Secondary Logo

Share this article on:

Unfavorable Pathology, Tissue Biomarkers and Genomic Tests With Clinical Implications in Prostate Cancer Management

Nguyen, Jane Kim, MD, PhD*; Magi-Galluzzi, Cristina, MD, PhD*,†

doi: 10.1097/PAP.0000000000000192
Review Articles

Prostate cancer management has traditionally relied upon risk stratification of patients based on Gleason score, pretreatment prostate-specific antigen and clinical tumor stage. However, these factors alone do not adequately reflect the inherent complexity and heterogeneity of prostate cancer. Accurate and individualized risk stratification at the time of diagnosis is instrumental to facilitate clinical decision-making and treatment selection tailored to each patient. The incorporation of tissue and genetic biomarkers into current prostate cancer prediction models may optimize decision-making and improve patient outcomes. In this review we discuss the clinical significance of unfavorable morphologic features such as cribriform architecture and intraductal carcinoma of the prostate, tissue biomarkers and genomic tests and assess their potential use in prostate cancer risk assessment and treatment selection.

*Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic

Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH

The authors have no conflicts of interest to disclose.

Reprints: Cristina Magi-Galluzzi, MD, PhD, Pathology and Laboratory Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, L25, Cleveland, OH 44195 (e-mail: magic@ccf.org).All figures can be viewed online in color at www.anatomicpathology.com.

Prostate cancer is the most common noncutaneous malignancy affecting men in the western world, and the second leading cause of cancer death in men in the United States.1 Prostatic adenocarcinoma is a multifactorial disease influenced by both environmental and genetic factors. After advancing age and racial background, genetic susceptibility is a major contributor to prostate cancer.2,3 A meta-analysis of 33 independent studies has demonstrated a pooled rate ratio of 2.48 for men with a first-degree family history (ie, affected father or brother) and a 4.39 rate ratio for those with 2 or more affected first-degree family members.4 Twin studies have recently estimated a heritability of >50% for prostate cancer, much higher than other common noncutaneous cancers (eg, lung, breast, and colon cancer), whereas shared environment has negligible effect.5

Traditionally, management decisions in prostate cancer have relied upon risk stratification of patients based on 3 clinicopathologic variables: Gleason score (GS), pretreatment prostate-specific antigen (PSA) and clinical tumor stage. However, these factors alone do not adequately reflect the inherent complexity and heterogeneity of prostate cancer, potentially leading to inaccurate assessment of prognosis and suboptimal treatment decisions.

Accurate and individualized risk stratification at the time of diagnosis is considered the “Holy Grail” for facilitating clinical decision-making and treatment selection that is tailored to each patient. The incorporation of genetic biomarkers into current prostate cancer prediction models may optimize decision-making and improve patient outcomes. In this review, we provide an overview of new concepts in prostate cancer prognostic parameters with unfavorable morphologic features, novel biomarkers, and genomic tests with clinical implications in prostate cancer risk stratification, management and therapeutic response.

Back to Top | Article Outline

UNFAVORABLE PATHOLOGY

Traditional adverse prognostic parameters in needle biopsy (number of positive cores, amount of tumor in cores, etc.) and radical prostatectomy (stage, seminal vesicle invasion, variant histology, etc.) specimens are summarized in Tables 1 and 2, respectively. However, traditional histopathologic parameters are not the focus of this review. Instead we will discuss additional histopathologic patterns (cribriform architecture, intraductal carcinoma, and tumor stromal response) that are independently associated with adverse outcomes in prostate cancer.

TABLE 1

TABLE 1

TABLE 2

TABLE 2

The most widely accepted pathologic grading of prostate cancer is the GS, which is based on architectural features of the glands and is comprised of the sum of 2 Gleason patterns. The criteria for Gleason pattern assignment have evolved over the past 50 years. Currently, under the 2014 criteria, Gleason pattern 3 comprises only well-formed glands with a central lumen.6 More importantly, the small cribriform gland morphology is no longer included in the pattern 3 category, allowing for a more homogenous pattern 3 designation. Gleason pattern 4 includes fused, poorly formed, glomeruloid, and all cribriform glands (Fig. 1), independently of their size. Prognostic Grade Group categories ranging from 1 to 5 have been established, such that low risk tumors (GS 3+3=6) are designated as Grade Group 1.6–8 Validation studies have demonstrated that the Grade Group system provides more accurate grade stratification than the current Gleason system.9–11 GS 7 prostatic adenocarcinomas consisting of variable proportions of pattern 3 and pattern 4 are considered to be intermediate risk, and represent the most heterogenous group of neoplasms with diverse clinical outcomes. The Grade Groups prevent blending of GS 7 categories (3+4=7 and 4+3=7) which are more clearly separated as Grade Group 2 (3+4=7) and Grade Group 3 (4+3=7), respectively. However, new studies have suggested that prognostic stratification could be even more accurate with the incorporation of specific morphologic patterns. These data are compelling, as current guidelines in clinical practice have made a stronger push toward active surveillance for patients with favorable low-risk disease.12 Therefore, the threshold for distinguishing GS 3+3=6 from 3+4=7 carcinomas has become more important, as the scope of active surveillance has expanded to include even low volume GS 3+4=7, thereby necessitating discriminatory factors to identify unfavorable pathology.

FIGURE 1

FIGURE 1

Studies of large cohorts have repeatedly shown statistically significant differences in patient outcomes between different Grade Groups.9–11,13 However, recent data suggest that certain subsets of histologically distinct carcinoma patterns may be misclassified, leading to inaccurate risk stratification.14 The greatest variability can be observed within Grade Group 2 (3+4=7), where a small focus of “poorly formed glands” is assigned the same risk group designation as a small focus of “cribriform glands,” although the presence of cribriform glands has been associated with worse outcome.15–17 Accordingly, this distinction is relevant at initial diagnosis for the consideration of definitive therapy, that is, whether the cancer is clinically significant or not.

Given the overall heterogeneity of prostate cancer, studies have looked at the presence of various morphologic features to help discern clinically aggressive disease. There is robust evidence that the presence of morphologic features such as cribriform architecture (Fig. 1) and intraductal carcinoma of the prostate (IDC-P) (Fig. 2) are associated with aggressive disease and have significant clinical implications.18–21 Such tumor morphologies may be useful in predicting biochemical recurrence (BCR) in addition to traditional prognostic features such as GS, extraprostatic extension, seminal vesicle invasion, and margin status in men with high-grade prostate cancer following radical prostatectomy.19 Recent studies have shown that cribriform architecture/IDC-P is an independent parameter for BCR after radical prostatectomy, thereby suggesting the presence of cribriform architecture/IDC-P should act as exclusion criteria for active surveillance.17,22

FIGURE 2

FIGURE 2

The morphologic hallmarks of IDC-P include: (1) expansile growth of malignant cells filling prostatic ducts or large acini and (2) preservation of basal cells (Figs. 2, 3). The concept of IDC-P has evolved significantly and has been recently recognized as a distinct entity in the 2016 WHO blue book.23 The most widely accepted diagnostic criteria for IDC-P were proposed by Guo and Epstein24 and require the presence of solid (Fig. 4A) or dense cribriform (Fig. 4B) architecture, or loose cribriform (Fig. 4C) or micropapillary pattern (Fig. 4D) with nonfocal comedonecrosis (involving 2 or more glands) or marked nuclear atypia (nuclear size at least 6 times larger than adjacent benign nuclei) (Fig. 3). It is critical to distinguish IDC-P from high-grade prostatic intraepithelial neoplasia (HGPIN). Although dense cribriform and solid architecture is seen only in IDC-P, there are overlapping architectural similarities between IDC-P and HGPIN when dealing with the loose cribriform or micropapillary patterns; in such cases comedonecrosis or marked nuclear pleomorphism are necessary findings in establishing a diagnosis of IDC-P.

FIGURE 3

FIGURE 3

FIGURE 4

FIGURE 4

IDC-P is associated with adverse findings in radical prostatectomies, including high GS, large tumor volume, high pathologic stage, and is also an independent predictor of clinical outcomes.25–27 In addition, studies have shown that cribriform architecture/IDC-P are associated with lymph node metastasis.28 Taken together, both cribriform architecture/IDC-P are associated with aggressive disease and poor clinical outcomes.15,29,30 Furthermore, the presence of IDC-P on needle biopsy is a significant prognostic factor in patients with metastatic castration-resistant prostate cancer (mCRPC) at initial presentation.31 Kato and colleagues demonstrated that the presence of IDC-P on needle biopsy was the strongest prognostic parameter for cancer-specific survival and overall survival. Additional studies have shown that the presence of IDC-P is an independent prognosticator for clinical outcomes and could be a potential marker in predicting poor response to initial androgen deprivation therapy (ADT) and sequential docetaxel-based chemotherapy.20,21,32

Cribriform architecture/IDC-P is also associated with increased genomic instability together with chromosomal deletions of 3p13, 6q15, 8p21–23, 10q23, 13q14, 16q21-24, 18q21-23, and amplification of 8q24. The genetic derangements include several genes related to aggressive prostate cancer, such as loss of PTEN, RB1, TP53, and amplification of MYC. Altogether, these findings support the hypothesis that cribriform architecture/IDC-P is a specific morphologic substrate of genomic alterations associated with aggressive disease.33

Tumor stromal response has been shown to be discriminatory in patients with higher risk of recurrence.34 By definition, stromogenic prostate cancer requires at least 50% reactive stroma (stroma/epithelium ratio ≥1). Typically, the reactive stroma is disorganized, pale, loose and rich in extracellular matrix with infiltrating angulated and distorted glands.35 McKenney and colleagues determined that “stromogenic carcinoma” is independently predictive of lower recurrence-free survival in GS 3+3=6 and GS 3+4=7 tumors after adjusting for preoperative serum PSA, patient age, extraprostatic extension, seminal vesicle invasion, and margin status.14 Furthermore, detailed histomorphologic analysis of “stromogenic carcinoma” has made evident that GS 6 and 7 tumors have the greatest benefit from the predictive information provided by tumor stromal response in the prognostication of BCR and overall survival.35,36 Various studies have shown that “stromogenic carcinoma” is an independent marker for BCR-free survival and should be considered in the armamentarium for the prediction of unfavorable disease.35,37

Back to Top | Article Outline

TISSUE BIOMARKERS PREDICTING UPGRADING AND/OR SIGNIFICANT DISEASE

Historically, histopathologic findings associated with prostate cancer have been the most useful in predicting tumor biology and disease course. However, recent studies have shown that certain genomic biomarkers can independently discriminate and predict clinical outcomes in a way that outperforms traditional tumor grading and staging.38 Table 3 provides a summary of the pertinent tissue biomarkers discussed in this review.

TABLE 3

TABLE 3

Back to Top | Article Outline

SChLAP1

IDC-P is associated with a number of genetic derangements that can predict disease aggressiveness, some of which remains to be elucidated. Prensner et al44 identified SChLAP1 as the highest-ranked overexpressed gene in prostate cancer with metastatic progression by gene expression assay.45 Furthermore, SChLAP1 expression increased with cancer progression and independently predicted BCR after radical prostatectomy.46,47 In one of the largest and most rigorously analyzed multi-institutional cohorts to assess the clinical and biological impact of IDC-P in men with localized prostate cancer, Chua and colleagues found that cribriform architecture/IDC-P was associated with a 2 to 3-fold higher rate of biochemical failure, and a 4-fold higher rate of metastasis. In an effort to identify a molecular fingerprint for the cribriform architecture/IDC-P phenotype, the authors discovered that SChLAP1 was expressed at over threefold higher levels in cribriform architecture/IDC-P positive tumors compared with cribriform architecture/IDC-P negative ones. The authors proposed a model of prostate cancer pathogenesis, termed “nimbosus,” consisting of a constellation of genomic instability, SChLAP1 overexpression, and hypoxia which manifests as increased metastatic capacity and lethality.39 This work sets the stage for further understanding of the pathogenesis of clinically aggressive disease by characterizing the chronology of molecular “hits” in the evolution of cribriform architecture/IDC-P tumors.

An interesting concept of field-wide changes in the prostate cancer microenvironment has emerged with the finding of diffuse expression of SChLAP1 by in situ hybridization or immunohistochemistry in both cribriform architecture/IDC-P and adjacent invasive acinar adenocarcinoma, suggesting that a common clonal ancestor to both histopathologies exists.48 Could SChLAP1 dysregulation and genomic instability represent early field-wide molecular aberrations that are responsible for driving the development of clonal prometastatic cribriform architecture/IDC-P and invasive acinar adenocarcinoma? This concept of field cancerization has been proposed by other investigators,40 who have suggested a model of retrograde colonization of prostatic ducts where there is a clonal relationship of IDC-P with adjacent invasive acinar adenocarcinoma. Haffner and colleagues demonstrated identical TMPRSS2-ERG breakpoints in IDC-P and adjacent invasive acinar adenocarcinoma in a subset of prostate cancer cases. Also, the majority of IDC-P showed loss of PTEN, similar to the adjacent invasive acinar adenocarcinoma, further supporting a model for retrograde invasion in the pathogenesis of IDC-P.40

Back to Top | Article Outline

ERG and PTEN

ERG gene rearrangements resulting in the TMPRSS2-ERG gene fusion is commonly found in prostate cancer,49,50 but detected only in ∼20% of HGPIN lesions.51 A study of borderline intraductal proliferations in radical prostatectomy specimens has shown that isolated lesions and HGPIN were entirely negative for ERG, while cancer-associated lesions and IDC-P were highly enriched (75%) for ERG gene rearrangement.51,52 In addition, a strong concordance with ERG gene fusion in IDC-P and adjacent invasive adenocarcinomas has been demonstrated.51

PTEN is a key tumor suppressor gene often deleted or inactivated in prostate cancer.53 Multiple studies have shown that PTEN loss is associated with adverse pathologic features and poor prognosis.54,55 Recently, Lotan’s group56–58 group reported that the majority of IDC-P cases demonstrated PTEN protein loss and ERG protein expression, whereas isolated HGPIN lesions failed to demonstrate PTEN protein loss with only 13% showing ERG protein expression. Thus, ERG protein expression and PTEN protein loss may help distinguishing IDC-P from HGPIN.

PTEN protein loss in prostate cancer has been found to be strongly associated with shorter recurrence-free survival after radical prostatectomy.59 In particular, PTEN loss demonstrated at the time of biopsy diagnosis is a strong indicator of disease progression and poor prognosis.60,61 Studies have evaluated immunohistochemical loss of PTEN expression in high-risk patients status after radical prostatectomy62 and have demonstrated PTEN to be an independent prognostic factor for progression-free survival.63,64 In low-risk patient cohorts PTEN immunohistochemical loss has been shown to be a strong independent predictor for prostate cancer survival by univariate analysis.65 Few studies have shown by multivariate analyses, after adjusting for age, preoperative PSA, clinical stage and race, that GS 6 tumors with PTEN protein loss on prostate needle biopsy were significantly more likely to be upgraded to GS 7 at radical prostatectomy compared with those without PTEN loss.62,66 These data suggest that careful consideration of genetic biomarker status, particularly PTEN protein loss at the time of prostate cancer diagnosis, may add prognostic information and influence clinical decision-making and treatment selection.

PTEN loss and chromosome 8p/8q alterations have been associated with aggressive disease. As such, Trock and colleagues evaluated whether measurement of PTEN gene or protein, chromosome 8q (MYC) gain, and 8p (LPL) loss could identify a more aggressive form of Gleason pattern 3 tumors. They concluded that PTEN protein loss, MYC/8q gain or LPL/8p loss in a Gleason pattern 3 tumor core is a strong indicator that the core comes from a Gleason 7 tumor, and more frequently occurs in GS 4+3=7 (Grade Group 3) than 3+4=7 (Grade Group 2) tumors. These results further support the idea of tumor clonality and suggest that Gleason pattern 3 in a GS 7 tumor is biologically distinct from Gleason pattern 3 from a GS 6 tumor. PTEN protein loss was more common in GS 6 tumors that were upgraded at radical prostatectomy.41

Back to Top | Article Outline

DNA METHYLATION

New evidence for an association between cribriform architecture and/or IDC-P and methylation biomarkers have emerged. A recent study examined the prognostic capability of DNA methylation biomarkers along with histologic evaluation of cribriform architecture and IDC-P patterns. Olkhov-Mitsel et al42 identified aberrant DNA methylation in tumor areas corresponding to specific tumor architectural features. Specifically, the increase in APC, RASSF1, and TBX15 methylation was shown to be associated with cribriform architecture/IDC-P. These data suggest the possibility of utilizing tissue-specific DNA methylation alterations as molecular indicators of cribriform architecture/IDC-P.

Back to Top | Article Outline

BRCA2

At the present time, genetic evaluation guidelines for prostate cancer primarily focus on BRCA1 and BRCA2 testing. Germline mutations in the BRCA2 tumor suppressor are associated with both an increased lifetime risk of developing prostate cancer and increased risk of aggressive disease. BRCA2-mutant prostate cancer harbors increased genomic instability and a mutational profile that more closely resembles metastatic than localized disease. BRCA2-mutant prostate cancer shows genomic and epigenomic dysregulation of the MED12L/MED12 axis, which is frequently dysregulated in mCRPC. This dysregulation is enriched in BRCA2-mutant prostate cancer with IDC-P.67

Recently, the presence of IDC-P was shown to be independently associated with overall survival in BRCA2 carriers and BRCAX patients, resulting in poorer outcome.43 This finding highlights the importance of recognition of IDC-P in BRCA2 carriers, who are already known to have poor overall survival, and suggests that IDC-P may be a useful new clinical marker in these patients.

Back to Top | Article Outline

TISSUE-BASED GENOMIC TESTS FOR DIAGNOSIS AND PROGNOSIS

There is an increased need for reliable biomarkers to complement and improve upon conventional risk assessment tools to aid in decision-making, particularly in challenging clinical settings. Several diagnostic and prognostic innovative biomarker panel tests have been introduced in the last decade. Diagnostic tests to guide biopsy decisions include PHI, 4K score, SelectMDx, ConfirmMDx, PCA3, MiPS, and ExoDX. Of those, ConfirmMDx is the only tissue-based assay. Prognostic tests that have been used to aid in treatment selection (ie, definitive treatment vs. active surveillance) include OncotypeDX GPS, Prolaris, ProMark, DNA-ploidy, and Decipher.68,69 The tests supported by the highest level of evidence and in widespread clinical use are herein reviewed (Table 4); although the ordering of these tests currently varies based on treating clinician or institution.

TABLE 4

TABLE 4

Back to Top | Article Outline

ConfirmMDx

ConfirmMDx (MDx Health, Irvine) is a commercially available test that detects the epigenetic field effect (halo) associated with the cancerization process. The test analyzes the DNA methylation level of GSTP1 (glutathion-S-transferase P1), APC (adenomatous polyposis coli), and RASSF1 (Ras association domain-containing protein 1) in cells adjacent to prostate cancer.70,71 The test aims to decrease the number of unnecessary repeat biopsies in patients with a previous negative biopsy.72 A negative test can safely spare a patient from biopsies with an 88% to 90% negative predictive value.70,71 Recently, a novel algorithm, EpiScore, has been developed to better stratify methylation-positive men at risk of significant (GS ≥7) occult disease with a negative predictive value of 96% for high-grade prostate cancer.73 Although long-term data are necessary to further evaluate the clinical utility of the test, ConfirmMDx is included in the National Comprehensive Cancer Network (NCCN) guidelines for men with at least 1 prior negative biopsy, before repeat biopsy.74

Back to Top | Article Outline

OncotypeDX

OncotypeDX Genomic Prostate Score (GPS) is a quantitative real-time polymerase chain reaction assay measuring the RNA expression of 12 cancer genes related to androgen signaling, cellular organization, proliferation and stromal response, normalized to 5 reference genes.75–77 The test was designed to be performed on paraffin-embedded needle biopsy tissue containing at least 1 mm in length of tumor; a commercial test for postprostatectomy risk stratification is not available.78 The GPS is expressed on a scale of 0 to 100 and a low GPS indicates higher likelihood of favorable pathology. The primary endpoint of the test is to predict the risk of adverse disease at radical prostatectomy.78 GPS aims to improve risk stratification over widely used clinical risk stratification tools [Cancer of the Prostate Risk Assessment (CAPRA), NCCN, and American Urological Association/European Association of Urology (AUA/EAU)] for men newly diagnosed with low or intermediate risk prostate cancer (GS 3+3=6 or low volume GS 3+4=7) on needle biopsy.79 In multivariable analysis, the GPS was able to predict high-grade and high-stage disease even after adjusting for the multivariable CAPRA score.76,79 Subsequently, GPS has been shown to significantly predict time to BCR.80 In a recent study, Van den Eeden and colleagues reported that GPS improved the accuracy of predicting time to metastasis and time to prostate cancer specific death compared with CAPRA and NCCN.81 The authors found that none of the men with very low-risk or low-risk prostate cancer and a GPS <20 developed metastases or died of their cancer in the next 10 years. As tumor heterogeneity and multifocality were addressed in the study design, GPS could reduce the risk of biopsy undersampling. The assay may help guide clinicians in selecting candidates for active surveillance versus therapeutic intervention by predicting adverse pathologic features at radical prostatectomy.76,80 OncotypeDX is currently included as a potential tool in the NCCN guidelines for men with postbiopsy NCCN very low and low-risk prostate cancer, with 10 to 20 years of life expectancy, who are considering active surveillance.74 According to current AUA guidelines, OncotypeDX has not yet been proven to have a major role in the selection of active surveillance candidates (Expert Opinion).82,83 The actual clinical benefit of the test is limited by a lack of large prospective studies evaluating the correlation with oncologic outcome.

Back to Top | Article Outline

PROLARIS

Prolaris is a quantitative real-time polymerase chain reaction assay measuring the average RNA expression of 31 cell cycle progression genes normalized to 15 housekeeping genes to generate a cell cycle progression score (CCP-score).84–86 The more aggressive the prostate cancer, the faster the rate of cell division/proliferation and the higher the Prolaris CCP-score. This gene signature can be determined on limited formalin-fixed paraffin-embedded tissue (with prostate cancer measuring >0.5 mm) obtained either by prostate biopsy or radical prostatectomy. The primary endpoint of the test is 10-year risk of prostate cancer death with conservative management.78 When the test is performed on biopsy tissue from low-risk prostate cancer patients, it may help in distinguishing suitable candidates for active surveillance from men best given definitive treatment.87,88 When the test is performed on prostate tissue after surgery, it helps determine if adjuvant treatment is indicated. The score has been validated and shown to add predictive value to the CAPRAs score postoperative risk model.89 The CCP-score generated from prostate biopsy samples from patients who underwent radical prostatectomy was significantly associated with BCR and metastasis.87 Low expression is associated with low risk of disease progression. Several studies have explored the role of the CCP-score on treatment decision-making90–92 and the results indicate that the score may improve prostate cancer risk stratification and reduce unnecessary treatments. In contrast, others studies point out the uncertain benefit of the CCP-score.93–95 The accuracy of the test depends on accuracy of the biopsy and may add unnecessary expense in following very low–risk prostate cancer patients. Current EAU guidelines state that prospective multicenter trials are necessary before a final recommendation can be made.96 Similar to OncotypeDx, the CCP-score is currently included as a potential tool in the NCCN guidelines for men with postbiopsy NCCN very-low and low-risk prostate cancer, with a life expectancy of 10 years or more, who are considering active surveillance as the preferred treatment option.74 Current AUA guidelines state that the CCP-score has not yet been proven to have a major role in the selection of active surveillance candidates (Expert Opinion).82,83

Back to Top | Article Outline

DECIPHER

High-risk prostate cancer poses a significant challenge regarding the ideal treatment approach. Currently, there is a great deal of debate over which prostate cancer patient benefit most from adjuvant treatment following localized treatment. Decipher is a signature developed and initially validated on formalin-fixed paraffin-embedded tissue tissue from radical prostatectomy specimens to predict early metastatic progression of localized prostate cancer.97–101 The Decipher Genomic Classifier consists of 22 genes at the mRNA level that are prognostic for metastatic progression and relate to cell adhesion migration, tumor motility, immune system modulation, cell cycle control, cellular differentiation, and androgen signaling.78 The Genomic Classifier outputs a score between 0 and 1 at increments of 0.1, representing a 10% increase in metastatic risk. The Genomic Classifier score predicts BCR, metastasis and prostate cancer specific mortality after radical prostatectomy38,102–107 and provides additional information that can aid in patient decision-making regarding adjuvant or salvage therapy.108,109 PRO_IMPACT is a multi-institutional prospective study to determine the clinical utility of Genomic Classifier in the postoperative setting.110 Recently, the Genomic Classifier score has been evaluated also in prostate biopsy samples.111,112 On multivariable analysis, including clinical pathologic variables, only the Genomic Classifier score was independently predictive of clinical progression in patients undergoing primary radiation therapy for prostate cancer.113

Back to Top | Article Outline

GENOMIC MARKERS OF RESPONSE/RESISTANCE TO THERAPY

Recent technological advances have raised the possibility of extending the use of molecular biomarkers in advanced prostate cancer disease by monitoring metastatic tumor burden, response, and resistance to therapy.114 Novel liquid biopsy approaches, such as circulating tumor cells (CTCs) in blood and circulating cell-free tumor DNA (cfDNA) in plasma, have been utilized as predictive biomarkers in metastatic CRPC and might support the advent of an individualized oncological approach in the nearer future. CTC may serve as a surrogate marker for treatment efficacy in CRPC patients. Studies have demonstrated the potential use of molecular analysis of CTCs in monitoring and predicting response to therapy. cfDNA testing can serve as an early indicator of recurrence, resistance, or metastasis.115 Exosomal RNAs is also another potential source for tumor genetic material. These molecular tests could impact clinical utility by reducing drugs toxicity, improving treatment selection and patients survival, and enhancing cost-effectiveness by reducing the use of ineffective drugs.116

Back to Top | Article Outline

cfDNA

cfDNA represents a noninvasive biomarker that can be isolated from human plasma, serum and other body fluids. Circulating tumor DNA shed from primary and metastatic tumors, primarily through apoptosis and/or necrosis of tumor cells, may allow real-time noninvasive serial monitoring of tumor genomes during treatment and disease progression through “liquid biopsies.” “Liquid biopsy” may unravel genetic and epigenetic alterations involved in the metastatic process and allow tracking of emerging subclones of tumor cells resistant to therapy.114,117

Back to Top | Article Outline

AR-V7

The standard treatment for metastatic and locally advanced prostate cancer is ADT. However, despite an initial response, most patients will eventually progress to and die of CRPC within a few years. Recently, various mechanisms of resistance to androgen receptor (AR)-targeting agents have been reported, including the AR splice variant 7 (AR-V7), a constitutionally active variant that lacks the ligand-binding domain, the target of enzalutamide and abiraterone.118 In small size studies, the expression of AR-V7 in CTCs has emerged as a potential predictive biomarker indicative of resistance to AR pathway inhibitors and retained sensitivity to taxanes in mCRPC.119–124 Consequently, the detection of AR-V7 in peripheral blood has been utilized to predict sensitivity or resistance to specific cancer treatment and guide clinical management by identifying patients more likely to benefit from alternative approaches. However, recent studies have failed to find any correlation between outcomes and AR-V7 expression.125,126 Therefore, the predictive clinical utility of AR-V7 expression in advanced CRPC remains uncertain. Larger prospective studies are necessary before AR-V7 expression can be used to guide treatment.

Recently, AR-V7 expression by immunohistochemistry has been evaluated in prostate biopsy tissue from men newly diagnosed with locally advanced or metastatic prostate cancer.127 Patients with AR-V7 positive tumors had significantly lower PSA response rates to ADT and shorter time to CRPC progression after ADT compared with men with AR-V7 negative tumors. Additional prospective, large-scale trials are warranted before AR-V7 detection on tissue can be considered for prognostic assessment in newly diagnosed prostate cancer patients who are planning to receive ADT.

Back to Top | Article Outline

3β-HYDROXYSTEROID DEHYDROGENASE TYPE 1 (3βHSD1)

Growth of prostate cancer cells is dependent on the androgen stimulation of the AR. Dihydrotestosterone (DHT) is the most potent androgen. 3βHSD1, encoded by the HSD3B1 gene, catalyzes the initial step in the conversion of adrenal-derived steroid dehydroepiandrosterone to DHT.128,129 A common inherited germline polymorphic variant (1245A→C) in the HSD3B1 gene encodes for a gain-of-function in 3βHSD1 leading to increased DHT synthesis from nongonadal precursors and higher concentrations of DHT compared with patients with wild-type HSD3B1 (1245A) inheritance.130 The allelic frequency of the HSD3B1 (1245C) variant ranged from 26% to 36% in different cohorts. In the study by Hearn et al,130 presence of 1 or 2 variant alleles of the HSD3B1 (1245C) was associated with decreased progression-free survival compared with the absence of the variant alleles. Independent cohorts have shown that patients with the HSD3B1 (1245C) variant have a shorter duration of response to ADT in hormone-sensitive prostate cancer and more rapid disease progression to CRPC.130–133

HSD3B1 genotype may represent the first predictive biomarker of response to therapy for patients newly diagnosed with metastatic hormone-sensitive prostate cancer. Patients homozygous for the variant allele HSD3B1 (1245C) (∼10% of the population) are likely to have suboptimal response to ADT alone and may benefit from up-front docetaxel treatment or from enrollment in clinical trials investigating novel androgen-signaling inhibitors. A Cleveland Clinic Phase II trial (NCT02770391) is currently enrolling men with newly diagnosed intermediate or high-risk prostate cancer and scheduled to undergo radical prostatectomy into 3 groups based on their HSD3B1 genotype.

Back to Top | Article Outline

CONCLUSIONS

The goal of identification of unfavorable pathology, genomic tests, and biomarkers is to not only accurately predict clinically aggressive disease, but also correctly stratify individual patient’s risk and optimize treatment modality. The detection of cribriform architecture and/or IDC-P on needle biopsy excludes the patient from active surveillance and is associated with poor prognostic features. Multifocality and intratumoral/intertumoral prostate cancer heterogeneity are essential challenges accounting for some of the limitations of the classification tools currently available. Both pathologic features detected on prostate biopsy specimens and genomic tests performed on biopsy tissue are somewhat limited by how accurately the samples reflect the biology of the entire tumor lesion. Multiparametric magnetic resonance imaging and ultrasound fusion biopsies may improve the detection of high-grade prostate cancer and help address the multifocality and heterogeneity issue.

Novel liquid biopsy techniques may allow a snap-shot of metastatic prostate cancer and expand the use of molecular biomarkers to advanced disease by monitoring tumor burden and response and resistance to therapy. Specific genotypes, such as HSD3B1, have the potential to become predictive biomarkers of response to therapy for patients with new onset metastatic prostate cancer.

Back to Top | Article Outline

REFERENCES

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67:7–30.
2. DeSantis CE, Siegel RL, Sauer AG, et al. Cancer statistics for African Americans, 2016: progress and opportunities in reducing racial disparities. CA Cancer J Clin. 2016;66:290–308.
3. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66:7–30.
4. Kicinski M, Vangronsveld J, Nawrot TS. An epidemiological reappraisal of the familial aggregation of prostate cancer: a meta-analysis. PLoS ONE. 2011;6:e27130.
5. Mucci LA, Hjelmborg JB, Harris JR, et al. Familial risk and heritability of cancer among twins in nordic countries. JAMA. 2016;315:68–76.
6. Epstein JI, Egevad L, Amin MB, et al. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason grading of prostatic carcinoma: definition of grading patterns and proposal for a new grading system. Am J Surg Pathol. 2016;40:244–252.
7. Magi-Galluzzi C, Montironi R, Epstein JI. Contemporary Gleason grading and novel Grade Groups in clinical practice. Curr Opin Urol. 2016;26:488–492.
8. Epstein JI, Amin MB, Reuter VE, et al. Contemporary Gleason Grading of prostatic carcinoma: an update with discussion on practical issues to implement the 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma. Am J Surg Pathol. 2017;41:e1–e7.
9. Epstein JI, Zelefsky MJ, Sjoberg DD, et al. A contemporary prostate cancer grading system: a validated alternative to the Gleason Score. Eur Urol. 2016;69:428–435.
10. Spratt DE, Cole AI, Palapattu GS, et al. Independent surgical validation of the new prostate cancer grade-grouping system. BJU Int. 2016;118:763–769.
11. Berney DM, Beltran L, Fisher G, et al. Validation of a contemporary prostate cancer grading system using prostate cancer death as outcome. Br J Cancer. 2016;114:1078–1083.
12. Perlis N, Klotz L. Contemporary active surveillance: candidate selection, follow-up tools, and expected outcomes. Urol Clin North Am. 2017;44:565–574.
13. Leapman MS, Cowan JE, Simko J, et al. Application of a prognostic Gleason grade grouping system to assess distant prostate cancer outcomes. Eur Urol. 2017;71:750–759.
14. McKenney JK, Wei W, Hawley S, et al. Histologic grading of prostatic adenocarcinoma can be further optimized: analysis of the relative prognostic strength of individual architectural patterns in 1275 patients from the Canary Retrospective Cohort. Am J Surg Pathol. 2016;40:1439–1456.
15. Kweldam CF, Kummerlin IP, Nieboer D, et al. Disease-specific survival of patients with invasive cribriform and intraductal prostate cancer at diagnostic biopsy. Mod Pathol. 2016;29:630–636.
16. Kweldam CF, Wildhagen MF, Steyerberg EW, et al. Cribriform growth is highly predictive for postoperative metastasis and disease-specific death in Gleason score 7 prostate cancer. Mod Pathol. 2015;28:457–464.
17. Choy B, Pearce SM, Anderson BB, et al. Prognostic significance of percentage and architectural types of contemporary Gleason pattern 4 prostate cancer in radical prostatectomy. Am J Surg Pathol. 2016;40:1400–1406.
18. Iczkowski KA, Paner GP, Van der Kwast T. The new realization about cribriform prostate cancer. Adv Anat Pathol. 2018;25:31–37.
19. Flood TA, Schieda N, Sim J, et al. Evaluation of tumor morphologies and association with biochemical recurrence after radical prostatectomy in grade group 5 prostate cancer. Virchows Arch. 2018;472:205–212.
20. Porter LH, Hashimoto K, Lawrence MG, et al. Intraductal carcinoma of the prostate can evade androgen deprivation, with emergence of castrate-tolerant cells. BJU Int. 2017. Doi: 10.1111/bju.14043. [Epub ahead of print].
21. Zhao J, Shen P, Sun G, et al. The prognostic implication of intraductal carcinoma of the prostate in metastatic castration-resistant prostate cancer and its potential predictive value in those treated with docetaxel or abiraterone as first-line therapy. Oncotarget. 2017;8:55374–55383.
22. Kweldam CF, Kummerlin IP, Nieboer D, et al. Presence of invasive cribriform or intraductal growth at biopsy outperforms percentage grade 4 in predicting outcome of Gleason score 3+4=7 prostate cancer. Mod Pathol. 2017;30:1126–1132.
23. Epstein JI, Oxley J, Ro JY, et alMoch H, Humphrey PA, Ulbright TM, Reuter VE. Intraductal carcinoma. WHO Classification of Tumors of the Urinary System and Male Genital Organs. Lyon: IARC; 2016:164–165.
24. Guo CC, Epstein JI. Intraductal carcinoma of the prostate on needle biopsy: Histologic features and clinical significance. Mod Pathol. 2006;19:1528–1535.
25. Zhao T, Liao B, Yao J, et al. Is there any prognostic impact of intraductal carcinoma of prostate in initial diagnosed aggressively metastatic prostate cancer? Prostate. 2015;75:225–232.
26. Watts K, Li J, Magi-Galluzzi C, et al. Incidence and clinicopathological characteristics of intraductal carcinoma detected in prostate biopsies: a prospective cohort study. Histopathology. 2013;63:574–579.
27. Robinson BD, Epstein JI. Intraductal carcinoma of the prostate without invasive carcinoma on needle biopsy: emphasis on radical prostatectomy findings. J Urol. 2010;184:1328–1333.
28. Kryvenko ON, Gupta NS, Virani N, et al. Gleason score 7 adenocarcinoma of the prostate with lymph node metastases: analysis of 184 radical prostatectomy specimens. Arch Pathol Lab Med. 2013;137:610–617.
29. Porter LH, Lawrence MG, Ilic D, et al. Systematic review links the prevalence of intraductal carcinoma of the prostate to prostate cancer risk categories. Eur Urol. 2017;72:492–495.
30. Kato M, Tsuzuki T, Kimura K, et al. The presence of intraductal carcinoma of the prostate in needle biopsy is a significant prognostic factor for prostate cancer patients with distant metastasis at initial presentation. Mod Pathol. 2016;29:166–173.
31. Trudel D, Downes MR, Sykes J, et al. Prognostic impact of intraductal carcinoma and large cribriform carcinoma architecture after prostatectomy in a contemporary cohort. Eur J Cancer. 2014;50:1610–1616.
32. Chen Z, Chen N, Shen P, et al. The presence and clinical implication of intraductal carcinoma of prostate in metastatic castration resistant prostate cancer. Prostate. 2015;75:1247–1254.
33. Bottcher R, Kweldam CF, Livingstone J, et al. Cribriform and intraductal prostate cancer are associated with increased genomic instability and distinct genomic alterations. BMC Cancer. 2018;18:8–18.
34. Ayala G, Frolov A, Ittman M, et al. Biological correlates of biochemical recurrence free survival using multiple markers in a large tissue microarray cohort. Ann Clin Lab Sci. 2013;43:11–21.
35. Yanagisawa N, Li R, Rowley D, et al. Stromogenic prostatic carcinoma pattern (carcinomas with reactive stromal grade 3) in needle biopsies predicts biochemical recurrence-free survival in patients after radical prostatectomy. Hum Pathol. 2007;38:1611–1620.
36. De Vivar AD, Sayeeduddin M, Rowley D, et al. Histologic features of stromogenic carcinoma of the prostate (carcinomas with reactive stroma grade 3). Hum Pathol. 2017;63:202–211.
37. Ayala GE, Muezzinoglu B, Hammerich KH, et al. Determining prostate cancer-specific death through quantification of stromogenic carcinoma area in prostatectomy specimens. Am J Pathol. 2011;178:79–87.
38. Spratt DE, Yousefi K, Deheshi S, et al. Individual patient-level meta-analysis of the performance of the Decipher Genomic Classifier in high-risk men after prostatectomy to predict development of metastatic disease. J Clin Oncol. 2017;35:1991–1998.
39. Chua MLK, Lo W, Pintilie M, et al. A prostate cancer “Nimbosus”: genomic instability and SChLAP1 dysregulation underpin aggression of intraductal and cribriform subpathologies. Eur Urol. 2017;72:665–674.
40. Haffner MC, Weier C, Xu MM, et al. Molecular evidence that invasive adenocarcinoma can mimic prostatic intraepithelial neoplasia (PIN) and intraductal carcinoma through retrograde glandular colonization. J Pathol. 2016;238:31–41.
41. Trock BJ, Fedor H, Gurel B, et al. PTEN loss and chromosome 8 alterations in Gleason grade 3 prostate cancer cores predicts the presence of un-sampled grade 4 tumor: implications for active surveillance. Mod Pathol. 2016;29:764–771.
42. Olkhov-Mitsel E, Siadat F, Kron K, et al. Distinct DNA methylation alterations are associated with cribriform architecture and intraductal carcinoma in Gleason pattern 4 prostate tumors. Oncol Lett. 2017;14:390–396.
43. Risbridger GP, Taylor RA, Clouston D, et al. Patient-derived Xenografts reveal that intraductal carcinoma of the prostate is a prominent pathology in BRCA2 mutation carriers with prostate cancer and correlates with poor prognosis. Eur Urol. 2015;67:496–503.
44. Prensner JR, Iyer MK, Sahu A, et al. The long noncoding RNA SChLAP1 promotes aggressive prostate cancer and antagonizes the SWI/SNF complex. Nat Genet. 2013;45:1392–1398.
45. Prensner JR, Zhao S, Erho N, et al. RNA biomarkers associated with metastatic progression in prostate cancer: a multi-institutional high-throughput analysis of SChLAP1. Lancet Oncol. 2014;15:1469–1480.
46. Mehra R, Shi Y, Udager AM, et al. A novel RNA in situ hybridization assay for the long noncoding RNA SChLAP1 predicts poor clinical outcome after radical prostatectomy in clinically localized prostate cancer. Neoplasia. 2014;16:1121–1127.
47. Mehra R, Udager AM, Ahearn TU, et al. Overexpression of the long non-coding RNA SChLAP1 independently predicts lethal prostate cancer. Eur Urol. 2016;70:549–552.
48. Cooper CS, Eeles R, Wedge DC, et al. Analysis of the genetic phylogeny of multifocal prostate cancer identifies multiple independent clonal expansions in neoplastic and morphologically normal prostate tissue. Nat Genet. 2015;47:367–372.
49. Tomlins SA, Laxman B, Varambally S, et al. Role of the TMPRSS2-ERG gene fusion in prostate cancer. Neoplasia. 2008;10:177–188.
50. Perner S, Mosquera JM, Demichelis F, et al. TMPRSS2-ERG fusion prostate cancer: an early molecular event associated with invasion. Am J Surg Pathol. 2007;31:882–888.
51. Han B, Suleman K, Wang L, et al. ETS gene aberrations in atypical cribriform lesions of the prostate: implications for the distinction between intraductal carcinoma of the prostate and cribriform high-grade prostatic intraepithelial neoplasia. Am J Surg Pathol. 2010;34:478–485.
52. Shah RB, Zhou M. Atypical cribriform lesions of the prostate: clinical significance, differential diagnosis and current concept of intraductal carcinoma of the prostate. Adv Anat Pathol. 2012;19:270–278.
53. Krohn A, Diedler T, Burkhardt L, et al. Genomic deletion of PTEN is associated with tumor progression and early PSA recurrence in ERG fusion-positive and fusion-negative prostate cancer. Am J Pathol. 2012;181:401–412.
54. Downes MR, Satturwar S, Trudel D, et al. Evaluation of ERG and PTEN protein expression in cribriform architecture prostate carcinomas. Pathol Res Pract. 2017;213:34–38.
55. Lahdensuo K, Erickson A, Saarinen I, et al. Loss of PTEN expression in ERG-negative prostate cancer predicts secondary therapies and leads to shorter disease-specific survival time after radical prostatectomy. Mod Pathol. 2016;29:1565–1574.
56. Lotan TL, Gumuskaya B, Rahimi H, et al. Cytoplasmic PTEN protein loss distinguishes intraductal carcinoma of the prostate from high-grade prostatic intraepithelial neoplasia. Mod Patho. 2013;26:587–603.
57. Morais CL, Guedes LB, Hicks J, et al. ERG and PTEN status of isolated high-grade PIN occurring in cystoprostatectomy specimens without invasive prostatic adenocarcinoma. Hum Pathol. 2016;55:117–125.
58. Morais CL, Han JS, Gordetsky J, et al. Utility of PTEN and ERG immunostaining for distinguishing high-grade PIN from intraductal carcinoma of the prostate on needle biopsy. Am J Surg Pathol. 2015;39:169–178.
59. Lotan TL, Wei W, Morais CL, et al. PTEN loss as determined by clinical-grade immunohistochemistry assay is associated with worse recurrence-free survival in prostate cancer. Eur Urol Focus. 2016;2:180–188.
60. Lokman U, Erickson AM, Vasarainen H, et al. PTEN loss but not ERG expression in diagnostic biopsies is associated with increased risk of progression and adverse surgical findings in men with prostate cancer on active surveillance. Eur Urol Focus. 2017; pii:S2405-4569(17)30072-X. [Epub ahead of print].
61. Guedes LB, Tosoian JJ, Hicks J, et al. PTEN loss in Gleason Score 3 + 4 = 7 prostate biopsies is associated with nonorgan confined disease at radical prostatectomy. J Urol. 2017;197:1054–1059.
62. Lotan TL, Carvalho FL, Peskoe SB, et al. PTEN loss is associated with upgrading of prostate cancer from biopsy to radical prostatectomy. Mod Pathol. 2015;28:128–137.
63. Antonarakis ES, Keizman D, Zhang Z, et al. An immunohistochemical signature comprising PTEN, MYC, and Ki67 predicts progression in prostate cancer patients receiving adjuvant docetaxel after prostatectomy. Cancer. 2012;118:6063–6071.
64. Ahearn TU, Pettersson A, Ebot EM, et al. A prospective investigation of PTEN loss and ERG expression in lethal prostate cancer. J Natl Cancer Inst. 2016;108.
65. Cuzick J, Yang ZH, Fisher G, et al. Prognostic value of PTEN loss in men with conservatively managed localised prostate cancer. Br J Cancer. 2013;108:2582–2589.
66. Carvalho FL, Lotan TL, Peskoe SB, et al. Association of PTEN protein loss with upgrading of prostate cancer from biopsy to radical prostatectomy. J Clin Oncol. 2014;32:127.
67. Taylor RA, Fraser M, Livingstone J, et al. Germline BRCA2 mutations drive prostate cancers with distinct evolutionary trajectories. Nat Commun. 2017;8.
68. Kretschmer A, Tilki D. Biomarkers in prostate cancer—current clinical utility and future perspectives. Crit Rev Oncol Hematol. 2017;120:180–193.
69. Cucchiara V, Cooperberg MR, Dall’Era M, et al. Genomic markers in prostate cancer decision making. Eur Urol. 2018;73:572–582.
70. Partin AW, Van Neste L, Klein EA, et al. Clinical validation of an epigenetic assay to predict negative histopathological results in repeat prostate biopsies. J Urol. 2014;192:1081–1087.
71. Stewart GD, Van Neste L, Delvenne P, et al. Clinical utility of an epigenetic assay to detect occult prostate cancer in histopathologically negative biopsies: results of the MATLOC study. J Urol. 2013;189:1110–1116.
72. Wojno KJ, Costa FJ, Cornell RJ, et al. Reduced rate of repeated prostate biopsies observed in ConfirmMDx clinical utility field study. Am Health Drug Benefits. 2014;7:129–134.
73. Van Neste L, Partin AW, Stewart GD, et al. Risk score predicts high-grade prostate cancer in DNA-methylation positive, histopathologically negative biopsies. Prostate. 2016;76:1078–1087.
74. The National Comprehensive Cancer Network. NCCN Guidelines Version 2.2017 Prostate Cancer, NCCN, 2017.
75. Cullen J, Rosner IL, Brand TC, et al. A biopsy-based 17-gene Genomic Prostate Score predicts recurrence after radical prostatectomy and adverse surgical pathology in a racially diverse population of men with clinically low- and intermediate-risk prostate cancer. Eur Urol. 2015;68:123–131.
76. Klein EA, Cooperberg MR, Magi-Galluzzi C, et al. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. Eur Urol. 2014;66:550–560.
77. Knezevic D, Goddard AD, Natraj N, et al. Analytical validation of the Oncotype DX prostate cancer assay—a clinical RT-PCR assay optimized for prostate needle biopsies. BMC Genomics. 2013;14:690.
78. Loeb S, Ross AE. Genomic testing for localized prostate cancer: where do we go from here? Curr Opin Urol. 2017;27:495–499.
79. Brand TC, Zhang N, Crager MR, et al. Patient-specific meta-analysis of 2 clinical validation studies to predict pathologic outcomes in prostate cancer using the 17-Gene Genomic Prostate Score. Urology. 2016;89:69–75.
80. Cullen J, Rosner IL, Brand TC, et al. A biopsy-based 17-gene Genomic Prostate Score predicts recurrence after radical prostatectomy and adverse surgical pathology in a racially diverse population of men with clinically low- and intermediate-risk prostate cancer. Eur Urol. 2015;68:123–131.
81. Van Den Eeden SK, Lu R, Zhang N, et al. A biopsy-based 17-gene Genomic Prostate Score as a predictor of metastases and prostate cancer death in surgically treated men with clinically localized disease. Eur Urol. 2018;73:129–138.
82. Sanda MG, Cadeddu JA, Kirkby E, et al. Clinically localized prostate cancer: AUA/ASTRO/SUO Guideline. Part I: risk stratification, shared decision making, and care options. J Urol. 2018;199:683–690.
83. Sanda MG, Cadeddu JA, Kirkby E, et al. Clinically localized prostate cancer: AUA/ASTRO/SUO Guideline. Part II: recommended approaches and details of specific care options. J Urol. 2018;199:990–997.
84. Cuzick J. Prognostic value of a cell cycle progression score for men with prostate cancer. Recent Results Cancer Res. 2014;202:133–140.
85. Cuzick J, Berney DM, Fisher G, et al. Prognostic value of a cell cycle progression signature for prostate cancer death in a conservatively managed needle biopsy cohort. Br J Cancer. 2012;106:1095–1099.
86. Cuzick J, Swanson GP, Fisher G, et al. Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. Lancet Oncol. 2011;12:245–255.
87. Bishoff JT, Freedland SJ, Gerber L, et al. Prognostic utility of the cell cycle progression score generated from biopsy in men treated with prostatectomy. J Urol. 2014;192:409–414.
88. Freedland SJ, Gerber L, Reid J, et al. Prognostic utility of cell cycle progression score in men with prostate cancer after primary external beam radiation therapy. Int J Radiat Oncol Biol Phys. 2013;86:848–853.
89. Oderda M, Cozzi G, Daniele L, et al. Cell-cycle progression-score might improve the current risk assessment in newly diagnosed prostate cancer patients. Urology. 2017;102:73–78.
90. Crawford ED, Scholz MC, Kar AJ, et al. Cell cycle progression score and treatment decisions in prostate cancer: results from an ongoing registry. Curr Med Res Opin. 2014;30:1025–1031.
91. Shore N, Concepcion R, Saltzstein D, et al. Clinical utility of a biopsy-based cell cycle gene expression assay in localized prostate cancer. Curr Med Res Opin. 2014;30:547–553.
92. Shore ND, Kella N, Moran B, et al. Impact of the cell cycle progression test on physician and patient treatment selection for localized prostate cancer. J Urol. 2016;195:612–618.
93. Ross AE. Multigene testing in localized prostate cancer. J Natl Compr Canc Netw. 2016;14:659–662.
94. Ross AE, D’Amico AV, Freedland SJ. Which, when and why? Rational use of tissue-based molecular testing in localized prostate cancer. Prostate Cancer Prostatic Dis. 2016;19:1–6.
95. Davis JW. Use of genomic markers to risk stratify men with prostate cancer. Trends Urol Mens Health. 2015;6:36–39.
96. Mottet N, Bellmunt J, Bolla M, et al. EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Part 1: screening, diagnosis, and local treatment with curative intent. Eur Urol. 2017;71:618–629.
97. Freedland SJ, Choeurng V, Howard L, et al. Utilization of a genomic classifier for prediction of metastasis following salvage radiation therapy after radical prostatectomy. Eur Urol. 2016;70:588–596.
98. Erho N, Crisan A, Vergara IA, et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PLoS ONE. 2013;8:e66855.
99. Karnes RJ, Bergstralh EJ, Davicioni E, et al. Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population. J Urol. 2013;190:2047–2053.
100. Klein EA, Yousefi K, Haddad Z, et al. A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high-risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy. Eur Urol. 2015;67:778–786.
101. Knudsen BS, Kim HL, Erho N, et al. Application of a clinical whole-transcriptome assay for staging and prognosis of prostate cancer diagnosed in needle core biopsy specimens. J Mol Diagn. 2016;18:395–406.
102. Den RB, Feng FY, Showalter TN, et al. Genomic prostate cancer classifier predicts biochemical failure and metastases in patients after postoperative radiation therapy. Int J Radiat Oncol Biol Phys. 2014;89:1038–1046.
103. Den RB, Yousefi K, Trabulsi EJ, et al. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. J Clin Oncol. 2015;33:944–951.
104. Spratt DE, Dai DLY, Den RB, et al. Performance of a prostate cancer genomic classifier in predicting metastasis in men with prostate-specific antigen persistence postprostatectomy. Eur Urol. 2017. [Epub ahead of print].
105. Ross AE, Feng FY, Ghadessi M, et al. A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis. 2014;17:64–69.
106. Ross AE, Johnson MH, Yousefi K, et al. Tissue-based genomics augments post-prostatectomy risk stratification in a natural history cohort of intermediate- and high-risk men. Eur Urol. 2016;69:157–165.
107. Cooperberg MR, Davicioni E, Crisan A, et al. Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort. Eur Urol. 2015;67:326–333.
108. Dalela D, Santiago-Jimenez M, Yousefi K, et al. Genomic classifier augments the role of pathological features in identifying optimal candidates for adjuvant radiation therapy in patients with prostate cancer: development and internal validation of a multivariable prognostic model. J Clin Oncol. 2017;35:1982–1990.
109. Ross AE, Den RB, Yousefi K, et al. Efficacy of post-operative radiation in a prostatectomy cohort adjusted for clinical and genomic risk. Prostate Cancer Prostatic Dis. 2016;19:277–282.
110. Gore JL, du Plessis M, Santiago-Jimenez M, et al. Decipher test impacts decision making among patients considering adjuvant and salvage treatment after radical prostatectomy: Interim results from the Multicenter Prospective PRO-IMPACT study. Cancer. 2017;123:2850–2859.
111. Nguyen PL, Haddad Z, Ross AE, et al. Ability of a genomic classifier to predict metastasis and prostate cancer-specific mortality after radiation or surgery based on needle biopsy specimens. Eur Urol. 2017;72:845–852.
112. Klein EA, Haddad Z, Yousefi K, et al. Decipher genomic classifier measured on prostate biopsy predicts metastasis risk. Urology. 2016;90:148–152.
113. Nguyen PL, Martin NE, Choeurng V, et al. Utilization of biopsy-based genomic classifier to predict distant metastasis after definitive radiation and short-course ADT for intermediate and high-risk prostate cancer. Prostate Cancer Prostatic Dis. 2017;20:186–192.
114. Vandekerkhove G, Chi KN, Wyatt AW. Clinical utility of emerging liquid biomarkers in advanced prostate cancer. Cancer Genet. 2017. pii:S2210-7762(17)30303-4.
115. Crowley E, Di Nicolantonio F, Loupakis F, et al. Liquid biopsy: monitoring cancer-genetics in the blood. Nat Rev Clin Oncol. 2013;10:472–484.
116. Zhang T, Armstrong AJ. Clinical utility of circulating tumor cells in advanced prostate cancer. Curr Oncol Rep. 2016;18:3.
117. Ritch E, Wyatt AW. Predicting therapy response and resistance in metastatic prostate cancer with circulating tumor DNA. Urol Oncol. 2017. pii:S1078-1439(17)30605-1.
118. Bastos DA, Antonarakis ES. Galeterone for the treatment of advanced prostate cancer: the evidence to date. Drug Des Dev Ther. 2016;10:2289–2297.
119. Antonarakis ES. Predicting treatment response in castration-resistant prostate cancer: could androgen receptor variant-7 hold the key? Expert Rev Anticancer Ther. 2015;15:143–145.
120. Antonarakis ES, Lu C, Chen Y, et al. Androgen receptor splice variant 7 and efficacy of taxane chemotherapy in patients with metastatic castration-resistant prostate cancer. JAMA Oncol. 2015;1:582–591.
121. Antonarakis ES, Lu C, Luber B, et al. Clinical significance of Androgen Receptor Splice Variant-7 mRNA detection in circulating tumor cells of men with metastatic castration-resistant prostate cancer treated with first- and second-line abiraterone and enzalutamide. J Clin Oncol. 2017;35:2149–2156.
122. Antonarakis ES, Lu C, Wang H, et al. AR-V7 and resistance to enzalutamide and abiraterone in prostate cancer. N Engl J Med. 2014;371:1028–1038.
123. Antonarakis ES, Lu C, Luber B, et al. Androgen Receptor Splice Variant 7 and efficacy of taxane chemotherapy in patients with metastatic castration-resistant prostate cancer. JAMA Oncol. 2015;1:582–591.
124. Onstenk W, Sieuwerts AM, Kraan J, et al. Efficacy of cabazitaxel in castration-resistant prostate cancer is independent of the presence of AR-V7 in circulating tumor cells. Eur Urol. 2015;68:939–945.
125. To SQ, Kwan EM, Fettke HC, et al. Expression of Androgen Receptor Splice Variant 7 or 9 in whole blood does not predict response to androgen-axis-targeting agents in metastatic castration-resistant prostate cancer. Eur Urol. 2018. pii:S0302-2838(18)30016-2.
126. Taplin ME, Antonarakis ES, Dransfield DT, et al. Androgen receptor modulation optimized for response: Splice variant (ARMOR3-SV)–randomized, open-label, multicenter, controlled study of galeterone vs enzalutamide in men with metastatic castration-resistant prostate cancer (mCRPC) expressing AR-V7 splice variant. J Clin Oncol. 2015;33:TPS5069.
127. Li H, Wang Z, Xiao W, et al. Androgen-receptor splice variant-7-positive prostate cancer: a novel molecular subtype with markedly worse androgen-deprivation therapy outcomes in newly diagnosed patients. Mod Pathol. 2018;31:198–208.
128. Simard J, Ricketts ML, Gingras S, et al. Molecular biology of the 3beta-hydroxysteroid dehydrogenase/delta5-delta4 isomerase gene family. Endocr Rev. 2005;26:525–582.
129. Chang KH, Li R, Kuri B, et al. A gain-of-function mutation in DHT synthesis in castration-resistant prostate cancer. Cell. 2013;154:1074–1084.
130. Hearn JWD, AbuAli G, Reichard CA, et al. HSD3B1 and resistance to androgen-deprivation therapy in prostate cancer: a retrospective, multicohort study. Lancet Oncol. 2016;17:1435–1444.
131. Hearn JWD, Xie W, Nakabayashi M, et al. Association of HSD3B1 genotype with response to androgen-deprivation therapy for biochemical recurrence after radiotherapy for localized prostate cancer. JAMA Oncol. 2018;4:558–562.
132. Agarwal N, Hahn AW, Gill DM, et al. Independent validation of effect of HSD3B1 genotype on response to androgen-deprivation therapy in prostate cancer. JAMA Oncol. 2017;3:856–857.
133. Shiota M, Fujimoto N, Imada K, et al. Independent validation of missense polymorphism in HSD3B1 in Japanese men treated with primary androgen-deprivation therapy for metastatic prostate cancer (abstr 179). J Clin Oncol. 2018;36:179.
Keywords:

prostate cancer; cribriform; intraductal; genomic tests; circulating tumor cells; ConfirmMDx; OncotypeDX; Prolaris; Decipher; 3βHSD1

Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.