Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics

https://doi.org/10.1016/j.pharmthera.2021.107932Get rights and content

Highlights

  • Detailed description of the genomic events that can be used for achieving more accurate diagnosis of prostate cancer.

  • Existing biomarkers with potential value in the risk stratification of patients, prognosis and precision-guided therapeutics.

  • Emerging biomarkers with enough pre-clinical and/or clinical evidence to suggest potential utility in disease management.

  • Currently used biomarker-based precision technological platforms for prostate cancer.

  • Challenges that are associated with the identification of clinically significant biomarkers for prostate cancer and possible ways to overcome them.

Abstract

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and among the leading causes of cancer-related death worldwide. It is a highly heterogeneous disease, ranging from remarkably slow progression or inertia to highly aggressive and fatal disease. As therapeutic decision-making, clinical trial design and outcome highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between benign versus more aggressive states. The incorporation of clinically valuable prognostic and predictive biomarkers is also potentially amenable in this process, in the timely prevention of metastatic disease and in the decision for therapy selection. This review summarizes the progress that has so far been made in the identification of the genomic events that can be used for the classification, prediction and prognostication of PCa, and as major targets for clinical intervention. We include an extensive list of emerging biomarkers for which there is enough preclinical evidence to suggest that they may constitute crucial targets for achieving significant advances in the management of the disease. Finally, we highlight the main challenges that are associated with the identification of clinically significant PCa biomarkers and recommend possible ways to overcome such limitations.

Introduction

Prostate cancer (PCa) is the most common type of malignancy in men over the age of 60 and the second leading cause of cancer-related mortality worldwide (Bray et al., 2018). Even though the majority of PCa patients are diagnosed with inert or extremely slow progressing disease, it has been estimated that approximately 20% of patients have a high-risk cancer that will progress to potentially lethal disease (Chang, Autio, Roach 3rd, & Scher, 2014). In addition, PCa is remarkably heterogeneous and can be subdivided into a number of intermediate clinical states, each of which may derive benefit from a different therapeutic modality. For example, active surveillance regimens are usually adopted for patients bearing tumors of low malignant potential or indolent disease, radiotherapy and radical prostatectomy surgery are employed for patients with localized disease, whereas cases with aggressive and metastatic cancer usually receive a combination of several targeted therapies such as hormonal therapy, radiotherapy, chemotherapy and immunotherapy (Leslie, Soon-Sutton, Sajjad, & Siref, 2020; Wilt, et al., 2012). Current treatment options include the chemotherapeutic drug cabazitaxel (de Bono et al., 2010), the two androgen signaling inhibitors abiraterone and enzalutamide (de Bono et al., 2011; Scher et al., 2012), the alpha-emitter bone-seeking radioisotope radium-233 (C. Parker et al., 2013; Wilson & Parker, 2016) and the immunotherapeutic drug Sipuleucel-T (Kantoff et al., 2010).

Androgen deprivation therapy (ADT), which involves suppression of the androgen receptor (AR), is the primary therapeutic approach in cases of metastatic disease; it is associated with high rates of progression-free survival (PFS) and clinical remissions usually lasting up to 2 years (Cheng, Lin, & Yu, 2012). However, a significant proportion of the patients receiving ADT (30-50%) eventually progress to castration-resistant prostate cancer (CRPC), which emerges from the adaptive response of prostate cancer cells to sustain a constitutively active AR in order to escape ADT; this may occur by either directly upregulating the AR or by intratumoral de novo steroid synthesis through CYP17 upregulation (Bryce & Antonarakis, 2016; Cai et al., 2011). Overall, the duration of response to initial ADT has been proposed as a prognostic factor, both for the efficacy of subsequent treatments using AR signaling inhibition and for clinical outcome; in particular, longer first-line ADT responses have been associated with longer radiographic PFS and better overall survival (OS) rates, as compared to shorter ADT responses (Angelergues et al., 2014; Bellmunt et al., 2016; Komura et al., 2018). Nonetheless, patients with advanced or metastatic CRPC (mCRPC) ultimately develop therapeutic resistance regardless of the treatment modality applied, have limited therapeutic options and a dismal prognosis (Gerritsen, 2012). In addition to abiraterone and enzalutamide, both of which have been shown to significantly improve survival in patients with mCRPC (de Bono et al., 2011; Scher et al., 2012), AR inhibitors apalutamide and darolutamide (originally approved by the FDA for the treatment of metastatic castration-sensitive PCa (mCSPC) and non-metastatic CRPC, respectively) are currently available for the treatment of high risk non-metastatic CRPC, in combination with ADT, with the aim to prevent and/or decrease disease progression to mCRPC and related mortality (Hellmis et al., 2021; Rajaram et al., 2020). However, despite substantial clinical evidence that these agents improve metastasis-free survival in all three PCa subtypes, they have also been associated with a number of unique side effects, especially in older patients, so their use in this particularly frail patient population comes with increasing awareness and a certain degree of diffidence (Feng & Graff, 2021).

In the era of precision medicine, the optimal implementation of rational combination treatments to biologically distinct patient subtypes is considered a necessary prerequisite for achieving the maximum therapeutic effect. As disease occurrence and progression in PCa are characterized by both complexity and heterogeneity, significant efforts are being made to identify the causative differentiators of disease pathogenesis; these have been found to be strongly dependent on an interplay between genetic variants, lifestyle, and environmental factors, the understanding of which has the potential to offer new prognostic and therapeutic capabilities (Lin, Chen, & B, S., 2017). In this respect, PCa is regarded as a function of genetic mutations or biomarkers and this also has direct consequences in the way that we view and design clinical trials (Renfro, An, & Mandrekar, 2017). As a result, trials are increasingly tailored so as to assess treatment efficacy in a patient sub-population that has been stratified on the basis of a known biomarker or a specific tumor genetic mutation, which may in turn apply to multiple disease subtypes. With the advent of immunotherapy, clinical trials have also began to include immune targeted biomarkers, many of which have already been approved for use by the FDA; for the treatment of PCa, Sipuleucel-T is currently the only FDA-approved immunotherapy option with demonstrated improvement of PFS (progression-free survival) or OS (overall survival) in clinical trials, yet numerous other molecules are also being investigated in an equally large number of clinical trials for their immunotherapeutic efficacy (Comiskey, Dallos, & Drake, 2018). Especially within the heterogeneous mCRPC group, the incorporation of clinically valuable prognostic and predictive biomarker stratification for appropriate patient selection is potentially amenable for the management of the therapeutic process and for the timely prevention of metastatic disease.

This review gives a detailed account of the current progress in the identification of the genomic events that can be used for the classification of PCa, for appropriate patient stratification and selection for clinical trials, for predicting prognosis and as major targets for therapeutic intervention. We present an extensive list of emerging biomarkers that have the potential to be implemented into clinical practice and to offer significant advances in the management of the disease. In addition, we discuss the major challenges associated with the identification of clinically valuable biomarkers for PCa, and propose possible solutions to overcoming these limitations.

Section snippets

Biomarkers of diagnostic and dual diagnostic/prognostic utility

As therapeutic decision-making, clinical trial design and outcome in PCa highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between indolent versus more aggressive disease (Rodrigues, et al., 2012). For this purpose, the National Comprehensive Cancer Network (NCCN) guidelines entail three basic clinical examination tests: the digital rectal exam (DRE), prostate-specific antigen (PSA) and Gleason score (Descotes, 2019; Hall, Lawton,

Genetic biomarkers

A significant and well-established risk factor for the development of PCa is familial history. In some families, the degree of genetic transmission is so high that the hereditary pattern seems to mimic an autosomal dominance trait (Lynch et al., 2016). Even though it has been suggested that environmental factors can lead to an overestimation of the hereditary impact on PCa, the role of genetic predisposition seems to play a pivotal role and remains independently significant even following

Challenges in identifying clinically significant PCa biomarkers and possible ways to overcome such limitations

One of the greatest challenges in identifying clinically valuable biomarkers for PCa is the multifocal nature of the disease, which is evidenced both as patient heterogeneity, even among the same disease subtype, and as inherent tumor heterogeneity. Tumor heterogeneity adds more complexity within the still heterogeneous group of patients, as it can occur both within the same tumor locus (intratumor heterogeneity) as well as among various tumor sites (intertumoral heterogeneity) (Boutros et al.,

Conclusions

The development of new technologies has greatly facilitated the characterization and subtyping of PCa at the genomic, transcriptomic, proteomic and metabolomic level, and has enhanced our understanding of the tumor microenvironment and of the pathways that are involved in disease progression and therapeutic resistance. A huge amount of data is emerging from next-generation sequencing and microarrays, leading to the discovery of a growing number of genetic aberrations with potential clinical

Declaration of Competing Interest

The authors declare no conflict of interest.

Acknowledgements

This study was co-funded by the European Regional Development Fund and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T1EDK-01404, project acronym and title: “NEOVIOPRO - Identification of new predictive biomarkers for prostate cancer”).

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