Genomic testing for localized prostate cancer: where do we go from here?

A novel assessment of whole-mount Gleason grading in prostate cancer to identify candidates for radical prostatectomy: a machine learning-based multiomics study

Purpose: This study aims to assess whole-mount Gleason grading (GG) in prostate cancer (PCa) accurately using a multiomics machine learning (ML) model and to compare its performance with biopsy-proven GG (bxGG) assessment. Materials and Methods: A total of 146 patients with PCa recruited in a pilot study of a prospective clinical trial (NCT02659527) were retrospectively included in the side study, all of whom underwent 68Ga-PSMA-11 integrated positron emission tomography (PET) / magnetic resonance (MR) before radical prostatectomy (RP) between May 2014 and April 2020. To establish a multiomics ML model, we quantified PET radiomics features, pathway-level genomics features from whole exome sequencing, and pathomics features derived from immunohistochemical staining of 11 biomarkers. Based on the multiomics dataset, five ML models were established and validated using 100-fold Monte Carlo cross-validation. Results: Among five ML models, the random forest (RF) model performed best in terms of the area under the curve (AUC). Compared to bxGG assessment alone, the RF model was superior in terms of AUC (0.87 vs 0.75), specificity (0.72 vs 0.61), positive predictive value (0.79 vs 0.75), and accuracy (0.78 vs 0.77) and showed slightly decreased sensitivity (0.83 vs 0.89) and negative predictive value (0.80 vs 0.81). Among the feature categories, bxGG was identified as the most important feature, followed by pathomics, clinical, radiomics and genomics features. The three important individual features were bxGG, PSA staining and one intensity-related radiomics feature. Conclusion: The findings demonstrate a superior assessment of the developed multiomics-based ML model in whole-mount GG compared to the current clinical baseline of bxGG. This enables personalized patient management by identifying high-risk PCa patients for RP.

Molecular Pathology of Prostate Cancer

Molecular profiling studies have shed new light on the complex biology of prostate cancer. Genomic studies have highlighted that structural rearrangements are among the most common recurrent alterations. In addition, both germline and somatic mutations in DNA repair genes are enriched in patients with advanced disease. Primary prostate cancer has long been known to be multifocal, but recent studies demonstrate that a large fraction of prostate cancer shows evidence of multiclonality, suggesting that genetically distinct, independently arising tumor clones coexist. Metastatic prostate cancer shows a high level of morphologic and molecular diversity, which is associated with resistance to systemic therapies. The resulting high level of intratumoral heterogeneity has important implications for diagnosis and poses major challenges for the implementation of molecular studies. Here we provide a concise review of the molecular pathology of prostate cancer, highlight clinically relevant alterations, and discuss opportunities for molecular testing.

Metastatic Hormone-Sensitive Prostate Cancer: Toward an Era of Adaptive and Personalized Treatment

The advent of more effective treatment combinations for metastatic hormone-sensitive prostate cancer (mHSPC) has been built on successes in therapy development for metastatic, castration-resistant prostate cancer (mCRPC). Both disease phases hold similar challenges and questions. Is there an optimal therapy sequence to maximize disease control and balance treatment burden? Are there clinical and biologically based subgroups that inform personalized and/or adaptive strategies? How can clinicians interpret data from clinical trials in the context of rapidly evolving technologies? Herein, we review the contemporary landscape of treatment for mHSPC, including disease subgroups informing both intensification and potential deintensification strategies. Furthermore, we provide current insights into the complex biology of mHSPC and discuss the potential clinical application of biomarkers to guide therapy selection and the development of novel personalized approaches.

Genomic Classifiers in Personalized Prostate Cancer Radiation Therapy Approaches: A Systematic Review and Future Perspectives Based on International Consensus

Current risk-stratification systems for prostate cancer (PCa) do not sufficiently reflect the disease heterogeneity. Genomic classifiers (GC) enable improved risk stratification after surgery, but less data exist for patients treated with definitive radiation therapy (RT) or RT in oligo-/metastatic disease stages. To guide future perspectives of GCs for RT, we conducted (1) a systematic review on the evidence of GCs for patients treated with RT and (2) a survey of experts using the Delphi method, addressing the role of GCs in personalized treatments to identify relevant fields of future clinical and translational research. We performed a systematic review and screened ongoing clinical trials on ClinicalTrials.gov. Based on these results, a multidisciplinary international team of experts received an adapted Delphi method survey. Thirty-one and 30 experts answered round 1 and round 2, respectively. Questions with ≥75% agreement were considered relevant and included in the qualitative synthesis. Evidence for GCs as predictive biomarkers is mainly available to the postoperative RT setting. Validation of GCs as prognostic markers in the definitive RT setting is emerging. Experts used GCs in patients with PCa with extensive metastases (30%), in postoperative settings (27%), and in newly diagnosed PCa (23%). Forty-seven percent of experts do not currently use GCs in clinical practice. Expert consensus demonstrates that GCs are promising tools to improve risk-stratification in primary and oligo-/metastatic patients in addition to existing classifications. Experts were convinced that GCs might guide treatment decisions in terms of RT-field definition and intensification/deintensification in various disease stages. This work confirms the value of GCs and the promising evidence of GC utility in the setting of RT. Additional studies of GCs as prognostic biomarkers are anticipated and form the basis for future studies addressing predictive capabilities of GCs to optimize RT and systemic therapy. The expert consensus points out future directions for GC research in the management of PCa.

Genetic Testing and Its Clinical Application in Prostate Cancer Management: Consensus Statements from the Hong Kong Urological Association and Hong Kong Society of Uro-Oncology

Background

In recent years, indications for genetic testing in prostate cancer (PC) have expanded from patients with a family history of prostate and/or related cancers to those with advanced castration-resistant disease, and even to early PC patients for determination of the appropriateness of active surveillance. The current consensus aims to provide guidance to urologists, oncologists and pathologists working with Asian PC patients on who and what to test for in selected populations.

Methods

A joint consensus panel from the Hong Kong Urological Association and Hong Kong Society of Uro-Oncology was convened over a series of 5 physical and virtual meetings. A background literature search on genetic testing in PC was performed in PubMed, ClinicalKey, EBSCOHost, Ovid and ProQuest, and three working subgroups were formed to review and present the relevant evidence. Meeting agendas adopted a modified Delphi approach to ensure that discussions proceed in a structured, iterative and balanced manner, which was followed by an anonymous voting on candidate statements. Of 5 available answer options, a consensus statement was accepted if ≥ 75% of the panelists chose “Accept Completely” (Option A) or “Accept with Some Reservation” (Option B).

Results

The consensus was structured into three parts: indications for testing, testing methods, and therapeutic implications. A list of 35 candidate statements were developed, of which 31 were accepted. The statements addressed questions on the application of PC genetic testing data and guidelines to Asian patients, including patient selection for germline testing, selection of gene panel and tissue sample, provision of genetic counseling, and use of novel systemic treatments in metastatic castration-resistant PC patients.

Conclusion

This consensus provides guidance to urologists, oncologists and pathologists working with Asian patients on indications for genetic testing, testing methods and technical considerations, and associated therapeutic implications.

A 25-year perspective on the evolution of radiation treatment of urologic cancers

Advances in radiotherapy technology and technique over the last 3 decades have revolutionized radiation treatment options for genitourinary malignancies. The development of more focused and accurate radiation treatment has facilitated safe delivery of dose-escalated treatment that improves disease control and the development of shorter-duration hypofractionated treatment regimens that are more convenient for patients and improve access to treatment. The management of oligometastatic disease is evolving with ablative treatment of oligometastasis and the primary for select patients and shorter-duration palliative treatment regimens. Work is ongoing to personalize radiation treatment regimens for genitourinary malignancies based on molecular biomarkers.

Identification of a five gene signature to predict time to biochemical recurrence after radical prostatectomy

BACKGROUND

Identification of novel biomarkers associated with high-risk prostate cancer or biochemical recurrence can drive improvement in detection, prognosis, and treatment. However, studies can be limited by small sample sizes and sparse clinical follow-up data. We utilized a large sample of prostate specimens to identify a predictive model of biochemical recurrence following radical prostatectomy and we validated this model in two external data sets.

METHODS

We analyzed prostate specimens from patients undergoing radical prostatectomy at Hartford Hospital between 2008 and 2011. RNA isolated from formalin-fixed paraffin-embedded prostates was hybridized to a custom Affymetrix microarray. Regularized (least absolute shrinkage and selection operator [Lasso]) Cox regression was performed with cross-validation to identify a model that incorporated gene expression and clinical factors to predict biochemical recurrence, defined as postoperative prostate-specific antigen (PSA) > 0.2 ng/ml or receipt of triggered salvage treatment. Model performance was assessed using time-dependent receiver operating curve (ROC) curves and survival plots.

RESULTS

A total of 606 prostate specimens with gene expression and both pre- and postoperative PSA data were available for analysis. We identified a model that included Gleason grade and stage as well as five genes (CNRIP1, endoplasmic reticulum protein 44 [ERP44], metaxin-2 [MTX2], Ras homolog family member U [RHOU], and OXR1). Using the Lasso method, we determined that the five gene model independently predicted biochemical recurrence better than a model that included Gleason grade and tumor stage alone. The time-dependent ROCAUC for the five gene signature including Gleason grade and tumor stage was 0.868 compared to an AUC of 0.767 when Gleason grade and tumor stage were included alone. Low and high-risk groups displayed significant differences in their recurrence-free survival curves. The predictive model was subsequently validated on two independent data sets identified through the Gene Expression Omnibus. The model included genes (RHOU, MTX2, and ERP44) that have previously been implicated in prostate cancer biology.

CONCLUSIONS

Expression of a small number of genes is associated with an increased risk of biochemical recurrence independent of classical pathological hallmarks.

Artificial intelligence in urological oncology: An update and future applications

There continues to be rapid developments and research in the field of Artificial Intelligence (AI) in Urological Oncology worldwide. In this review we discuss the basics of AI, application of AI per tumour group (Renal, Prostate and Bladder Cancer) and application of AI in Robotic Urological Surgery. We also discuss future applications of AI being developed with the benefits to patients with Urological Oncology.

Genomic Strategies to Personalize Use of Androgen Deprivation Therapy With Radiotherapy

The use of combination RT and androgen deprivation therapy in many prostate cancer curative-intent treatment scenarios is supported by level 1 evidence. However, in our current clinical paradigm, we have no ability to determine a priori which patients truly benefit from combination therapy and therefore apply the combination RT and androgen deprivation therapy intensification strategy to all patients, which results in overtreatment or undertreatment of the majority of our patients. Genomics has the ability to more deeply and objectively characterize the disease, in turn refining our prognostication capabilities and enabling the individualization of treatments. We review the commercially available prostate cancer genomic tests, focusing on those able to predict patient outcomes following radiotherapy or guide radiotherapy treatment decisions.

Correlative analysis between two commercially available post-prostatectomy genomic tests

BACKGROUND

Multiple genomic tests are available following radical prostatectomy (RP), however, there is a lack of head-to-head evidence for these tests. We sought to compare the performance of two genomic tests in predicting post-RP oncological outcomes.

METHODS

A cohort of 16 post-RP patients with adverse pathological features who had obtained both Decipher (D) and Prolaris (P) testing. The Pearson correlation was used to compare scores from D and cell cycle progression (CCP) from P. Then, we derived a microarray CCP (mCCP) from D and correlated with P-CCP. The associations of D and mCCP with biochemical recurrence (BCR) and metastasis (M) was evaluated in multivariable survival analysis (MVA) in a large cohort of RP patients treated at Johns Hopkins University (1992-2010). In addition, we characterized the expression of the 31 P-CCP genes and mCCP scores in a cohort of 17,967 RP samples from Decipher platform.

RESULTS

There was significant correlation between the D score and P-CCP (r = 0.67, p = 0.004), and between the 10-year probability of BCR reported by P and 5-year probability of M reported by D (r = 0.69, p = 0.003). In this cohort, mCCP derived from the D platform was highly correlated to the reported P-CCP scores from the P platform (r = 0.88, p = 6.7e-6). In a comparative retrospective RP cohort, both mCCP and D were significantly associated with M outcome (p < 0.01 for both). On MVA, D was a predictor of M (HR 1.3, 95% CI [1.12-1.52], p = 0.0005), while mCCP was not a predictor of M (p = 0.62). In the D platform cohort, the 31 P-CCP genes were correlated to each other, and TOP2A was the most correlated to mCCP (r = 0.7).

CONCLUSIONS

We found that P and D scores post-RP were correlated and help in identifying patients who at high risk of BCR in this cohort. In a larger cohort with longer follow-up, D was predictor of M, whereas mCCP was not.

Genomic and phenotypic heterogeneity in prostate cancer

From a clinical, morphological and molecular perspective, prostate cancer is a heterogeneous disease. Primary prostate cancers are often multifocal, having topographically and morphologically distinct tumour foci. Sequencing studies have revealed that individual tumour foci can arise as clonally distinct lesions with no shared driver gene alterations. This finding demonstrates that multiple genomically and phenotypically distinct primary prostate cancers can be present in an individual patient. Lethal metastatic prostate cancer seems to arise from a single clone in the primary tumour but can exhibit subclonal heterogeneity at the genomic, epigenetic and phenotypic levels. Collectively, this complex heterogeneous constellation of molecular alterations poses obstacles for the diagnosis and treatment of prostate cancer. However, advances in our understanding of intra-tumoural heterogeneity and the development of novel technologies will allow us to navigate these challenges, refine approaches for translational research and ultimately improve patient care.

The Role of Radiation Therapy in the Older Patient

PURPOSE OF REVIEW

Older patients represent a unique subgroup of the cancer patient population for which the role of radiation therapy (RT) requires special consideration. This review will discuss many of these considerations as well as various radiation treatment techniques in the context of a variety of disease sites.

RECENT FINDINGS

Several recent studies give insight into the management of older cancer patients considering their age, performance status, comorbid conditions, quality of life, genetics, cost, and individual goals. RT plays an evolving and pivotal role in providing optimal care for this population. Recent advances in RT technique allow for more precise treatment delivery and reduced toxicity. Studies evaluating the use of radiation therapy in breast, brain, lung, prostate, rectal, pancreatic, esophageal, and oligometastatic cancer are summarized and discussed in the context of treating the older patient population. Individual age, performance and functional status, comorbid conditions, and patients' objectives and goals should all be considered when presenting treatment options for older patients and age alone should not disqualify patients from curative intent treatments. When possible, hypofractionated courses should be utilized as outcomes are often equivalent and toxicities are reduced. In many cases, RT may be preferable to other treatment options due to decreased toxicity profile and acceptable disease control.

Prostate biopsy histopathologic features correlate with a commercial gene expression assay's reclassification of patient NCCN risk category

BACKGROUND

For biopsies with Gleason 3 + 3 = 6 or 3 + 4 = 7 prostate cancer, the Genomic Prostate Score (GPS; OncotypeDx) is designed to predict severe pathology at prostatectomy, and, in some cases, recommends reclassification of the National Comprehensive Cancer Network (NCCN) risk category. We hypothesized that certain histopathologic features that were not considered in the original design of the assay actually would be associated with the NCCN risk category change indicated by GPS testing.

METHODS

For patients with recommended NCCN risk category change, the biopsy cores used for GPS were re-reviewed for stromal reaction, chronic inflammation, and tumor nuclear polarization.

RESULTS

Of 520 patients from May 2011 to December 2018, GPS testing suggested NCCN risk reclassification in 131 (25%); 127 of these slides were available. Of these, the NCCN risk category increased from intermediate to high in 8, low to intermediate in 15, very low to low in 1, and decreased from intermediate to low in 32, and low to very low in 71. Biopsies with NCCN risk increase were associated with moderate or severe stromal reaction (p < .001) and chronic inflammation (p < .001); biopsies with NCCN risk decrease were associated with absence of these features. In Gleason 3 + 3 = 6 cases (n = 93), presence of nuclear polarization was associated with NCCN risk decrease and its absence with increase (p < .001).

CONCLUSIONS

Moderate or severe stromal reaction, chronic inflammation, and lack of nuclear polarization in Gleason score 3 + 3 = 6 tumors were each associated with an increase in NCCN risk category indicated by GPS and vice versa. Our results suggest that GPS captures histologic features associated with aggressiveness that are not routinely assessed in standard histopathologic assessments, and that consideration of such histologic features may improve upon current tumor grading approaches.

The PTEN Conundrum: How to Target PTEN-Deficient Prostate Cancer

Loss of the tumor suppressor phosphatase and tensin homologue deleted on chromosome 10 (PTEN), which negatively regulates the PI3K-AKT-mTOR pathway, is strongly linked to advanced prostate cancer progression and poor clinical outcome. Accordingly, several therapeutic approaches are currently being explored to combat PTEN-deficient tumors. These include classical inhibition of the PI3K-AKT-mTOR signaling network, as well as new approaches that restore PTEN function, or target PTEN regulation of chromosome stability, DNA damage repair and the tumor microenvironment. While targeting PTEN-deficient prostate cancer remains a clinical challenge, new advances in the field of precision medicine indicate that PTEN loss provides a valuable biomarker to stratify prostate cancer patients for treatments, which may improve overall outcome. Here, we discuss the clinical implications of PTEN loss in the management of prostate cancer and review recent therapeutic advances in targeting PTEN-deficient prostate cancer. Deepening our understanding of how PTEN loss contributes to prostate cancer growth and therapeutic resistance will inform the design of future clinical studies and precision-medicine strategies that will ultimately improve patient care.

A 38-gene model comprised of key TET2-associated genes shows additive utility to high-risk prostate cancer cases in the prognostication of biochemical recurrence

BACKGROUND

Early treatment of patients at risk for developing aggressive prostate cancer is able to delay metastasis and reduce mortality; as such, up-front identification of these patients is critical. Several risk classification systems, including CAPRA-S, are currently used for disease prognostication. However, high-risk patients identified by these systems can still exhibit wide-ranging disease outcomes, leading to overtreatment of some patients in this group.

METHODS

The master methylation regulator TET2 is downregulated in prostate cancer, where its loss is linked to aggressive disease and poor outcome. Using a random forest strategy, we developed a model based on the expression of 38 genes associated with TET2 utilizing 100 radical prostatectomy samples (training cohort) with a 49% biochemical recurrence rate. This 38-gene model was comprised of both upregulated and downregulated TET2-associated genes with a binary outcome, and was further assessed in an independent validation (n = 423) dataset for association with biochemical recurrence.

RESULTS

38-gene model status was able to correctly identify patients exhibiting recurrence with 81.4% sensitivity in the validation cohort, and added significant prognostic utility to the high-risk CAPRA-S classification group. Patients considered high-risk by CAPRA-S with negative 38-gene model status exhibited no statistically significant difference in time to recurrence from low-risk CAPRA-S patients, indicating that the expression of TET2-associated genes is able to separate truly high-risk cases from those which have a more benign disease course.

CONCLUSIONS

The 38-gene model may hold potential in determining which patients would truly benefit from aggressive treatment course, demonstrating a novel role for genes linked to TET2 in the prognostication of PCa and indicating the importance of TET2 dysregulation among high-risk patient groups.

A Novel Predictor Tool of Biochemical Recurrence after Radical Prostatectomy Based on a Five-MicroRNA Tissue Signature

Within five to ten years after radical prostatectomy (RP), approximately 15–34% of prostate cancer (PCa) patients experience biochemical recurrence (BCR), which is defined as recurrence of serum levels of prostate-specific antigen >0.2 µg/L, indicating probable cancer recurrence. Models using clinicopathological variables for predicting this risk for patients lack accuracy. There is hope that new molecular biomarkers, like microRNAs (miRNAs), could be potential candidates to improve risk prediction. Therefore, we evaluated the BCR prognostic capability of 20 miRNAs, which were selected by a systematic literature review. MiRNA expressions were measured in formalin-fixed, paraffin-embedded (FFPE) tissue RP samples of 206 PCa patients by RT-qPCR. Univariate and multivariate Cox regression analyses were performed, to assess the independent prognostic potential of miRNAs. Internal validation was performed, using bootstrapping and the split-sample method. Five miRNAs (miR-30c-5p/31-5p/141-3p/148a-3p/miR-221-3p) were finally validated as independent prognostic biomarkers. Their prognostic ability and accuracy were evaluated using C-statistics of the obtained prognostic indices in the Cox regression, time-dependent receiver-operating characteristics, and decision curve analyses. Models of miRNAs, combined with relevant clinicopathological factors, were built. The five-miRNA-panel outperformed clinically established BCR scoring systems, while their combination significantly improved predictive power, based on clinicopathological factors alone. We conclude that this miRNA-based-predictor panel will be worth to be including in future studies.

Gene expression profiles define molecular subtypes of prostate cancer bone metastases with different outcomes and morphology traceable back to the primary tumor

Bone metastasis is the lethal end-stage of prostate cancer (PC), but the biology of bone metastases is poorly understood. The overall aim of this study was therefore to explore molecular variability in PC bone metastases of potential importance for therapy. Specifically, genome-wide expression profiles of bone metastases from untreated patients (n = 12) and patients treated with androgen-deprivation therapy (ADT, n = 60) were analyzed in relation to patient outcome and to morphological characteristics in metastases and paired primary tumors. Principal component analysis and unsupervised classification were used to identify sample clusters based on mRNA profiles. Clusters were characterized by gene set enrichment analysis and related to histological and clinical parameters using univariate and multivariate statistics. Selected proteins were analyzed by immunohistochemistry in metastases and matched primary tumors (n = 52) and in transurethral resected prostate (TUR-P) tissue of a separate cohort (n = 59). Three molecular subtypes of bone metastases (MetA-C) characterized by differences in gene expression pattern, morphology, and clinical behavior were identified. MetA (71% of the cases) showed increased expression of androgen receptor-regulated genes, including prostate-specific antigen (PSA), and glandular structures indicating a luminal cell phenotype. MetB (17%) showed expression profiles related to cell cycle activity and DNA damage, and a pronounced cellular atypia. MetC (12%) exhibited enriched stroma-epithelial cell interactions. MetB patients had the lowest serum PSA levels and the poorest prognosis after ADT. Combined analysis of PSA and Ki67 immunoreactivity (proliferation) in bone metastases, paired primary tumors, and TUR-P samples was able to differentiate MetA-like (high PSA, low Ki67) from MetB-like (low PSA, high Ki67) tumors and demonstrate their different prognosis. In conclusion, bone metastases from PC patients are separated based on gene expression profiles into molecular subtypes with different morphology, biology, and clinical outcome. These findings deserve further exploration with the purpose of improving treatment of metastatic PC.

Analysis of the prognostic utility of the cell cycle progression (CCP) score generated from needle biopsy in men treated with definitive therapy

BACKGROUND

Accurate risk stratification can help guide appropriate treatment decisions in men with localized prostate cancer. Here, we evaluated the independent ability of the molecular cell cycle progression (CCP) score and the combined cell-cycle clinical risk (CCR) score to predict 10-year risk of progression to metastatic disease in a large, pooled analysis of men with definitively treated prostate cancer.

METHODS

The pooled analysis included 1,062 patients from four institutions (Martini Clinic, Durham VA Medical Center, Intermountain Healthcare, Ochsner Clinic) treated definitively for localized prostate cancer by either radical prostatectomy or radiotherapy (brachytherapy or external beam radiotherapy ± hormone therapy). The CCP score was determined using the RNA expression of 46 genes from archival formalin-fixed paraffin-embedded biopsy tissue. The CCR score was calculated using a predefined linear combination of the CCP score and the Cancer of the Prostate Risk Assessment (CAPRA) score. The scores were evaluated for association with 10-year risk of metastatic disease following definitive therapy after adjusting for other clinical variables.

RESULTS

The CCP score was strongly associated with 10-year risk of metastatic disease in multivariable analysis [Hazard Ratio per unit score = 2.21; 95% confidence interval (CI) 1.64, 2.98; p = 1.9 × 10^-6] after adjusting for CAPRA, treatment type, and cohort. CCR was also highly prognostic (Hazard Ratio per unit score = 4.00; 95% CI 2.95, 5.42; p = 6.3 × 10^-21). There was no evidence of interaction between CCP or CCR and cohort (p = 0.79 and p = 0.86, respectively) or treatment type (p = 0.55 and p = 0.78, respectively). Observed patient CCR-based predicted risks for metastatic disease by 10 years ranged from 0.1 to 99.4%, (IQR 0.7%, 4.6%).

CONCLUSIONS

Both CCP and CCR scores provided independent prognostic information for predicting progression to metastatic disease after both surgery and radiation. These results further demonstrate their potential use as a risk stratification tool in patients with newly-diagnosed prostate cancer.

Germline and Somatic Mutations in Prostate Cancer for the Clinician

It is increasingly important for clinicians involved in the management of prostate cancer to understand the relevance of heritable (germline) mutations that, for select patients, affect prostate cancer risk and cancer biology, and acquired (somatic) mutations that occur in prostate cancer cells. In the advanced disease setting, mutations in homologous recombination repair genes (eg, BRCA1, BRCA2, ATM, CHEK2, PALB2) suggest candidacy for platinum chemotherapy and PARP inhibitor trials. Similarly, microsatellite instability and mismatch repair deficiency, which may arise in the setting of MLH1, MSH2, MSH6, and PMS2 mutations, suggest potential vulnerability to PD-1 inhibitors. Germline genetic testing has potential importance in the treatment and assessment of familial risk, and tumor-directed somatic sequencing may guide treatment decision-making. This review provides clinicians with knowledge of basic genetic terminology, awareness of the importance of family history of cancer (not limited to prostate cancer), contrasts between the different but potentially related objectives of germline versus somatic testing of tumor tissue, and indications for genetic counseling. Specific clinical scenarios, objectives of testing, and nature of the assays are reviewed. Germline and somatic mutations of known and potential relevance to prostate cancer are discussed in the context of treatment options, and algorithms to assist clinicians in approaching this area are proposed.

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

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.

Tissue-based multigene expression tests for pretreatment prostate cancer risk assessment: current status and future perspectives

Prostate cancer is a highly prevalent disease with ample spectrum of aggressiveness and treatment options. Low-risk disease can be safely managed by nonintervention strategies, such as active surveillance; however, accurate risk assessment is warranted. Molecular tests have been developed and validated to complement standard clinicopathological parameters and help to improve risk stratification in prostate cancer. Herein, we review selected tissue-based assays, including genomic prostate score, cell cycle progression score and genomic classifier, with particular emphasis on their role in patient risk assessment in a pretreatment setting, in view of their current or potential utilization in active surveillance.

Association Between Early Confirmatory Testing and the Adoption of Active Surveillance for Men With Favorable-risk Prostate Cancer

OBJECTIVE

To examine the relationship between the use and results of early confirmatory testing and persistence on active surveillance (AS).

METHODS

We identified all men in the Michigan Urological Surgery Improvement Collaborative registry diagnosed with favorable-risk prostate cancer from June 2016 to June 2017. We next examined trends in the use of early confirmatory test(s), defined as repeat biopsy, prostate magnetic resonance imaging, or molecular classifiers obtained within 6 months of the initial cancer diagnosis, in patients with favorable-risk prostate cancer. We then compared the proportion of men remaining on AS 6 months after diagnosis according to reassuring vs nonreassuring results, also stratifying by age and Gleason score.

RESULTS

Among 2529 patients, 32.7% underwent early confirmatory testing within 6 months of diagnosis. Its use increased from 25.4% in the second quarter of 2016 to 34.9% in the second quarter of 2017 (P = .025). Molecular classifiers were most frequently used (55%), followed by magnetic resonance imaging (34%) and repeat biopsy (11%). Sixty-four percent (n = 523) had a reassuring result. Rates of AS were higher for patients with early reassuring results; 82% remained on AS (n = 427) compared to 52% (n = 157) of those with nonreassuring results and 51% (n = 873) with no early confirmatory testing (P <.001).

CONCLUSION

Rates of AS are higher among men with early reassuring results, supporting the clinical utility of these tests. Nonetheless, high rates of AS among patients with nonreassuring results underscore the complexity of shared decision-making in this setting.

Prostate Cancer Markers

Diagnostic biomarkers derived from blood, urine, or prostate tissue provide additional information beyond clinical calculators to determine the risk of detecting high-grade prostate cancer. Once diagnosed, multiple markers leverage prostate cancer biopsy tissue to prognosticate clinical outcomes, including adverse pathology at radical prostatectomy, disease recurrence, and prostate cancer mortality; however the clinical utility of some outcomes to patient decision making is unclear. Markers using tissue from radical prostatectomy specimens provide additional information about the risk of biochemical recurrence, development of metastatic disease, and subsequent mortality beyond existing multivariable clinical calculators (the use of a marker to simply sub-stratify risk groups such as the NCCN groups is of minimal value). No biomarkers currently available for prostate cancer have been prospectively validated to be predict an improved clinical outcome for a specific therapy based on the test result; however, further research and development of these tests may produce a truly predictive biomarker for prostate cancer treatment.

Future Perspectives and Challenges of Prostate MR Imaging

MR imaging is an important part of prostate cancer diagnosis. Variations in quality and skill in general practice mean results are not as impressive as they were in academic centers. This observation provides an impetus to improve the method. Improved quality assurance will likely result in better outcomes. Improved characterization of clinically significant prostate cancer may assist in making MR imaging more useful. Improved methods of registering MR imaging with transrectal ultrasound imaging and robotic arms controlling the biopsy can reduce the impact of inexperienced operators and make the entire system of MR imaging-guided biopsies more robust.