse range of cancer types. These genetic events occur via chromosomal translocations, deletions, and inversions, leading to the fusion of previously separate genes. Due to the drastic nature of these mutations, they often result in profound alterations of cellular behavior. The identification of oncofusions has revolutionized cancer research, with advancements in sequencing technologies facilitating the discovery of novel fusion events at an accelerated pace. Oncofusions exert their effects through the manipulation of critical cellular signaling pathways that regulate processes such as proliferation, differentiation, and survival. Extensive investigations have been conducted to understand the roles of oncofusions in solid tumors, leukemias, and lymphomas. Large-scale initiatives, including the Cancer Genome Atlas, have played a pivotal role in unraveling the landscape of oncofusions by characterizing a vast number of cancer samples across different tumor types. While validating the functional relevance of oncofusions remains a challenge, even non-driver mutations can hold significance in cancer treatment. Oncofusions have demonstrated potential value in the context of immunotherapy through the production of neoantigens. Their clinical importance has been observed in both treatment and diagnostic settings, with specific fusion events serving as therapeutic targets or diagnostic markers. However, despite the progress made, there is still considerable untapped potential within the field of oncofusions. Further research and validation efforts are necessary to understand their effects on a functional basis and to exploit the new targeted treatment avenues offered by oncofusions. Through further functional and clinical studies, oncofusions will enable the advancement of precision medicine and the drive towards more effective and specific treatments for cancer patients.

Transcriptome Profiling of Prostate Cancer, Considering Risk Groups and the TMPRSS2-ERG Molecular Subtype

Molecular heterogeneity in prostate cancer (PCa) is one of the key reasons underlying the differing likelihoods of recurrence after surgical treatment in individual patients of the same clinical category. In this study, we performed RNA-Seq profiling of 58 localized PCa and 43 locally advanced PCa tissue samples obtained as a result of radical prostatectomy on a cohort of Russian patients. Based on bioinformatics analysis, we examined features of the transcriptome profiles within the high-risk group, including within the most commonly represented molecular subtype, TMPRSS2-ERG. The most significantly affected biological processes in the samples were also identified, so that they may be further studied in the search for new potential therapeutic targets for the categories of PCa under consideration. The highest predictive potential was found with the EEF1A1P5, RPLP0P6, ZNF483, CIBAR1, HECTD2, OGN, and CLIC4 genes. We also reviewed the main transcriptome changes in the groups at intermediate risk of PCa-Gleason Score 7 (groups 2 and 3 according to the ISUP classification)-on the basis of which the LPL, MYC, and TWIST1 genes were identified as promising additional prognostic markers, the statistical significance of which was confirmed using qPCR validation.

Prognostic Values of Gene Copy Number Alterations in Prostate Cancer

Whilst risk prediction for individual prostate cancer (PCa) cases is of a high priority, the current risk stratification indices for PCa management have severe limitations. This study aimed to identify gene copy number alterations (CNAs) with prognostic values and to determine if any combination of gene CNAs could have risk stratification potentials. Clinical and genomic data of 500 PCa cases from the Cancer Genome Atlas stable were retrieved from the Genomic Data Commons and cBioPortal databases. The CNA statuses of a total of 52 genetic markers, including 21 novel markers and 31 previously identified potential prognostic markers, were tested for prognostic significance. The CNA statuses of a total of 51/52 genetic markers were significantly associated with advanced disease at an odds ratio threshold of ≥1.5 or ≤0.667. Moreover, a Kaplan-Meier test identified 27/52 marker CNAs which correlated with disease progression. A Cox Regression analysis showed that the amplification of MIR602 and deletions of MIR602, ZNF267, MROH1, PARP8, and HCN1 correlated with a progression-free survival independent of the disease stage and Gleason prognostic group grade. Furthermore, a binary logistic regression analysis identified twenty-two panels of markers with risk stratification potentials. The best model of 7/52 genetic CNAs, which included the SPOP alteration, SPP1 alteration, CCND1 amplification, PTEN deletion, CDKN1B deletion, PARP8 deletion, and NKX3.1 deletion, stratified the PCa cases into a localised and advanced disease with an accuracy of 70.0%, sensitivity of 85.4%, specificity of 44.9%, positive predictive value of 71.67%, and negative predictive value of 65.35%. This study validated prognostic gene level CNAs identified in previous studies, as well as identified new genetic markers with CNAs that could potentially impact risk stratification in PCa.

Mass spectrometry-based targeted proteomics for analysis of protein mutations

Cancers are caused by accumulated DNA mutations. This recognition of the central role of mutations in cancer and recent advances in next-generation sequencing, has initiated the massive screening of clinical samples and the identification of 1000s of cancer-associated gene mutations. However, proteomic analysis of the expressed mutation products lags far behind genomic (transcriptomic) analysis. With comprehensive global proteomics analysis, only a small percentage of single nucleotide variants detected by DNA and RNA sequencing have been observed as single amino acid variants due to current technical limitations. Proteomic analysis of mutations is important with the potential to advance cancer biomarker development and the discovery of new therapeutic targets for more effective disease treatment. Targeted proteomics using selected reaction monitoring (also known as multiple reaction monitoring) and parallel reaction monitoring, has emerged as a powerful tool with significant advantages over global proteomics for analysis of protein mutations in terms of detection sensitivity, quantitation accuracy and overall practicality (e.g., reliable identification and the scale of quantification). Herein we review recent advances in the targeted proteomics technology for enhancing detection sensitivity and multiplexing capability and highlight its broad biomedical applications for analysis of protein mutations in human bodily fluids, tissues, and cell lines. Furthermore, we review recent applications of top-down proteomics for analysis of protein mutations. Unlike the commonly used bottom-up proteomics which requires digestion of proteins into peptides, top-down proteomics directly analyzes intact proteins for more precise characterization of mutation isoforms. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale targeted detection and quantification of important protein mutations are discussed.

Complexities of Prostate Cancer

Prostate cancer has a long disease history and a wide variety and uncertainty in individual patients' clinical progress. In recent years, we have seen a revolutionary advance in both prostate cancer patient care and in the research field. The power of deep sequencing has provided cistromic and transcriptomic knowledge of prostate cancer that has not discovered before. Our understanding of prostate cancer biology, from bedside and molecular imaging techniques, has also been greatly advanced. It is important that our current theragnostic schemes, including our diagnostic modalities, therapeutic responses, and the drugs available to target non-AR signaling should be improved. This review article discusses the current progress in the understanding of prostate cancer biology and the recent advances in diagnostic and therapeutic strategies.

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.

ALDH3A2, ODF2, QSOX2, and MicroRNA-503-5p Expression to Forecast Recurrence in TMPRSS2-ERG-Positive Prostate Cancer

Following radical surgery, patients may suffer a relapse. It is important to identify such patients so that therapy tactics can be modified appropriately. Existing stratification schemes do not display the probability of recurrence with enough precision since locally advanced prostate cancer (PCa) is classified as high-risk but is not ranked in greater detail. Between 40 and 50% of PCa cases belong to the TMPRSS2-ERG subtype that is a sufficiently homogeneous group for high-precision prognostic marker search to be possible. This study includes two independent cohorts and is based on high throughput sequencing and qPCR data. As a result, we have been able to suggest a perspective-trained model involving a deep neural network based on both qPCR data for mRNA and miRNA and clinicopathological criteria that can be used for recurrence risk forecasts in patients with TMPRSS2-ERG-positive, locally advanced PCa (the model uses ALDH3A2 + ODF2 + QSOX2 + hsa-miR-503-5p + ISUP + pT, with an AUC = 0.944). In addition to the prognostic model’s use of identified differentially expressed genes and miRNAs, miRNA–target pairs were found that correlate with the prognosis and can be presented as an interactome network.

In situ expression of ERG protein in the context of tumor heterogeneity identifies prostate cancer patients with inferior prognosis

Prognostic biomarkers for prostate cancer are needed to improve prediction of disease course and guide treatment decisions. However, biomarker development is complicated by the common multifocality and heterogeneity of the disease. We aimed to determine the prognostic value of candidate biomarkers transcriptional regulator ERG and related ETS family genes, while considering tumor heterogeneity. In a multisampled, prospective, and treatment‐naïve radical prostatectomy cohort from one tertiary center (2010–2012, median follow‐up 8.1 years), we analyzed ERG protein (480 patients; 2047 tissue cores), and RNA of several ETS genes in a subcohort (165 patients; 778 fresh‐frozen tissue samples). Intra‐ and interfocal heterogeneity was identified in 29% and 33% (ERG protein) and 39% and 27% (ETS RNA) of patients, respectively. ERG protein and ETS RNA was identified exclusively in a nonindex tumor in 31% and 32% of patients, respectively. ERG protein demonstrated independent prognostic value in predicting biochemical (P = 0.04) and clinical recurrence (P = 0.004) and appeared to have greatest prognostic value for patients with Grade Groups 4–5. In conclusion, when heterogeneity is considered, ERG protein is a robust prognostic biomarker for prostate cancer.

Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer

Background

TMPRSS2-ERG gene rearrangement, the most common E26 transformation specific (ETS) gene fusion within prostate cancer, is known to contribute to the pathogenesis of this disease and carries diagnostic annotations for prostate cancer patients clinically. The ERG rearrangement status in prostatic adenocarcinoma currently cannot be reliably identified from histologic features on H&E-stained slides alone and hence requires ancillary studies such as immunohistochemistry (IHC), fluorescent in situ hybridization (FISH) or next generation sequencing (NGS) for identification.

Methods

Objective

We accordingly sought to develop a deep learning-based algorithm to identify ERG rearrangement status in prostatic adenocarcinoma based on digitized slides of H&E morphology alone.

Design

Setting, and Participants: Whole slide images from 392 in-house and TCGA cases were employed and annotated using QuPath. Image patches of 224 × 224 pixel were exported at 10 ×, 20 ×, and 40 × for input into a deep learning model based on MobileNetV2 convolutional neural network architecture pre-trained on ImageNet. A separate model was trained for each magnification. Training and test datasets consisted of 261 cases and 131 cases, respectively. The output of the model included a prediction of ERG-positive (ERG rearranged) or ERG-negative (ERG not rearranged) status for each input patch.

Outcome measurements and statistical analysis: Various accuracy measurements including area under the curve (AUC) of the receiver operating characteristic (ROC) curves were used to evaluate the deep learning model.

Results and Limitations

All models showed similar ROC curves with AUC results ranging between 0.82 and 0.85. The sensitivity and specificity of these models were 75.0% and 83.1% (20 × model), respectively.

Conclusions

A deep learning-based model can successfully predict ERG rearrangement status in the majority of prostatic adenocarcinomas utilizing only H&E-stained digital slides. Such an artificial intelligence-based model can eliminate the need for using extra tumor tissue to perform ancillary studies in order to assess for ERG gene rearrangement in prostatic adenocarcinoma.

The Expression of Proto-Oncogene ETS-Related Gene (ERG) Plays a Central Role in the Oncogenic Mechanism Involved in the Development and Progression of Prostate Cancer

The ETS-related gene (ERG) is proto-oncogene that is classified as a member of the ETS transcription factor family, which has been found to be consistently overexpressed in about half of the patients with clinically significant prostate cancer (PCa). The overexpression of ERG can mostly be attributed to the fusion of the ERG and transmembrane serine protease 2 (TMPRSS2) genes, and this fusion is estimated to represent about 85% of all gene fusions observed in prostate cancer. Clinically, individuals with ERG gene fusion are mostly documented to have advanced tumor stages, increased mortality, and higher rates of metastasis in non-surgical cohorts. In the current review, we elucidate ERG’s molecular interaction with downstream genes and the pathways associated with PCa. Studies have documented that ERG plays a central role in PCa progression due to its ability to enhance tumor growth by promoting inflammatory and angiogenic responses. ERG has also been implicated in the epithelial–mesenchymal transition (EMT) in PCa cells, which increases the ability of cancer cells to metastasize. In vivo, research has demonstrated that higher levels of ERG expression are involved with nuclear pleomorphism that prompts hyperplasia and the loss of cell polarity.

Polycystic ovary syndrome and risks for COVID-19 infection: A comprehensive review : PCOS and COVID-19 relationship

This comprehensive review aimed to evaluate the relationship between SARS-CoV-2 infection (the cause of coronavirus disease 2019, or COVID-19) and the metabolic and endocrine characteristics frequently found in women with polycystic ovary syndrome (PCOS). In the general population, COVID-19 is more severe in subjects with dyslipidemia, obesity, diabetes mellitus, and arterial hypertension. Because these conditions are comorbidities commonly associated with PCOS, it was hypothesized that women with PCOS would be at higher risk for acquiring COVID-19 and developing more severe clinical presentations. This hypothesis was confirmed in several epidemiological studies. The present review shows that women with PCOS are at 28%-50% higher risk of being infected with the SARS-CoV-2 virus at all ages and that, in these women, COVID-19 is associated with increased rates of hospitalization, morbidity, and mortality. We summarize the mechanisms of the higher risk of COVID-19 infection in women with PCOS, particularly in those with carbohydrate and lipid abnormal metabolism, hyperandrogenism, and central obesity.

Molecular mechanisms and genetic alterations in prostate cancer: From diagnosis to targeted therapy

Prostate cancer remains one of the most lethal malignancies among men worldwide. Although the primary tumor can be successfully managed by surgery and radiotherapy, advanced metastatic carcinoma requires better therapeutic approaches. In this context, a deeper understanding of the molecular mechanisms that underlie the initiation and progression of this disease is urgently needed, leading to the identification of new diagnostic/prognostic markers and the development of more effective treatments. Herein, the current state of knowledge of prostate cancer genetic alterations is discussed, with a focus on their potential in tumor detection and staging as well as in the screening of novel therapeutics.

Chromosome compartmentalization alterations in prostate cancer cell lines model disease progression

Prostate cancer aggressiveness and metastatic potential are influenced by gene expression and genomic aberrations, features that can be influenced by the 3D structure of chromosomes inside the nucleus. Using chromosome conformation capture (Hi-C), we conducted a systematic genome architecture comparison on a cohort of cell lines that model prostate cancer progression, from normal epithelium to bone metastasis. We describe spatial compartment identity (A-open versus B-closed) changes with progression in these cell lines and their relation to gene expression changes in both cell lines and patient samples. In particular, 48 gene clusters switch from the B to the A compartment, including androgen receptor, WNT5A, and CDK14. These switches are accompanied by changes in the structure, size, and boundaries of topologically associating domains (TADs). Further, compartment changes in chromosome 21 are exacerbated with progression and may explain, in part, the genesis of the TMPRSS2-ERG translocation. These results suggest that discrete 3D genome structure changes play a deleterious role in prostate cancer progression. .

Intraductal Carcinoma of the Prostate as a Cause of Prostate Cancer Metastasis: A Molecular Portrait

Simple Summary

Most men with prostate cancer will live as long as those who do not have prostate cancer. However, some men will die early of their disease due to a particular type of prostate cancer associated with recurrence and metastasis: intraductal carcinoma of the prostate. In this review, we discuss the associations between intraductal carcinoma of the prostate and metastasis, and the contemporary knowledge about the molecular alterations of intraductal carcinoma of the prostate.

Abstract

Intraductal carcinoma of the prostate (IDC-P) is one of the most aggressive types of prostate cancer (PCa). IDC-P is identified in approximately 20% of PCa patients and is associated with recurrence, metastasis, and PCa-specific death. The main feature of this histological variant is the colonization of benign glands by PCa cells. Although IDC-P is a well-recognized independent parameter for metastasis, mechanisms by which IDC-P cells can spread and colonize other tissues are not fully known. In this review, we discuss the molecular portraits of IDC-P determined by immunohistochemistry and genomic approaches and highlight the areas in which more research is needed.

What Do We Have to Know about PD-L1 Expression in Prostate Cancer? A Systematic Literature Review (Part 6): Correlation of PD-L1 Expression with the Status of Mismatch Repair System, BRCA, PTEN, and Other Genes

Pembrolizumab (anti-PD-1) is allowed in selected metastatic castration-resistant prostate cancer (PC) patients showing microsatellite instability/mismatch repair system deficiency (MSI-H/dMMR). BRCA1/2 loss-of-function is linked to hereditary PCs and homologous recombination DNA-repair system deficiency: poly-ADP-ribose-polymerase inhibitors can be administered to BRCA-mutated PC patients. Recently, docetaxel-refractory metastatic castration-resistant PC patients with BRCA1/2 or ATM somatic mutations had higher response rates to pembrolizumab. PTEN regulates cell cycle/proliferation/apoptosis through pathways including the AKT/mTOR, which upregulates PD-L1 expression in PC. Our systematic literature review (PRISMA guidelines) investigated the potential correlations between PD-L1 and MMR/MSI/BRCA/PTEN statuses in PC, discussing few other relevant genes. Excluding selection biases, 74/677 (11%) PCs showed dMMR/MSI; 8/67 (12%) of dMMR/MSI cases were PD-L1+. dMMR-PCs included ductal (3%) and acinar (14%) PCs (all cases tested for MSI were acinar-PCs). In total, 15/39 (39%) PCs harbored BRCA1/2 aberrations: limited data are available for PD-L1 expression in these patients. 13/137 (10%) PTEN- PCs were PD-L1+; 10/29 (35%) PD-L1+ PCs showed PTEN negativity. SPOP mutations may increase PD-L1 levels, while the potential correlation between PD-L1 and ERG expression in PC should be clarified. Further research should verify how the efficacy of PD-1 inhibitors in metastatic castration-resistant PCs is related to dMMR/MSI, DNA-damage repair genes defects, or PD-L1 expression.

The Role of Somatic Mutations on the Immune Response of the Tumor Microenvironment in Prostate Cancer

Immunotherapy has improved patient survival in many types of cancer, but for prostate cancer, initial results with immunotherapy have been disappointing. Prostate cancer is considered an immunologically excluded or cold tumor, unable to generate an effective T-cell response against cancer cells. However, a small but significant percentage of patients do respond to immunotherapy, suggesting that some specific molecular subtypes of this tumor may have a better response to checkpoint inhibitors. Recent findings suggest that, in addition to their function as cancer genes, somatic mutations of PTEN, TP53, RB1, CDK12, and DNA repair, or specific activation of regulatory pathways, such as ETS or MYC, may also facilitate immune evasion of the host response against cancer. This review presents an update of recent discoveries about the role that the common somatic mutations can play in changing the tumor microenvironment and immune response against prostate cancer. We describe how detailed molecular genetic analyses of the tumor microenvironment of prostate cancer using mouse models and human tumors are providing new insights into the cell types and pathways mediating immune responses. These analyses are helping researchers to design drug combinations that are more likely to target the molecular and immunological pathways that underlie treatment failure.

Gene Duplication and Gene Fusion Are Important Drivers of Tumourigenesis during Cancer Evolution

Chromosomal rearrangement and genome instability are common features of cancer cells in human. Consequently, gene duplication and gene fusion events are frequently observed in human malignancies and many of the products of these events are pathogenic, representing significant drivers of tumourigenesis and cancer evolution. In certain subsets of cancers duplicated and fused genes appear to be essential for initiation of tumour formation, and some even have the capability of transforming normal cells, highlighting the importance of understanding the events that result in their formation. The mechanisms that drive gene duplication and fusion are unregulated in cancer and they facilitate rapid evolution by selective forces akin to Darwinian survival of the fittest on a cellular level. In this review, we examine current knowledge of the landscape and prevalence of gene duplication and gene fusion in human cancers.

An overview of the latest in state-of-the-art murine models for prostate cancer

INTRODUCTION

Prostate cancer (PCa) is a complex, heterogenous and multifocal disease, which is debilitating for patients and often fatal - due to bone metastasis and castration-resistant cancer. The use of murine models that mimic human disease has been crucial in the development of innovative therapies and for better understanding the mechanisms associated with initiation and progression of PCa.

AREAS COVERED

This review presents a critical analysis of murine models for the study of PCa, highlighting their strengths, weaknesses and applications.

EXPERT OPINION

In animal models, disease may not occur exactly as it does in humans, and sometimes the levels of efficacy that certain treatments obtain in animal models cannot be translated into clinical practice. To choose the most appropriate animal model for each research work, it is crucial to understand the anatomical and physiological differences between the mouse and the human prostate, while it is also important to identify biological similarities and differences between murine and human prostate tumors. Although significant progress has already been made, thanks to many years of research and study, the number of new challenges and obstacles to overcome mean there is a long and difficult road still to travel.

Impact TMPRSS2-ERG Molecular Subtype on Prostate Cancer Recurrence

Currently, seven molecular subtypes of prostate cancer (PCa) are known, the most common of which being the subtype characterized by the presence of the TMPRSS2-ERG fusion transcript. While there is a considerable amount of work devoted to the influence of this transcript on the prognosis of the disease, data on its role in the progression and prognosis of PCa remain controversial. The present study is devoted to the analysis of the association between the TMPRSS2-ERG transcript and the biochemical recurrence of PCa. The study included two cohorts: the RNA-Seq sample of Russian patients with PCa (n = 72) and the TCGA-PRAD data (n = 203). The results of the analysis of the association between the TMPRSS2-ERG transcript and biochemical recurrence were contradictory. The differential expression analysis (biochemical recurrence cases versus biochemical recurrence-free) and the gene set enrichment analysis revealed a list of genes involved in major cellular pathways. The GNL3, QSOX2, SSPO, and SYS1 genes were selected as predictors of the potential prognostic model (AUC = 1.000 for a cohort of Russian patients with PCa and AUC = 0.779 for a TCGA-PRAD cohort).

Current Trends in Prevalence and Role of Long Noncoding RNA and Gene Fusion in Prostate Cancer: An Overview

Objectives The aim of this study is to analyze the current scenario in the diagnostic modalities for prostate cancer.

Materials and Methods We searched PubMed, Google Scholar, and ResearchGate for relevant data. Articles published in the last 10 years were taken into consideration. The role of long noncoding RNA and gene fusion products in the context of prostate cancer was reviewed, which included their roles in diagnosis, prognosis, and assessment of response to therapy.

Results Several long noncoding RNAs (lncRNA) have been isolated and have been shown to be useful in diagnosing and prognosticating prostate cancer. We have also looked into the role of TMPRSS2:ERG gene fusion in prostate carcinoma diagnosis. These molecular parameters have been looked into due to the fact that the current parameters in use such as prostate-specific antigen have several drawbacks that limit their potential.

Targeting host cell proteases as a potential treatment strategy to limit the spread of SARS-CoV-2 in the respiratory tract

As the death toll of Coronavirus disease 19 (COVID-19) continues to rise worldwide, it is imperative to explore novel molecular mechanisms for targeting SARS-CoV-2. Rather than looking for drugs that directly interact with key viral proteins inhibiting its replication, an alternative and possibly add-on approach is to dismantle the host cell machinery that enables the virus to infect the host cell and spread from one cell to another. Excellent examples of such machinery are host cell proteases whose role in viral pathogenesis has been demonstrated in numerous coronaviruses. In this review, we propose two therapeutic modalities to tackle SARS-CoV-2 infections; the first is to transcriptionally modulate the expression of cellular proteases and their endogenous inhibitors and the second is to directly inhibit their enzymatic activity. We present a nonexhaustive collection of clinically investigated drugs that act by one of these mechanisms and thus represent promising candidates for preclinical in vitro testing and hopefully clinical testing in COVID-19 patients.

A review of current clinical biomarkers for prostate cancer: towards personalised and targeted therapy

Background:

Prostate cancer is the most commonly diagnosed cancer in men and it is responsible for about 10% of all cancer mortality in Canadian men. The current ‘gold standard’ for the diagnosis of prostate cancer is a prostate biopsy and the decision on when to biopsy a patient with non-suspicious Digital Rectal Examination (DRE) result and total prostate specific antigen (tPSA) of 4–10 ng/ml can be challenging. In order to shift the treatment paradigm of prostate cancer toward more personalised and targeted therapy, there is the need for a clear system that makes its detection binary so as to decrease the rate of inaccurate detections. Therefore in recent years, there have been several investigations into the development of various biomarkers with high sensitivity and specificity for screening, early detection and personalised patient-specific targeted medicine from diagnosis to treatment of the disease.

Materials and methods:

This paper reports on nine currently available clinical biomarkers used in screening for early detection and diagnosis, to reduce the number of unnecessary biopsies, in risk assessment of aggressive disease and in monitoring treatment response of prostate cancer.

Conclusion:

Current clinical prostate cancer biomarkers have the potential for a personalised risk assessment of aggressive disease and the risk of developing distant metastatic disease and have been proven to be useful tools to guide clinicians in personalised patient-specific targeted treatment and in the shared decision making between patients and their physicians regarding prostate biopsy and treatment. Using biomarkers to select patients with a significant probability of aggressive prostate cancer would potentially avoid premature death from the disease, while at the same time would safely preclude patients who do not require unnecessary invasive intervention.

Are sex discordant outcomes in COVID-19 related to sex hormones?

COVID-19 has a clear sex disparity in clinical outcome. Globally, infection rates between men and women are similar; however, men are more likely to have more severe disease and are more likely to die. The causes for this disparity are currently under investigation and are most likely multifactorial. Sex hormones play an important role in the immune response with estrogen seen as immune boosting and testosterone as immunosuppressing. Additionally, an important protease involved in viral entry, TMPRSS2, is regulated by androgens. Many observational and prospective studies are ongoing or initiating to further examine the role of sex hormones in SARS-CoV-2 infection and if modulation of them is a realistic treatment option.

PTEN and ERG expression in MRI-ultrasound guided fusion biopsy correlated with radical prostatectomy findings in men with prostate cancer

BACKGROUND

Conventional systematic prostate biopsies (SBx) have multiple limitations, and magnetic resonance imaging (MRI)-ultrasound fusion targeting is increasingly applied (fusion biopsies [FBx]). In our previous studies, we have shown that loss of the tumor suppressor gene phosphatase and tensin homolog (PTEN) in radical prostatectomy (RP) specimens predicts poor disease-specific survival, and in active surveillance (AS), PTEN loss in SBx predicts an adverse AS outcome, although SBx PTEN status does not correlate well with the corresponding RP status. Here, we have hypothesized that PTEN and erythroblast transformation-specific related gene (ERG) status in FBx correlate better with RP than they would in SBx.

METHODS

A total of 106 men, who had undergone FBx and subsequent RP in a single center between June 2015 and May 2017 were included. Fifty-three of the men had concomitant or previous SBx's. All biopsy and RP specimens were collected, and tissue microarrays (TMA) were constructed from RP specimens. Immunohistochemical stainings for PTEN and ERG expression were conducted on biopsies and RP TMAs and results were compared by using Fisher's exact test.

RESULTS

The immunohistochemical predictive power of FBx, determined by the concordance of biopsy PTEN and ERG status with RP, is superior to SBx (77.6% vs 66.7% in PTEN, 92.4% vs 66.6% in ERG). FBx was superior to SBx in correlation with RP Gleason Grade Groups and MRI prostate imaging reporting and data system scores.

CONCLUSION

FBx grading correlates with RP histology and MRI findings and predicts the biomarker status in the RP specimens more accurately than SBx. A longer follow-up is needed to evaluate if this translates to better prediction of disease outcomes, especially in AS and radiation therapy where prostatectomy specimens are not available for prognostication.

The Role of AMACR, CD10, TMPRSS2-ERG, and p27 Protein Expression Among Different Gleason Grades of Prostatic Adenocarcinoma on Needle Biopsy

OBJECTIVE

We examined the immunohistochemical expression of α-methyl acyl coenzyme A racemase (AMACR), CD10, TMPRSS2-ERG, and p27 in prostate adenocarcinoma tumors with different Gleason growth patterns and nonneoplastic prostate tissues to elucidate their roles in prostate carcinogenesis and histological aggressiveness.

MATERIAL AND METHODS

In total, 80 archival core biopsy tissues diagnosed as prostate carcinoma, benign prostate hyperplasia, and atrophy cases were included. Immunoreactivity was evaluated by calculating the percentage of positively stained cells and the staining intensity. The mean values and test of significance were obtained using the Kruskal-Wallis test.

RESULTS

We obtained mostly intense immunoreactivity for AMACR, CD10, and ERG in adenocarcinomas. Although no significant differences were noted regarding AMACR and ERG expression, samples with Gleason growth patterns 3 and 5 tended to be strongly positive for ERG. Pattern 3 tumors exhibited the weakest positivity for CD10. The p27 expression was strong and diffuse in nonneoplastic prostate tissues. The loss of p27 expression was more frequent for pattern 5 tumors.

CONCLUSION

ERG and AMACR were powerful markers to detect cancer. Especially, ERG is evident in early tumors may reflect its interaction with functional androgen receptors in cancer initiation. Pattern 5 tumors associated with stroma may have been exposed to more stromal substrates and upregulate their CD10 content as a protein degrader. We suggest that CD10 expression is associated with an increasing tumor grade. Decreased concentrations of p27 protein might be implicated in prostate carcinogenesis and may be a useful immunohistochemical adjunct in predicting histological aggressiveness.

Characterization of long G4-rich enhancer-associated genomic regions engaging in a novel loop:loop 'G4 Kissing' interaction

Mammalian antibody switch regions (∼1500 bp) are composed of a series of closely neighboring G4-capable sequences. Whereas numerous structural and genome-wide analyses of roles for minimal G4s in transcriptional regulation have been reported, Long G4-capable regions (LG4s)-like those at antibody switch regions-remain virtually unexplored. Using a novel computational approach we have identified 301 LG4s in the human genome and find LG4s prone to mutation and significantly associated with chromosomal rearrangements in malignancy. Strikingly, 217 LG4s overlap annotated enhancers, and we find the promoters regulated by these enhancers markedly enriched in G4-capable sequences suggesting G4s facilitate promoter-enhancer interactions. Finally, and much to our surprise, we also find single-stranded loops of minimal G4s within individual LG4 loci are frequently highly complementary to one another with 178 LG4 loci averaging >35 internal loop:loop complements of >8 bp. As such, we hypothesized (then experimentally confirmed) that G4 loops within individual LG4 loci directly basepair with one another (similar to characterized stem-loop kissing interactions) forming a hitherto undescribed, higher-order, G4-based secondary structure we term a 'G4 Kiss or G4K'. In conclusion, LG4s adopt novel, higher-order, composite G4 structures directly contributing to the inherent instability, regulatory capacity, and maintenance of these conspicuous genomic regions.

First comprehensive computational analysis of functional consequences of TMPRSS2 SNPs in susceptibility to SARS-CoV-2 among different populations

Current SARS-CoV-2 pandemy mortality created the hypothesis that some populations may be more susceptible to SARS-CoV-2. TMPRSS2 encodes a transmembrane serine protease which plays a crucial role in SARS-CoV-2 cell entry. Single nucleotide polymorphisms (SNPs) in TMPRSS2 might influence SARS-CoV2 entry into the cell. This study aimed to investigate the impact of SNPs on TMPRSS2 function and structure. In silico tools such as Ensembl, Gtex, ExPASY 2, GEPIA, CCLE, KEGG and GO were engaged to characterize TMPRSS2 and its expression profile. The functional effects of SNPs were analyzed by PolyPhen-2, PROVEN, SNAP2, SIFT and HSF. Also, Phyre2, GOR IV and PSIPRED were used to predict the secondary structure of TMPRSS2. Moreover, post-translational modification (PTM) and secretory properties were analyzed through Modpredand Phobius, respectively. Finally, miRNA profiles were investigated by PolymiRTS and miRSNPs. Out of 11,184 retrieved SNPs from dbSNP, 92 showed a different frequency between Asians and other populations. Only 21 SNPs affected the function and structure of TMPRSS2 by influencing the protein folding, PTM, splicing and miRNA function. Particularly, rs12329760 may create a de novo pocket protein. rs875393 can create a donor site, silencer and broken enhancer motifs. rs12627374 affects a wide spectrum of miRNAs profile. This study highlighted the role of TMPRSS2 SNPs and epigenetic mechanisms especially non-coding RNAs in appearance of different susceptibility to SARS-CoV-2 among different populations. Also, this study could pave the way to potential therapeutic implication of TMPRSS2 in designing antiviral drugs.

Communicated by Ramaswamy H. Sarma

Comprehensive metabolomics analysis of prostate cancer tissue in relation to tumor aggressiveness and TMPRSS2-ERG fusion status

Background

Prostate cancer (PC) can display very heterogeneous phenotypes ranging from indolent asymptomatic to aggressive lethal forms. Understanding how these PC subtypes vary in their striving for energy and anabolic molecules is of fundamental importance for developing more effective therapies and diagnostics. Here, we carried out an extensive analysis of prostate tissue samples to reveal metabolic alterations during PC development and disease progression and furthermore between TMPRSS2-ERG rearrangement-positive and -negative PC subclasses.

Methods

Comprehensive metabolomics analysis of prostate tissue samples was performed by non-destructive high-resolution magic angle spinning nuclear magnetic resonance (¹H HR MAS NMR). Subsequently, samples underwent moderate extraction, leaving tissue morphology intact for histopathological characterization. Metabolites in tissue extracts were identified by ¹H/³¹P NMR and liquid chromatography-mass spectrometry (LC-MS). These metabolomics profiles were analyzed by chemometric tools and the outcome was further validated using proteomic data from a separate sample cohort.

Results

The obtained metabolite patterns significantly differed between PC and benign tissue and between samples with high and low Gleason score (GS). Five key metabolites (phosphocholine, glutamate, hypoxanthine, arginine and α-glucose) were identified, who were sufficient to differentiate between cancer and benign tissue and between high to low GS. In ERG-positive PC, the analysis revealed several acylcarnitines among the increased metabolites together with decreased levels of proteins involved in β-oxidation; indicating decreased acyl-CoAs oxidation in ERG-positive tumors. The ERG-positive group also showed increased levels of metabolites and proteins involved in purine catabolism; a potential sign of increased DNA damage and oxidative stress.

Conclusions

Our comprehensive metabolomic analysis strongly indicates that ERG-positive PC and ERG-negative PC should be considered as different subtypes of PC; a fact requiring different, sub-type specific treatment strategies for affected patients.

miR-223-5p targeting ERG inhibits prostate cancer cell proliferation and migration

Ectopic expression of miR-223-5p, the lagging strand of miR-223 duplex, has been reported acting as anti-tumor miRNA in many cancers. How miR-223-5p influencing prostate cancer (PCa) remains obscure and worth of experimental investigation. In this study, the expressions of miR-223-5p and ERG in common PCa cell lines were detected and compared to RWPE-1, respectively. Then luciferase reporter assay was performed to verify whether miR-223-5p could specifically target and regulate ERG. Further discovery ERG's role in the PCa oncogenesis was also conducted by up or down regulating miR-223-3p expression. We found miR-223-5p was significantly down-regulated in DU145, while it was only up-regulated in LNCaP. Similarly, ERG expression remarkably decreased in both PC-3 and DU145 than that in RWPE-1, but significantly increasing in LNCaP. Luciferase assay demonstrated slightly decreased ERG expression after miR-223-5p-mimics but significantly increased ERG expression after miR-223-5p-inhibtor. Using gene interference, we further confirmed that both ERG mRNA and protein expressions were decreased in all PCa lines transfected ERG siRNA, but increasing in both DU145 and LNCaP cells with miR-223-5p antisense oligonucleotides. MTT assay, Transwell invasion and migration assay supported the function of ERG in PCa oncogenesis. We revealed tumor suppressive abilities of miR-223-5p in PCa by negatively targeting ERG gene. It could serve as a fundamental supplement and extension of our previous study about miR-223-3p in PCa, revealing the coordinative regulation between miR-223-5p and miR-223-3p in PCa cell biological behaviors. Exploration of miR-233-duplex orientated pathway networks may help us develop novel potential therapeutic options for PCa.

Protease-activated prodrugs: strategies, challenges, and future directions

Proteases play critical roles in virtually all biological processes, including proliferation, cell death and survival, protein turnover, and migration. However, when dysregulated, these enzymes contribute to the progression of multiple diseases, with cancer, neurodegenerative disorders, inflammation, and blood disorders being the most prominent examples. For a long time, disease-associated proteases have been used for the activation of various prodrugs due to their well-characterized catalytic activity and ability to selectively cleave only those substrates that strictly correspond with their active site architecture. To date, versatile peptide sequences that are cleaved by proteases in a site-specific manner have been utilized as bioactive linkers for the targeted delivery of multiple types of cargo, including fluorescent dyes, photosensitizers, cytotoxic drugs, antibiotics, and pro-antibodies. This platform is highly adaptive, as multiple protease-labile conjugates have already been developed, some of which are currently in clinical use for cancer treatment. In this review, recent advancements in the development of novel protease-cleavable linkers for selective drug delivery are described. Moreover, the current limitations regarding the selectivity of linkers are discussed, and the future perspectives that rely on the application of unnatural amino acids for the development of highly selective peptide linkers are also presented.

Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American Patients

PURPOSE

Between 30%-40% of patients with prostate cancer experience disease recurrence following radical prostatectomy. Existing clinical models for recurrence risk prediction do not account for population-based variation in the tumor phenotype, despite recent evidence suggesting the presence of a unique, more aggressive prostate cancer phenotype in African American (AA) patients. We investigated the capacity of digitally measured, population-specific phenotypes of the intratumoral stroma to create improved models for prediction of recurrence following radical prostatectomy.

EXPERIMENTAL DESIGN

This study included 334 radical prostatectomy patients subdivided into training (VT, n = 127), validation 1 (V1, n = 62), and validation 2 (V2, n = 145). Hematoxylin and eosin-stained slides from resected prostates were digitized, and 242 quantitative descriptors of the intratumoral stroma were calculated using a computational algorithm. Machine learning and elastic net Cox regression models were constructed using VT to predict biochemical recurrence-free survival based on these features. Performance of these models was assessed using V1 and V2, both overall and in population-specific cohorts.

RESULTS

An AA-specific, automated stromal signature, AAstro, was prognostic of recurrence risk in both independent validation datasets [V1,AA: AUC = 0.87, HR = 4.71 (95% confidence interval (CI), 1.65-13.4), P = 0.003; V2,AA: AUC = 0.77, HR = 5.7 (95% CI, 1.48-21.90), P = 0.01]. AAstro outperformed clinical standard Kattan and CAPRA-S nomograms, and the underlying stromal descriptors were strongly associated with IHC measurements of specific tumor biomarker expression levels.

CONCLUSIONS

Our results suggest that considering population-specific information and stromal morphology has the potential to substantially improve accuracy of prognosis and risk stratification in AA patients with prostate cancer.

Bioinformatic identification of differentially expressed genes associated with prognosis of locally advanced lymph node-positive prostate cancer

Prostate cancer (PCa) is one of the primary causes of cancer-related mortality in men worldwide. Patients with locally advanced PCa with metastases in regional lymph nodes are usually marked as a high-risk group. One of the chief concerns for this group is to make an informed decision about the necessity of conducting adjuvant androgen deprivation therapy after radical surgical treatment. During the oncogenic transformation and progression of the disease, the expression of many genes is altered. Some of these genes can serve as markers for diagnosis, predicting the prognosis or effectiveness of drug therapy, as well as possible therapeutic targets. We undertook bioinformatic analysis of the RNA-seq data deposited in The Cancer Genome Atlas consortium database to identify possible prognostic markers. We compared the groups with favorable and unfavorable prognosis for the cohort of patients with PCa showing lymph node metastasis (pT2N1M0, pT3N1M0, and pT4N1M0) and for the most common molecular type carrying the fusion transcript TMPRSS2-ERG. For the entire cohort, we revealed at least six potential markers (IDO1, UGT2B15, IFNG, MUC6, CXCL11, and GBP1). Most of these genes are involved in the positive regulation of immune response. For the TMPRSS2-ERG subtype, we also identified six genes, the expression of which may be associated with prognosis: TOB1, GALNT7, INAFM1, APELA, RAC3, and NNMT. The identified genes, after additional studies and validation in the extended cohort, could serve as a prognostic marker of locally advanced lymph node-positive PCa.

The Transcription Factor ERG Regulates Super-Enhancers Associated With an Endothelial-Specific Gene Expression Program

RATIONALE

The ETS (E-26 transformation-specific) transcription factor ERG (ETS-related gene) is essential for endothelial homeostasis, driving expression of lineage genes and repressing proinflammatory genes. Loss of ERG expression is associated with diseases including atherosclerosis. ERG's homeostatic function is lineage-specific, because aberrant ERG expression in cancer is oncogenic. The molecular basis for ERG lineage-specific activity is unknown. Transcriptional regulation of lineage specificity is linked to enhancer clusters (super-enhancers).

OBJECTIVE

To investigate whether ERG regulates endothelial-specific gene expression via super-enhancers.

METHODS AND RESULTS

Chromatin immunoprecipitation with high-throughput sequencing in human umbilical vein endothelial cells showed that ERG binds 93% of super-enhancers ranked according to H3K27ac, a mark of active chromatin. These were associated with endothelial genes such as DLL4 (Delta-like protein 4), CLDN5 (claudin-5), VWF (von Willebrand factor), and CDH5 (VE-cadherin). Comparison between human umbilical vein endothelial cell and prostate cancer TMPRSS2 (transmembrane protease, serine-2):ERG fusion-positive human prostate epithelial cancer cell line (VCaP) cells revealed distinctive lineage-specific transcriptome and super-enhancer profiles. At a subset of endothelial super-enhancers (including DLL4 and CLDN5), loss of ERG results in significant reduction in gene expression which correlates with decreased enrichment of H3K27ac and MED (Mediator complex subunit)-1, and reduced recruitment of acetyltransferase p300. At these super-enhancers, co-occupancy of GATA2 (GATA-binding protein 2) and AP-1 (activator protein 1) is significantly lower compared with super-enhancers that remained constant following ERG inhibition. These data suggest distinct mechanisms of super-enhancer regulation in endothelial cells and highlight the unique role of ERG in controlling a core subset of super-enhancers. Most disease-associated single nucleotide polymorphisms from genome-wide association studies lie within noncoding regions and perturb transcription factor recognition sequences in relevant cell types. Analysis of genome-wide association studies data shows significant enrichment of risk variants for cardiovascular disease and other diseases, at ERG endothelial enhancers and super-enhancers.

CONCLUSIONS

The transcription factor ERG promotes endothelial homeostasis via regulation of lineage-specific enhancers and super-enhancers. Enrichment of cardiovascular disease-associated single nucleotide polymorphisms at ERG super-enhancers suggests that ERG-dependent transcription modulates disease risk.

5hmC Level Predicts Biochemical Failure Following Radical Prostatectomy in Prostate Cancer Patients with ERG Negative Tumors

This study aimed to validate whether 5-hydroxymethylcytosine (5hmC) level in combination with ERG expression is a predictive biomarker for biochemical failure (BF) in men undergoing radical prostatectomy (RP) for prostate cancer (PCa). The study included 592 PCa patients from two consecutive Danish RP cohorts. 5hmC level and ERG expression were analyzed using immunohistochemistry in RP specimens. 5hmC was scored as low or high and ERG was scored as negative or positive. Risk of BF was analyzed using stratified cumulative incidences and multiple cause-specific Cox regression using competing risk assessment. Median follow-up was 10 years (95% CI: 9.5–10.2). In total, 246 patients (41.6%) had low and 346 patients (58.4%) had high 5hmC level. No significant association was found between 5hmC level or ERG expression and time to BF (p = 0.2 and p = 1.0, respectively). However, for men with ERG negative tumors, high 5hmC level was associated with increased risk of BF following RP (p = 0.01). In multiple cause-specific Cox regression analyses of ERG negative patients, high 5hmC expression was associated with time to BF (HR: 1.8; 95% CI: 1.2–2.7; p = 0.003). In conclusion, high 5hmC level was correlated with time to BF in men with ERG negative PCa, which is in accordance with previous results.

Prostate-specific markers to identify rare prostate cancer cells in liquid biopsies

Despite improvements in early detection and advances in treatment, patients with prostate cancer continue to die from their disease. Minimal residual disease after primary definitive treatment can lead to relapse and distant metastases, and increasing evidence suggests that circulating tumour cells (CTCs) and bone marrow-derived disseminated tumour cells (BM-DTCs) can offer clinically relevant biological insights into prostate cancer dissemination and metastasis. Using epithelial markers to accurately detect CTCs and BM-DTCs is associated with difficulties, and prostate-specific markers are needed for the detection of these cells using rare cell assays. Putative prostate-specific markers have been identified, and an optimized strategy for staining rare cancer cells from liquid biopsies using these markers is required. The ideal prostate-specific marker will be expressed on every CTC or BM-DTC throughout disease progression (giving high sensitivity) and will not be expressed on non-prostate-cancer cells in the sample (giving high specificity). Some markers might not be specific enough to the prostate to be used as individual markers of prostate cancer cells, whereas others could be truly prostate-specific and would make ideal markers for use in rare cell assays. The goal of future studies is to use sensitive and specific prostate markers to consistently and reliably identify rare cancer cells.

Oncogenic ETS Factors in Prostate Cancer

Prostate cancer is unique among carcinomas in that a fusion gene created by a chromosomal rearrangement is a common driver of the disease. The TMPRSS2/ERG rearrangement drives aberrant expression of the ETS family transcription factor ERG in 50% of prostate tumors. Similar rearrangements promote aberrant expression of the ETS family transcription factors ETV1 and ETV4 in another 10% of cases. Together, these three ETS factors are thought to promote tumorigenesis in the majority of prostate cancers. A goal of precision medicine is to be able to apply targeted therapeutics that are specific to disease subtypes. ETS gene rearrangement positive tumors represent the largest molecular subtype of prostate cancer, but to date there is no treatment specific to this marker. In this chapter we will review the latest findings regarding the molecular mechanisms of ETS factor function in the prostate. These molecular details may provide a path towards new therapeutic targets for this subtype of prostate cancer. Further, we will describe efforts to target the oncogenic functions of ETS family transcription factors directly as well as indirectly.

Immunoreactivity for prostate specific antigen and Ki67 differentiates subgroups of prostate cancer related to outcome

Based on gene-expression profiles, prostate tumors can be subdivided into subtypes with different aggressiveness and response to treatment. We investigated if similar clinically relevant subgroups can be identified simply by the combination of two immunohistochemistry markers: one for tumor cell differentiation (prostate specific antigen, PSA) and one for proliferation (Ki67). This was analyzed in men with prostate cancer diagnosed at transurethral resection of the prostate 1975-1991 (n = 331) where the majority was managed by watchful waiting. Ki67 and PSA immunoreactivity was related to outcome and to tumor characteristics previously associated with prognosis. Increased Ki67 and decreased PSA were associated with poor outcome, and they provided independent prognostic information from Gleason score. A combinatory score for PSA and Ki67 immunoreactivity was produced using the median PSA and Ki67 levels as cut-off (for Ki67 the upper quartile was also evaluated) for differentiation into subgroups. Patients with PSA low/Ki67 high tumors showed higher Gleason score, more advanced tumor stage, and higher risk of prostate cancer death compared to other patients. Their tumor epithelial cells were often ERG positive and expressed higher levels of ErbB2, phosphorylated epidermal growth factor receptor (pEGF-R) and protein kinase B (pAkt), and their tumor stroma showed a reactive response with type 2 macrophage infiltration, high density of blood vessels and hyaluronic acid, and with reduced levels of caveolin-1, androgen receptors, and mast cells. In contrast, men with PSA high/Ki67 low tumors were characterized by low Gleason score, and the most favorable outcome amongst PSA/Ki67-defined subgroups. Men with PSA low/Ki67 low tumors showed clinical and tumor characteristics intermediate of the two groups above. A combinatory PSA/Ki67 immunoreactivity score identifies subgroups of prostate cancers with different epithelial and stroma phenotypes and highly different outcome but the clinical usefulness of this approach needs to be validated in other cohorts.

Characterize the difference between TMPRSS2-ERG and non-TMPRSS2-ERG fusion patients by clinical and biological characteristics in prostate cancer

The TMPRSS2-ERG gene fusion were frequently found in prostate cancer, and thought to play some fundamental mechanisms for the development of prostate cancer. However, until now, the clinical and prognostic significance of TMPRSS2-ERG gene fusion was not fully understood. In this study, based on the 281 prostate cancers that constructed from a historical watchful waiting cohort, the statistically significant associations between TMPRSS2-ERG gene fusion and clinicopathologic characteristics were identified. In addition, the Elastic Net algorithm was used to predict the patients with TMPRSS2-ERG fusion status, and good predictive results were obtained, indicating that this algorithm was suitable to this prediction problem. The differential gene network was constructed from the network, and the KEGG enrichment analysis demonstrated that the module genes were significantly enriched in several important pathways.

An analysis of a multiple biomarker panel to better predict prostate cancer metastasis after radical prostatectomy

A plethora of individual candidate biomarkers for predicting biochemical relapse in localized prostate cancer (PCa) have been proposed. Combined biomarkers may improve prognostication, and ensuring validation against more clinically relevant endpoints are required. The Australian PCa Research Centre NSW has contributed to numerous studies of molecular biomarkers associated with biochemical relapse. In the current study, these biomarkers were re-analyzed for biochemical relapse, metastatic relapse and PCa death with extended follow-up. Biomarkers of significance were then used to develop a combined prognostic model for clinical outcomes and validated in a large independent cohort. The discovery cohort (n = 324) was based on 12 biomarkers with a median follow-up of 16 years. Seven biomarkers were significantly associated with biochemical relapse. Three biomarkers were associated with metastases: AZGP1, Ki67 and PML. Only AZGP1 was associated with PCa death. In their individual and combinational forms, AZGP1 and Ki67 as a dual BM signature was the most robust predictor of metastatic relapse (AUC 0.762). The AZPG1 and Ki67 signature was validated in an independent cohort of 347 PCa patients. The dual BM signature of AZGP1 and Ki67 predicted metastasis in the univariable (HR 7.2, 95% CI, 1.6-32; p = 0.01) and multivariable analysis (HR 5.4, 95% CI, 1.2-25; p = 0.03). The dual biomarker signature marginally improved risk prediction compared to AZGP1 alone (AUC 0.758 versus 0.738, p < 0.001). Our findings indicate that biochemical relapse is not an adequate surrogate for metastasis or PCa death. The dual biomarker signature of AZGP1 and Ki67 offers a small benefit in predicting metastasis over AZGP1 alone.

Proteomic approaches for cancer epigenetics research

Introduction: Epigenetic dysregulation drives or supports numerous human cancers. The chromatin landscape in cancer cells is often marked by abnormal histone post-translational modification (PTM) patterns and by aberrant assembly and recruitment of protein complexes to specific genomic loci. Mass spectrometry-based proteomic analyses can support the discovery and characterization of both phenomena. Areas covered: We broadly divide this literature into two parts: 'modification-centric' analyses that link histone PTMs to cancer biology; and 'complex-centric' analyses that examine protein-protein interactions that occur de novo as a result of oncogenic mutations. We also discuss proteomic studies of oncohistones. We highlight relevant examples, discuss limitations, and speculate about forthcoming innovations regarding each application. Expert commentary: 'Modification-centric' analyses have been used to further understanding of cancer's histone code and to identify associated therapeutic vulnerabilities. 'Complex-centric' analyses have likewise revealed insights into mechanisms of oncogenesis and suggested potential therapeutic targets, particularly in MLL-associated leukemia. Proteomic experiments have also supported some of the pioneering studies of oncohistone-mediated tumorigenesis. Additional applications of proteomics that may benefit cancer epigenetics research include middle-down and top-down histone PTM analysis, chromatin reader profiling, and genomic locus-specific protein identification. In the coming years, proteomic approaches will remain powerful ways to interrogate the biology of cancer.

Nuclear receptor ERRα and transcription factor ERG form a reciprocal loop in the regulation of TMPRSS2:ERG fusion gene in prostate cancer

The TMPRSS2:ERG (T:E) fusion gene is generally believed to be mainly regulated by the activated androgen receptor (AR) signaling in androgen-dependent prostate cancer. However, its persistent expression in castration-resistant and neuroendocrine prostate cancers implies that other transcription factors might also regulate its expression. Here, we showed that up-regulation of nuclear receptor estrogen-related receptor alpha (ERRα) was closely associated with the oncogenic transcription factor ERG expression in prostate cancer, and their increased coexpression patterns were closely associated with high Gleason scores and metastasis in patients. Both ERRα and ERG exhibited a positive expression correlation in a castration-resistant prostate cancer (CRPC) xenograft model VCaP-CRPC. We showed that ERRα could directly transactivate T:E fusion gene in both AR-positive and -negative prostate cancer cells via both ERR-binding element- and AR-binding element-dependent manners. Ectopic T:E expression under ERRα regulation could promote both in vitro invasion and in vivo metastasis capacities of AR-negative prostatic cells. Intriguingly, ERG expressed by the T:E fusion could also transactivate the ERRα (ESRRA) gene. Hereby, ERRα and ERG can synergistically regulate each other and form a reciprocal regulatory loop to promote the advanced growth of prostate cancer. Inhibition of ERRα activity by ERRα inverse agonist could suppress T:E expression in prostate cancer cells, implicating that targeting ERRα could be a potential therapeutic strategy for treating the aggressive T:E-positive prostate cancer.

C-MYC, HIF-1α, ERG, TKT, and GSTP1: an Axis in Prostate Cancer?

To analyze putative biomarkers for prostate cancer (PCA) characterization, the second leading cause of cancer-associated mortality in men. Quantification of the expression level of c-myc and HIF-1α was performed in 72 prostate cancer specimens. A cohort of 497 prostate cancer patients from The Cancer Genome Atlas (TCGA) database was further analyzed, in order to test our hypothesis. We found that high c-myc level was significantly associated with HIF-1α elevated expression (p = 0.008) in our 72 samples. Statistical analysis of 497 TCGA prostate cancer specimens confirmed the strong association (p = 0.0005) of c-myc and HIF-1α expression levels, as we found in our series. Moreover, we found high c-myc levels significantly associated with low Glutatione S-transferase P1 (GSTP1) expression (p = 0.01), with high Transketolase (TKT) expression (p < 0.0001). High TKT levels were found in TCGA samples with low GSTP1 mRNA (p < 0.0001), as shown for c-myc, and with ERG increased expression (p = 0.02). Finally, samples with low GSTP1 expression displayed higher ERG mRNA levels than samples with high GSTP1 score (p < 0.0001), as above shown for c-myc. Our study emphasizes the notion of a potential value of HIF-1α and c-myc as putative biomarkers in prostate cancer; moreover TCGA data analysis showed a putative crosstalk between c-myc, HIF-1α, ERG, TKT, and GSTP1, suggesting a potential use of this axis in prostate cancer.