Identification of key pathways and genes with aberrant methylation in prostate cancer using bioinformatics analysis

Early detection and diagnosis of cancer with interpretable machine learning to uncover cancer-specific DNA methylation patterns

Cancer, a collection of more than two hundred different diseases, remains a leading cause of morbidity and mortality worldwide. Usually detected at the advanced stages of disease, metastatic cancer accounts for 90% of cancer-associated deaths. Therefore, the early detection of cancer, combined with current therapies, would have a significant impact on survival and treatment of various cancer types. Epigenetic changes such as DNA methylation are some of the early events underlying carcinogenesis. Here, we report on an interpretable machine learning model that can classify 13 cancer types as well as non-cancer tissue samples using only DNA methylome data, with 98.2% accuracy. We utilize the features identified by this model to develop EMethylNET, a robust model consisting of an XGBoost model that provides information to a deep neural network that can generalize to independent data sets. We also demonstrate that the methylation-associated genomic loci detected by the classifier are associated with genes, pathways and networks involved in cancer, providing insights into the epigenomic regulation of carcinogenesis.

Epigenetic regulation of androgen dependent and independent prostate cancer

Prostate cancer is one of the most common malignancies among men worldwide. Besides genetic alterations, epigenetic modulations including DNA methylation, histone modifications and miRNA mediated alteration of gene expression are the key driving forces for the prostate tumor development and cancer progression. Aberrant expression and/or the activity of the epigenetic modifiers/enzymes, results in aberrant expression of genes involved in DNA repair, cell cycle regulation, cell adhesion, apoptosis, autophagy, tumor suppression and hormone response and thereby disease progression. Altered epigenome is associated with prostate cancer recurrence, progression, aggressiveness and transition from androgen-dependent to androgen-independent phenotype. These epigenetic modifications are reversible and various compounds/drugs targeting the epigenetic enzymes have been developed that are effective in cancer treatment. This chapter focuses on the epigenetic alterations in prostate cancer initiation and progression, listing different epigenetic biomarkers for diagnosis and prognosis of the disease and their potential as therapeutic targets. This chapter also summarizes different epigenetic drugs approved for prostate cancer therapy and the drugs available for clinical trials.

Integrative analysis of transcriptomic and metabolomic profiles reveals enhanced arginine metabolism in androgen-independent prostate cancer cells

BACKGROUND

Prostate cancer is a common solid tumor that affects a significant number of men worldwide. Conventional androgen deprivation therapy (ADT) increases the risk of developing castration-resistant prostate cancer (CRPC). Effective clinical management of patients with CRPC is challenging due to the limited understanding.

METHODS

In this study, transcriptomic and metabolomic profiles of androgen-dependent prostate cancer cell line LNCaP and the androgen-independent cells developed from LNCaP cells (LNCaP-ADR) were investigated using RNA-sequencing and LC-MS/MS, respectively. The differentially expressed genes and metabolites were analyzed, and integrative analysis of transcriptomic and metabolomic data was further conducted to obtain a comprehensive understanding of the metabolic characteristics in LNCaP-ADR cells. Quantitative real-time PCR (QPCR) was employed to ascertain the mRNA expression levels of the selected differentially expressed genes.

RESULTS

The arginine and proline metabolism pathway was identified as a commonly altered pathway at both the transcriptional and metabolic levels. In the LNCaP-ADR cells, significant upregulation was observed for metabolites including 5-Aminopentanoic acid, L-Arginine, L-Glutamic acid, N-Acetyl-L-alanine, and Pyrrole-2-carboxylic acid at the metabolic level. At the transcriptional level, MAOA, ALDH3A2, ALDH2, ARG1, CKMT2, and CNDP1 were found to be significantly upregulated in the LNCaP-ADR cells. Gene set enrichment analysis (GSEA) identified various enriched gene sets in the LNCaP-ADR cells, encompassing inflammatory response, 9plus2 motile cilium, motile cilium, ciliary plasm, cilium or flagellum-dependent cell motility, cilium movement, cilium, response to endoplasmic reticulum stress, PTEN DN.V1 DN, SRC UP.V1 UP, IL15 UP.V1 DN, RB DN.V1 DN, AKT UP MTOR DN.V1 UP, VEGF A UP.V1 UP, and KRAS.LUNG.BREAST UP.V1 UP.

CONCLUSIONS

These findings highlight the substantial association between the arginine and proline metabolism pathway and CRPC, emphasizing the need to prioritize strategies that target dysregulated metabolites and differentially expressed genes as essential interventions in the clinical management of CRPC.

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.

Prostate Cancer: Genetics, Epigenetics and the Need for Immunological Biomarkers

Epidemiological data highlight prostate cancer as a significant global health issue, with high incidence and substantial impact on patients' quality of life. The prevalence of this disease is associated with various factors, including age, heredity, and race. Recent research in prostate cancer genetics has identified several genetic variants that may be associated with an increased risk of developing the disease. However, despite the significance of these findings, genetic markers for prostate cancer are not currently utilized in clinical practice as reliable indicators of the disease. In addition to genetics, epigenetic alterations also play a crucial role in prostate cancer development. Aberrant DNA methylation, changes in chromatin structure, and microRNA (miRNA) expression are major epigenetic events that influence oncogenesis. Existing markers for prostate cancer, such as prostate-specific antigen (PSA), have limitations in terms of sensitivity and specificity. The cost of testing, follow-up procedures, and treatment for false-positive results and overdiagnosis contributes to the overall healthcare expenditure. Improving the effectiveness of prostate cancer diagnosis and prognosis requires either narrowing the risk group by identifying new genetic factors or enhancing the sensitivity and specificity of existing markers. Immunological biomarkers (both circulating and intra-tumoral), including markers of immune response and immune dysfunction, represent a potentially useful area of research for enhancing the diagnosis and prognosis of prostate cancer. Our review emphasizes the need for developing novel immunological biomarkers to improve the diagnosis, prognosis, and management of prostate cancer. We highlight the most recent achievements in the identification of biomarkers provided by circulating monocytes and tumor-associated macrophages (TAMs). We highlight that monocyte-derived and TAM-derived biomarkers can enable to establish the missing links between genetic predisposition, hormonal metabolism and immune responses in prostate cancer.

In-silico identification of frequently mutated genes and their co-enriched metabolic pathways associated with Prostate cancer progression

Prostate cancer (PCa) has emerged as a significant health burden in men globally. Several genetic anomalies such as mutations and also epigenetic aberrations are responsible for the heterogeneity of this disease. This study identified the 20 most frequently mutated genes reported in PCa based on literature and database survey. Further gene ontology and functional enrichment analysis were conducted to determine their co-modulated molecular and biological pathways. A protein-protein interaction network was used for the identification of hub genes. These hub genes identified were then subjected to survival analysis. The prognostic values of these identified genes were investigated using GEPIA and HPA. Gene Ontology analysis of the identified genes depicted that these genes significantly contributed to the cell cycle, apoptosis, angiogenesis and TGF-β receptor signalling. Further, the research showed that high expressions of identified mutated genes led to a reduction in the long-term survival of PCa patients, which was supported by immunohistochemical and mRNA expression level data. Our results suggest that identified panel of mutated genes viz., CTNNB1, TP53, ATM, AR and KMT2D play crucial roles in the onset and progression of PCa, thereby providing candidate diagnostic markers for PCa for individualised treatment in the future.

Quantitative SWATH-Based Proteomic Profiling for Identification of Mechanism-Driven Diagnostic Biomarkers Conferring in the Progression of Metastatic Prostate Cancer

Prostate cancer (PCa), the most frequently diagnosed malignancy in men is associated with significant mortality and morbidity. Therefore, demand exists for the identification of potential biomarkers for patient stratification according to prognostic risks and the mechanisms involved in cancer development and progression to avoid over/under treatment of patients and prevent relapse. Quantitative proteomic mass spectrometry profiling and gene enrichment analysis of TGF-β induced-EMT in human Prostate androgen-dependent (LNCaP) and androgen-independent (PC-3) adenocarcinoma cell lines was performed to investigate proteomics involved in Prostate carcinogenesis and their effect onto the survival of PCa patients. Amongst 1,795 proteins, which were analyzed, 474 proteins were significantly deregulated. These proteins contributed to apoptosis, gluconeogenesis, transcriptional regulation, RNA splicing, cell cycle, and MAPK cascade and hence indicating the crucial roles of these proteins in PCa initiation and progression. We have identified a panel of six proteins viz., GOT1, HNRNPA2B1, MAPK1, PAK2, UBE2N, and YWHAB, which contribute to cancer development, and the transition of PCa from androgen dependent to independent stages. The prognostic values of identified proteins were evaluated using UALCAN, GEPIA, and HPA datasets. The results demonstrate the utility of SWATH-LC-MS/MS for understanding the proteomics involved in EMT transition of PCa and identification of clinically relevant proteomic biomarkers.

MTSS1 hypermethylation is associated with prostate cancer progression

This study was conducted to evaluate the influence of DNA methylation of metastasis suppressor 1 (MTSS1) on prostate cancer (PCa) progression. Forty-nine paired PCa tissue samples and normal tissue samples from The Cancer Genome Atlas were analyzed. Methylome analysis, CpG island arrays and Hierarchical clustering were used to analyze methylation profiles of PCa tissues. MTSS1 methylation level was detected by methylation-specific PCR. Relative messenger RNA and the expression level of MTSS1 protein were identified by quantitative real-time PCR (qRT-PCR) and western blot analysis. The migration, invasion, proliferation, and cell cycle were detected separately by wound-healing assay, transwell chamber assay, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay and flow cytometry. The roles of MTSS1 in PCa progression were demonstrated in vivo by tumor formation assays in nude mice. MTSS1 expression was decreased in PCa tissues in comparison with paired adjacent normal prostate tissues. Compared to the methylation of MTSS1 in normal prostate tissues based on the MethHC website, the MTSS1 in PCa tissues was hypermethylated. The expression of MTSS1 detected by qRT-PCR and western blot analysis was found to be downregulated in PCa cells and tissues. The reduced expression of MTSS1 by small interfering RNA-MTSS1 was recovered by 5-aza-2'-deoxycytidine treatment. Besides, MTSS1 demethylation inhibited migration, invasion, and proliferation of PCa cells, and induced cell cycle to be arrested at G0/G1 phase. Furthermore, it was shown by tumor xenograft assay that MTSS1 inhibited the growth of tumor in vivo. Hypermethylated MTSS1 promoted PCa cells migration, invasion, and proliferation, and suppressed cell cycle arrest at the G0/G1 phase.

The Relevance of Gender in Tumor-Influencing Epigenetic Traits

Tumorigenesis as well as the molecular orchestration of cancer progression are very complex mechanisms that comprise numerous elements of influence and regulation. Today, many of the major concepts are well described and a basic understanding of a tumor's fine-tuning is given. Throughout the last decade epigenetics has been featured in cancer research and it is now clear that the underlying mechanisms, especially DNA and histone modifications, are important regulators of carcinogenesis and tumor progression. Another key regulator, which is well known but has been neglected in scientific approaches as well as molecular diagnostics and, consequently, treatment conceptualization for a long time, is the subtle influence patient gender has on molecular processes. Naturally, this is greatly based on hormonal differences, but from an epigenetic point of view, the diverse susceptibility to stress and environmental influences is of prime interest. In this review we present the current view on which and how epigenetic modifications, emphasizing DNA methylation, regulate various tumor diseases. It is our aim to elucidate gender and epigenetics and their interconnectedness, which will contribute to understanding of the prospect molecular orchestration of cancer in individual tumors.

The future of prostate cancer research: bringing data together, looking back and forward

The use of digital data in large data sets will be of pivotal importance to unravel the biological basis of prostate cancer, and to improve on prevention and treatment. For the screening of asymptomatic tumors, their identification, and their treatment with better and targeted therapies, the integration of information from imaging, genomics, and biomarkers is needed. To bring these (un)structured data together, block chain technology is required, while knowledgeable analysts should be available. Therefore, it is of utmost importance to ‘team up’ and provide a common strategy for innovation. Its implementation needs the involvement of all stakeholders (patients, industries, professionals, scientists, governments). This article provides thoughts on how initial steps in urology have been taken, and how to proceed.