MYC Overexpression at the Protein and mRNA Level and Cancer Outcomes among Men Treated with Radical Prostatectomy for Prostate Cancer

STEAP1 Knockdown Decreases the Sensitivity of Prostate Cancer Cells to Paclitaxel, Docetaxel and Cabazitaxel

The Six Transmembrane Epithelial Antigen of the Prostate 1 (STEAP1) protein has been indicated as an overexpressed oncoprotein in prostate cancer (PCa), associated with tumor progression and aggressiveness. Taxane-based antineoplastic drugs such as paclitaxel, docetaxel, or cabazitaxel, have been investigated in PCa treatment, namely for the development of combined therapies with the improvement of therapeutic effectiveness. This study aimed to evaluate the expression of STEAP1 in response to taxane-based drugs and assess whether the sensitivity of PCa cells to treatment with paclitaxel, docetaxel, or cabazitaxel may change when the STEAP1 gene is silenced. Thus, wild-type and STEAP1 knockdown LNCaP and C4-2B cells were exposed to paclitaxel, docetaxel or cabazitaxel, and STEAP1 expression, cell viability, and survival pathways were evaluated. The results obtained showed that STEAP1 knockdown or taxane-based drugs treatment significantly reduced the viability and survival of PCa cells. Relatively to the expression of proliferation markers and apoptosis regulators, LNCaP cells showed a reduced proliferation, whereas apoptosis was increased. However, the effect of paclitaxel, docetaxel, or cabazitaxel treatment was reversed when combined with STEAP1 knockdown. Besides, these chemotherapeutic drugs may stimulate the cell growth of PCa cells knocked down for STEAP1. In conclusion, this study demonstrated that STEAP1 expression levels might influence the response of PCa cells to chemotherapeutics drugs, indicating that the use of paclitaxel, docetaxel, or cabazitaxel may lead to harmful effects in PCa cells with decreased expression of STEAP1.

Selected by bioinformatics and molecular docking analysis, Dhea and 2–14,15-Eg are effective against cholangiocarcinoma

Object

To identify novel targets for the diagnosis, treatment and prognosis of cholangiocarcinoma, we screen ideal lead compounds and preclinical drug candidates with MYC inhibitory effect from the ZINC database, and verify the therapeutic effect of Dhea and 2–14,15-Eg on cholangiocarcinoma.

Methods

The gene expression profiles of GSE132305, GSE89749, and GSE45001 were obtained respectively from the Gene Expression Omnibus database. The DEGs were identified by comparing the gene expression profiles of cholangiocarcinoma and normal tissues. GO, KEGG analysis and PPI network analyses were performed. LibDock, ADME and toxicity prediction, molecular docking and molecular dynamics simulations were used to identify potential inhibitors of MYC. Moreover, in vitro, MTT assay, colony-forming assay, the scratch assay and Western blotting were performed to verify the therapeutic effect of Dhea and 2–14,15-Eg.

Results

PPI network analysis showed that ALB, MYC, APOB, IGF1 and KNG1 were hub genes, of which MYC was mainly studied in this study. A battery of computer-aided virtual techniques showed that Dhea and 2–14,15-Eg have lower rodent carcinogenicity, Ames mutagenicity, developmental toxicity potential, and high tolerance to cytochrome P4502D6, as well as could exist stably in natural circumstances. In vitro assays showed that Dhea and 2–14,15-Eg inhibited cholangiocarcinoma cellular viability, proliferation, and migration inhibiting expression of MYC.

Conclusion

This study suggested that Dhea and 2–14,15-Eg were novel potential inhibitors of MYC targeting, as well as are a promising drug in dealing with cholangiocarcinoma and have a perspective application.

Extent, impact, and mitigation of batch effects in tumor biomarker studies using tissue microarrays

Tissue microarrays (TMAs) have been used in thousands of cancer biomarker studies. To what extent batch effects, measurement error in biomarker levels between slides, affects TMA-based studies has not been assessed systematically. We evaluated 20 protein biomarkers on 14 TMAs with prospectively collected tumor tissue from 1448 primary prostate cancers. In half of the biomarkers, more than 10% of biomarker variance was attributable to between-TMA differences (range, 1–48%). We implemented different methods to mitigate batch effects (R package batchtma), tested in plasmode simulation. Biomarker levels were more similar between mitigation approaches compared to uncorrected values. For some biomarkers, associations with clinical features changed substantially after addressing batch effects. Batch effects and resulting bias are not an error of an individual study but an inherent feature of TMA-based protein biomarker studies. They always need to be considered during study design and addressed analytically in studies using more than one TMA.

To understand cancer, researchers need to know which molecules tumor cells use. These so-called ‘biomarkers’ tag cancer cells as being different from healthy cells, and can be used to predict how aggressive a tumor may be, or how well it might respond to treatment.

A popular technique for assessing biomarkers across multiple tumors is to use tissue microarrays. This involves taking samples from different tumors and embedding them in a block of wax, which is then cut into micro-thin slices and stained with reagents that can detect specific biomarkers, such as proteins. Each block contains hundreds of samples, which all experience the same conditions. So, any patterns detected in the staining are likely to represent real variations in the biomarkers present.

Many cancer studies, however, often compare samples from multiple tissue microarrays, which may increase the risk of technical artifacts: for example, staining may look stronger in one batch of tissue samples than another, even though the amount of biomarker present in these different arrays is roughly the same. These ‘batch effects’ could potentially bias the results of the experiment and lead to the identification of misleading patterns.

To evaluate how batch effects impact tissue microarray studies, Stopsack et al. examined 14 wax blocks which contained tumor samples from 1,448 men with prostate cancer. This revealed that for some biomarkers, but not others, there were noticeable differences between tissue microarrays that were clearly the result of batch effects. Stopsack et al. then tested six different ways of fixing these discrepancies using statistical methods. All six approaches were successful, even if the arrays included tumors with different characteristics, such as tumors that had been diagnosed more or less recently.

This work highlights the importance of considering batch effects when using tissue microarrays to study cancer. Stopsack et al. have used their statistical approaches to develop freely available software which can reduce the biases that sometimes arise from these technical artifacts. This could help researchers avoid misleading patterns in their data and make it easier to detect real variations in the biomarkers present between tumor samples.

More Than Meets the Eye Regarding Cancer Metabolism

In spite of the continuous improvement in our knowledge of the nature of cancer, the causes of its formation and the development of new treatment methods, our knowledge is still incomplete. A key issue is the difference in metabolism between normal and cancer cells. The features that distinguish cancer cells from normal cells are the increased proliferation and abnormal differentiation and maturation of these cells, which are due to regulatory changes in the emerging tumour. Normal cells use oxidative phosphorylation (OXPHOS) in the mitochondrion as a major source of energy during division. During OXPHOS, there are 36 ATP molecules produced from one molecule of glucose, in contrast to glycolysis which provides an ATP supply of only two molecules. Although aerobic glucose metabolism is more efficient, metabolism based on intensive glycolysis provides intermediate metabolites necessary for the synthesis of nucleic acids, proteins and lipids, which are in constant high demand due to the intense cell division in cancer. This is the main reason why the cancer cell does not "give up" on glycolysis despite the high demand for energy in the form of ATP. One of the evolving trends in the development of anti-cancer therapies is to exploit differences in the metabolism of normal cells and cancer cells. Currently constructed therapies, based on cell metabolism, focus on the attempt to reprogram the metabolic pathways of the cell in such a manner that it becomes possible to stop unrestrained proliferation.

Gene signatures predict biochemical recurrence-free survival in primary prostate cancer patients after radical therapy

Background

This study evaluated the predictive value of gene signatures for biochemical recurrence (BCR) in primary prostate cancer (PCa) patients.

Methods

Clinical features and gene expression profiles of PCa patients were attained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets, which were further classified into a training set (n = 419), a validation set (n = 403). The least absolute shrinkage and selection operator Cox (LASSO‐Cox) method was used to select discriminative gene signatures in training set for biochemical recurrence‐free survival (BCRFS). Selected gene signatures established a risk score system. Univariate and multivariate analyses of prognostic factors about BCRFS were performed using the Cox proportional hazards regression models. A nomogram based on multivariate analysis was plotted to facilitate clinical application. Kyoto Encyclopedia of Gene and Genomes (KEGG) and Gene Ontology (GO) analyses were then executed for differentially expressed genes (DEGs).

Results

Notably, the risk score could significantly identify BCRFS by time‐dependent receiver operating characteristic (t‐ROC) curves in the training set (3‐year area under the curve (AUC) = 0.820, 5‐year AUC = 0.809) and the validation set (3‐year AUC = 0.723, 5‐year AUC = 0.733).

Conclusions

Clinically, the nomogram model, which incorporates Gleason score and the risk score, could effectively predict BCRFS and potentially be utilized as a useful tool for the screening of BCRFS in PCa.

Integrative molecular characterization of Chinese prostate cancer specimens

Prostate cancer (PCa) exhibits epidemiological and molecular heterogeneity. Despite extensive studies of its phenotypic and genetic properties in Western populations, its molecular basis is not clear in Chinese patients. To determine critical molecular characteristics and explore correlations between genomic markers and clinical parameters in Chinese populations, we applied an integrative genetic/transcriptomic assay that combines targeted next-generation sequencing and quantitative real-time PCR (qRT-PCR) on samples from 46 Chinese patients with PCa. Lysine (K)-specific methyltransferase 2D (KMT2D), zinc finger homeobox 3 (ZFHX3), A-kinase anchoring protein 9 (AKAP9), and GLI family zinc finger 1 (GLI1) were frequently mutated in our cohort. Moreover, a clinicopathological analysis showed that RB transcriptional corepressor 1 (RB1) deletion was common in patients with a high risk of disease progression. Remarkably, four genomic events, MYC proto-oncogene (MYC) amplification, RB1 deletion, APC regulator of WNT signaling pathway (APC) mutation or deletion, and cyclin-dependent kinase 12 (CDK12) mutation, were correlated with poor disease-free survival. In addition, a close link between KMT2D expression and the androgen receptor (AR) signaling pathway was observed both in our cohort and in The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) data. In summary, our results demonstrate the feasibility and benefits of integrative molecular characterization of PCa samples in disease pathology research and personalized medicine.

USP16 regulates castration-resistant prostate cancer cell proliferation by deubiquitinating and stablizing c-Myc

Background

c-Myc, a well-established oncogene, plays an important role in the initiation and progression of various cancers, including prostate cancer. However, its mechanism in cancer cell remains largely unknown and whether there exist a deubiquitinase targeting c-Myc also remains elusive.

Methods

Bioinformatic analysis and shRNA screening methods were used to identify potential deubiquitinases that correlate with c-Myc gene signature. Cell proliferation and viability were measured by Cell-Counting-Kit 8 and colony formation assays. A mouse xenograft model of PC3 cells was established to confirm the function of USP16 in vivo. The interaction between USP16 and c-Myc protein was assessed by co-immunoprecipitation and protein co-localization assays. Immunohistochemistry staining was performed to detect the expression of USP16, Ki67, and c-Myc in xenograft tissues and clinical tumour tissues. Furthermore, the correlation between USP16 and c-Myc was confirmed by RNA sequencing.

Results

Functional analyses identified USP16, known as a deubiquitinase, was strongly correlated with the c-Myc gene signature. Depletion of USP16 was shown to significantly suppress the growth of PCa cells both in vitro and in vivo. Co-immunoprecipitation and ubiquitination assays confirmed that USP16 served as a novel deubiquitinase of c-Myc and overexpression of c-Myc significantly rescued the effects of USP16 disruption. Immunohistochemistry staining and RNA-seq tactics were further used to confirm the positive correlation between USP16 and c-Myc expression. Expression of USP16 in human PCa tissues was higher than that seen in normal prostate tissues and its high expression was found associated with poor prognosis.

Conclusions

USP16 serves as a novel deubiquitinase of c-Myc. Downregulation of USP16 markedly suppressed PCa cell growth both in vitro and in vivo. USP16 regulates PCa cell proliferation by deubiquitinating and stabilizing c-Myc, making it a potential therapeutic candidate for the treatment of PCa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01843-8.

Cellular and Molecular Progression of Prostate Cancer: Models for Basic and Preclinical Research

Simple Summary

The molecular progression of prostate cancer is complex and elusive. Biological research relies heavily on in vitro and in vivo models that can be used to examine gene functions and responses to the external agents in laboratory and preclinical settings. Over the years, several models have been developed and found to be very helpful in understanding the biology of prostate cancer. Here we describe these models in the context of available information on the cellular and molecular progression of prostate cancer to suggest their potential utility in basic and preclinical prostate cancer research. The information discussed herein should serve as a hands-on resource for scholars engaged in prostate cancer research or to those who are making a transition to explore the complex biology of prostate cancer.

Abstract

We have witnessed noteworthy progress in our understanding of prostate cancer over the past decades. This basic knowledge has been translated into efficient diagnostic and treatment approaches leading to the improvement in patient survival. However, the molecular pathogenesis of prostate cancer appears to be complex, and histological findings often do not provide an accurate assessment of disease aggressiveness and future course. Moreover, we also witness tremendous racial disparity in prostate cancer incidence and clinical outcomes necessitating a deeper understanding of molecular and mechanistic bases of prostate cancer. Biological research heavily relies on model systems that can be easily manipulated and tested under a controlled experimental environment. Over the years, several cancer cell lines have been developed representing diverse molecular subtypes of prostate cancer. In addition, several animal models have been developed to demonstrate the etiological molecular basis of the prostate cancer. In recent years, patient-derived xenograft and 3-D culture models have also been created and utilized in preclinical research. This review is an attempt to succinctly discuss existing information on the cellular and molecular progression of prostate cancer. We also discuss available model systems and their tested and potential utility in basic and preclinical prostate cancer research.

Genomic and Functional Regulation of TRIB1 Contributes to Prostate Cancer Pathogenesis

Prostate cancer is the most frequent malignancy in European men and the second worldwide. One of the major oncogenic events in this disease includes amplification of the transcription factor cMYC. Amplification of this oncogene in chromosome 8q24 occurs concomitantly with the copy number increase in a subset of neighboring genes and regulatory elements, but their contribution to disease pathogenesis is poorly understood. Here we show that TRIB1 is among the most robustly upregulated coding genes within the 8q24 amplicon in prostate cancer. Moreover, we demonstrate that TRIB1 amplification and overexpression are frequent in this tumor type. Importantly, we find that, parallel to its amplification, TRIB1 transcription is controlled by cMYC. Mouse modeling and functional analysis revealed that aberrant TRIB1 expression is causal to prostate cancer pathogenesis. In sum, we provide unprecedented evidence for the regulation and function of TRIB1 in prostate cancer.

miR-449c-5p availability is antagonized by circ-NOTCH1 for MYC-induced NOTCH1 upregulation as well as tumor metastasis and stemness in gastric cancer

Gastric cancer (GC), identified as the most common gastrointestinal malignancy, is one of the primary causes of cancer-related mortality in the world. Although surgery and chemotherapy for GC treatment have been improved, the 5-year overall survival rate is still unsatisfactory. Circ-NOTCH1 is a novel circular RNA derived from its host gene NOTCH1, and has not been studied in any cancers. Here we explored the potential role and mediatory mechanism of circ-NOTCH1 in GC. In this study, circ-NOTCH1 exhibited increased expression in GC tissues and cells. Suppression of circ-NOTCH1 inhibited cell migration, invasion, tumor spheroids number, and side population ratio. Circ-NOTCH1 also promoted GC growth and metastasis in vivo. Additionally, it was found that circ-NOTCH1 could bind to miR-449c-5p. Circ-NOTCH1 promoted metastasis and stemness in GC through sponging miR-449c-5p. Subsequently, MYC was identified as a downstream gene of miR-449c-5p. MYC could bind to the promoter of NOTCH1 to regulate GC progression. Furthermore, rescue assays demonstrated that NOTCH1 knockdown reversed the effects of overexpression of MYC in metastasis and stemness in AGS cells/sh-circNOTCH1. Above findings explained that circ-NOTCH1 promoted metastasis and stemness in GC by targeting miR-449c-5p/MYC/NOTCH1 axis, suggesting the possibility of circ-NOTCH1 as a therapeutic marker for GC.

The Genomic and Molecular Pathology of Prostate Cancer: Clinical Implications for Diagnosis, Prognosis, and Therapy

Prostate cancer (PCa) is the most common noncutaneous malignancy affecting American men and the second most common cause of cancer death. The traditional risk classification schemes for PCa are limited due to the vast clinical and molecular heterogeneity of the disease. Fortunately, recent advancements in sequencing technologies have provided us with valuable insight into the genomics of PCa. To date, a wide array of recurrent genomic alterations in PCa have been identified. Incorporating these distinct molecular subtypes of PCa into prediction models provides opportunities for improved risk stratification and ultimately better patient outcomes. In this review, we summarize the key molecular subtypes of PCa and focus on those genomic alterations that have clinical implications for diagnosis, prognosis, and therapeutic response.

Assessment of biochemical recurrence of prostate cancer (Review)

The assessment of the risk of biochemical recurrence (BCR) is critical in the management of males with prostate cancer (PC). Over the past decades, a comprehensive effort has been focusing on improving risk stratification; a variety of models have been constructed using PC-associated pathological features and molecular alterations occurring at the genome, protein and RNA level. Alterations in RNA expression (lncRNA, miRNA and mRNA) constitute the largest proportion of the biomarkers of BCR. In this article, we systemically review RNA-based BCR biomarkers reported in PubMed according to the PRISMA guidelines. Individual miRNAs, mRNAs, lncRNAs and multi-gene panels, including the commercially available signatures, Oncotype DX and Prolaris, will be discussed; details related to cohort size, hazard ratio and 95% confidence intervals will be provided. Mechanistically, these individual biomarkers affect multiple pathways critical to tumorigenesis and progression, including epithelial-mesenchymal transition (EMT), phosphatase and tensin homolog (PTEN), Wnt, growth factor receptor, cell proliferation, immune checkpoints and others. This variety in the mechanisms involved not only validates their associations with BCR, but also highlights the need for the coverage of multiple pathways in order to effectively stratify the risk of BCR. Updates of novel biomarkers and their mechanistic insights are considered, which suggests new avenues to pursue in the prediction of BCR. Additionally, the management of patients with BCR and the potential utility of the stratification of the risk of BCR in salvage treatment decision making for these patients are briefly covered. Limitations will also be discussed.

High-fat diet fuels prostate cancer progression by rewiring the metabolome and amplifying the MYC program

Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet.

Parallel-Reaction-Monitoring-Based Proteome-Wide Profiling of Differential Kinase Protein Expression during Prostate Cancer Metastasis in Vitro

Prostate cancer is the most common type of cancer in men, and kinases are heavily pursued as drug targets for anticancer therapy. In this study, we applied our recently reported parallel-reaction-monitoring (PRM)-based targeted proteomic method to examine the reprogramming of the human kinome associated with bone metastasis of prostate cancer in vitro. The method displayed superior sensitivity over the shotgun-proteomic approach, and it facilitated the quantification of the relative expression of 276 kinase proteins in a pair of bone metastatic prostate cancer cells. Among the differentially expressed kinases, mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4) stimulates the migration and invasion of cultured prostate cancer cells, partially by modulating the activity of secreted matrix metalloproteinases 9 (MMP-9). We also found that the upregulation of MAP4K4 in metastatic prostate cancer cells is driven by the MYC proto-oncogene. Cumulatively, we identify MAP4K4 as a potential promoter for prostate cancer metastasis in vitro.

Aneuploidy drives lethal progression in prostate cancer

Aneuploidy, defined as chromosome gains and losses, is a hallmark of cancer. However, compared with other tumor types, extensive aneuploidy is relatively rare in prostate cancer. Thus, whether numerical chromosome aberrations dictate disease progression in prostate cancer patients is not known. Here, we report the development of a method based on whole-transcriptome profiling that allowed us to identify chromosome-arm gains and losses in 333 primary prostate tumors. In two independent cohorts (n = 404) followed prospectively for metastases and prostate cancer-specific death for a median of 15 years, increasing extent of tumor aneuploidy as predicted from the tumor transcriptome was strongly associated with higher risk of lethal disease. The 23% of patients whose tumors had five or more predicted chromosome-arm alterations had 5.3 times higher odds of lethal cancer (95% confidence interval, 2.2 to 13.1) than those with the same Gleason score and no predicted aneuploidy. Aneuploidy was associated with lethality even among men with high-risk Gleason score 8-to-10 tumors. These results point to a key role of aneuploidy in driving aggressive disease in primary prostate cancer.

Metabolomic profiling for the identification of novel diagnostic markers and therapeutic targets in prostate cancer: an update

INTRODUCTION

An altered metabolic regulation is involved in the development and progression of different cancer types. As well as this, many genes associated with tumors are shown to have an important role in control of the metabolism. The incidence of prostate cancer (PCa) is increased in men with metabolic disorders. In particular, obesity is an established risk factor for PCa. An increased body mass index correlates with aggressive disease, and a higher risk of biochemical recurrence and prostate cancer-specific mortality. Increased lipogenesis is also one of the most significant events in PCa metabolism reprogramming. Areas covered: In this article, we provide an updated review of the current understanding of the PCa metabolome and evaluate the possibility of unveiling novel therapeutic targets. Expert opinion: Obesity is an established risk factor for PCa, and an increased BMI correlates with aggressive disease, and a higher risk of biochemical recurrence and prostate cancer-specific mortality. PCa metabolome is characterized by the accumulation of metabolic intermediates and an increased expression of genes in the tricarboxylic acid cycle, the induction of de novo lipogenesis and cholesterogenesis. PCa cells can induce different alterations in their microenvironment by modulating the crosstalk between cancer and stromal cells.

Loss of FOXP3 and TSC1 Accelerates Prostate Cancer Progression through Synergistic Transcriptional and Posttranslational Regulation of c-MYC

Although c-MYC and mTOR are frequently activated proteins in prostate cancer, any interaction between the two is largely untested. Here, we characterize the functional cross-talk between FOXP3-c-MYC and TSC1-mTOR signaling during tumor progression. Deletion of Tsc1 in mouse embryonic fibroblasts (MEF) decreased phosphorylation of c-MYC at threonine 58 (pT58) and increased phosphorylation at serine 62 (pS62), an observation validated in prostate cancer cells. Conversely, inhibition of mTOR increased pT58 but decreased pS62. Loss of both FOXP3 and TSC1 in prostate cancer cells synergistically enhanced c-MYC expression via regulation of c-Myc transcription and protein phosphorylation. This crosstalk between FOXP3 and TSC1 appeared to be mediated by both the mTOR-4EBP1-c-MYC and FOXP3-c-MYC pathways. In mice, Tsc1 and Foxp3 double deletions in the prostate led to prostate carcinomas at an early age; this did not occur in these mice with an added c-Myc deletion. In addition, we observed synergistic antitumor effects of cotreating mice with inhibitors of mTOR and c-MYC in prostate cancer cells and in Foxp3 and Tsc1 double-mutant mice. In human prostate cancer, loss of nuclear FOXP3 is often accompanied by low expression of TSC1. Because loss of FOXP3 transcriptionally induces c-Myc expression and loss of TSC1 activates mTOR signaling, these data suggest cross-talk between FOXP3-c-MYC and TSC1-mTOR signaling that converges on c-MYC to regulate tumor progression. Coadministration of c-MYC and mTOR inhibitors may overcome the resistance to mTOR inhibition commonly observed in prostate cancer cells. SIGNIFICANCE: These results establish the principle of a synergistic action of TSC1 and FOXP3 during prostate cancer progression and provide new therapeutic targets for patients who have prostate cancer with two signaling defects.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/7/1413/F1.large.jpg.

Targeting the turnover of oncoproteins as a new avenue for therapeutics development in castration-resistant prostate cancer

The current therapeutic armamentarium for castration-resistant prostate cancer (CRPC) includes second-generation agents such as the Androgen Receptor (AR) inhibitor enzalutamide and the androgen synthesis inhibitor abiraterone acetate, immunotherapies like sipuleucel-T, chemotherapies including docetaxel and cabazitaxel and the radiopharmaceutical radium 223 dichloride. However, relapse of CRPC resistant to these therapeutic modalities occur rapidly. The mechanisms of resistance to these treatments are complex, including specific mutations or alternative splicing of oncogenic proteins. An alternative approach to treating CRPC may be to target the turnover of these molecular drivers of CRPC. In this review, the mechanisms by which protein stability of several oncoproteins such as AR, ERG, GR, CYP17A1 and MYC, will be discussed, as well as how these findings could be translated into novel therapeutic agents.