Omics Derived Biomarkers and Novel Drug Targets for Improved Intervention in Advanced Prostate Cancer

The prognostic value of Dickkopf-3 (Dkk3), TGFB1 and ECM-1 in prostate cancer

Prostate cancer (PCa) is considered one of the most common cancers worldwide. Despite advances in patient diagnosis, management, and risk stratification, 10%-20% of patients progress to castration-resistant disease. Our previous report highlighted a protective role of Dickkopf-3 (DKK3) in PCa stroma. This role was proposed to be mediated through opposing extracellular matrix protein 1 (ECM-1) and TGF-β signalling activity. However, a detailed analysis of the prognostic value of DKK3, ECM-1 and members of the TGF-β signalling pathway in PCa was not thoroughly investigated. In this study, we explored the prognostic value of DKK3, ECM-1 and TGFB1 using a bioinformatical approach through analysis of large publicly available datasets from The Cancer Genome Atlas Program (TGCA) and Pan-Cancer Atlas databases. Our results showed a significant gradual loss of DKK3 expression with PCa progression (p < 0.0001) associated with increased DNA methylation in its promoter region (p < 1.63E-12). In contrast, patients with metastatic lesions showed significantly higher levels of TGFB1 expression compared to primary tumours (p < 0.00001). Our results also showed a marginal association between more advanced tumour stage presented as positive lymph node involvement and low DKK3 mRNA expression (p = 0.082). However, while ECM1 showed no association with tumour stage (p = 0.773), high TGFB1 expression showed a significant association with more advanced stage presented as advanced T3 stage compared to patients with low TGFB1 mRNA expression (p < 0.001). Interestingly, while ECM1 showed no significant association with patient outcome, patients with high DKK3 mRNA expression showed a significant association with favourable outcomes presented as prolonged disease-specific (p = 0.0266), progression-free survival (p = 0.047) and disease-free (p = 0.05). In contrast, high TGFB1 mRNA expression showed a significant association with poor patient outcomes presented as shortened progression-free (p = 0.00032) and disease-free survival (p = 0.0433). Moreover, DKK3, TGFB1 and ECM1 have acted as immune-associated genes in the PCa tumour microenvironment. In conclusion, our findings showed a distinct prognostic value for this three-gene signature in PCa. While both DKK3 and TGFB1 showed a potential role as a clinical marker for PCa stratification, ECM1 showed no significant association with the majority of clinicopathological parameters, which reduce its clinical significance as a reliable prognostic marker.

Prostate cancer patient stratification by molecular signatures in the Veterans Precision Oncology Data Commons

Veterans are at an increased risk for prostate cancer, a disease with extraordinary clinical and molecular heterogeneity, compared with the general population. However, little is known about the underlying molecular heterogeneity within the veteran population and its impact on patient management and treatment. Using clinical and targeted tumor sequencing data from the National Veterans Affairs health system, we conducted a retrospective cohort study on 45 patients with advanced prostate cancer in the Veterans Precision Oncology Data Commons (VPODC), most of whom were metastatic castration-resistant. We characterized the mutational burden in this cohort and conducted unsupervised clustering analysis to stratify patients by molecular alterations. Veterans with prostate cancer exhibited a mutational landscape broadly similar to prior studies, including KMT2A and NOTCH1 mutations associated with neuroendocrine prostate cancer phenotype, previously reported to be enriched in veterans. We also identified several potential novel mutations in PTEN, MSH6, VHL, SMO, and ABL1 Hierarchical clustering analysis revealed two subgroups containing therapeutically targetable molecular features with novel mutational signatures distinct from those reported in the Catalogue of Somatic Mutations in Cancer database. The clustering approach presented in this study can potentially be used to clinically stratify patients based on their distinct mutational profiles and identify actionable somatic mutations for precision oncology.

m1A Regulatory gene signatures are associated with certain immune cell compositions of the tumor microenvironment and predict survival in kidney renal clear cell carcinoma

Adenosine N1 methylation (m1A) of RNA, a type of post-transcriptional modification, has been shown to play a significant role in the progression of cancer. The objective of the current research was to analyze the genetic alteration and prognostic significance of m1A regulators in kidney renal clear cell carcinoma (KIRC). Genomic and clinicopathological characteristics were obtained from 558 KIRC patients in the Cancer Genome Atlas (TCGA) and Gene Omnibus Expression (GEO) databases. Alterations in the gene expression of ten m1A-regulators were analyzed and survival analysis was performed using the Cox regression method. We also identified three clusters of patients based on their distinct m1A alteration patterns, using integrated analysis of the ten m1A-related regulators, which were significantly related to overall survival (OS), disease-free survival (DFS) and tumor microenvironment (TME) immune cell infiltration cells in KIRC. Our findings showed that m1A alteration patterns have critical roles in determining TME complexity and its immune cell composition. Furthermore, different m1A expression patterns were significantly associated with DFS and OS rates in KIRC patients. In conclusion, the identified m1A RNA modification patterns offer a potentially effective way to classify KIRC patients based on their TME immune cell infiltration, enabling the development of more personalized and successful treatment strategies for these patients.

Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate Cancer

Precision oncology is an absolute need today due to the emergence of treatment resistance and heterogeneity among cancerous profiles. Target-propelled cancer therapy is one of the treasures of precision oncology which has come together with substantial medical accomplishment. Prostate cancer is one of the most common cancers in males, with tremendous biological heterogeneity in molecular and clinical behavior. The spectrum of molecular abnormalities and varying clinical patterns in prostate cancer suggest substantial heterogeneity among different profiles. To identify novel therapeutic targets and precise biomarkers implicated with prostate cancer, we performed a state-of-the-art bioinformatics study, beginning with analyzing high-throughput genomic datasets from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) suggests a set of five dysregulated hub genes (MAF, STAT6, SOX2, FOXO1, and WNT3A) that played crucial roles in biological pathways associated with prostate cancer progression. We found overexpressed STAT6 and SOX2 and proposed them as candidate biomarkers and potential targets in prostate cancer. Furthermore, the alteration frequencies in STAT6 and SOX2 and their impact on the patients' survival were explored through the cBioPortal platform. The Kaplan-Meier survival analysis suggested that the alterations in the candidate genes were linked to the decreased overall survival of the patients. Altogether, the results signify that STAT6 and SOX2 and their genomic alterations can be explored in therapeutic interventions of prostate cancer for precision oncology, utilizing early diagnosis and target-propelled therapy.

Plasma Metabolomics for Discovery of Early Metabolic Markers of Prostate Cancer Based on Ultra-High-Performance Liquid Chromatography-High Resolution Mass Spectrometry

BACKGROUND

The prevention and early screening of PCa is highly dependent on the identification of new biomarkers. In this study, we investigated whether plasma metabolic profiles from healthy males provide novel early biomarkers associated with future risk of PCa.

METHODS

Using the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, we identified plasma samples collected from 146 PCa cases up to 13 years prior to diagnosis and 272 matched controls. Plasma metabolic profiles were characterized using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS).

RESULTS

Orthogonal partial least squares discriminant analysis (OPLS-DA) discriminated PCa cases from controls, with a median area under the receiver operating characteristic curve (AU-ROC) of 0.92 using a 1000-time repeated random sub-sampling validation. Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) identified the top 10 most important metabolites (p < 0.001) discriminating PCa cases from controls. Among them, phosphate, ethyl oleate, eicosadienoic acid were higher in individuals that developed PCa than in the controls during the follow-up. In contrast, 2-hydroxyadenine, sphinganine, L-glutamic acid, serotonin, 7-keto cholesterol, tiglyl carnitine, and sphingosine were lower.

CONCLUSION

Our results support the dysregulation of amino acids and sphingolipid metabolism during the development of PCa. After validation in an independent cohort, these signatures may promote the development of new prevention and screening strategies to identify males at future risk of PCa.

The Regulating Effect of Autophagy-Related MiRNAs in Kidney, Bladder, and Prostate Cancer

Autophagy is a treatment target for many disorders, including cancer, and its specific role is becoming increasingly well known. In tumors, researchers pay attention to microribonucleic acids (miRNAs) with regulatory effects to develop more effective therapeutic drugs for autophagy and find new therapeutic targets. Various studies have shown that autophagy-related miRNAs play an irreplaceable role in different tumors, such as miR-495, miR-30, and miR-101. These miRNAs are associated with autophagy resistance in gastric cancer, non-small cell lung cancer, and cervical cancer. In recent years, autophagy-related miRNAs have also been reported to play a role in autophagy in urinary system tumors. This article reviews the regulatory effects of autophagy-related miRNAs in kidney, bladder, and prostate cancer and provides new ideas for targeted therapy of the three major tumors of the urinary system.

Special Issue "Diagnostic Biomarkers in Prostate Cancer 2020"

The search for novel prostate cancer biomarkers is one of the major topics in recent urologic research [...].

Novel therapies are changing treatment paradigms in metastatic prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) remains a terminal diagnosis with an aggressive disease course despite currently approved therapeutics. The recent successful development of poly ADP-ribose polymerase (PARP) inhibitors for patients with mCRPC and mutations in DNA damage repair genes has added to the treatment armamentarium and improved personalized treatments for prostate cancer. Other promising therapeutic agents currently in clinical development include the radiotherapeutic 177-lutetium-prostate-specific membrane antigen (PSMA)-617 targeting PSMA-expressing prostate cancer and combinations of immunotherapy with currently effective treatment options for prostate cancer. Herein, we have highlighted the progress in systemic treatments for mCRPC and the promising agents currently in ongoing clinical trials.