Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-22T05:18:14.816Z Has data issue: false hasContentIssue false

Review of novel liquid-based biomarkers for prostate cancer: towards personalised and targeted medicine

Published online by Cambridge University Press:  06 April 2021

Ernest Osei*
Affiliation:
Department of Medical Physics, Grand River Regional Cancer Centre, Kitchener, ON, Canada Department of Physics and Astronomy, University of Waterloo, Waterloo, ON, Canada Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
Stephanie Swanson
Affiliation:
Department of Medical Physics, Grand River Regional Cancer Centre, Kitchener, ON, Canada Department of Physics and Astronomy, University of Waterloo, Waterloo, ON, Canada
Ruth Francis
Affiliation:
Department of Biology, University of Waterloo, Waterloo, ON, Canada
*
Author for correspondence: Dr Ernest Osei, Department of Medical Physics, Grand River Regional Cancer Centre, 835 King Street West, Kitchener, ON, N2G 1G3, Canada. Tel: 519 749 4300. E-mail: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Background:

Prostate cancer is the most commonly diagnosed cancer in men and it is responsible for about 10% of all cancer mortalities in both American and Canadian men. At present, serum prostate-specific antigen levels remain the most commonly used test to detect prostate cancer, and the standard and definitive diagnosis of the disease is via prostate biopsy. Conventional tissue biopsies are usually invasive, expensive, painful, time-consuming, and unsuitable for screening and need to be consistently evaluated by expert pathologists and have limited repeatability. Consequently, liquid biopsies are emerging as a favourable alternative to conventional tissue biopsies, providing a non-invasive and cost-effective approach for screening, diagnosis, treatment and monitoring of prostate cancer patients.

Materials and methods:

We searched several databases from August to December 2020 for relevant studies published in English between 2000 and 2020 and reporting on liquid-based biomarkers available in detectable quantities in patient bodily fluid samples. In this narrative review paper, we describe seven novel and promising liquid-based biomarkers that potentially account for individual patient variability as well as used in disease risk assessment, screening for early disease detection and diagnosis, identification of patients’ risk for metastatic disease and subsequent relapse, monitoring patient response to specific treatment and providing clinicians the potential to stratify patients likely to benefit from a particular treatment.

Conclusions:

The concept of precision medicine from prevention to treatment techniques that take individual patient variability into account will depend on the development of effective clinical biomarkers that interrogate key aberrant pathways potentially targetable with molecular targets or immunologic therapies. Liquid-based biomarkers with high sensitivity and specificity for prostate cancer are emerging as minimally invasive, lower risk, readily obtainable and easily repeatable technique for screening for early disease detection and diagnosis, patient stratification at diagnosis into different risk categories, identification of patients’ risk for metastatic disease and subsequent relapse, and real-time monitoring of patient response to specific treatment. Thus, effective liquid-based biomarkers will potentially shift the treatment paradigm of prostate cancer towards more personalised and targeted medicine.

Type
Literature Review
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Introduction

Prostate cancer is the most commonly diagnosed cancer in men and it is responsible for about 10% of all cancer mortalities in both American and Canadian men. In 2020, it was estimated that approximately 23,300 new prostate cancer cases will be diagnosed and more than 4,200 men will die from the disease in Canada 1,Reference Brenner, Weir and Demers2 and about 238,590 newly diagnosed cases and 29,720 mortalities in the United States. Reference Siegel, Miller and Jemal3 At present, serum prostate-specific antigen (PSA) levels remain the most commonly used test to detect prostate cancer, and the standard and definitive diagnosis of the disease is via prostate biopsy. However, several studies Reference Osei and Swanson4Reference Osei, Walters and Masella23 have reported that the serum PSA level can also be elevated in benign conditions, has limited specificity, and results in high rates of over-diagnosis and treatment of indolent prostate cancers. Furthermore, it has a low positive predictive value and results in a significant proportion of negative biopsies which often leads to repeat PSA measurements and biopsies. Reed and Parekh Reference Reed and Parekh18 reported a negative biopsy rate of approximately 60–75% in men with serum PSA levels in the 3–10 ng/mL range, Hu et al. Reference Hu, Yang and Yang19 also reported that only 25% of patients with PSA levels in the 2–4 ng/mL range have prostate cancer, and according to White et al., Reference White, Shenoy and Tutrone20 approximately 85% of men with PSA levels <4 ng/mL show non-cancerous biopsy results. Additionally, screening and diagnosis of prostate cancer has been hampered by the inability to predict who has the potential to develop fatal disease and who has indolent cancer. Consequently, several studies have focused on the identification of effective prostate cancer-specific biomarkers that can be utilised for early detection of disease, prediction of disease aggressiveness and as therapeutic targets for androgen-independent prostate cancer. Reference Bourdoumis, Papatsoris, Chrisofos, Efstathiou, Skolarikos and Deliveliotis6Reference Kremer, Klein and Mendelson21,Reference Fox, Tabone and Kandpal24Reference Khan, Jutzy and Valenzuela96 The identification of effective clinical biomarkers that potentially accounts for individual patient variability and capable of interrogating key genetic aberrant pathways likely targetable with molecular targets or immunologic therapies will likely shift the diagnoses and treatment of prostate cancer towards more personalised and targeted medicine.

Although biomarkers commonly used for diagnosis, prognostication and therapeutic monitoring can be obtained through either liquid or tissue biopsies, liquid biopsies are emerging as a favourable alternative to conventional tissue biopsies by providing a cost-effective non-invasive approach for the detection and monitoring of cancer. Conventional tissue biopsies are typically surgical biopsy, radiologically guided biopsy or endoscopic biopsy and are invasive, expensive, painful, difficult to obtain, time-consuming, not suitable for screening, required to be consistently evaluated by expert pathologists, limited in repeatability, and limited by patient comorbidity and may introduce clinical risks to patients. Reference Osei, Lumini and Gunasekara22,Reference Osei, Walters and Masella23 Liquid-based biomarkers on the other hand can be found in several patient body fluids, including blood serum and plasma, pleural fluid, saliva, exhaled breath condensate, and urine. Liquid biopsy offers a new and unique opportunity to identify potential tumour biomarkers and has a significant number of advantages such as being relatively less invasive, minimally painful, lower risk, inexpensive, readily obtainable and easily repeatable as well as has the potential for screening and real-time monitoring of patient treatment. Reference Osei, Lumini and Gunasekara22,Reference Osei, Walters and Masella23,Reference Hao and Zhang97Reference Perakis and Speicher100 In a previous study, Osei and Swanson Reference Osei and Swanson4 presented a comprehensive literature review of currently available clinical biomarkers, and more recently Osei et al. Reference Osei, Swanson, Ibrahim and Sheraz5 reported on novel and promising tissue-based biomarkers for the management of prostate cancer. The goal of this narrative review paper is to describe seven novel and promising liquid-based biomarkers that could potentially account for individual patient variabilities and capable for disease risk assessment, screening for early detection and diagnosis, identification of patients’ risk for metastatic disease and subsequent relapse, and monitoring patient response to specific treatment and could provide clinicians the potential to stratify patients likely to benefit from a particular treatment.

Materials and Methods

The following databases PubMed, PMC, NCBI, PNAS, Springer Link, Wiley Online Library, Lacent, Science Direct and Medline were searched from August to December 2020 for relevant studies published in English between 2000 and 2020 and reporting on biomarkers available in detectable quantities from bodily fluid samples and has the potential for diagnostic, predictive, prognostic and therapeutic monitoring of prostate cancer patients. The literature search used the following keywords: ‘emerging biomarkers and prostate cancer’, ‘prostate cancer biomarkers’, ‘liquid biomarkers for prostate cancer’, ‘liquid-based biomarkers’, ‘biomarkers for prostate cancer’ and novel biomarkers and prostate cancer’. The searches were not limited by study design and included conference abstracts, full research articles and reviews. Several publications on biomarkers for the management of prostate cancer were identified, and we excluded articles that report on currently available clinical biomarkers and novel tissue-based biomarkers. For the current report, we reviewed articles reporting on novel and promising liquid-based biomarkers for prostate cancer management.

Ephrin-A2

Fourteen human type 1 transmembrane protein members of the erythropoietin-producing hepatoma (Eph) family of receptors make up the largest family of receptor tyrosine kinases and are associated with eight members of a class of ligands known as Ephrins. Reference Fox, Tabone and Kandpal24Reference Salem, Gambini and Billet33 Fourteen Eph receptors are divided into the Eph-A subclass of nine members (Eph-A1 to Eph-A8, and Eph-A10) and the Eph-B subclass of five members (Eph-B1 to Eph-B4, and Eph-B6) based on amino acid sequence homology and relative binding affinities to glycosylphosphatidylinositol-linked Ephrin-A or transmembrane Ephrin-B ligands. Reference Fox, Tabone and Kandpal24Reference Astin, Batson and Kadir26,Reference Merlos-Suárez and Batlle28Reference Wang, Zheng, Peng, Zhang and Qin31 Similarly, the eight Ephrin ligands are also divided into the Ephrin-A subclass of five members (Ephrin-A1 to Ephrin-A5) and the Ephrin-B subclass of three members (Ephrin-B1 to Ephrin-B3). Reference Lisle, Mertens-Walker, Rutkowski, Herington and Stephenson25,Reference Surawska, Ma and Salgia29Reference Wang, Zheng, Peng, Zhang and Qin31 Numerous studies have reported that several Eph receptors and their Ephrin ligands regulate contact inhibition of locomotion, control cell movements by regulating the actin cytoskeleton, are activated by cell–cell contact and are involved in the development or progression of certain cancers including prostate. Reference Fox, Tabone and Kandpal24,Reference Astin, Batson and Kadir26,Reference Surawska, Ma and Salgia29,Reference Xi, Wu, Wei and Chen30,Reference Taddei, Parri and Angelucci32,Reference Salem, Gambini and Billet33 The Ephrin-A2 (EFNA2) gene is located on the short arm of chromosome 19 at position 13.3 (19p13.3) and encodes a membrane-bound protein with a glycosylphosphatidylinositol lipid anchor which is a ligand to several Eph receptors including Eph-A3 to Eph-A5 and Eph-A8. The Ephrin-A2 is implicated in several physiological processes including tissue and organ development, neovascularisation, cell adhesion and separation, as well as the progression of many diseases including oncogenesis. Reference Fox, Tabone and Kandpal24,Reference Astin, Batson and Kadir26,Reference Li, Zhao and Chen27,Reference Surawska, Ma and Salgia29,Reference Xi, Wu, Wei and Chen30 Li et al. Reference Li, Zhao and Chen27 reported that the level of circulating Ephrin-A2 in serum is significantly elevated in prostate cancer patients compared to benign prostatic hyperplasia (BPH) patients and is also up-regulated in patients with osteoporosis, which is a common complication of prostate cancer patients undergoing androgen deprivation therapy. Several studies have reported that the Ephs–Ephrins signalling plays a key role in developmental processes, including axon guidance, cancers of epithelial origin through stimulation of oncogenic transformation, tumour angiogenesis, tissue boundary formation, and promotion of increased cell survival, invasion and migration. Reference Fox, Tabone and Kandpal24Reference Xi, Wu, Wei and Chen30,Reference Taddei, Parri and Angelucci32,Reference Li, Zhu and Ma34,Reference Petty, Myshkin and Qin35 Furthermore, serum Ephrin-A2 is reported to be a potential diagnostic and prognostic biomarker for the management of targeted prostate cancer therapy. Reference Li, Zhao and Chen27,Reference Li, Wu and Chen36

Li et al. Reference Li, Zhao and Chen27 investigated whole serum Ephrin-A2 and circulating exosomal Ephrin-A2 in clinical samples from 20 healthy controls, 21 BPH patients and 50 prostate cancer patients. They also assessed any correlation between exosomal Ephrin-A2 and tumour–node–metastasis (TNM) staging and Gleason score as well as its diagnostic effectiveness for BPH and prostate cancer. They observed significantly elevated expression levels of whole serum Ephrin-A2 and exosomal Ephrin-A2 in prostate cancer patients compared to BPH patients and controls. They reported that exosomal Ephrin-A2 expression is positively correlated with TNM staging and Gleason score and has superior diagnostic efficiency over serum PSA in discriminating prostate cancer patients from BPH patents. They concluded that exosomal Ephrin-A2 has high potential as a biomarker for the detection of prostate cancer and offers a new therapeutic target for the disease. In another study, Li et al [36] evaluated the diagnostic and prognostic importance of Ephrin-A2 levels in 88 serum samples and reported mean serum circulating Ephrin-A2 levels of 522 ± 36 ng/L, 394 ± 38 ng/L and 257 ± 46 ng/L in prostate cancer patients, BPH patients and controls, respectively. Furthermore, they reported significantly higher serum circulating Ephrin-A2 levels in patients with a high Gleason score of 8–10 compared to patients with low Gleason score of 6–7. They concluded that low serum Ephrin-A2 levels are associated with the presence of BPH, while elevated levels are associated with the presence of prostate cancer, and serum Ephrin-A2 level can differentiate prostate cancer from BPH more effectively than pre-surgical serum PSA level, making it a potential diagnostic and prognostic biomarker, as well as a promising molecular therapeutic target to mitigate prostate cancer progression. Reference Li, Wu and Chen36

Glutathione S-transferase pi 1 (GSTP1)

The glutathione S-transferases (GSTs) are a family of phase 2 detoxification enzymes that catalyse the conjugation of glutathione to a broad variety of endogenous and exogenous electrophilic compounds. They are divided into two distinct super-family members, namely the membrane-bound microsomal GSTs, which play a key role in the endogenous metabolism of leukotrienes and prostaglandins, and the cytosolic GSTs which are highly polymorphic and are divided into six classes (i.e., α, κ, μ, π, σ and θ). Reference Laborde37Reference Martignano, Gurioli and Salvi42 The GST pi 1 (GSTP1) gene is located on the long arm of chromosome 11 at position 13.2 (11q13.2) and encodes the GSTP1 protein which is implicated in a large number of detoxification and metabolic reactions, as well as prevention of cell genome damage and carcinoma. Reference Laborde37Reference Mahon, Qu and Lin40,Reference Martignano, Gurioli and Salvi42 According to Schnekenburger et al. Reference Schnekenburger, Karius and Diederich38 and Mahon et al., Reference Mahon, Qu and Lin40 GSTP1 is involved in cell death regulation as well as interacts with apoptotic signalling pathways, and the epigenetic silencing of the gene is reported as the most common (>90%) genetic alteration in prostate cancer. The loss of GSTP1 expression as a consequence of gene methylation is reported to be associated with the first events to cause a preneoplastic phenotype to develop into a malignant phenotype Reference Martignano, Gurioli and Salvi42 and also increases the sensitivity to metabolic or environmental toxins as well as promotes mutations and cancer development. Reference Schnekenburger, Karius and Diederich38 Several studies have reported that the hypermethylation of GSTP1 in prostate cancer patients may lead to inactivation of GSTP1 expression, is frequently associated with tumour development, progression or poor prognosis, and is confined to prostate cancer cells as well as prostatic intraepithelial neoplasia. Reference Schnekenburger, Karius and Diederich38Reference Mahon, Qu and Lin40,Reference Martignano, Gurioli and Salvi42,Reference Bastian, Palapattu and Lin43 According to Martignano et al., Reference Martignano, Gurioli and Salvi42 approximately 70–80% of prostate cancer cases are hypermethylated whereas BPH cases are normally hypomethylated; thus, GSTP1 expression has the potential to discriminate benign from malignant transformations. Consequently, epigenetic silencing of GSTP1 could be a potential marker of the transformation from normal prostate epithelium to prostate carcinoma. Mahon et al., Reference Mahon, Qu and Lin40 reported that serum-free methylated GSTP1 (mGSTP1) in circulation is associated with tumour aggressiveness and disease burden and is more specific to prostate carcinoma since it is undetected in normal prostate tissue. Therefore, according to Schnekenburger et al., Reference Schnekenburger, Karius and Diederich38 the detection of GSTP1 methylation in all types of body fluids of prostate cancer patients represents a promising epigenetic biomarker for early prostate cancer diagnosis.

Mahon et al. Reference Mahon, Qu and Lin40 investigated the relationship between serum-free mGSTP1 and treatment outcomes in 600 patients enrolled in a phase 3 multicentre randomised clinical trial assessing the impact of concurrent use of custirsen and docetaxel for the treatment of metastatic castration-resistant prostate cancer (mCRPC). They evaluated the relationships between serum-free mGSTP1 at baseline, change in mGSTP1 after docetaxel treatment, overall survival and time to PSA progression. They observed detectable levels of mGSTP1 at baseline in over 81% of patients and reported that undetectable levels of mGSTP1 at baseline and post-treatment are significantly associated with longer overall survival and longer time to PSA progression. They concluded that serum-free mGSTP1 deoxyribonucleic acid (DNA) is an early response and prognostic marker in mCRPC patients receiving first-line docetaxel treatment and has potential usefulness in the clinic to guide treatment decisions. Bastian et al. Reference Bastian, Palapattu and Lin43 studied circulating cell-free DNA GSTP1 CpG island hypermethylation in preoperative serum from 85 clinically confirmed gland-confined prostate cancer patients treated with radical prostatectomy, 35 patients with negative biopsy and a dataset of 55 paired samples from radical prostatectomy treated patients with gland-confined disease and matched for Gleason score (i.e., 55 patients with PSA recurrence and 55 patients who were free of disease at last follow-up). They reported undetectable levels of circulating cell-free DNA with GSTP1 CpG island hypermethylation in serum of patients with negative biopsy; however, 12% of patients with localised disease and 28% with metastatic disease showed detectable levels. Furthermore, in the matched dataset, they reported GSTP1 CpG island hypermethylation positivity in 15% (8 out of 55) of patients who developed PSA recurrence and GSTP1 CpG island hypermethylation negativity in all disease-free patients, and serum DNA with GTSP1 CpG island hypermethylation positivity is a significant predictor of PSA recurrence. They concluded that GSTP1 CpG island hypermethylation is an important DNA-based prognostic serum biomarker for prostate cancer. Zhou et al. Reference Zhou, Jiao and Dou39 conducted a comprehensive systematic review and meta-analysis of 15 studies involving 1540 samples to investigate the association between GSTP1 promoter methylation and incidence of prostate cancer. They reported a high incidence of GSTP1 promoter methylation in patients with prostate cancer compared to those without the disease and observed that GSTP1 promoter methylation is highly correlated with prostate cancer incidence. They concluded that methylation of the GSTP1 promoter increases the risk of prostate cancer and is a potential biomarker for disease diagnosis.

Serum metabolites

Metabolites are small molecule intermediates or end products (e.g., amino acids, organic acids and bases, fatty acids, bile acids, lipids, and carbohydrates) of enzyme-catalysed metabolic reactions within a cell that characterises the cell’s metabolism in physiological or pathophysiological conditions and are altered in diseases such as carcinomas. Reference Trock44Reference Psychogios, Hau and Peng49 Chaleckis et al. Reference Chaleckis, Murakami, Takada, Kondoh and Yanagida48 reported that metabolites in human blood can provide evidence for individual physiological states influenced by genetic, epigenetic and lifestyle factors. Dysregulation of metabolism has been reported to play an important role in the development and progression of prostate carcinoma, and in addition, differences in serum or plasma metabolite concentrations and prostatic secretions between patients and healthy controls have also been reported. Reference Trock44Reference Kelly, Vander Heiden, Giovannucci and Mucci47,Reference Giskeødegård, Hansen and Bertilsson50Reference Huang, Weinstein and Moore53 According to Lima et al., Reference Lima, de Lourdes Bastos, Carvalho and de Pinho45 neoplastic cells have a unique metabolic phenotype associated with cancer development and progression, and therefore, the identification of dysfunctional metabolic pathways via metabolomics has the potential to identify new diagnostic markers for the detection and prognosis of diseases, to monitor the response to therapeutic interventions and to facilitate the discovery of therapeutic targets. Schmidt et al. Reference Schmidt, Fensom and Rinaldi54 and Trock Reference Trock44 have reported various metabolites that are associated with the risk of prostate cancer, advanced stage disease, disease aggressiveness and prostate cancer-specific mortality. Röhnisch et al. Reference Röhnisch, Kyrø, Olsen, Thysell, Hallmans and Moazzami52 have also reported an association between pre-diagnostic levels of plasma and serum metabolites and the risk of prostate cancer incidence. According to Trock, Reference Trock44 due to the functional significance of metabolites, metabolomic biomarkers or profiles hold promise for personalised and targeted medicine.

Giskeødegård et al. Reference Giskeødegård, Hansen and Bertilsson50 investigated differences in metabolic markers in serum and plasma samples from 29 prostate cancer patients and 21 controls with BPH via metabolomic analysis using magnetic resonance spectroscopy, mass spectrometry and gas chromatography. They reported that metabolic profiles have a potential to discriminate prostate cancer patients from controls with BPH with a sensitivity and specificity of 82% and 75%, respectively. They observed significantly different levels of metabolites such as amino acids, lipids and metabolites involved in energy metabolism between patients and controls. They also reported elevated levels of decanoylcarnitine, tetradecenoylcarnitine, octanoylcarnitine, dimethyl-sulfone, phenylalanine and lysine metabolites in prostate cancer patients, whereas phosphatidylcholine diacyl and lipid2 metabolites levels were elevated in the controls. They concluded that a combined analysis of serum and plasma samples by different metabolomic measurement techniques has the potential to discriminate prostate cancer from controls, and that changes in fatty acid, choline and amino acid metabolism are potential markers for prostate cancer. Stabler et al. Reference Stabler, Koyama and Zhao55 analysed serum samples from 58 patients with rapid recurrent prostate cancer and recurrence-free patients after radical prostatectomy for metabolites capable of differentiating patients who developed early biochemical recurrence within 2 years of surgery from those who remained recurrence-free after more than 5 years. They reported elevated concentrations of homocysteine, cystathionine and cysteine in the serum of patients with recurrent disease compared to recurrence-free patients. They concluded that elevated levels of serum homocysteine, cystathionine and cysteine concentrations independently predict both risk of early biochemical recurrence and disease aggressiveness.

Zang et al. Reference Zang, Jones and Long51 studied untargeted metabolomic profiling of age-matched serum samples from 64 prostate cancer patients and 50 healthy individuals to profile and identify a panel of metabolites in blood serum that discriminates cancer patients from healthy individuals. They used ultraperformance liquid chromatography coupled to high-resolution mass spectrometry and tandem mass spectrometry combined with machine learning techniques. They reported a panel of 40 metabolic spectral features capable of discriminating prostate cancer patients from controls with 92% sensitivity, 94% specificity and 93% accuracy. Furthermore, they reported that the identification of fatty acids, amino acids, lysophospholipids and bile acids provided additional insights into the metabolic alterations associated with the disease. Röhnisch et al. Reference Röhnisch, Kyrø, Olsen, Thysell, Hallmans and Moazzami52 investigated the association between plasma metabolite concentrations and the risk of prostate cancer in 777 cancer patients and 777 matched controls stratified by disease aggressiveness and age at baseline. They reported that lysophosphatidylcholines are positively associated with the risk of overall prostate cancer with stronger correlation observed in older patients, and glycine positivity is associated with the risk of overall prostate cancer in younger patients. They concluded that several glycerophospholipids are positively associated with the risk of overall and aggressive prostate cancer. Huang et al. Reference Huang, Weinstein and Moore53 investigated metabolites in pre-diagnostic serum from 197 prostate cancer cases in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study and identified 625 metabolites. They reported that sterol/steroid metabolite score increased the risk of prostate cancer death by 46%, and lipids and elevated levels of serum N-oleoyltaurine are significantly associated with prostate cancer-specific mortality. They concluded that pre-diagnostic serum N-oleoyl taurine and sterol/steroid metabolites are associated with prostate cancer survival.

Ferritin

Ferritin is an intracellular protein that stores iron and releases it in a controlled manner, thereby acting as a buffer against iron deficiency and iron overload in humans, and is present in both glycosylated and non-glycosylated forms. Reference Verma, Chakraverty, Baweja, Girotra, Chatterjee and Chugh56Reference Vela60 According to Wang et al. Reference Wang, An and Zeng58 and Su et al., Reference Su, Lei and Zhang59 ferritin plays important roles in many physiological and pathological processes, including immunosuppression, neurodegenerative, cardiovascular diseases, proliferation, angiogenesis and carcinogenesis. In general, the normal serum ferritin levels in men range 20–250 µg/L; however, these levels are elevated in patients with a variety of malignant cancer types and are correlated with the risk of prostate cancer. Reference Wang, An and Zeng58 According to Vela, Reference Vela60 prostate cancer cells require iron for survival as it is used in the activity of enzymes that control androgen receptor transcriptional activity, which is a known promoter of the disease. Several studies have reported that elevated levels of serum ferritin are associated with iron overload, inflammatory responses such as cancer, infections, autoimmune diseases and poor prognosis for prostate cancer. Reference Zhao, Zhao, Lei and Zhang57,Reference Su, Lei and Zhang59,Reference Vela60 According to Zhao et al., Reference Zhao, Zhao, Lei and Zhang57 serum ferritin level is a potential diagnostic indicator of prostate cancer and others Reference Su, Lei and Zhang59,Reference Rouillon, Lefebvre and Denard61,Reference Solé, Goicoechea and Goñi62 have also reported the increasing use of urine as a source of biomarkers for prostate cancer screening due to its non-invasiveness, convenience, easily available and potential to capture the disease at an earlier stage. Su et al. Reference Su, Lei and Zhang59 reported that the changes of the composition, quantity and quality of urine can provide information that reflect the generation, development and prognosis of urinary diseases including prostate cancer, and thus an increasing number of investigations are ongoing in urinary proteomics in prostate cancer biomarkers research.

Studies have reported an association between high serum or urinary ferritin levels and an increased risk of prostate cancer, although some of the results are inconsistent. Reference Zhao, Zhao, Lei and Zhang57Reference Su, Lei and Zhang59,Reference Kuvibidila, Gauthier and Rayford63,Reference Koike, Robles and da Silva Bonacini64 Kuvibidila et al. Reference Kuvibidila, Gauthier and Rayford63 evaluated ferritin levels in serum samples from 34 newly diagnosed, untreated prostate cancer patients and 84 healthy individuals ranging in age from 49 to 78 years to determine whether elevated serum ferritin (i.e., > 300 μg/L) is associated with increased risk of prostate cancer. They reported significantly lower mean concentrations of serum ferritin in prostate cancer patients and concluded that serum ferritin levels are negatively associated with the presence of prostate cancer. On the contrary, Wang et al. Reference Wang, An and Zeng58 conducted a large-scale case–control study consisting of 2002 prostate cancer patients and 951 BPH patients as control to examine the relationship between serum ferritin and the risk, diagnosis and prognosis of prostate cancer. They reported that elevated levels of serum ferritin are positively associated with increased PSA levels, prostate cancer risk, higher Gleason scores and higher predictive accuracy for serum PSA. They concluded that serum ferritin is significantly associated with prostate cancer risk and is a potential non-invasive biomarker to complement PSA test in the diagnosis and prognostic evaluation of the disease. Zhao et al. Reference Zhao, Zhao, Lei and Zhang57 also investigated the potential of urinary ferritin as a prostate cancer diagnostic biomarker in three prostate cancer patients, three BPH patients and three age-, gender-, and ethnicity-matched healthy individuals. They reported 15 overexpressed proteins including ferritin heavy-chain gene and ferritin light-chain gene in the urine of prostate cancer patients compared to BPH patients and control individuals. They concluded that there are notable differences in urinary proteins among patients with prostate cancer, BPH and normal controls, and both ferritin heavy chain and ferritin light chain are potential biomarkers for prostate cancer that play important but different roles in the disease. Su et al. Reference Su, Lei and Zhang59 also conducted a study to identify potential urine biomarkers capable of identifying and discriminating prostate cancer from BPH in a cohort of nine prostate cancer patients, nine BPH patients, and nine sex- and ethnicity-matched healthy controls. They reported significantly elevated levels of ferritin in the urine of prostate cancer patients in comparison with BPH patients and controls and concluded that urine ferritin has the potential to distinguish prostate cancer patients from BPH patients. Solé et al. Reference Solé, Goicoechea and Goñi62 used the next-generation sequencing technique to evaluate the urinary transcriptome of 178 whole urine samples from high-stage and low-stage prostate cancer patients as well as from BPH patients. They identified and validated five differentially expressed messenger RNA (mRNA) biomarkers (i.e., ferritin heavy chain 1 (FTH1), bromodomain and PHD finger containing 1 (BRPF1), oxysterol binding protein (OSBP), polyhomeotic homolog 3 (PHC3) and uveal autoantigen with coiled-coil domains and ankyrin repeats (UACA)) capable of discriminating prostate cancer patients from BPH patients and healthy controls. They concluded that urine is a valuable source of biomarkers that warrants further investigation for clinical utilisation.

Prostate-specific membrane antigen (PSMA)

Prostate-specific membrane antigen (PSMA) is a type II membrane glycoprotein with an intracellular segment, a transmembrane domain and an extensive extracellular domain Reference Osei, Swanson, Ibrahim and Sheraz5,Reference Bouchelouche, Choyke and Capala65Reference Nagaya, Nagata and Lu74 that, in humans, is encoded by the PSMA (or FOLH1, folate hydrolase 1) gene located on the short arm of chromosome 11 at position 11.12 (11p11.12). Reference Ghosh, Heston, LaRochelle and Shimkets71,Reference Chang72 The expression and enzymatic activities of PSMA are reported to be elevated in malignant prostatic epithelial cells and high-grade prostatic intraepithelial carcinoma; however, it is observed to be absent or moderately expressed in hyperplastic and benign tissue. Reference Wüstemann, Haberkorn, Babich and Mier67Reference Chang72,Reference Nagaya, Nagata and Lu74,Reference Park, Shin and Jung75 Several studies have reported that high PSMA levels correlate with tumour stage, tumour aggressiveness, androgen independence, metastatic disease, Gleason score, as well as disease recurrence, and the PSMA level is maintained in hormone-refractory prostate cancer. Reference Ross, Sheehan and Fisher68,Reference Hupe, Philippi and Roth70,Reference Chang72,Reference Nagaya, Nagata and Lu74,Reference Park, Shin and Jung75 This suggests that PSMA expression is an adverse prognostic factor for prostate cancer and an independent predictor of disease recurrence. Reference Bouchelouche, Choyke and Capala65,Reference Ross, Sheehan and Fisher68Reference Hupe, Philippi and Roth70,Reference Park, Shin and Jung75 According to Wüstemann et al., Reference Wüstemann, Haberkorn, Babich and Mier67 this tumour-associated biomarker provides the possibility for the development of new strategies for diagnosis and therapy of prostate cancer, since it is known to be highly overexpressed on malignant prostate tumour cells and its expression level correlates with disease aggressiveness. Therefore, several studies are exploiting PSMA specificity to prostate cancer for diagnostic imaging strategies using anti-PSMA antibodies and its upregulation by androgen deprivation for anti-PSMA therapies for the treatment of hormone-refractory prostate cancer and metastatic disease. Reference Bouchelouche, Choyke and Capala65,Reference Wüstemann, Haberkorn, Babich and Mier67Reference Chang72

Paller et al. Reference Paller, Piana and Eshleman69 investigated PSMA expression in circulating tumour cells (CTCs) at the time of therapeutic decisions and its correlation with PSA and/or radiographic progression or response in 15 patients undergoing sequential therapies with androgen receptor-targeting agents, taxane chemotherapies and PSMA-directed therapies. They reported PSMA positivity at baseline in about 73% (11 of 15) of patients and PSMA negativity in the remaining 27% of patients. Furthermore, they reported that PSMA expression significantly decreased in patients treated with Lu-PSMA-617 (a PSMA-targeted radioligand therapy) and serum PSA levels declined with decreased PSMA expression. They concluded that PSMA expression in CTCs is a dynamic marker, PSMA transcript decline is associated with concurrent decreases in serum PSA, and sequential CTC sampling could provide a non-invasive response assessment to systemic treatment for mCRPC. Zhang et al. Reference Zhang, Wang and Yang66 evaluated the use of the MJ Opticon Monitor II apparatus for real-time quantitative polymerase chain reaction (PCR) of PSMA in peripheral blood specimens from 13 healthy individuals, 17 metastatic prostate cancer patients, 20 patients with localised prostate cancer and 68 patients with BPH. They reported significant differences in PSMA mRNA levels in blood samples among BPH, locally confined prostate cancer and metastatic prostate cancer and demonstrated that real-time quantitative PCR is a sensitive, accurate and high reproducibility technique for PSMA detection in peripheral blood. They concluded that the technique improves accuracy and reliability of assessment of disseminated prostate cancer cells in peripheral blood and is promising for clinical diagnosis purposes. Xiao et al. Reference Xiao, Adam and Cazares73 used a novel protein biochip immunoassay technique to quantify and compare serum PSMA levels in healthy men and patients with either benign or malignant prostate disease. They reported mean serum PSMA levels of 623 ng/mL, 117·1 ng/mL, 272·9 ng/mL and 359·4 ng/mL for prostate cancer patients, BPH patients, control group aged <50 years and control group aged >50 years, respectively. They concluded that serum PSMA may be a more effective marker than PSA and a clinically useful diagnostic biomarker to improve the specificity in differentiating prostate cancer from BPH and thus warrants further study to evaluate its clinical utility. Nagaya et al. Reference Nagaya, Nagata and Lu74 investigated the clinical significance of PSMA expression in 203 CTC samples from 79 CRPC patients and further evaluated the association between PSMA expression in CTCs and treatment response in 71% (i.e., 56 out of 79) of the patients who progressed on therapy and were subsequently provided a new treatment. They reported that 36% (i.e., 20 out of the 56) of the patients expressed PSMA positivity in CTCs and also PSMA expression is inversely associated with percentage change in PSA. Furthermore, they reported that PSA progression-free survival and overall survival are significantly shorter in the PSMA-positive patients. They concluded that PSMA expression is predictive of poorer treatment response, shorter PSA progression-free survival and overall survival, and PSMA expression in CTCs is a novel poor prognostic marker for CRPC patients.

MicroRNA (miRNA)

MicroRNAs (miRNAs), first discovered in 1993, are a class of endogenous small non-coding ribonucleic acid (RNA) molecules (19–22 bases in length) that regulate protein-coding gene expression by repressing translation or cleaving RNA transcripts in a sequence-specific manner. Reference Goto, Kurozumi, Enokida, Ichikawa and Seki76Reference Bidarra, Constâncio and Barros-Silva79 Several studies have reported that miRNAs regulate the expression of several genes and thus are involved in almost all biological processes, including genome stability, cell development, proliferation, cell cycle, apoptosis, adhesion, migration, inflammation, invasion and metastasis Reference Goto, Kurozumi, Enokida, Ichikawa and Seki76Reference Liu, Mao and Zhu78 According to Goto et al., Reference Goto, Kurozumi, Enokida, Ichikawa and Seki76 miRNAs regulate the expression of approximately 60% of all genes and thus are considered as a mechanism of fine-tuning regulation. Liu et al. Reference Liu, Mao and Zhu78 reported that miRNAs affect tumorigenesis mainly by interrupting the cell cycle at the cellular level and by interacting with signalling pathways, oncogenes and with the response to environmental factors at the molecular level. Aberrant miRNA expression is reported to contribute to cancer initiation, progression, metastasis and drug resistance by targeting several cancer-related genes moreover, highly expressed miRNAs function as oncogenes by repressing tumour suppressors and low miRNA expression suppresses tumours by negatively regulating oncogenes. Reference Goto, Kurozumi, Enokida, Ichikawa and Seki76,Reference Liu, Mao and Zhu78,Reference Esquela-Kerscher and Slack80Reference Calin and Croce85 Studies have reported that over half of miRNA genes are located in or near fragile sites or cancer-associated genomic regions which are preferential sites of sister chromatid exchange, deletion, translocation, amplification or integration of plasmid DNA and tumour-associated virus, which frequently cause aberrant miRNA expression during pathogenesis. Reference Goto, Kurozumi, Enokida, Ichikawa and Seki76Reference Liu, Mao and Zhu78 According to Goto et al. Reference Goto, Kurozumi, Enokida, Ichikawa and Seki76 and Massillo et al., Reference Massillo, Dalton, Farré, De Luca and De Siervi77 there is a growing body of evidence suggesting that miRNAs contribute to prostate cancer development, progression and metastasis. Massillo et al. Reference Massillo, Dalton, Farré, De Luca and De Siervi77 and Bidarra et al. Reference Bidarra, Constâncio and Barros-Silva79 also reported that miRNAs are observed to circulate in biological fluids including serum with significant stability, thereby making circulating miRNAs potential tumour-specific and fluid-circulating biomarkers for diagnosis and follow-up of prostate cancer patients. According to Massillo et al., Reference Massillo, Dalton, Farré, De Luca and De Siervi77 miRNA expression could predict clinical outcome as well as prognosis and could be used as markers of disease relapse and metastases. Therefore, miRNAs are emerging as promising tools for the diagnosis, prognosis and management of prostate cancer patients as well as for potential miRNA-based cancer treatment.

Al-Kafaji et al. Reference Al-Kafaji, Said, Alam and Al Naieb86 assessed the potential use of circulating miRNAs in serum to distinguish localised prostate cancer from BPH and to discriminate between low- and high-risk patients at an early stage in a population of 35 patients with localised disease, 35 BPH patients and 30 healthy individuals. They stratified patients based on tumour stage, PSA level and Gleason score into low-risk (T1 or T2, PSA < 10 ng/ml or GS ≤ 7) and high-risk (T3 or T4, PSA > 20 ng/mL or GS ≥ 8) cohorts. They reported that patients with localised prostate cancer exhibited significantly lower expression of miR-15a, miR-126, miR-192 and miR-377 compared to patients with BPH or healthy subjects. Furthermore, they reported that the expression of the four miRNAs was lower in high-risk prostate cancer patients compared to low-risk patients and was significantly and independently associated with prostate cancer risk. They demonstrated that the miRNAs significantly distinguished prostate cancer patients from BPH patients and controls, and low-risk prostate cancer patients from high-risk cancer patients. They concluded that the expression of these miRNAs in circulating blood is a promising, non-invasive biomarker for the early detection of localised prostate cancer, and for prostate cancer risk stratification; however, they suggested validations of the clinical implementation in a larger cohort. Hoey et al. Reference Hoey, Ahmed and Fotouhi Ghiam87 investigated the expression levels of circulating miRNAs and their potential to independently predict patient risk stratification after radical prostatectomy in 78 patients. They stratified patients into high-risk and low-risk categories based on Gleason score, pathological T stage, surgical margin status and diagnostic PSA level. According to their categorisation, all patients with Gleason score≥8, pT3a and positive margin, pT3b and any margin, or diagnostic PSA > 20 μg/mL were classified as high risk (n = 44) and all other patients were classified as low risk (n = 31). They identified four miRNA (miR-17, miR-20a, miR-20b and miR-106a) that are capable of discriminating high-risk from low-risk patients and reported that elevated expression levels of these miRNAs are associated with shorter time to biochemical recurrence and confer an aggressive phenotype. They concluded that these circulating miRNAs have the potential to independently predict risk stratification of prostate cancer patients after radical prostatectomy.

Huang et al. Reference Huang, Yuan and Liang88 studied circulating plasma exosomal miRNAs that could be associated with overall survival in a screening cohort of 23 CRPC patients and identified miRNAs were further evaluated for prognosis in a follow-up cohort of 100 patients. They observed an association of miR-1290, miR-1246 and miR-375 with overall survival and reported that higher levels of miR-1290 and miR-375 are significantly associated with poor overall survival in the follow-up cohort. Furthermore, they reported that the combination of miR-1290 and miR-375 into accepted clinical prognostic factors-based models in the CRPC stage significantly improved the predictive performance. They concluded that plasma exosomal miR-1290 and miR-375 are promising prognostic biomarkers for CRPC patients; however, they suggested that prospective validation is required for evaluation of these candidate miRNAs since the non-invasive blood-based test has great potential in the management of late-stage prostate cancer. Bidarra et al. Reference Bidarra, Constâncio and Barros-Silva79 examined the potential of circulating plasma miR-128-5p and miR-375-3p levels as non-invasive screening and prognostic biomarkers in 252 clinically localised prostate cancer patients undergoing curative-intent treatment and 52 controls. They reported significantly elevated levels of circulating miR-128-5p expression in prostate cancer patients and patients who developed disease metastasis compared to controls. Furthermore, they reported that miR-182-5p expression levels identified prostate cancer patients with a 77% specificity and 99% negative predictive value, and both circulating miR-182-5p and miR-375-3p levels are associated with more advanced pathologic stages. In addition, they indicated that at the time of diagnosis, circulating miR-375-3p levels predicted patients who would develop metastasis with approximately 50% sensitivity, 76% specificity and 89% negative predictive value. They concluded that these two circulating miRNAs could be clinically useful as non-invasive biomarkers for detection and prediction of metastasis development at diagnosis when used in conjunction with clinical variables used in routine practice.

Exosomes

Exosomes are small extracellular vesicles secreted by a variety of cells and contain constituents such as proteins, DNA, mRNA, miRNA, lipids, metabolites, as well as long non-coding RNA that can be taken up by distant cells and effectively alter their biological response. Reference Lorenc, Klimczyk, Michalczewska, Słomka, Kubiak-Tomaszewska and Olejarz89Reference Gabriel, Ingram and Austin94 They are present and detectable in various human bodily fluids, such as blood, urine, saliva, semen, etc., and are emerging as a valued non-invasive source of diagnostic, prognostic and predictive cancer biomarkers. Reference Lorenc, Klimczyk, Michalczewska, Słomka, Kubiak-Tomaszewska and Olejarz89Reference Soekmadji, Russell and Nelson91,Reference Krishn, Singh and Bowler93Reference Khan, Jutzy and Valenzuela96 Exosomes are reported to mediate intercellular communication and regulate tumour progression, immune responses, angiogenesis, migration, apoptosis, metastasis and drug resistance in prostate cancer. Reference Park, Shin and Jung75,Reference Lorenc, Klimczyk, Michalczewska, Słomka, Kubiak-Tomaszewska and Olejarz89,Reference Kalluri and LeBleu92 Pan et al. Reference Pan, Ding, Xu, Yang and Mao90 reported that exosomes derived from prostate cancer patients showed high levels of miR-21 and miR-141 (regulators of osteoclastogenesis and osteoblastogenesis), contained transforming growth factor beta (TGF-β) (inducer of the conversion from bone marrow mesenchymal stem cells to fibroblasts) and carried integrin α3 and integrin β1 (promoters of migration and invasion of epithelial cells). According to Lorenc et al., Reference Lorenc, Klimczyk, Michalczewska, Słomka, Kubiak-Tomaszewska and Olejarz89 serum exosomes can serve as novel tools for various therapeutic approaches, such as drug delivery, anti-tumour therapy, pathogen vaccination, as well as immune-modulatory and regenerative therapies. Furthermore, they reported that urinary exosomes (e.g., miR-21 and miR-375) are an emerging source of biomarkers in the detection and prognosis of prostate cancer and a valuable aid in the decision-making process regarding prostate biopsy and the development of therapeutic strategies.

Øverbye et al. Reference Øverbye, Skotland and Koehler95 investigated the proteome of urinary exosomes in 16 patients and 15 healthy male specimens to identify proteins that are differentially expressed in prostate cancer patients compared to healthy controls. They observed 246 proteins differentially expressed between cancer patients and healthy controls and reported that 90% (221 out of 246) of the proteins are up-regulated in prostate cancer patients. When they narrowed the evaluation to a selected list of 37 proteins, they observed that 17 out of the 37 proteins had 100% specificity and over 60% sensitivity to discriminate prostate cancer patients from healthy controls. They also reported that the transmembrane protein 256 (TM256) has the highest sensitivity at 94%, whereas the LAMTOR proteins have very high specificity. They concluded that a combination of multiple proteins into a multi-panel test holds the promise to fully differentiate prostate cancer patients from healthy controls, and that urinary exosomes have potential in the diagnosis and clinical management of prostate cancer. Krishn et al. Reference Krishn, Singh and Bowler93 studied the alpha-v beta-3 (αvβ3) integrin in plasma-derived exosomes and its exosomal intercellular transfer in exosomes isolated from plasma samples from 70 prostate cancer patients and 14 age-matched healthy controls. They reported that exosome-enriched extracellular vesicles contain elevated levels of αvβ3 integrin and CD9 in plasma derived from prostate cancer patients compared to age-matched control. They also reported that the levels of αvβ3, CD63 and CD9 remain unaltered in exosomes-enriched extracellular vesicles isolated from the blood of prostate cancer patients treated with enzalutamide. They concluded that the detection of exosomal αvβ3 integrin in prostate cancer patients is a clinically valuable and non-invasive marker for prostate cancer management, and the potential transfer of αvβ3 integrin from exosomes-enriched extracellular vesicles to recipient cells provides a strong rationale for further investigation of the role of αvβ3 integrin in prostate cancer pathogenesis as well as its potential as a therapeutic target. Khan et al. Reference Khan, Jutzy and Valenzuela96 investigated the expression of exosomal Survivin in plasma and serum from 39 prostate cancer patients, 20 BPH patients, 8 patients with advanced disease after unsuccessful chemotherapy with Taxotere and 16 healthy controls. They observed Survivin expressions in plasma exosomes from healthy controls, pre-inflammatory BPH patients and prostate cancer patients and reported significantly elevated plasma exosomes levels in cancer patients and those who had relapsed on chemotherapy compared to BPH patients and controls. They concluded that exosomal Survivin exists in the plasma of patients with newly diagnosed low-grade prostate cancer and thereby provides a rationale to further investigate its potential as an early, easily measurable biomarker for prostate cancer diagnosis and treatment management of patients with advanced disease. Gabriel et al. Reference Gabriel, Ingram and Austin94 investigated the diagnostic potential of phosphatase and tensin homolog (PTEN) in plasma-derived exosomes and the intercellular exchange of PTEN via exosomes using blood samples from 30 pre-prostatectomy patients and 8 healthy, age-matched controls. They observed PTEN expression in all exosomes from prostate cancer patients, but no expression in exosomes from healthy controls and reported that PTEN is incorporated in the cargo of exosomes circulating in patients’ blood. They concluded that exosomal PTEN can compensate for PTEN loss in PTEN-deficient cells and has potential diagnostic value for prostate cancer.

Conclusion

The identification of clinical liquid-based biomarkers that potentially account for individual patient variabilities and capable of therapeutic targeting of specific genetically aberrant pathways which play key roles in malignant tumour formation as well as offers improved understanding of the biology responsible for prostate carcinogenesis and progression will likely shift the treatment paradigm of prostate cancer towards a more non-invasive personalised and targeted medicine. Liquid-based biomarkers with high sensitivity and specificity for prostate cancer have proven potential to provide a non-invasive and cost-effective approach for screening, early-stage disease diagnoses and patient stratification at diagnosis into different risk categories and guide the provision of optimal targeted treatment selection in clinical practice. Furthermore, they have potential roles in the development of novel effective therapies inhibiting prostate cancer progression and metastasis, and thereby substantially impacting disease mortality, increasing patient survival and potentially reducing the rates of invasive treatments by enhancing the safety of active surveillance strategies as well as providing clinicians the ability to identify patients likely to respond to specific treatments.

Acknowledgements

The authors would like to acknowledge with much gratitude the financial support from the Kitchener-Waterloo Chapter of the TELUS Ride for Dad and the Prostate Cancer Fight Foundation for prostate cancer research at Grand River Hospital.

References

Canadian Cancer Society. Prostate cancer statistics. https://www.cancer.ca/en/cancer-information/cancer-type/prostate/statistics/?region=on. Accessed on 17th April 2020.Google Scholar
Brenner, D R, Weir, H K, Demers, A A et al. Projected estimates of cancer in Canada in 2020. CMAJ 2020; 192 (9): e199e205.CrossRefGoogle ScholarPubMed
Siegel, R L, Miller, K D, Jemal, A. Cancer statistics, 2020. CA Cancer J Clin 2020; 70 (1): 730.CrossRefGoogle ScholarPubMed
Osei, E, Swanson, S. A review of current clinical biomarkers for prostate cancer: towards personalised and targeted therapy. J Radiother Pract 2020; 110 (Online Publication).Google Scholar
Osei, E, Swanson, S, Ibrahim, N, Sheraz, L. Review of novel tissue-based biomarkers for prostate cancers: towards personalised and targeted medicine. J Radiother Pract 2021 (in Press).Google Scholar
Bourdoumis, A, Papatsoris, A G, Chrisofos, M, Efstathiou, E, Skolarikos, A, Deliveliotis, C. The novel prostate cancer antigen 3 (PCA3) biomarker. Int Braz J Urol 2010; 36 (6): 665669.CrossRefGoogle ScholarPubMed
Cao, L, Lee, C H, Ning, J, Handy, B C, Wagar, E A, Meng, Q H. Combination of prostate cancer antigen 3 and prostate-specific antigen improves diagnostic accuracy in men at risk of prostate cancer. Arch Pathol Lab Med 2018; 142 (9): 11061112.CrossRefGoogle ScholarPubMed
Filella, X, Fernández-Galan, E, Bonifacio, R F, Foj, L. Emerging biomarkers in the diagnosis of prostate cancer. Pharmgenomics Pers Med 2018; 11: 8394.Google ScholarPubMed
Zappala, S M, Dong, Y, Linder, V et al. The 4Kscore blood test accurately identifies men with aggressive prostate cancer prior to prostate biopsy with or without DRE information. Int J Clin Pract Suppl 2017; 71 (6): e12943.CrossRefGoogle ScholarPubMed
Alford, A V, Brito, J M, Yadav, K K, Yadav, S S, Tewari, A K, Renzulli, J. The use of biomarkers in prostate cancer screening and treatment. Rev Urol 2017; 19 (4): 221234.Google ScholarPubMed
Hong, S K. Kallikreins as biomarkers for prostate cancer. Biomed Res Int 2014; 2014: 10.CrossRefGoogle ScholarPubMed
Punnen, S, Pavan, N, Parekh, D J. Finding the wolf in sheep’s clothing: the 4Kscore is a novel blood test that can accurately identify the risk of aggressive prostate cancer. Rev Urol 2015; 17 (1): 313.Google ScholarPubMed
Foley, R W, Gorman, L, Sharifi, N et al. Improving multivariable prostate cancer risk assessment using the Prostate Health Index. BJU Int 2016; 117 (3): 409417.CrossRefGoogle ScholarPubMed
Fossati, N, Lazzeri, M, Haese, A et al. Clinical performance of serum isoform [-2]proPSA (p2PSA), and its derivatives %p2PSA and the Prostate Health Index, in men aged <60 years: results from a multicentric European study. BJU Int 2015; 115 (6): 913920.Google ScholarPubMed
Hsieh, P F, Chang, C H, Yang, C R et al. Prostate Health Index (PHI) improves prostate cancer detection at initial biopsy in Taiwanese men with PSA 4–10 ng/mL. Kaohsiung J Med Sci 2018; 34 (8): 461466.CrossRefGoogle ScholarPubMed
Lepor, A, Catalona, W J, Loeb, S. The Prostate Health Index: its utility in prostate cancer detection. Urol Clin North Am 2016; 43 (1): 16.CrossRefGoogle ScholarPubMed
Loeb, S, Catalona, W J. The Prostate Health Index: a new test for the detection of prostate cancer. Ther Adv Urol 2014; 6 (2): 7477.CrossRefGoogle ScholarPubMed
Reed, A B, Parekh, D J. Biomarkers for prostate cancer detection. Expert Rev Anticancer Ther 2010; 10 (1): 103114.CrossRefGoogle ScholarPubMed
Hu, B, Yang, H, Yang, H. Diagnostic value of urine prostate cancer antigen 3 test using a cutoff value of 35 μg/L in patients with prostate cancer. Tumor Biol 2014; 35 (9): 85738580.Google ScholarPubMed
White, J, Shenoy, B V, Tutrone, R F et al. Clinical utility of the Prostate Health Index (phi) for biopsy decision management in a large group urology practice setting. Prostate Cancer Prostatic Dis 2017; 21 (1): 7884.CrossRefGoogle Scholar
Kremer, C L, Klein, R R, Mendelson, J et al. Expression of mTOR signaling pathway markers in prostate cancer progression. Prostate 2006; 66 (11): 12031212.CrossRefGoogle ScholarPubMed
Osei, E, Lumini, J, Gunasekara, D et al. A review of predictive, prognostic and diagnostic biomarkers for non-small-cell lung cancer: towards personalised and targeted cancer therapy. J Radiother Pract 2019; 19(4): 370384. doi: 10.1017/S1460396919000876 CrossRefGoogle Scholar
Osei, E, Walters, P, Masella, O et al. A review of predictive, prognostic and diagnostic biomarkers for brain tumors: towards personalised and targeted cancer therapy. J Radiother Pract 2019; 116 (Online Publication).Google Scholar
Fox, B P, Tabone, C J, Kandpal, R P. Potential clinical relevance of Eph receptors and ephrin ligands expressed in prostate carcinoma cell lines. Mol Cell Biol Res Commun 2006; 342 (4): 12631272.Google ScholarPubMed
Lisle, J E, Mertens-Walker, I, Rutkowski, R, Herington, A C, Stephenson, S. Eph receptors and their ligands: promising molecular biomarkers and therapeutic targets in prostate cancer. Biochim Biophys Acta Rev Cancer 2013; 1835 (2): 243257.CrossRefGoogle ScholarPubMed
Astin, J W, Batson, J, Kadir, S et al. Competition amongst Eph receptors regulates contact inhibition of locomotion and invasiveness in prostate cancer cells. Nat Cell Biol 2010; 12 (12): 11941204.CrossRefGoogle ScholarPubMed
Li, S, Zhao, Y, Chen, W et al. Exosomal ephrinA2 derived from serum as a potential biomarker for prostate cancer. J Cancer 2018; 9 (15): 26592665.CrossRefGoogle ScholarPubMed
Merlos-Suárez, A, Batlle, E. Eph–ephrin signalling in adult tissues and cancer. Curr Opin Cell Biol 2008; 20 (2): 194200.CrossRefGoogle ScholarPubMed
Surawska, H, Ma, P C, Salgia, R. The role of ephrins and Eph receptors in cancer. Cytokine Growth Factor Rev 2004; 15 (6): 419433.CrossRefGoogle ScholarPubMed
Xi, H, Wu, X, Wei, B, Chen, L. Eph receptors and ephrins as targets for cancer therapy. J Cell Mol Med 2012; 16 (12): 28942909.CrossRefGoogle ScholarPubMed
Wang, J, Zheng, X, Peng, Q, Zhang, X, Qin, Z. Eph receptors: the bridge linking host and virus. Cell Mol Life Sci 2019; 77 (12): 23552365.CrossRefGoogle Scholar
Taddei, M L, Parri, M, Angelucci, A et al. Kinase-dependent and -independent roles of EphA2 in the regulation of prostate cancer invasion and metastasis. Am J Pathol 2009; 174 (4): 14921503.CrossRefGoogle ScholarPubMed
Salem, A F, Gambini, L, Billet, S et al. Prostate cancer metastases are strongly inhibited by agonistic Epha2 ligands in an orthotopic mouse model. Cancers 2020; 12 (10): 2854.CrossRefGoogle Scholar
Li, S, Zhu, Y, Ma, C et al. Downregulation of EphA5 by promoter methylation in human prostate cancer. BMC cancer 2015; 15: 18.CrossRefGoogle ScholarPubMed
Petty, A, Myshkin, E, Qin, H et al. A small molecule agonist of EphA2 receptor tyrosine kinase inhibits tumor cell migration in vitro and prostate cancer metastasis in vivo. PloS One 2012; 7 (8): e42120.CrossRefGoogle ScholarPubMed
Li, S, Wu, Z, Chen, Y et al. Diagnostic and prognostic value of tissue and circulating levels of Ephrin-A2 in prostate cancer. Tumor Biol 2016; 37 (4): 53655374.CrossRefGoogle ScholarPubMed
Laborde, E. Glutathione transferases as mediators of signaling pathways involved in cell proliferation and cell death. Cell Death Differ 2010; 17 (9): 13731380.CrossRefGoogle ScholarPubMed
Schnekenburger, M, Karius, T, Diederich, M. Regulation of epigenetic traits of the glutathione S-transferase P1 gene: from detoxification toward cancer prevention and diagnosis. Front Pharmacol 2014; 5: 170.CrossRefGoogle ScholarPubMed
Zhou, X, Jiao, D, Dou, M et al. Association of glutathione-S-transferase p1 gene promoter methylation and the incidence of prostate cancer: a systematic review and meta-analysis. J Cancer Res Clin Oncol 2019; 145 (8): 19391948.CrossRefGoogle ScholarPubMed
Mahon, K L, Qu, W, Lin, H et al. Serum free methylated glutathione S-transferase 1 DNA levels, survival, and response to docetaxel in metastatic, castration-resistant prostate cancer: post hoc analyses of data from a phase 3 trial. Eur Urol 2019; 76 (3): 306312.CrossRefGoogle ScholarPubMed
Mian, O Y, Khattab, M H, Hedayati, M et al. GSTP1 loss results in accumulation of oxidative DNA base damage and promotes prostate cancer cell survival following exposure to protracted oxidative stress. Prostate 2016; 76 (2): 199206.CrossRefGoogle ScholarPubMed
Martignano, F, Gurioli, G, Salvi, S et al. GSTP1 methylation and protein expression in prostate cancer: diagnostic implications. Dis Markers 2016; 2016: 4358292.CrossRefGoogle ScholarPubMed
Bastian, P J, Palapattu, G S, Lin, X et al. Preoperative serum DNA GSTP1 CpG island hypermethylation and the risk of early prostate-specific antigen recurrence following radical prostatectomy. Clin Cancer Res 2005; 11 (11): 40374043.CrossRefGoogle ScholarPubMed
Trock, B J. Application of metabolomics to prostate cancer. Urol Oncol 2011; 29 (5): 572581.CrossRefGoogle ScholarPubMed
Lima, A R, de Lourdes Bastos, M, Carvalho, M, de Pinho, P G. Biomarker discovery in human prostate cancer: an update in metabolomics studies. Transl Oncol 2016; 9 (4): 357370.CrossRefGoogle ScholarPubMed
Kdadra, M, Höckner, S, Leung, H, Kremer, W, Schiffer, E. Metabolomics biomarkers of prostate cancer: a systematic review. Diagnostics 2019; 9 (1): 21.CrossRefGoogle ScholarPubMed
Kelly, R S, Vander Heiden, M G, Giovannucci, E, Mucci, L A. Metabolomic biomarkers of prostate cancer: prediction, diagnosis, progression, prognosis, and recurrence. Cancer Epidemiol Biomarkers Prev 2016; 25 (6): 887906.CrossRefGoogle Scholar
Chaleckis, R, Murakami, I, Takada, J, Kondoh, H, Yanagida, M. Individual variability in human blood metabolites identifies age-related differences. Proc Natl Acad Sci U S A 2016; 113 (16): 42524259.CrossRefGoogle ScholarPubMed
Psychogios, N, Hau, D D, Peng, J et al. The human serum metabolome. PloS One 2011; 6 (2): e16957.CrossRefGoogle ScholarPubMed
Giskeødegård, G F, Hansen, A F, Bertilsson, H et al. Metabolic markers in blood can separate prostate cancer from benign prostatic hyperplasia. Br J Cancer 2015; 113 (12): 17121719.CrossRefGoogle ScholarPubMed
Zang, X, Jones, C M, Long, T Q et al. Feasibility of detecting prostate cancer by ultraperformance liquid chromatography–mass spectrometry serum metabolomics. J Proteome Res 2014; 13 (7): 34443454.CrossRefGoogle ScholarPubMed
Röhnisch, H E, Kyrø, C, Olsen, A, Thysell, E, Hallmans, G, Moazzami, A A. Identification of metabolites associated with prostate cancer risk: a nested case-control study with long follow-up in the Northern Sweden Health and Disease Study. BMC Med 2020; 18 (1): 1187.CrossRefGoogle ScholarPubMed
Huang, J, Weinstein, S J, Moore, S C et al. Pre-diagnostic serum metabolomic profiling of prostate cancer survival. J Gerontol A Biol Sci Med Sci 2019; 74 (6): 853859.CrossRefGoogle ScholarPubMed
Schmidt, J A, Fensom, G K, Rinaldi, S et al. Pre-diagnostic metabolite concentrations and prostate cancer risk in 1077 cases and 1077 matched controls in the European Prospective Investigation into Cancer and Nutrition. BMC Med 2017; 15: 122.CrossRefGoogle ScholarPubMed
Stabler, S, Koyama, T, Zhao, Z et al. Serum methionine metabolites are risk factors for metastatic prostate cancer progression. PloS One 2011; 6 (8): e22486.CrossRefGoogle ScholarPubMed
Verma, N, Chakraverty, J, Baweja, P, Girotra, A, Chatterjee, L, Chugh, M. Extremely high ferritinemia associated with haemophagocytic lympho histiocytosis (HLH). Ind J Clin Biochem 2016; 32 (1): 117120.CrossRefGoogle Scholar
Zhao, H, Zhao, X, Lei, T, Zhang, M. Screening, identification of prostate cancer urinary biomarkers and verification of important spots. Invest New Drugs 2019; 37 (5): 935947.CrossRefGoogle Scholar
Wang, X, An, P, Zeng, J et al. Serum ferritin in combination with prostate-specific antigen improves predictive accuracy for prostate cancer. Oncotarget 2017; 8 (11): 1786217872.CrossRefGoogle ScholarPubMed
Su, Q, Lei, T, Zhang, M. Association of ferritin with prostate cancer. J BUON 2017; 22 (3): 766770.Google ScholarPubMed
Vela, D. Iron metabolism in prostate cancer; from basic science to new therapeutic strategies. Front Oncol 2018; 8: 547.CrossRefGoogle ScholarPubMed
Rouillon, J, Lefebvre, T, Denard, J et al. High urinary ferritin reflects myoglobin iron evacuation in DMD patients. Neuromuscul Disord 2018; 28 (7): 564571.CrossRefGoogle ScholarPubMed
Solé, C, Goicoechea, I, Goñi, A et al. The urinary transcriptome as a source of biomarkers for prostate cancer. Cancers 2020; 12 (2): 513.CrossRefGoogle ScholarPubMed
Kuvibidila, S R, Gauthier, T, Rayford, W. Serum ferritin levels and transferrin saturation in men with prostate cancer. J Natl Med Assoc 2004; 96 (5): 641649.Google ScholarPubMed
Koike, A, Robles, B E F, da Silva Bonacini, A G et al. Thiol groups as a biomarker for the diagnosis and prognosis of prostate cancer. Sci Rep 2020; 10: 9093.CrossRefGoogle ScholarPubMed
Bouchelouche, K, Choyke, P L, Capala, J. Prostate specific membrane antigen- a target for imaging and therapy with radionuclides. Discov Med 2010; 9 (44): 5561.Google ScholarPubMed
Zhang, L, Wang, C, Yang, R et al. Real-time quantitative RT-PCR assay of prostate-specific antigen and prostate-specific membrane antigen in peripheral blood for detection of prostate cancer micrometastasis. Urol Oncol 2008; 26 (6): 634640.CrossRefGoogle ScholarPubMed
Wüstemann, T, Haberkorn, U, Babich, J, Mier, W. Targeting prostate cancer: prostate-specific membrane antigen based diagnosis and therapy. Med Res Rev 2019; 39 (1): 4069.CrossRefGoogle ScholarPubMed
Ross, J S, Sheehan, C E, Fisher, H A G et al. Correlation of primary tumor prostate-specific membrane antigen expression with disease recurrence in prostate cancer. Clin Cancer Res 2003; 9 (17): 6357.Google ScholarPubMed
Paller, C J, Piana, D, Eshleman, J R et al. A pilot study of prostate-specific membrane antigen (PSMA) dynamics in men undergoing treatment for advanced prostate cancer. Prostate 2019; 79 (14): 15971603.CrossRefGoogle ScholarPubMed
Hupe, M C, Philippi, C, Roth, D et al. Expression of prostate-specific membrane antigen (PSMA) on biopsies is an independent risk stratifier of prostate cancer patients at time of initial diagnosis. Front Oncol 2018; 8: 623.CrossRefGoogle ScholarPubMed
Ghosh, A, Heston, W. Understanding prostate-specific membrane antigen and its implication in prostate cancer. In: LaRochelle, W J, Shimkets, R A (eds). The Oncogenomics Handbook. Cancer Drug Discovery and Development. Totowa, NJ: Humana Press, 2005: 597615.Google Scholar
Chang, S S. Overview of prostate-specific membrane antigen. Rev Urol 2004; 6 (suppl 10), S13S18.Google ScholarPubMed
Xiao, Z, Adam, B L, Cazares, L H et al. Quantitation of serum prostate-specific membrane antigen by a novel protein biochip immunoassay discriminates benign from malignant prostate disease. Cancer Res 2001; 61 (16): 60296033.Google ScholarPubMed
Nagaya, N, Nagata, M, Lu, Y et al. Prostate-specific membrane antigen in circulating tumor cells is a new poor prognostic marker for castration-resistant prostate cancer. PloS One 2020; 15 (1): e0226219.CrossRefGoogle ScholarPubMed
Park, Y H, Shin, H W, Jung, A R et al. Prostate-specific extracellular vesicles as a novel biomarker in human prostate cancer. Sci Rep 2016; 6: 30386.CrossRefGoogle ScholarPubMed
Goto, Y, Kurozumi, A, Enokida, H, Ichikawa, T, Seki, N. Functional significance of aberrantly expressed microRNAs in prostate cancer. Int J Urol 2015; 22 (3): 242252.CrossRefGoogle ScholarPubMed
Massillo, C, Dalton, G N, Farré, P L, De Luca, P, De Siervi, A. Implications of microRNA dysregulation in the development of prostate cancer. Reproduction 2017; 154 (4): R81R97.CrossRefGoogle ScholarPubMed
Liu, W, Mao, S Y, Zhu, W Y. Impact of tiny miRNAs on cancers. World J Gastroenterol 2007; 13 (4): 497502.CrossRefGoogle ScholarPubMed
Bidarra, D, Constâncio, V, Barros-Silva, D et al. Circulating microRNAs as biomarkers for prostate cancer detection and metastasis development prediction. Front Oncol 2019; 9 (11): 900.CrossRefGoogle ScholarPubMed
Esquela-Kerscher, A, Slack, F J. Oncomirs — microRNAs with a role in cancer. Nat Rev Cancer 2006; 6 (4): 259269.CrossRefGoogle ScholarPubMed
Garzon, R, Calin, G A, Croce, C M. MicroRNAs in cancer. Annu Rev Med 2009; 60 (1): 167179.CrossRefGoogle ScholarPubMed
Ma, J, Dong, C, Ji, C. MicroRNA and drug resistance. Cancer Gene Ther 2010; 17 (8): 523531.Google ScholarPubMed
Wu, W, Sun, M, Zou, G, Chen, J. MicroRNA and cancer: current status and prospective. Int J Cancer 2006; 120 (5): 953960.CrossRefGoogle Scholar
Nelson, K M, Weiss, G J. MicroRNAs and cancer: past, present, and potential future. Mol Cancer Ther 2008; 7 (12): 36553660.CrossRefGoogle ScholarPubMed
Calin, G A, Croce, C M. MicroRNA signatures in human cancers. Nat Rev Cancer 2006; 6 (11): 857866.CrossRefGoogle ScholarPubMed
Al-Kafaji, G, Said, H M, Alam, M A, Al Naieb, Z T. Blood-based microRNAs as diagnostic biomarkers to discriminate localized prostate cancer from benign prostatic hyperplasia and allow cancer-risk stratification. Oncol Lett 2018; 16 (1): 13571365.Google ScholarPubMed
Hoey, C, Ahmed, M, Fotouhi Ghiam, A et al. Circulating miRNAs as non-invasive biomarkers to predict aggressive prostate cancer after radical prostatectomy. J Transl Med 2019; 17: 173.CrossRefGoogle ScholarPubMed
Huang, X, Yuan, T, Liang, M et al. Exosomal miR-1290 and miR-375 as prognostic markers in castration-resistant prostate cancer. Eur Urol 2015; 67 (1): 3341.CrossRefGoogle ScholarPubMed
Lorenc, T, Klimczyk, K, Michalczewska, I, Słomka, M, Kubiak-Tomaszewska, G, Olejarz, W. Exosomes in prostate cancer diagnosis, prognosis and therapy. Int J Mol Sci 2020; 21 (6): 2118.CrossRefGoogle Scholar
Pan, J, Ding, M, Xu, K, Yang, C, Mao, L. Exosomes in diagnosis and therapy of prostate cancer. Oncotarget 2017; 8 (57): 9769397700.CrossRefGoogle ScholarPubMed
Soekmadji, C, Russell, PJ, Nelson, CC. Exosomes in prostate cancer: putting together the pieces of a puzzle. Cancers 2013; 5 (4): 15221544.CrossRefGoogle ScholarPubMed
Kalluri, R, LeBleu, V S. The biology, function, and biomedical applications of exosomes. Science 2020; 367 (6478): eaau6977.CrossRefGoogle ScholarPubMed
Krishn, SR, Singh, A, Bowler, N et al. Prostate cancer sheds the αvβ3 integrin in vivo through exosomes. Matrix Biol 2019; 77: 4157.CrossRefGoogle ScholarPubMed
Gabriel, K, Ingram, A, Austin, R et al. Regulation of the tumor suppressor PTEN through exosomes: a diagnostic potential for prostate cancer. PloS One 2013; 8 (7): e70047.CrossRefGoogle ScholarPubMed
Øverbye, A, Skotland, T, Koehler, C J et al. Identification of prostate cancer biomarkers in urinary exosomes. Oncotarget 2015; 6 (30): 3035730376.CrossRefGoogle ScholarPubMed
Khan, S, Jutzy, J M S, Valenzuela, M M A et al. Plasma-derived exosomal Survivin, a plausible biomarker for early detection of prostate cancer. PloS One 2012; 7 (10): e46737.CrossRefGoogle ScholarPubMed
Hao, N, Zhang, J X J. Microfluidic screening of circulating tumor biomarkers toward liquid biopsy. Sep Purif Rev 2018; 47 (1): 130.CrossRefGoogle Scholar
Chen, X, Ba, Y, Ma, L et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 2008; 18 (10): 9971006.Google ScholarPubMed
Sausen, M, Parpart, S, Diaz, L A. Circulating tumor DNA moves further into the spotlight. Genome Med 2014; 6 (5): 35.CrossRefGoogle ScholarPubMed
Perakis, S, Speicher, M R. Emerging concepts in liquid biopsies. BMC Med 2017; 15: 75.CrossRefGoogle ScholarPubMed