Association between a 17-gene genomic prostate score and multi-parametric prostate MRI in men with low and intermediate risk prostate cancer (PCa)

Risks of grade reclassification among patients with Gleason grade group 1 prostate cancer and PI-RADS 5 findings on prostate MRI

BACKGROUND AND OBJECTIVE

As most Prostate Imaging Reporting and Data System (PI-RADS) 5 lesions on MRI harbor Gleason grade (GG) group ≥2 disease on biopsy, optimal management of patients with imaging-biopsy discordance remains unclear. To estimate grade misclassification, we evaluated the incidence of Gleason upgrading among patients with GG1 disease in the setting of a PI-RADS 5 lesion.

METHODS

We conducted a single-institution retrospective analysis to identify patients with GG1 prostate cancer on fusion biopsy with MRI demonstrating ≥1 PI-RADS 5 lesion. Primary study outcome was identification of ≥GG2 disease on subsequent active surveillance (AS) biopsy or radical prostatectomy (RP). We used multivariable models to examine factors associated with reclassification.

RESULTS

We identified 110 patients with GG1 disease on initial biopsy and ≥1 PI-RADS 5 lesion. There were 104 patients (94.6%) initially managed with AS and 6 (5.5%) received treatment. Sixty-one patients (58.7%) on AS underwent additional biopsies. Of these, 43 (70.5%) patients had tumor upgrading, with 32 (74.4%) upgraded on first surveillance biopsy. Forty-four (40%) patients ultimately received treatment, including prostatectomy in 15 (13.6%) and radiation in 25 (22.7%). Two patients (1.8%) developed metastases. In multivariable models, genomic classifier score was associated with upgrading. Limitations include a lack of multi-institutional data and long-term outcomes data.

CONCLUSIONS

Most patients diagnosed with GG1 prostate cancer on MRI-Ultrasound fusion biopsy in the setting of a PI-RADS 5 lesion were found to have ≥GG2 disease on subsequent tissue sampling, suggesting substantial initial misclassification and reinforcing the need for confirmatory testing.

Molecular Correlates of Prostate Cancer Visibility on Multiparametric Magnetic Resonance Imaging: A Systematic Review

BACKGROUND AND OBJECTIVE

Although prostate magnetic resonance imaging (MRI) is increasingly used to diagnose and stage prostate cancer (PCa), the biologic and clinical significance of MRI visibility of the disease is unclear. Our aim was to examine the existing knowledge regarding the molecular correlates of MRI visibility of PCa.

METHODS

The PubMed, Scopus, and Web of Science databases were queried through November 2023. We defined MRI-visible and MRI-invisible lesions based on the Prostate Imaging Reporting and Data System (PI-RADS) score, and compared these based on the genomic, transcriptomic, and proteomic characteristics.

KEY FINDINGS AND LIMITATIONS

From 2015 individual records, 25 were selected for qualitative data synthesis. Current evidence supports the polygenic nature of MRI visibility, primarily influenced by genes related to stroma, adhesion, and cellular organization. Several gene signatures related to MRI visibility were associated with oncologic outcomes, which support that tumors appearing as PI-RADS 4-5 lesions harbor lethal disease. Accordingly, MRI-invisible tumors detected by systematic biopsies were, generally, less aggressive and had a more favorable prognosis; however, some MRI-invisible tumors harbored molecular features of biologically aggressive PCa. Among the commercially available prognostic gene panels, only Decipher was strongly associated with MRI visibility.

CONCLUSIONS AND CLINICAL IMPLICATIONS

High PI-RADS score is associated with biologically and clinically aggressive PCa molecular phenotypes, and could potentially be used as a biomarker. However, MRI-invisible lesions can harbor adverse features, advocating the continued use of systemic biopsies. Further research to refine the integration of imaging data to prognostic assessment is warranted.

PATIENT SUMMARY

Magnetic resonance imaging visibility of prostate cancer is a polygenic trait. Higher Prostate Imaging Reporting and Data System scores are associated with features of biologically and clinically aggressive cancer.

A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer

BACKGROUND

Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics.

METHODS

All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments.

RESULTS

Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies.

CONCLUSIONS

We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.

Radiogenomics Analysis Linking Multiparametric MRI and Transcriptomics in Prostate Cancer

Prostate cancer (PCa) is a highly prevalent cancer type with a heterogeneous prognosis. An accurate assessment of tumor aggressiveness can pave the way for tailored treatment strategies, potentially leading to better outcomes. While tumor aggressiveness is typically assessed based on invasive methods (e.g., biopsy), radiogenomics, combining diagnostic imaging with genomic information can help uncover aggressive (imaging) phenotypes, which in turn can provide non-invasive advice on individualized treatment regimens. In this study, we carried out a parallel analysis on both imaging and transcriptomics data in order to identify features associated with clinically significant PCa (defined as an ISUP grade ≥ 3), subsequently evaluating the correlation between them. Textural imaging features were extracted from multi-parametric MRI sequences (T2W, DWI, and DCE) and combined with DCE-derived parametric pharmacokinetic maps obtained using magnetic resonance dispersion imaging (MRDI). A transcriptomic analysis was performed to derive functional features on transcription factors (TFs), and pathway activity from RNA sequencing data, here referred to as transcriptomic features. For both the imaging and transcriptomic features, different machine learning models were separately trained and optimized to classify tumors in either clinically insignificant or significant PCa. These models were validated in an independent cohort and model performance was used to isolate a subset of relevant imaging and transcriptomic features to be further investigated. A final set of 31 imaging features was correlated to 33 transcriptomic features obtained on the same tumors. Five significant correlations (p < 0.05) were found, of which, three had moderate strength (|r| ≥ 0.5). The strongest significant correlations were seen between a perfusion-based imaging feature-MRDI A median-and the activities of the TFs STAT6 (-0.64) and TFAP2A (-0.50). A higher-order T2W textural feature was also significantly correlated to the activity of the TF STAT6 (-0.58). STAT6 plays an important role in controlling cell proliferation and migration. Loss of the AP2alpha protein expression, quantified by TFAP2A, has been strongly associated with aggressiveness and progression in PCa. According to our findings, a combination of texture features extracted from T2W and DCE, as well as perfusion-based pharmacokinetic features, can be considered for the prediction of clinically significant PCa, with the pharmacokinetic MRDI A feature being the most correlated with the underlying transcriptomic information. These results highlight a link between quantitative imaging features and the underlying transcriptomic landscape of prostate tumors.

Loading of "cocktail siRNAs" into extracellular vesicles via TAT-DRBD peptide for the treatment of castration-resistant prostate cancer

Extracellular vesicles (EVs) are cell-derived, membranous nanoparticles that mediate intercellular communication by transferring biomolecules between cells. As natural vehicles, EVs may exhibit higher delivery efficiency, lower immunogenicity, and better compatibility than existing RNA carriers. A major limitation of their therapeutic use is the shortage of efficient, robust, and scalable methods to load siRNA of interest. Here, we report a novel strategy using polycationic membrane-penetrating peptide TAT to encapsulate siRNAs into EVs. Three TAT peptides were co-expressed with DRBD as 3TD fusion protein. The sequence-independent binding of DRBD facilitates multiplex genes targeting of mixed siRNAs. Functional assays for siRNA-mediated gene silencing of CRPC were performed after engineered EVs treatment. EVs were isolated using differential centrifugation from WPMY-1 cell culture medium. The increase of merged yellow fluorescence in the engineered EVs showed by TIRFM and the decrease in zeta potential absolute values certified the co-localization of siRNA with EVs, which indicated that siRNA had been successfully delivered into WPMY-1 EVs. qRT-PCR analysis revealed that the mRNA level of FLOH1, NKX3, and DHRS7 was dramatically decreased when cells were treated with engineered EVs loaded with siRNAs mixtures relative to the level of untreated cells. Western and flow cytometry results indicate that delivery of siRNA mixtures by engineered EVs can effectively downregulate AR expression and induce LNCaP-AI cell apoptosis. The uptake efficiency of the EVs and the significantly downregulated expression of three genes suggested the potential of TAT as efficient siRNA carriers by keeping the function of the cargoes.

Active Surveillance in Intermediate-Risk Prostate Cancer: A Review of the Current Data

Simple Summary

AS is an option for the initial management of selected patients with intermediate-risk PC. The proper way to predict which men will have an aggressive clinical course or indolent PC who would benefit from AS has not been unveiled. Genetics and MRI can help in the decision-making, but it remains unclear which men would benefit from which tests. In addition, there are several differences between AS protocols in inclusion criteria, monitoring follow-up, and triggers for active treatment. Large series and a few RCTs are under investigation, and more research is needed to establish an optimal therapeutic strategy for patients with intermediate-risk PC. This study summarizes the current data on patients with intermediate-risk PC under AS, recent findings, and discusses future directions.

Abstract

Active surveillance (AS) is a monitoring strategy to avoid or defer curative treatment, minimizing the side effects of radiotherapy and prostatectomy without compromising survival. AS in intermediate-risk prostate cancer (PC) has increasingly become used. There is heterogeneity in intermediate-risk PC patients. Some of them have an aggressive clinical course and require active treatment, while others have indolent disease and may benefit from AS. However, intermediate-risk patients have an increased risk of metastasis, and the proper way to select the best candidates for AS is unknown. In addition, there are several differences between AS protocols in inclusion criteria, monitoring follow-up, and triggers for active treatment. A few large series and randomized trials are under investigation. Therefore, more research is needed to establish an optimal therapeutic strategy for patients with intermediate-risk disease. This study summarizes the current data on patients with intermediate-risk PC under AS, recent findings, and discusses future directions.

Unified model involving genomics, magnetic resonance imaging and prostate-specific antigen density outperforms individual co-variables at predicting biopsy upgrading in patients on active surveillance for low risk prostate cancer

BACKGROUND

Active surveillance (AS) is the reference standard treatment for the management of low risk prostate cancer (PCa). Accurate assessment of tumor aggressiveness guides recruitment to AS programs to avoid conservative treatment of intermediate and higher risk patients. Nevertheless, underestimating the disease risk may occur in some patients recruited, with biopsy upgrading and the concomitant potential for delayed treatment.

AIM

To evaluate the accuracy of mpMRI and GPS for the prediction of biopsy upgrading during active surveillance (AS) management of prostate cancer (PCa).

METHOD

A retrospective analysis was performed on 144 patients recruited to AS from October 2013 to December 2020. Median follow was 4.8 (IQR 3.6, 6.3) years. Upgrading was defined as upgrading to biopsy grade group ≥2 on follow up biopsies. Cox proportional hazard regression was used to investigate the effect of PSA density (PSAD), baseline Prostate Imaging-Reporting and Data System (PI-RADS) v2.1 score and GPS on upgrading. Time-to-event outcome, defined as upgrading, was estimated using the Kaplan-Meier method with log-rank test.

RESULTS

Overall rate of upgrading was 31.9% (n = 46). PSAD was higher in the patients who were upgraded (0.12 vs. 0.08 ng/ml2 , p = .005), while no significant difference was present for median GPS in the overall cohort (overall median GPS 21; 22 upgrading vs. 20 no upgrading, p = .2044). On univariable cox proportional hazard regression analysis, the factors associated with increased risk of biopsy upgrading were PSA (HR = 1.30, CI 1.16-1.47, p = <.0001), PSAD (HR = 1.08, CI 1.05-1.12, p = <.0001) and higher PI-RADS score (HR = 3.51, CI 1.56-7.91, p = .0024). On multivariable cox proportional hazard regression analysis, only PSAD (HR = 1.10, CI 1.06-1.14, p = <.001) and high PI-RADS score (HR = 4.11, CI 1.79-9.44, p = .0009) were associated with upgrading. A cox regression model combining these three clinical features (PSAD ≥0.15 ng/ml2 at baseline, PI-RADS Score and GPS) yielded a concordance index of 0.71 for the prediction of upgrading.

CONCLUSION

In this study PSAD has higher accuracy over baseline PI-RADS score and GPS score for the prediction of PCa upgrading during AS. However, combined use of PSAD, GPS and PI-RADS Score yielded the highest predictive ability with a concordance index of 0.71.

Biomarkers for prostate cancer detection and risk stratification

Although prostate cancer (PCa) is the most commonly diagnosed cancer in men, most patients do not die from the disease. Prostate specific antigen (PSA), the most widely used oncologic biomarker, has revolutionized screening and early detection, resulting in reduced proportion of patients presenting with advanced disease. However, given the inherent limitations of PSA, additional diagnostic and prognostic tools are needed to facilitate early detection and accurate risk stratification of disease. Serum, urine, and tissue-based biomarkers are increasingly being incorporated into the clinical care paradigm, but there is still a limited understanding of how to use them most effectively. In the current article, we review test characteristics and clinical performance data for both serum [4 K score, prostate health index (phi)] and urine [SelectMDx, ExoDx Prostate Intelliscore, MyProstateScore (MPS), and PCa antigen 3 (PCA3)] biomarkers to aid decisions regarding initial or repeat biopsies as well as tissue-based biomarkers (Confirm MDx, Decipher, Oncotype Dx, and Polaris) aimed at risk stratifying patients and identifying those patients most likely to benefit from treatment versus surveillance or monotherapy versus multi-modal therapy.

Prostate cancer

The management of prostate cancer continues to evolve rapidly, with substantial advances being made in understanding the genomic landscape and biology underpinning both primary and metastatic prostate cancer. Similarly, the emergence of more sensitive imaging methods has improved diagnostic and staging accuracy and refined surveillance strategies. These advances have introduced personalised therapeutics to clinical practice, with treatments targeting genomic alterations in DNA repair pathways now clinically validated. An important shift in the therapeutic framework for metastatic disease has taken place, with metastatic-directed therapies being evaluated for oligometastatic disease, aggressive management of the primary lesion shown to benefit patients with low-volume metastatic disease, and with several novel androgen pathway inhibitors significantly improving survival when used as a first-line therapy for metastatic disease. Research into the molecular characterisation of localised, recurrent, and progressive disease will undoubtedly have an impact on clinical management. Similarly, emerging research into novel therapeutics, such as targeted radioisotopes and immunotherapy, holds much promise for improving the lives of patients with prostate cancer.

Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.

Prostate cancer biomarkers and multiparametric MRI: is there a role for both in prostate cancer management?

Several advancements have been made in recent years with regards to the detection and evaluation of prostate cancer (PCa). The low specificity of prostate specific antigen (PSA) has left much to be desired in a test, but a boom in novel biomarkers has made screening and surveillance more complicated. Several attempts at identifying a niche for these tests has helped somewhat, but much is still undetermined about the benefit that each test provides. In addition to laboratory tests, advancements in multiparametric magnetic resonance imaging (mpMRI) and PIRADSv.2 scoring have provided significant benefit to the evaluation of PCa. With the widespread use of prostate imaging, it is important to re-evaluate the impact of novel biomarkers in the context of furthering PCa screening and management. In this review, we aim to assess the influence mpMRI has on the role of nine different novel biomarkers in the detection and evaluation of PCa. We performed a review of current peer-reviewed literature to assess this question. Much data has been published on the role of these tests, allowing for their placement into one of three best-fit categories: tests for biopsy-naïve men (Prostate Health Index, Mi Prostate Score, 4K Score); tests for men with prior negative biopsies (ConfirmMDx, Progensa PCA3); and men on active surveillance (OncotypeDx, Prolaris, Decipher). Data on the role of these tests with the use of mpMRI have not been comprehensive and excludes several of the markers. More research is needed to determine the combined impact mpMRI and the novel biomarkers on the evaluation and management of PCa.

How should radiologists incorporate non-imaging prostate cancer biomarkers into daily practice?

OBJECTIVE

To review the current body of evidence surrounding non-imaging biomarkers in patients with known or suspected prostate cancer.

RESULTS

Several non-imaging biomarkers have been developed and are available that aim to improve risk estimates at several clinical junctures. For patients with suspicion of prostate cancer who are considering first-time or repeat biopsy, blood- and urine-based assays can improve the prediction of harboring clinically significant disease and may reduce unnecessary biopsy. Blood- and urine-based biomarkers have been evaluated in association with prostate MRI, offering insights that might augment decision-making in the pre and post-MRI setting. Tissue-based genomic and proteomic assays have also been developed that provide independent assessments of prostate cancer aggressiveness that can complement imaging.

CONCLUSION

A growing number of non-imaging biomarkers are available to assist in clinical decision-making for men with known or suspected prostate cancer. An appreciation for the intersection of imaging and biomarkers may improve clinical care and resource utilization for men with prostate cancer.

Incorporating Magnetic Resonance Imaging and Biomarkers in Active Surveillance Protocols - Results From the Prospective Stockholm3 Active Surveillance Trial (STHLM3AS)

BACKGROUND

Active surveillance (AS) for men with low-risk prostate cancer (PC) can lead to patient morbidity and healthcare overutilization. The aim of this study was to evaluate an AS protocol using the Stockholm3 test and magnetic resonance imaging (MRI) to reduce biopsy intensity.

METHODS

We conducted a prospective multicenter study of 280 invited men from a contemporary screening study (STHLM3), with Gleason Score (GS) 3 + 3 PC on a current AS protocol. Patients underwent prostate-MRI and blood sampling for analysis of the Stockholm3 test including protein biomarkers, genetic variants, and clinical variables to predict risk of GS ≥3 + 4 PC followed by systematic biopsies and targeted biopsies (for Prostate Imaging Reporting and Data System version 2 ≥3 lesions) in all men. Primary outcomes were reclassification to GS ≥3 + 4 PC and clinically significant PC (csPCa), including unfavorable intermediate risk PC or higher based on National Comprehensive Cancer Network guidelines.

RESULTS

Adding MRI-targeted biopsies to systematic biopsies increased sensitivity of GS ≥3 + 4 PC compared with systematic biopsies alone (relative sensitivity [RS] = 1.52, 95% confidence interval [CI] = 1.28 to 1.85). Performing biopsies in only MRI positive increased sensitivity of GS ≥3 + 4 PC (RS = 1.30, 95% CI = 1.04 to 1.67) and reduced number of biopsy procedures by 49.3% while missing 7.2% GS ≥3 + 4 PC and 1.4% csPCa. Excluding men with negative Stockholm3 test reduced the number of MRI investigations at follow-up by 22.5% and biopsies by 56.8% while missing 6.9% GS ≥3 + 4 PC and 1.3% csPCa.

CONCLUSION

Including MRI and targeted/systematic biopsies in the follow-up for men on AS increased sensitivity of PC reclassification. Incorporation of risk prediction models including biomarkers may reduce the need for MRI use in men with low-risk PC.

Genetic Landscape of Prostate Cancer Conspicuity on Multiparametric Magnetic Resonance Imaging: A Systematic Review and Bioinformatic Analysis

Context

Multiparametric magnetic resonance imaging (mpMRI) detects most, but not all, clinically significant prostate cancer. The genetic basis of prostate cancer visibility and invisibility on mpMRI remains uncertain.

Objective

To systematically review the literature on differential gene expression between mpMRI-visible and mpMRI-invisible prostate cancer, and to use bioinformatic analysis to identify enriched processes or cellular components in genes validated in more than one study.

Evidence acquisition

We performed a systematic literature search of the Medline, EMBASE, PubMed, and Cochrane databases up to January 2020 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. The primary endpoint was differential genetic features between mpMRI-visible and mpMRI-invisible tumours. Secondary endpoints were explanatory links between gene function and mpMRI conspicuity, and the prognostic value of differential gene enrichment.

Evidence synthesis

We retrieved 445 articles, of which 32 met the criteria for inclusion. Thematic synthesis from the included studies showed that mpMRI-visible cancer tended towards enrichment of molecular features associated with increased disease aggressivity, including phosphatase and tensin homologue (PTEN) loss and higher genomic classifier scores, such as Oncotype and Decipher. Three of the included studies had accompanying publicly available data suitable for further bioinformatic analysis. An over-representation analysis of these datasets revealed increased expression of genes associated with extracellular matrix components in mpMRI-visible tumours.

Conclusions

Prostate cancer that is visible on mpMRI is generally enriched with molecular features of tumour development and aggressivity, including activation of proliferative signalling, DNA damage, and inflammatory processes. Additionally, there appears to be concordant cellular components and biological processes associated with mpMRI conspicuity, as highlighted by bioinformatic analysis of large genetic datasets.

Patient summary

Prostate cancer that is detected by magnetic resonance imaging (MRI) tends to have genetic features that are associated with more aggressive disease. This suggests that MRI can be used to assess the likelihood of aggressive prostate cancer, based on tumour visibility.

Prostate cancer and the role of biomarkers

PURPOSE

To review available prostate cancer biomarkers and their performance in a clinical order, from prostate cancer detection, to treatment of localized and advanced disease.

METHODS

We used an electronic literature search of the PubMed database using the key words "prostate biomarkers," "genomic markers," and "prostate cancer screening," as well as specific biomarkers, until March 2019.

RESULTS

Prostate-specific antigen (PSA) lacks sensitivity for prostate cancer detection, and PSA derivatives have slightly improved its specificity, but have not resolved the limitations of PSA screening. Prostate cancer biomarkers have emerged as an ancillary tool to guide the clinical decision-making in different clinical scenarios. Urine-based tests can identify patients who may benefit from a prostate biopsy, and issue-based markers are helpful in guiding the decision regarding a second biopsy, stratifying patient with newly diagnosed prostate cancer to active surveillance or treatment, and identifying patients who may benefit from adjuvant treatment after surgery.

CONCLUSIONS

New biomarkers have improved risk stratification in diagnosing and treating prostate cancer. Many of these markers are still considered experimental, and their efficacy and cost utility have not been determined.

Molecular Biomarkers in Localized Prostate Cancer: ASCO Guideline

PURPOSE

This guideline provides recommendations for available tissue-based prostate cancer biomarkers geared toward patient selection for active surveillance, identification of clinically significant disease, choice of postprostatectomy adjuvant versus salvage radiotherapy, and to address emerging questions such as the relative value of tissue biomarkers compared with magnetic resonance imaging.

METHODS

An ASCO multidisciplinary Expert Panel, with representatives from the European Association of Urology, American Urological Association, and the College of American Pathologists, conducted a systematic literature review of localized prostate cancer biomarker studies between January 2013 and January 2019. Numerous tissue-based molecular biomarkers were evaluated for their prognostic capabilities and potential for improving management decisions. Here, the Panel makes recommendations regarding the clinical use and indications of these biomarkers.

RESULTS

Of 555 studies identified, 77 were selected for inclusion plus 32 additional references selected by the Expert Panel. Few biomarkers had rigorous testing involving multiple cohorts and only 5 of these tests are commercially available currently: Oncotype Dx Prostate, Prolaris, Decipher, Decipher PORTOS, and ProMark. With various degrees of value and validation, multiple biomarkers have been shown to refine risk stratification and can be considered for select men to improve management decisions. There is a paucity of prospective studies assessing short- and long-term outcomes of patients when these markers are integrated into clinical decision making.

RECOMMENDATIONS

Tissue-based molecular biomarkers (evaluating the sample with the highest volume of the highest Gleason pattern) may improve risk stratification when added to standard clinical parameters, but the Expert Panel endorses their use only in situations in which the assay results, when considered as a whole with routine clinical factors, are likely to affect a clinical decision. These assays are not recommended for routine use as they have not been prospectively tested or shown to improve long-term outcomes-for example, quality of life, need for treatment, or survival. Additional information is available at www.asco.org/genitourinary-cancer-guidelines.

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.

Magnetic resonance imaging in active surveillance-a modern approach

In recent years, active surveillance has been increasingly adopted as a conservative management approach to low and sometimes intermediate risk prostate cancer, to avoid or delay treatment until there is evidence of higher risk disease. A number of studies have investigated the role of multiparametric magnetic resonance imaging (mpMRI) in this setting. MpMRI refers to the use of multiple MRI sequences (T2-weighted anatomical and functional imaging which can include diffusion-weighted imaging, dynamic contrast enhanced imaging, spectroscopy). Each of the parameters investigates different aspects of the prostate gland (anatomy, cellularity, vascularity, etc.). In addition to a qualitative assessment, the radiologist can also extrapolate quantitative imaging biomarkers from these sequences, for example the apparent diffusion coefficient from diffusion-weighted imaging. There are many different types of articles (e.g., reviews, commentaries, consensus meetings, etc.) that address the use of mpMRI in men on active surveillance for prostate cancer. In this paper, we compare original articles that investigate the role of the different mpMRI sequences in men on active surveillance for prostate cancer, in order to discuss the relative utility of the different sequences, and combinations of sequences. We searched MEDLINE/PubMed for manuscripts published from inception to 1^st December 2017. The search terms used were (prostate cancer or prostate adenocarcinoma or prostatic carcinoma or prostate carcinoma or prostatic adenocarcinoma) and (MRI or NMR or magnetic resonance imaging or mpMRI or multiparametric MRI) and active surveillance. Overall, 425 publications were found. All abstracts were reviewed to identify papers with original data. Twenty-five papers were analysed and summarised. Some papers based their analysis only on one mpMRI sequence, while others assessed two or more. The evidence from this review suggests that qualitative assessments and quantitative data from different mpMRI sequences hold promise in the management of men on active surveillance for prostate cancer. Both qualitative and quantitative approaches should be considered when assessing mpMRI of the prostate. There is a need for robust studies assessing the relative utility of different combinations of sequences in a systematic manner to determine the most efficient use of mpMRI in men on active surveillance.

Active Surveillance Use Among a Low-risk Prostate Cancer Population in a Large US Payer System: 17-Gene Genomic Prostate Score Versus Other Risk Stratification Methods

Many men with low-risk prostate cancer (PCa) receive definitive treatment despite recommendations that have been informed by two large, randomized trials encouraging active surveillance (AS). We conducted a retrospective cohort study using the Optum™ Research Database (Eden Prairie, MN) of electronic health records and administrative claims data to assess AS use for patients tested with a 17-gene Genomic Prostate Score™ (GPS; Genomic Health, Redwood City, CA) assay and/or prostate magnetic resonance imaging (MRI). De-identified records were extracted on health plan members enrolled from June 2013 to June 2016 who had ≥1 record of PCa (n 5 291,876). Inclusion criteria included age ≥18 years, new diagnosis, American Urological Association low-risk PCa (stage T1-T2a, prostate-specific antigen ≤10 ng/mL, Gleason score 5 6), and clinical activity for at least 12 months before and after diagnosis. Data included baseline characteristics, use of GPS testing and/or MRI, and definitive procedures. GPS or MRI testing was performed in 17% of men (GPS, n 5 375, 4%; MRI, n 5 1174, 13%). AS use varied from a low of 43% for men who only underwent MRI to 89% for GPStested men who did not undergo MRI (P <.001). At 6-month follow-up, AS use was 31.0% higher (95% CI, 27.6%-34.5%; P <.001) for men receiving the GPS test only versus men who did not undergo GPS testing or MRI; the difference was 30.5% at 12-month follow-up. In a large US payer system, the GPS assay was associated with significantly higher AS use at 6 and 12 months compared with men who had MRI only, or no GPS or MRI testing.