Transcriptomic heterogeneity in multifocal prostate cancer

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.

Development and Validation of an 18-Gene Urine Test for High-Grade Prostate Cancer

Importance

Benefits of prostate cancer (PCa) screening with prostate-specific antigen (PSA) alone are largely offset by excess negative biopsies and overdetection of indolent cancers resulting from the poor specificity of PSA for high-grade PCa (ie, grade group [GG] 2 or greater).

Objective

To develop a multiplex urinary panel for high-grade PCa and validate its external performance relative to current guideline-endorsed biomarkers.

Design, Setting, and Participants

RNA sequencing analysis of 58 724 genes identified 54 markers of PCa, including 17 markers uniquely overexpressed by high-grade cancers. Gene expression and clinical factors were modeled in a new urinary test for high-grade PCa (MyProstateScore 2.0 [MPS2]). Optimal models were developed in parallel without prostate volume (MPS2) and with prostate volume (MPS2+). The locked models underwent blinded external validation in a prospective National Cancer Institute trial cohort. Data were collected from January 2008 to December 2020, and data were analyzed from November 2022 to November 2023.

Exposure

Protocolized blood and urine collection and transrectal ultrasound-guided systematic prostate biopsy.

Main Outcomes and Measures

Multiple biomarker tests were assessed in the validation cohort, including serum PSA alone, the Prostate Cancer Prevention Trial risk calculator, and the Prostate Health Index (PHI) as well as derived multiplex 2-gene and 3-gene models, the original 2-gene MPS test, and the 18-gene MPS2 models. Under a testing approach with 95% sensitivity for PCa of GG 2 or greater, measures of diagnostic accuracy and clinical consequences of testing were calculated. Cancers of GG 3 or greater were assessed secondarily.

Results

Of 761 men included in the development cohort, the median (IQR) age was 63 (58-68) years, and the median (IQR) PSA level was 5.6 (4.6-7.2) ng/mL; of 743 men included in the validation cohort, the median (IQR) age was 62 (57-68) years, and the median (IQR) PSA level was 5.6 (4.1-8.0) ng/mL. In the validation cohort, 151 (20.3%) had high-grade PCa on biopsy. Area under the receiver operating characteristic curve values were 0.60 using PSA alone, 0.66 using the risk calculator, 0.77 using PHI, 0.76 using the derived multiplex 2-gene model, 0.72 using the derived multiplex 3-gene model, and 0.74 using the original MPS model compared with 0.81 using the MPS2 model and 0.82 using the MPS2+ model. At 95% sensitivity, the MPS2 model would have reduced unnecessary biopsies performed in the initial biopsy population (range for other tests, 15% to 30%; range for MPS2, 35% to 42%) and repeat biopsy population (range for other tests, 9% to 21%; range for MPS2, 46% to 51%). Across pertinent subgroups, the MPS2 models had negative predictive values of 95% to 99% for cancers of GG 2 or greater and of 99% for cancers of GG 3 or greater.

Conclusions and Relevance

In this study, a new 18-gene PCa test had higher diagnostic accuracy for high-grade PCa relative to existing biomarker tests. Clinically, use of this test would have meaningfully reduced unnecessary biopsies performed while maintaining highly sensitive detection of high-grade cancers. These data support use of this new PCa biomarker test in patients with elevated PSA levels to reduce the potential harms of PCa screening while preserving its long-term benefits.

Integrative multi-region molecular profiling of primary prostate cancer in men with synchronous lymph node metastasis

Localized prostate cancer is frequently composed of multiple spatially distinct tumors with significant inter- and intra-tumoral molecular heterogeneity. This genomic diversity gives rise to many competing clones that may drive the biological trajectory of the disease. Previous large-scale sequencing efforts have focused on the evolutionary process in metastatic prostate cancer, revealing a potential clonal progression to castration resistance. However, the clonal origin of synchronous lymph node (LN) metastases in primary disease is still unknown. Here, we perform multi-region, targeted next generation sequencing and construct phylogenetic trees in men with prostate cancer with synchronous LN metastasis to better define the pathologic and molecular features of primary disease most likely to spread to the LNs. Collectively, we demonstrate that a combination of histopathologic and molecular factors, including tumor grade, presence of extra-prostatic extension, cellular morphology, and oncogenic genomic alterations are associated with synchronous LN metastasis.

Transcriptomic Heterogeneity of Expansile Cribriform and Other Gleason Pattern 4 Prostate Cancer Subtypes

BACKGROUND

Prostate cancers featuring an expansile cribriform (EC) pattern are associated with worse clinical outcomes following radical prostatectomy (RP). However, studies of the genomic characteristics of Gleason pattern 4 subtypes are limited.

OBJECTIVE

To explore transcriptomic characteristics and heterogeneity within Gleason pattern 4 subtypes (fused/poorly formed, glomeruloid, small cribriform, EC/intraductal carcinoma [IDC]) and the association with biochemical recurrence (BCR)-free survival.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective cohort study including 165 men with grade group 2-4 prostate cancer who underwent RP at a single academic institution (2016-2020) and Decipher testing of the RP specimen. Patients with Gleason pattern 5 were excluded. IDC and EC patterns were grouped. Median follow-up was 2.5 yr after RP for patients without BCR.

OUTCOMES MEASUREMENTS AND STATISTICAL ANALYSIS

Prompted by heterogeneity within pattern 4 subtypes identified via exploratory analyses, we investigated transcriptomic consensus clusters using partitioning around medoids and hallmark gene set scores. The primary clinical outcome was BCR, defined as two consecutive prostate-specific antigen measurements >0.2 ng/ml at least 8 wk after RP, or any additional treatment. Multivariable Cox proportional-hazards models were used to determine factors associated with BCR-free survival.

RESULTS AND LIMITATIONS

In this cohort, 99/165 patients (60%) had EC and 67 experienced BCR. Exploratory analyses and clustering demonstrated transcriptomic heterogeneity within each Gleason pattern 4 subtype. In the multivariable model controlled for pattern 4 subtype, margin status, Cancer of the Prostate Risk Assessment Post-Surgical score, and Decipher score, a newly identified steroid hormone-driven cluster (hazard ratio 2.35 95% confidence interval 1.01-5.47) was associated with worse BCR-free survival. The study is limited by intermediate follow-up, no validation cohort, and lack of accounting for intratumoral and intraprostatic heterogeneity.

CONCLUSIONS

Transcriptomic heterogeneity was present within and across each Gleason pattern 4 subtype, demonstrating there is additional biologic diversity not captured by histologic subtypes. This heterogeneity can be used to develop novel signatures and to classify transcriptomic subtypes, which may help in refining risk stratification following RP to further guide decision-making on adjuvant and salvage treatments.

PATIENT SUMMARY

We studied prostatectomy specimens and found that tumors with similar microscopic appearance can have genetic differences that may help to predict outcomes after prostatectomy for prostate cancer. Our results demonstrate that further gene expression analysis of prostate cancer subtypes may improve risk stratification after prostatectomy. Future studies are needed to develop novel gene expression signatures and validate these findings in independent sets of patients.

Prostate cancer: Molecular aspects, consequences, and opportunities of the multifocal nature

Prostate cancer is unique compared to other major cancers due to the presence of multiple primary malignant foci in the majority of patients at the time of diagnosis. Each malignant focus has distinct somatic mutations and gene expression patterns, which represents a challenge for the development of prognostic tests for localized prostate cancer. Additionally, the molecular heterogeneity of advanced prostate cancer has important implications for management, particularly for patients with metastatic and locally recurrent cancer. Studies have shown that prostate cancers with mutations in DNA damage response genes are more sensitive to drugs inhibiting the poly ADP-ribose polymerase (PARP) enzyme. However, testing for such mutations should consider both spatial and temporal heterogeneity. Here, we summarize studies where multiregional genomics and transcriptomics analyses have been performed for primary prostate cancer. We further discuss the vast interfocal heterogeneity and how prognostic biomarkers and a molecular definition of the index tumor should be developed. The concept of focal treatments in prostate cancer has been evolving as a demand from patients and clinicians and is one example where there is a need for defining an index tumor. Here, biomarkers must have proven value for individual malignant foci. The potential discovery and implementation of biomarkers that are agnostic to heterogeneity are also explored as an alternative to multisample testing. Thus, deciding upon whole-organ treatment, such as radical prostatectomy, should depend on information from biomarkers which are informative for the whole organ.

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.

PRADclass: Hybrid Gleason Grade-Informed Computational Strategy Identifies Consensus Biomarker Features Predictive of Aggressive Prostate Adenocarcinoma

BACKGROUND

Prostate adenocarcinoma (PRAD) is a common cancer diagnosis among men globally, yet large gaps in our knowledge persist with respect to the molecular bases of its progression and aggression. It is mostly indolent and slow-growing, but aggressive prostate cancers need to be recognized early for optimising treatment, with a view to reducing mortality.

METHODS

Based on TCGA transcriptomic data pertaining to PRAD and the associated clinical metadata, we determined the sample Gleason grade, and used it to execute: (i) Gleason-grade wise linear modeling, followed by five contrasts against controls and ten contrasts between grades; and (ii) Gleason-grade wise network modeling via weighted gene correlation network analysis (WGCNA). Candidate biomarkers were obtained from the above analysis and the consensus found. The consensus biomarkers were used as the feature space to train ML models for classifying a sample as benign, indolent or aggressive.

RESULTS

The statistical modeling yielded 77 Gleason grade-salient genes while the WGCNA algorithm yielded 1003 trait-specific key genes in grade-wise significant modules. Consensus analysis of the two approaches identified two genes in Grade-1 (SLC43A1 and PHGR1), 26 genes in Grade-4 (including LOC100128675, PPP1R3C, NECAB1, UBXN10, SERPINA5, CLU, RASL12, DGKG, FHL1, NCAM1, and CEND1), and seven genes in Grade-5 (CBX2, DPYS, FAM72B, SHCBP1, TMEM132A, TPX2, UBE2C). A RandomForest model trained and optimized on these 35 biomarkers for the ternary classification problem yielded a balanced accuracy ∼ 86% on external validation.

CONCLUSIONS

The consensus of multiple parallel computational strategies has unmasked candidate Gleason grade-specific biomarkers. PRADclass, a validated AI model featurizing these biomarkers achieved good performance, and could be trialed to predict the differentiation of prostate cancers. PRADclass is available for academic use at: https://apalania.shinyapps.io/pradclass (online) and https://github.com/apalania/pradclass (command-line interface).

Cell-Free DNA Genomic Profiling and Its Clinical Implementation in Advanced Prostate Cancer

Most men with prostate cancer (PCa), despite potentially curable localized disease at initial diagnosis, progress to metastatic disease. Despite numerous treatment options, choosing the optimal treatment for individual patients remains challenging. Biomarkers guiding treatment sequences in an advanced setting are lacking. To estimate the diagnostic potential of liquid biopsies in guiding personalized treatment of PCa, we evaluated the utility of a custom-targeted next-generation sequencing (NGS) panel based on the AmpliSeq HD Technology. Ultra-deep sequencing on plasma circulating free DNA (cfDNA) samples of 40 metastatic castration-resistant PCa (mCRPC) and 28 metastatic hormone-naive PCa (mCSPC) was performed. CfDNA somatic mutations were detected in 48/68 (71%) patients. Of those 68 patients, 42 had matched tumor and cfDNA samples. In 21/42 (50%) patients, mutations from the primary tumor tissue were detected in the plasma cfDNA. In 7/42 (17%) patients, mutations found in the primary tumor were not detected in the cfDNA. Mutations from primary tumors were detected in all tested mCRPC patients (17/17), but only in 4/11 with mCSPC. AR amplifications were detected in 12/39 (31%) mCRPC patients. These results indicate that our targeted NGS approach has high sensitivity and specificity for detecting clinically relevant mutations in PCa.

Immunohistochemical markers as predictors of prognosis in multifocal prostate cancer

The impact of tumor focality on prostate cancer (PCa) prognosis has been addressed in several studies with conflicting results. Tumor foci from multifocal (MF) PCa can show highly heterogeneous molecular features. Our aim was to analyze the protein expression of PTEN, SPOP, SLC45A3, ETV1, ERG and the "triple hit" (ERG overexpression, PTEN plus SLC45A3 loss) in unifocal (UF) and MF PCa, to evaluate their value as prognostic markers according to focality, and the role of tumor heterogeneity in MF disease. PTEN, SPOP, SLC45A3, ETV1 and ERG immunohistochemical expression was evaluated in 185 PCa from 9 TMAs, 51 UF and 134 MF. In a subset of 69 MF cases, the dominant and secondary foci (DF and SF) were compared. Heterogeneity was considered when both tumor foci presented different expression patterns. Relationship with clinicopathological features was also analyzed. MF PCa was diagnosed in significantly younger patients when compared to UF ones (p = 0.007). ETV1 overexpression was associated with UF disease (p = 0.028). A shorter time to PSA recurrence was related to SLC45A3 wt expression in UF PCa (p = 0.052), and to SPOP expression loss (p = 0.043) or "triple hit" phenotype in MF PCa (p = 0.041). In MF cases, PTEN loss, SLC45A3 loss and "triple hit" phenotype were associated with the DF and had significant heterogeneity. In conclusion, our results indicate that UF and MF PCa have relevant and consistent molecular differences. The analysis of an immunohistochemical panel, composed by PTEN, SPOP, SLC45A3, ETV1 and ERG, could be useful to predict outcome in MF cases.

Prostate-derived circulating microRNAs add prognostic value to prostate cancer risk calculators

Prostate cancer is the second leading cause of malignancy-related deaths among American men. Active surveillance is a safe option for many men with less aggressive disease, yet definitively determining low-risk cancer is challenging with biopsy alone. Herein, we sought to identify prostate-derived microRNAs in patient sera and serum extracellular vesicles, and determine if those microRNAs improve upon the current clinical risk calculators for prostate cancer prognosis before and after biopsy. Prostate-derived intracellular and extracellular vesicle-contained microRNAs were identified by small RNA sequencing of prostate cancer patient explants and primary cells. Abundant microRNAs were included in a custom microRNA PCR panel that was queried in whole serum and serum extracellular vesicles from a diverse cohort of men diagnosed with prostate cancer. The levels of these circulating microRNAs significantly differed between indolent and aggressive disease and improved the area under the curve for pretreatment nomograms of prostate cancer disease risk. The microRNAs within the extracellular vesicles were the most informative and improved the AUC to 0.739 compared to the existing nomogram alone, which has an AUC of 0.561. The microRNAs in the whole serum improved it to AUC 0.675. In summary, quantifying microRNAs circulating in extracellular vesicles is a clinically feasible assay that may provide additional information for assessing prostate cancer risk stratification.

Development and validation of nomogram to improve the specificity of multiparametric MRI for clinically significant prostate cancer

OBJECTIVE

To develop and validate a nomogram to improve the specificity of prostate imaging reporting and data system (PI-RADS) on multiparametric magnetic resonance imaging (MRI) for clinically significant prostate cancer on targeted fusion biopsy.

METHODS

A retrospective review of patients who underwent fusion biopsy for PI-RADS 3-5 lesions using UroNav and Artemis systems between 2016 and 2022 was performed. Patients were divided into those with CS disease on fusion biopsy (Gleason grade group ≥2) versus those without. Multivariable analysis was used to identify variables associated with CS disease. A 100-point nomogram was constructed, and ROC curve was generated.

RESULTS

1485 lesions (1032 patients) were identified, 510 (34%) were PI-RADS 3, 586 (40%) were PI-RADS 4, and 389 (26%) were PI-RADS 5. Of these, 11% of PI-RADS 3, 39% of PI-RADS 4, and 61% of PI-RADS 5 showed CS disease. CS disease was associated with older age (OR 1.04, 95% CI 1.02-1.06, p < 0.01), previous negative biopsy (OR 0.52, 95% CI 0.36-0.74, p < 0.01), presence of multiple PI-RADS 3-5 lesions (OR 0.61, 95% CI 0.45-0.83, p < 0.01), peripheral zone location (OR 1.88, 95% CI 1.30-2.70, p < 0.01), PSA density (OR 1.48 per 0.1 unit, 95% CI 1.33-1.64, p < 0.01), PI-RADS score 4 (OR 3.28, 95% CI 2.21-4.87, p < 0.01), and PI-RADS score 5 (OR 7.65, 95% CI 4.93-11.85, p < 0.01). Area under ROC curve was 82% for nomogram compared to 75% for PI-RADS score alone.

CONCLUSION

We report a nomogram that combines PI-RADS score with other clinical parameters. The nomogram outperforms PI-RADS score for the detection of CS prostate cancer.

Loss of PDE4D7 expression promotes androgen independence, neuroendocrine differentiation and alterations in DNA repair: implications for therapeutic strategies

BACKGROUND

Androgen signalling remains the seminal therapeutic approach for the management of advanced prostate cancer. However, most tumours eventually shift towards an aggressive phenotype, characterised by androgen independence and treatment resistance. The cyclic adenosine monophosphate (cAMP) pathway plays a crucial role in regulating various cellular processes, with the phosphodiesterase PDE4D7 being a vital modulator of cAMP signalling in prostate cancer cells.

METHODS

Using shRNA-mediated PDE4D7 knockdown in LNCaP cells and downstream analysis via RNA sequencing and phenotypic assays, we replicate clinical observations that diminished PDE4D7 expression promotes an aggressive prostate cancer phenotype.

RESULTS

Our study provides evidence that loss of PDE4D7 expression represents a pivotal switch driving the transition from an androgen-sensitive state to hormone unresponsiveness and neuroendocrine differentiation. In addition, we demonstrate that PDE4D7 loss affects DNA repair pathways, conferring resistance to poly ADP ribose polymerase (PARP) inhibitors.

CONCLUSION

Reinstating PDE4D7 expression sensitises prostate cancer cells to anti-androgens, DNA damage response inhibitors, and cytotoxic therapies. These findings provide significant insight into the regulatory role of PDE4D7 in the development of lethal prostate cancer and the potential of its modulation as a novel therapeutic strategy.

Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated "Omics" Approaches to Explore Measurable Metrics

Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.

Prostate-derived circulating microRNAs add prognostic value to prostate cancer risk calculators

Prostate cancer is the second leading cause of malignancy-related deaths among American men. Active surveillance is a safe option for many men with less aggressive disease, yet definitively determining low-risk cancer is challenging with biopsy alone. Herein, we sought to identify prostate-derived microRNAs in patient sera and serum extracellular vesicles, and determine if those microRNAs improve upon the current clinical risk calculators for prostate cancer prognosis before and after biopsy. Prostate-derived intracellular and extracellular vesicle-contained microRNAs were identified by small RNA sequencing of prostate cancer patient explants and primary cells. Abundant microRNAs were included in a custom microRNA PCR panel that was queried in whole serum and serum extracellular vesicles from a diverse cohort of men diagnosed with prostate cancer. The levels of these circulating microRNAs significantly differed between indolent and aggressive disease and improved the area under the curve for pretreatment nomograms of prostate cancer disease risk. The microRNAs within the extracellular vesicles had improved prognostic value compared to the microRNAs in the whole serum. In summary, quantifying microRNAs circulating in extracellular vesicles is a clinically feasible assay that may provide additional information for assessing prostate cancer risk stratification.

Highly Recurrent IDH1 Mutations in Prostate Cancer With Psammomatous Calcification

Prostate cancer is a heterogeneous disease with several well-recognized morphologic subtypes and histologic variants-subsets of which are enriched for or associated with specific genomic alterations. Herein, we report a cohort of 4 unique prostate cancers characterized by intratumoral psammomatous calcification-which we have termed prostate cancer with psammomatous calcification (PCWPC). Clinicopathologic review demonstrates that PCWPCs are high-grade (grade group ≥3) tumors that involve the anterior prostate, and integrative targeted next-generation sequencing reveals recurrent hotspot IDH1 mutations. This morphology-molecular correlation is independently confirmed in The Cancer Genome Atlas prostatic adenocarcinoma cohort, with 3 of the 5 IDH1-mutant prostate cancers showing psammomatous calcification (rφ = 0.67; Fisher exact test, P < .0001). Overall, these findings suggest that PCWPC represents a novel subtype of prostate cancer enriched for an anterior location and the presence of hotspot IDH1 mutations. Recognition of these unique morphologic features could help identify IDH1-mutant prostate cancer cases retrospectively and prospectively-facilitating future large research studies and enabling clinical trial enrollment and precision medicine approaches for patients with advanced and/or aggressive disease.

Intermediate Grade Prostate Cancer and Risk for Adverse Pathology Radical Prostatectomy: Implications for Partial Gland Ablation Case Selection

PURPOSE

Using nationally representative data, we determined the likelihood of adverse pathology at radical prostatectomy (RP) to better inform case selection for partial gland ablation (PGA).

MATERIALS AND METHODS

We identified men with clinically localized GG2 (n = 106,048) and GG3 (n = 55,488) prostate cancer on biopsy from 2010 through 2019 who subsequently underwent RP. Men with GG2 were stratified as unfavorable and favorable per NCCN guidelines. RP adverse pathology was defined as upgrading to GG4-5, pT3-4, or nodal involvement (pN1), respectively. Logistic regression determined factors associated with adverse pathology, and the Cochran-Armitage Test was used to evaluate temporal trends.

RESULTS

Men with biopsy GG3 vs. GG2 experienced significant upgrading (11.3% vs. 3.6%, P < .001), more EPE (26.9% vs. 21.1%), SVI (11.9% vs. 5.3%), and pN1 (4.3% vs. 1.6%), all P < .001. When comparing unfavorable vs. favorable GG2, men experienced more EPE (25.3% vs. 16.5%), SVI (7.2% vs. 3%), and pN1 (2.2% vs. 0.8%), all P < .001. In adjusted analysis, age, Hispanic race, PSA > 10 ng/mL, and ≥ 50% positive biopsy cores were associated with adverse pathology (all P < .001). The likelihood of RP adverse pathology for men with biopsy GG3 increased significantly during the study period from 38.8% in 2010 to 47.3% in 2019 (P < .001).

CONCLUSION

Approximately 40% of men with GG3 and more than 30% with unfavorable GG2 prostate cancer harbor adverse pathology that may not be curable by PGA. Given MRI often understages prostate cancer, our findings have significant implications for optimizing PGA case selection and cancer control outcomes.

P-score in preoperative biopsies accurately predicts P-score in final pathology at radical prostatectomy in patients with localized prostate cancer

BACKGROUND

Prostate cancer (PCa) is a highly heterogeneous, multifocal disease, and identification of clinically significant lesions is challenging, which complicates the choice of adequate treatment. The Prostatype® score (P-score) is intended to guide treatment decisions for newly diagnosed PCa patients based on a three-gene signature (IGFBP3, F3, and VGLL3) and clinicopathological information obtained at diagnosis. This study evaluated association of the P-score measured in preoperative magnetic resonance imaging/transrectal ultrasound fusion-guided core needle biopsies (CNBs) and the P-score measured in radical prostatectomy (RP) specimens of PCa patients. We also evaluated the P-score association with the pathology of RP specimens. Furthermore, concordance of the P-score in paired CNB and RP specimens, as well as in index versus concomitant nonindex tumor foci from the same RP was investigated.

METHODS

The study included 100 patients with localized PCa. All patients were diagnosed by CNB and underwent RP between 2015 and 2018. Gene expression was assessed with the Prostatype® real-time quantitative polymerase chain reaction kit and the P-score was calculated. Patients were categorized into three P-score risk groups according to previously defined cutoffs.

RESULTS

For 71 patients, sufficient CNB tumor material was available for comparison with the RP specimens. The CNB-based P-score was associated with the pathological T-stage in RP specimens (p = 0.02). Moreover, the CNB-based P-score groups were in substantial agreement with the RP-based P-score groups (weighted κ score: 0.76 [95% confidence interval, 95% CI: 0.60-0.92]; Spearman's rank correlation coefficient r = 0.83 [95% CI: 0.74-0.89]; p < 0.0001). Similarly, the P-score groups based on paired index tumor and concomitant nonindex tumor foci (n = 64) were also in substantial agreement (weighted κ score: 0.74 [95% CI: 0.57-0.91]; r = 0.83 [95% CI: 0.73-0.89], p < 0.0001).

CONCLUSIONS

Our findings suggest that the P-score based on preoperative CNB accurately reflects the pathology of the whole tumor, highlighting its value as a decision support tool for newly diagnosed PCa patients.

Experimental in vitro, ex vivo and in vivo models in prostate cancer research

Androgen deprivation therapy has a central role in the treatment of advanced prostate cancer, often causing initial tumour remission before increasing independence from signal transduction mechanisms of the androgen receptor and then eventual disease progression. Novel treatment approaches are urgently needed, but only a fraction of promising drug candidates from the laboratory will eventually reach clinical approval, highlighting the demand for critical assessment of current preclinical models. Such models include standard, genetically modified and patient-derived cell lines, spheroid and organoid culture models, scaffold and hydrogel cultures, tissue slices, tumour xenograft models, patient-derived xenograft and circulating tumour cell eXplant models as well as transgenic and knockout mouse models. These models need to account for inter-patient and intra-patient heterogeneity, the acquisition of primary or secondary resistance, the interaction of tumour cells with their microenvironment, which make crucial contributions to tumour progression and resistance, as well as the effects of the 3D tissue network on drug penetration, bioavailability and efficacy.

Somatic mutations reveal complex metastatic seeding from multifocal primary prostate cancer

Primary prostate cancer shows a striking intraorgan molecular heterogeneity, with multiple spatially separated malignant foci in the majority of patients. Metastatic prostate cancer, however, typically reveals more homogenous molecular profiles, suggesting a monoclonal origin of the metastatic lesions. Longitudinal mutational spectra, comparing multiple primary lesions with metastases from the same patients remain poorly defined. We have here analyzed somatic mutations in multisampled, spatio-temporal biobanked lesions (38 samples from primary foci and 1 sample from each of 8 metastases from seven prostate cancer patients) applying a custom-designed panel targeting 68 prostate cancer relevant genes. The metastatic samples were taken at time of primary surgery and up to 7 years later, and sampling included circulating tumor DNA in plasma or solid metastatic tissue samples. A total of 282 somatic mutations were detected, with a range of 0 to 25 mutations per sample. Although seven samples had solely private mutations, the remaining 39 samples had both private and shared mutations. Seventy-four percent of mutations in metastases were not found in any primary samples, and vice versa, 96% of mutations in primary cancers were not found in any metastatic samples. However, for three patients, shared mutations were found suggesting the focus of origin, including mutations in AKT1, FOXA1, HOXB13, RB1 and TP53. In conclusion, the spatio-temporal heterogeneous nature of multifocal disease is emphasized in our study, and underlines the importance of testing a recent sample in genomics-based precision medicine for metastatic prostate cancer.

Diagnosis of childhood and adolescent growth hormone deficiency using transcriptomic data

BACKGROUND

Gene expression (GE) data have shown promise as a novel tool to aid in the diagnosis of childhood growth hormone deficiency (GHD) when comparing GHD children to normal children. The aim of this study was to assess the utility of GE data in the diagnosis of GHD in childhood and adolescence using non-GHD short stature children as a control group.

METHODS

GE data was obtained from patients undergoing growth hormone stimulation testing. Data were taken for the 271 genes whose expression was utilized in our previous study. The synthetic minority oversampling technique was used to balance the dataset and a random forest algorithm applied to predict GHD status.

RESULTS

24 patients were recruited to the study and eight subsequently diagnosed with GHD. There were no significant differences in gender, age, auxology (height SDS, weight SDS, BMI SDS) or biochemistry (IGF-I SDS, IGFBP-3 SDS) between the GHD and non-GHD subjects. A random forest algorithm gave an AUC of 0.97 (95% CI 0.93 - 1.0) for the diagnosis of GHD.

CONCLUSION

This study demonstrates highly accurate diagnosis of childhood GHD using a combination of GE data and random forest analysis.

Development of a Whole-urine, Multiplexed, Next-generation RNA-sequencing Assay for Early Detection of Aggressive Prostate Cancer

BACKGROUND

Despite biomarker development advances, early detection of aggressive prostate cancer (PCa) remains challenging. We previously developed a clinical-grade urine test (Michigan Prostate Score [MiPS]) for individualized aggressive PCa risk prediction. MiPS combines serum prostate-specific antigen (PSA), the TMPRSS2:ERG (T2:ERG) gene fusion, and PCA3 lncRNA in whole urine after digital rectal examination (DRE).

OBJECTIVE

To improve on MiPS with a novel next-generation sequencing (NGS) multibiomarker urine assay for early detection of aggressive PCa.

DESIGN, SETTING, AND PARTICIPANTS

Preclinical development and validation of a post-DRE urine RNA NGS assay (Urine Prostate Seq [UPSeq]) assessing 84 PCa transcriptomic biomarkers, including T2:ERG, PCA3, additional PCa fusions/isoforms, mRNAs, lncRNAs, and expressed mutations. Our UPSeq model was trained on 73 patients and validated on a held-out set of 36 patients representing the spectrum of disease (benign to grade group [GG] 5 PCa).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The area under the receiver operating characteristic curve (AUC) of UPSeq was compared with PSA, MiPS, and other existing models/biomarkers for predicting GG ≥3 PCa.

RESULTS AND LIMITATIONS

UPSeq demonstrated high analytical accuracy and concordance with MiPS, and was able to detect expressed germline HOXB13 and somatic SPOP mutations. In an extreme design cohort (n = 109; benign/GG 1 vs GG ≥3 PCa, stratified to exclude GG 2 cancer in order to capture signal difference between extreme ends of disease), UPSeq showed differential expression for T2:ERG.T1E4 (1.2 vs 78.8 median normalized reads, p < 0.00001) and PCA3 (1024 vs 2521, p = 0.02), additional T2:ERG splice isoforms, and other candidate biomarkers. Using machine learning, we developed a 15-transcript model on the training set (n = 73) that outperformed serum PSA and sequencing-derived MiPS in predicting GG ≥3 PCa in the held-out validation set (n = 36; AUC 0.82 vs 0.69 and 0.69, respectively).

CONCLUSIONS

These results support the potential utility of our novel urine-based RNA NGS assay to supplement PSA for improved early detection of aggressive PCa.

PATIENT SUMMARY

We have developed a new urine-based test for the detection of aggressive prostate cancer, which promises improvement upon current biomarker tests.

Genomic Sequencing Should Be Part of the Standard of Care for Most Urologic Cancers: For

Genomic sequencing should be part of the standard of care for most urologic cancers.

Identification of prostate cancer subtypes based on immune signature scores in bulk and single-cell transcriptomes

Prostate cancer (PC) is heterogeneous in the tumor immune microenvironment (TIME). Subtyping of PC based on the TIME could provide new insights into intratumor heterogeneity and its correlates of clinical features. Based on the enrichment scores of 28 immune cell types in the TIME, we performed unsupervised clustering to identify immune-specific subtypes of PC. The clustering analysis was performed in ten different bulk tumor transcriptomic datasets and in a single-cell RNA-Seq (scRNA-seq) dataset, respectively. We identified two PC subtypes: PC immunity high (PC-ImH) and PC immunity low (PC-ImL), consistently in these datasets. Compared to PC-ImL, PC-ImH displayed stronger immune signatures, worse clinical outcomes, higher epithelial-mesenchymal transition (EMT) signature, tumor stemness, intratumor heterogeneity (ITH) and genomic instability, and lower incidence of TMPRSS2-ERG fusion. Tumor mutation burden (TMB) showed no significant difference between PC-ImH and PC-ImL, while copy number alteration (CNA) was more significant in PC-ImL than in PC-ImH. PC-ImH could be further divided into two subgroups, which had significantly different immune infiltration levels and clinical features. In conclusion, "hot" PCs have stronger anti-tumor immune response, while worse clinical outcomes versus "cold" PCs. CNA instead of TMB plays a crucial role in the regulation of TIME in PC. TMPRSS2-ERG fusion correlates with decreased anti-tumor immune response while better disease-free survival in PC. The identification of immune-specific subtypes has potential clinical implications for PC immunotherapy.

Germline mutations in penetrant cancer predisposition genes are rare in men with prostate cancer selecting active surveillance

BACKGROUND

Pathogenic germline mutations in several rare penetrant cancer predisposition genes are associated with an increased risk of aggressive prostate cancer (PC). Our objectives were to determine the prevalence of pathogenic germline mutations in men with low-risk PC on active surveillance, and assess whether pathogenic germline mutations associate with grade reclassification or adverse pathology, recurrence, or metastases, in men treated after initial surveillance.

METHODS

Men prospectively enrolled in the Canary Prostate Active Surveillance Study (PASS) were retrospectively sampled for the study. Germline DNA was sequenced utilizing a hereditary cancer gene panel. Mutations were classified according to the American College of Clinical Genetics and Genomics' guidelines. The association of pathogenic germline mutations with grade reclassification and adverse characteristics was evaluated by weighted Cox proportional hazards modeling and conditional logistic regression, respectively.

RESULTS

Overall, 29 of 437 (6.6%) study participants harbored a pathogenic germline mutation of which 19 occurred in a gene involved in DNA repair (4.3%). Eight participants (1.8%) had pathogenic germline mutations in three genes associated with aggressive PC: ATM, BRCA1, and BRCA2. The presence of pathogenic germline mutations in DNA repair genes did not associate with adverse characteristics (univariate analysis HR = 0.87, 95% CI: 0.36-2.06, p = 0.7). The carrier rates of pathogenic germline mutations in ATM, BRCA1, and BRCA2did not differ in men with or without grade reclassification (1.9% vs. 1.8%).

CONCLUSION

The frequency of pathogenic germline mutations in penetrant cancer predisposition genes is extremely low in men with PC undergoing active surveillance and pathogenic germline mutations had no apparent association with grade reclassification or adverse characteristics.

Comparative genomics of primary prostate cancer and paired metastases: insights from 12 molecular case studies

Primary prostate cancer (PCa) can show marked molecular heterogeneity. However, systematic analyses comparing primary PCa and matched metastases in individual patients are lacking. We aimed to address the molecular aspects of metastatic progression while accounting for the heterogeneity of primary PCa. In this pilot study, we collected 12 radical prostatectomy (RP) specimens from men who subsequently developed metastatic castration‐resistant prostate cancer (mCRPC). We used histomorphology (Gleason grade, focus size, stage) and immunohistochemistry (IHC) (ERG and p53) to identify independent tumors and/or distinct subclones of primary PCa. We then compared molecular profiles of these primary PCa areas to matched metastatic samples using whole‐exome sequencing (WES) and amplicon‐based DNA and RNA sequencing. Based on combined pathology and molecular analysis, seven (58%) RP specimens harbored monoclonal and topographically continuous disease, albeit with some degree of intratumor heterogeneity; four (33%) specimens showed true multifocal disease; and one displayed monoclonal disease with discontinuous topography. Early (truncal) events in primary PCa included SPOP p.F133V (one patient), BRAF p.K601E (one patient), and TMPRSS2:ETS rearrangements (eight patients). Activating AR alterations were seen in nine (75%) mCRPC patients, but not in matched primary PCa. Hotspot TP53 mutations, found in metastases from three patients, were readily present in matched primary disease. Alterations in genes encoding epigenetic modifiers were observed in several patients (either shared between primary foci and metastases or in metastatic samples only). WES‐based phylogenetic reconstruction and/or clonality scores were consistent with the index focus designated by pathology review in six out of nine (67%) cases. The three instances of discordance pertained to monoclonal, topographically continuous tumors, which would have been considered as unique disease in routine practice. Overall, our results emphasize pathologic and molecular heterogeneity of primary PCa, and suggest that comprehensive IHC‐assisted pathology review and genomic analysis are highly concordant in nominating the ‘index’ primary PCa area. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Expressed prognostic biomarkers for primary prostate cancer independent of multifocality and transcriptome heterogeneity

The majority of prostate cancer patients are diagnosed with multiple primary malignant foci. The distinct foci are exceptionally heterogeneous with regard to DNA mutations, but whether this is recapitulated at the transcriptome level remains unknown. In this study, inter- and intrafocal heterogeneity has been assessed by whole-transcriptome sequencing of 87 tissue samples from 23 patients with localized prostate cancer treated with radical prostatectomy. From each patient, multiple samples were taken from one or more malignant foci, in addition to one sample from benign prostate tissue. Transcriptomic profiles of different malignant foci from the same patient showed a similar level of heterogeneity as tumors from different patients. This applies to expression of genes, fusion genes, and somatic mutations. Within-patient pair-wise analyses identified expression patterns linked to ETS status and extraprostatic extension. A set of 62 genes were found with low intrapatient heterogeneity and high interpatient heterogeneity, retaining stable expression profiles across foci within the same patient. Among these, 16 genes are associated with biochemical recurrence in a separately published study and are therefore nominated as biomarkers with prognostic value regardless of which malignant focus is sampled. In conclusion, an extensive heterogeneity in multifocal prostate cancer is confirmed at the gene expression level. Diagnostic biomarkers were identified for ETS positive samples and samples from extraprostatic extensions. Finally, prognostic biomarkers independent of multifocal heterogeneity were found.

Prostate zones and cancer: lost in transition?

Localized prostate cancer shows great clinical, genetic and environmental heterogeneity; however, prostate cancer treatment is currently guided solely by clinical staging, serum PSA levels and histology. Increasingly, the roles of differential genomics, multifocality and spatial distribution in tumorigenesis are being considered to further personalize treatment. The human prostate is divided into three zones based on its histological features: the peripheral zone (PZ), the transition zone (TZ) and the central zone (CZ). Each zone has variable prostate cancer incidence, prognosis and outcomes, with TZ prostate tumours having better clinical outcomes than PZ and CZ tumours. Molecular and cell biological studies can improve understanding of the unique molecular, genomic and zonal cell type features that underlie the differences in tumour progression and aggression between the zones. The unique biology of each zonal tumour type could help to guide individualized treatment and patient risk stratification.

Fibroblast heterogeneity in prostate carcinogenesis

Our understanding of stromal components, specifically cancer-associated fibroblasts (CAF), in prostate cancer (PCa), has evolved from considering these cells as inert bystanders to acknowledging their significance as players in prostate tumorigenesis. CAF are multifaceted-they promote cancer cell growth, migration and remodel the tumor microenvironment. Although targeting CAF could be a promising strategy for PCa treatment, they incorporate a high but undefined degree of intrinsic cellular heterogeneity. The interaction between CAF subpopulations, with the normal and tumor epithelium and with other cell types is not yet characterized. Defining these interactions and the critical signaling nodes that support tumorigenesis will enable the development of novel strategies to control prostate cancer progression. Here we will discuss the origins, molecular and functional heterogeneity of CAF in PCa. We highlight the challenges associated with delineating CAF heterogeneity and discuss potential areas of research that would assist in expanding our knowledge of CAF and their role in PCa tumorigenesis.

Molecular Characterization of Clear Cell Renal Cell Carcinoma Reveals Prognostic Significance of Epithelial-mesenchymal Transition Gene Expression Signature

BACKGROUND

There is an ongoing need to develop prognostic biomarkers to improve the management of clear cell renal cell carcinoma (ccRCC).

OBJECTIVE

To leverage enriched pathways in ccRCC to improve risk-stratification.

DESIGN, SETTING, AND PARTICIPANTS

We retrospectively identified two complementary discovery cohorts of patients with ccRCC who underwent (1) radical nephrectomy (RNx) with inferior vena cava tumor thrombectomy (patients = 5, samples = 24) and (2) RNx for localized disease and developed recurrence versus no recurrence (n = 36). Patients with localized ccRCC (M0) in The Cancer Genome Atlas (TCGA, n = 386) were used for validation.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

A differential expression gene (DEG) analysis was performed on targeted RNA next-generation sequencing data from both discovery cohorts. Using TCGA for validation, Kaplan-Meier survival analysis and multivariable Cox proportional hazard testing were utilized to investigate the prognostic impact of DEGs, cell cycle proliferation (CCP), and a novel epithelial-mesenchymal transition (EMT) score on progression-free (PFS) and disease-specific (DSS) survival.

RESULTS AND LIMITATIONS

In the discovery cohorts, we observed overexpression of WT1 and CCP genes in the tumor thrombus versus the primary tumor, as well as in patients with recurrence versus those without recurrence. A hallmark pathway analysis demonstrated enrichment of the EMT- and CCP-related pathways in patients with high WT1 expression in the TCGA (validation) ccRCC cohort. CCP and EMT scores were derived in the validation cohort, which was stratified into four risk groups using Youden Index cut points: CCP^low/EMT^low, CCP^low/EMT^high, CCP^high/EMT^low, and CCP^high/EMT^high. The CCP^high/EMT^high risk group was associated with the worst PFS and DSS (both p < 0.001). In a multivariable analysis, CCP^high/EMT^high was independently associated with poor PFS and DSS (hazard ratio = 4.6 and 10.3, respectively; p < 0.001).

CONCLUSIONS

We demonstrate the synergistic prognostic impact of EMT in tumors with a high CCP score. Our novel EMT score has the potential to improve risk stratification and provide potential novel therapeutic targets.

PATIENT SUMMARY

Genes involved in epithelial-mesenchymal transition provides important prognostic information for patients with clear cell renal cell carcinoma.

Comparison of approaches to transcriptomic analysis in multi-sampled tumors

Intratumoral heterogeneity is a well-documented feature of human cancers and is associated with outcome and treatment resistance. However, a heterogeneous tumor transcriptome contributes an unknown level of variability to analyses of differentially expressed genes (DEGs) that may contribute to phenotypes of interest, including treatment response. Although current clinical practice and the vast majority of research studies use a single sample from each patient, decreasing costs of sequencing technologies and computing power have made repeated-measures analyses increasingly economical. Repeatedly sampling the same tumor increases the statistical power of DEG analysis, which is indispensable toward downstream analysis and also increases one's understanding of within-tumor variance, which may affect conclusions. Here, we compared five different methods for analyzing gene expression profiles derived from repeated sampling of human prostate tumors in two separate cohorts of patients. We also benchmarked the sensitivity of generalized linear models to linear mixed models for identifying DEGs contributing to relevant prostate cancer pathways based on a ground-truth model.

An RNA-Seq-Based Framework for Characterizing Canine Prostate Cancer and Prioritizing Clinically Relevant Biomarker Candidate Genes

Prostate cancer (PCa) in dogs is a highly malignant disease akin to its human counterpart. In contrast to the situation in humans, multi-gene approaches facilitating risk stratification of canine PCa are barely established. The aims of this study were the characterization of the transcriptional landscape of canine PCa and the identification of diagnostic, prognostic and/or therapeutic biomarkers through a multi-step screening approach. RNA-Sequencing of ten malignant tissues and fine-needle aspirations (FNA), and 14 nonmalignant tissues and FNAs was performed to find differentially expressed genes (DEGs) and deregulated pathways. The 4098 observed DEGs were involved in 49 pathways. These 49 pathways could be grouped into five superpathways summarizing the hallmarks of canine PCa: (i) inflammatory response and cytokines; (ii) regulation of the immune system and cell death; (iii) cell surface and PI3K signaling; (iv) cell cycle; and (v) phagosome and autophagy. Among the highly deregulated, moderately to strongly expressed DEGs that were members of one or more superpathways, 169 DEGs were listed in relevant databases and/or the literature and included members of the PCa pathway, oncogenes, prostate-specific genes, and druggable genes. These genes are novel and promising candidate diagnostic, prognostic and/or therapeutic canine PCa biomarkers.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

Chromatin and Epigenetic Dysregulation of Prostate Cancer Development, Progression, and Therapeutic Response

The dysregulation of chromatin and epigenetics has been defined as the overarching cancer hallmark. By disrupting transcriptional regulation in normal cells and mediating tumor progression by promoting cancer cell plasticity, this process has the ability to mediate all defined hallmarks of cancer. In this review, we collect and assess evidence on the contribution of chromatin and epigenetic dysregulation in prostate cancer. We highlight important mechanisms leading to prostate carcinogenesis, the emergence of castration-resistance upon treatment with androgen deprivation therapy, and resistance to antiandrogens. We examine in particular the contribution of chromatin structure and epigenetics to cell lineage commitment, which is dysregulated during tumorigenesis, and cell plasticity, which is altered during tumor progression.

Role of PCA3 and SelectMDx in the optimization of active surveillance in prostate cancer

INTRODUCTION & OBJECTIVES

A not negligible percentage of patients included in active surveillance (AS) for low and very low risk prostate cancer (PCa) are reclassified in the confirmatory biopsy or have disease progression during follow-up. Our aim is to evaluate the role of PCA3 and SelectMDx, in an individual and combined way, in the prediction of pathological progression (PP) in a standard AS program.

MATERIALS & METHODS

Prospective and observational study comprised of 86 patients enrolled in an AS program from 2009 to 2019, with results for PCA3 and SelectMDx previous to PCa diagnosis or during their confirmatory period. Univariate and multivariate analysis were performed to correlate PCA3 and SelectMDx scores as well as clinical and pathological variables with PP-free survival (PPFS). The most reliable cut-offs for both biomarkers in the context of AS were defined.

RESULTS

SelectMDx showed statistically significant differences related to PPFS (HR 1.035, 95%CI: 1.012-1.057) (p = 0.002) with a C-index of 0.670 (95%CI: 0.529-0.810) and AUC of 0.714 (95%CI: 0.603-0.825) at 5 years. In our series, the most reliable cut-off point for SelectMDx was 5, with a sensitivity and specificity for PP of 69.8% and 67.4%, respectively. Same figure for PCA3 was 65, with a sensitivity and specificity for PP of 51.16% and 74.42%, respectively. The combination of both biomarkers did not improve the prediction of PP, C-index 0.630 (95%CI: 0.455-0.805).

CONCLUSIONS

In the context of low or very low risk PCa, SelectMDx > 5 predicted 5 years PP free survival with a moderate discrimination ability outperforming PCA3. The combination of both tests did not improved outcomes.

A novel nomogram provides improved accuracy for predicting biochemical recurrence after radical prostatectomy

Background:

Various prediction tools have been developed to predict biochemical recurrence (BCR) after radical prostatectomy (RP); however, few of the previous prediction tools used serum prostate-specific antigen (PSA) nadir after RP and maximum tumor diameter (MTD) at the same time. In this study, a nomogram incorporating MTD and PSA nadir was developed to predict BCR-free survival (BCRFS).

Methods:

A total of 337 patients who underwent RP between January 2010 and March 2017 were retrospectively enrolled in this study. The maximum diameter of the index lesion was measured on magnetic resonance imaging (MRI). Cox regression analysis was performed to evaluate independent predictors of BCR. A nomogram was subsequently developed for the prediction of BCRFS at 3 and 5 years after RP. Time-dependent receiver operating characteristic (ROC) curve and decision curve analyses were performed to identify the advantage of the new nomogram in comparison with the cancer of the prostate risk assessment post-surgical (CAPRA-S) score.

Results:

A novel nomogram was developed to predict BCR by including PSA nadir, MTD, Gleason score, surgical margin (SM), and seminal vesicle invasion (SVI), considering these variables were significantly associated with BCR in both univariate and multivariate analyses (P < 0.05). In addition, a basic model including Gleason score, SM, and SVI was developed and used as a control to assess the incremental predictive power of the new model. The concordance index of our model was slightly higher than CAPRA-S model (0.76 vs. 0.70, P = 0.02) and it was significantly higher than that of the basic model (0.76 vs. 0.66, P = 0.001). Time-dependent ROC curve and decision curve analyses also demonstrated the advantages of the new nomogram.

Conclusions:

PSA nadir after RP and MTD based on MRI before surgery are independent predictors of BCR. By incorporating PSA nadir and MTD into the conventional predictive model, our newly developed nomogram significantly improved the accuracy in predicting BCRFS after RP.

Prostate cancer patient-derived organoids: detailed outcome from a prospective cohort of 81 clinical specimens

Patient‐derived organoids (PDOs) represent promising preclinical models in various tumor types. In the context of prostate cancer (PCa), however, their establishment has been hampered by poor success rates, which impedes their broad use for translational research applications. Along with the necessity to improve culture conditions, there is a need to identify factors influencing outcomes and to determine how to assess success versus failure in organoid generation. In the present study, we report our unbiased efforts to generate PDOs from a cohort of 81 PCa specimens with diverse pathological and clinical features. We comprehensively analyzed histological features of each enrolled sample (Gleason score, tumor content, proliferation index) and correlated them with organoid growth patterns. We identified improved culture conditions favoring the generation of PCa organoids, yet no specific intrinsic tumor feature was broadly associated with sustained organoid growth. In addition, we performed phenotypic and molecular characterization of tumor–organoid pairs using immunohistochemistry, immunofluorescence, fluorescence in situ hybridization, and targeted sequencing. Morphological and immunohistochemical profiles of whole organoids altogether provided a fast readout to identify the most promising ones. Notably, primary samples were associated with an initial take‐rate of 83% (n = 60/72) in culture, with maintenance of cancer cells displaying common PCa alterations, such as PTEN loss and ERG overexpression. These cancer organoids were, however, progressively overgrown by organoids with a benign‐like phenotype. Finally, out of nine metastasis samples, we generated a novel organoid model derived from a hormone‐naïve lung metastasis, which displays alterations in the PI3K/Akt and Wnt/β‐catenin pathways and responds to androgen deprivation. Taken together, our comprehensive study explores determinants of outcome and highlights the opportunities and challenges associated with the establishment of stable tumor organoid lines derived from PCa patients. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

High expression of SCHLAP1 in primary prostate cancer is an independent predictor of biochemical recurrence, despite substantial heterogeneity

In primary prostate cancer, the common multifocality and heterogeneity are major obstacles in finding robust prognostic tissue biomarkers. The long noncoding RNA SCHLAP1 has been suggested, but its prognostic value has not been investigated in the context of tumor heterogeneity. In the present study, expression of SCHLAP1 was investigated using real-time RT-PCR in a multisampled series of 778 tissue samples from radical prostatectomies of 164 prostate cancer patients (median follow-up time 7.4 y). The prognostic value of SCHLAP1 was evaluated with biochemical recurrence as endpoint. In total, 29% of patients were classified as having high expression of SCHLAP1 in at least one malignant sample. Among these, inter- and intrafocal heterogeneity was detected in 72% and 56%, respectively. High expression of SCHLAP1 was shown to be a predictor of biochemical recurrence in both uni- and multivariable cox regression analyses (P < 0.001 and P = 0.02). High expression of SCHLAP1 was also significantly associated with adverse clinicopathological characteristics, including grade group, high pT stage, invasive cribriform growth/intraductal carcinoma of the prostate, and reactive stroma. In conclusion, high expression of SCHLAP1 in at least one malignant sample is a robust prognostic biomarker in primary prostate cancer. For the first time, high SCHLAP1 expression has been associated with the aggressive histopathologic feature reactive stroma. The expression of SCHLAP1 is highly heterogeneous, and analysis of multiple samples is therefore crucial in determination of the SCHLAP1 status of a patient.

Genetic and non-genetic clonal diversity in cancer evolution

The observation and analysis of intra-tumour heterogeneity (ITH), particularly in genomic studies, has advanced our understanding of the evolutionary forces that shape cancer growth and development. However, only a subset of the variation observed in a single tumour will have an impact on cancer evolution, highlighting the need to distinguish between functional and non-functional ITH. Emerging studies highlight a role for the cancer epigenome, transcriptome and immune microenvironment in functional ITH. Here, we consider the importance of both genetic and non-genetic ITH and their role in tumour evolution, and present the rationale for a broad research focus beyond the cancer genome. Systems-biology analytical approaches will be necessary to outline the scale and importance of functional ITH. By allowing a deeper understanding of tumour evolution this will, in time, encourage development of novel therapies and improve outcomes for patients.

A Systematic Review of Prostate Cancer Heterogeneity: Understanding the Clonal Ancestry of Multifocal Disease

CONTEXT

Studies characterising genomic changes in prostate cancer (PCa) during natural progression have greatly increased our understanding of the disease. A better understanding of the evolutionary history of PCa would allow advances in diagnostics, prognostication, and novel therapies that together will improve patient outcomes.

OBJECTIVE

To review the molecular heterogeneity of PCa and assess recent efforts to profile intratumoural heterogeneity and clonal evolution.

EVIDENCE ACQUISITION

We screened a total of 1313 abstracts from PubMed published between 2009 and 2020, of which we reviewed 84 full-text articles. We excluded 49, resulting in 35 studies for qualitative analysis.

EVIDENCE SYNTHESIS

In studies of primary disease (16 studies, 4793 specimens), there is a lack of consensus regarding the monoclonal or polyclonal origin of primary PCa. There is no consistent mutation giving rise to primary PCa. Detailed clonal analysis of primary PCa has been limited by current techniques. By contrast, clonal relationships between PCa metastases and a potentiating clone have been consistently identified (19 studies, 732 specimens). Metastatic specimens demonstrate consistent truncal genomic aberrations that suggest monoclonal metastatic progenitors.

CONCLUSIONS

The relationship between the clonal dynamics of PCa and clinical outcomes needs further investigation. It is likely that this will provide a biological rationale for whether radical treatment of the primary tumour benefits patients with oligometastatic PCa. Future studies on the mutational burden in primary disease at single-cell resolution should permit the identification of clonal patterns underpinning the origin of lethal PCa.

PATIENT SUMMARY

Prostate cancers arise in different parts of the prostate because of DNA mutations that occur by chance at different times. These cancer cells and their origin can be tracked by DNA mapping. In this review we summarise the state of the art and outline what further science is needed to provide the missing answers.

Tissue-Based Biomarkers for the Risk Stratification of Men With Clinically Localized Prostate Cancer

Risk stratification of men with clinically localized prostate cancer has historically relied on basic clinicopathologic parameters such as prostate specific antigen level, grade group, and clinical stage. However, prostate cancer often behaves in ways that cannot be accurately predicted by these parameters. Thus, recent efforts have focused on developing tissue-based genomic tests that provide greater insights into the risk of a given patient's disease. Multiple tests are now commercially available and provide additional prognostic information at various stages of the care pathway for prostate cancer. Indeed, early evidence suggests that these assays may have a significant impact on patient and physician decision-making. However, the impact of these tests on oncologic outcomes remains less clear. In this review, we highlight recent advances in the use of tissue-based biomarkers in the treatment of prostate cancer and identify the existing evidence supporting their clinical use.

Role of PCA3 and SelectMDx in the optimization of active surveillance in prostate cancer

INTRODUCTION AND OBJECTIVES

A not negligible percentage of patients included in active surveillance (AS) for low and very low risk prostate cancer (PCa) are reclassified in the confirmatory biopsy or have disease progression during follow-up. Our aim is to evaluate the role of PCA3 and SelectMDx, in an individual and combined way, in the prediction of pathological progression (PP) in a standard AS program.

MATERIALS AND METHODS

Prospective and observational study comprised of 86 patients enrolled in an AS program from 2009 to 2019, with results for PCA3 and SelectMDx previous to PCa diagnosis or during their confirmatory period. Univariate and multivariate analysis were performed to correlate PCA3 and SelectMDx scores as well as clinical and pathological variables with PP-free survival (PPFS). The most reliable cut-offs for both biomarkers in the context of AS were defined.

RESULTS

SelectMDx showed statistically significant differences related to PPFS (HR: 1.035; 95%CI: 1.012-1.057) (P=.002) with a C-index of 0.670 (95%CI: 0.529-0.810) and AUC of 0.714 (95%CI: 0.603-0.825) at 5years. In our series, the most reliable cut-off point for SelectMDx was 5, with a sensitivity and specificity for PP of 69.8% and 67.4%, respectively. Same figure for PCA3 was 65, with a sensitivity and specificity for PP of 51.16% and 74.42%, respectively. The combination of both biomarkers did not improve the prediction of PP, C-index 0.630 (95%CI: 0.455-0.805).

CONCLUSIONS

In the context of low or very low risk PCa, SelectMDx >5 predicted 5years PP free survival with a moderate discrimination ability outperforming PCA3. The combination of both tests did not improved outcomes.

Serial Molecular Profiling of Low-grade Prostate Cancer to Assess Tumor Upgrading: A Longitudinal Cohort Study

BACKGROUND

The potential for low-grade (grade group 1 [GG1]) prostate cancer (PCa) to progress to high-grade disease remains unclear.

OBJECTIVE

To interrogate the molecular and biological features of low-grade PCa serially over time.

DESIGN, SETTING, AND PARTICIPANTS

Nested longitudinal cohort study in an academic active surveillance (AS) program. Men were on AS for GG1 PCa from 2012 to 2017.

INTERVENTION

Electronic tracking and resampling of PCa using magnetic resonance imaging/ultrasound fusion biopsy.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

ERG immunohistochemistry (IHC) and targeted DNA/RNA next-generation sequencing were performed on initial and repeat biopsies. Tumor clonality was assessed. Molecular data were compared between men who upgraded and those who did not upgrade to GG ≥ 2 cancer.

RESULTS AND LIMITATIONS

Sixty-six men with median age 64 yr (interquartile range [IQR], 59-69) and prostate-specific antigen 4.9 ng/mL (IQR, 3.3-6.4) underwent repeat sampling of a tracked tumor focus (median interval, 11 mo; IQR, 6-13). IHC-based ERG fusion status was concordant at initial and repeat biopsies in 63 men (95% vs expected 50%, p <  0.001), and RNAseq-based fusion and isoform expression were concordant in nine of 13 (69%) ERG+ patients, supporting focal resampling. Among 15 men who upgraded with complete data at both time points, integrated DNA/RNAseq analysis provided evidence of shared clonality in at least five cases. Such cases could reflect initial undersampling, but also support the possibility of clonal temporal progression of low-grade cancer. Our assessment was limited by sample size and use of targeted sequencing.

CONCLUSIONS

Repeat molecular assessment of low-grade tumors suggests that clonal progression could be one mechanism of upgrading. These data underscore the importance of serial tumor assessment in men pursuing AS of low-grade PCa.

PATIENT SUMMARY

We performed targeted rebiopsy and molecular testing of low-grade tumors on active surveillance. Our findings highlight the importance of periodic biopsy as a component of monitoring for cancer upgrading during surveillance.

A review on the role of tissue-based molecular biomarkers for active surveillance

PURPOSE

Over the last decade, we have seen the emergence of tissue-based genomic prognostic markers that can be used for decision-making regarding the need for treatment. This review provides an up-to-date summary of the relevant literature surrounding these markers with a discussion of the relevant strength and limitations.

METHODS

We performed a literature search of tissue-based genomic prognostic markers and selected those that were currently available for clinical use. We selected the following markers for further review: Decipher (Decipher Bioscience), Polaris (Myriad), Genome Prostate Score (Oncotype Dx), and Promark. We selected the initial validation study for each marker along with other validation studies in independent cohorts. Furthermore, we selected available clinical utility studies or studies combining multi parametric MRI.

RESULTS

In this article, we provide an in-depth review of four commercially available biomarkers and discuss the current literature surrounding these markers, including the benefits and limitations of their use. We found that each of these markers has evidence supporting their role as an independent predictor of relevant prostate cancer endpoints, which can be helpful for clinical decision-making. However, issues related to heterogeneity and a lack of prospective randomized studies supporting their utility are limitations. Evidence appears to suggest that MRI and genomic risk assessment maybe complementary.

CONCLUSION

Although these markers can help in improved risk stratification of patients eligible for AS, more prospective studies with head to head comparison between markers are needed to elucidate the true potential of these markers in AS.

Tumor size and genomic risk in localized prostate cancer

PURPOSE

Unlike many other cancers, measurement of primary prostate tumor size has no defined role in the management of localized prostate cancer. Here, we assess whether prostate tumor size is associated with aggressive tumor biology using biomarkers of genomic risk.

MATERIALS AND METHODS

We abstracted or imputed tumor size from the primary pathology reports of prostate cancers incorporated in The Cancer Genome Atlas. We used transcriptomic data to estimate the Cell Cycle Progression Score (CCPS, Prolaris), the Genomic Classifier Score (GCS, Decipher) and the Genomic Prostate Score (GPS, OncotypeDx), SChLaP1 expression, and copy number alteration percentage (%CNA) as well as hallmark gene set enrichment analysis.

RESULTS

Tumor size and gene expression data was available for 267 men. On multivariable regression adjusted for Gleason Grade Group and tumor purity, tumor size was independently associated with the calculated (c)GCS, cGPS, SChLaP1 expression, and %CNA (P< 0.05), but not cCCPS. Gene set enrichment analysis demonstrated that tumors <5 cc, when adjusting for Gleason grade group, were enriched for androgen response genes, while tumors >5 cc were enriched for MYC targets and genes associated with epithelial mesenchymal transition.

CONCLUSIONS

Prostate tumor size is independently associated with established markers of genomic risk. This study nominates the size of a primary prostate cancer as candidate for inclusion in future novel risk scores seeking to quantify cancer aggressiveness.

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.

Update and optimization of active surveillance in prostate cancer in 2021

INTRODUCTION AND OBJECTIVES

Within the paradigm shift of the last decade in the management of prostate cancer (PCa), perhaps the most relevant event has been the emergence of active surveillance (AS) as a mandatory strategy in low-risk disease. We carry out a critical review of the clinical, pathological and radiological improvements that allow optimizing AS in 2021.

MATERIAL AND METHODS

Critical narrative review of the literature on improvement issues and controversial aspects of AS.

RESULTS

Adequate use of traditional criteria, optimized by enhanced biopsy and calculation of the prostate volume technique thanks to multiparametric magnetic resonance imaging (mpMRI) allow a better selection of patients for AS. This management should not be limited to patients under 60years of age, and patients with intermediate-risk PCa should be carefully selected to be included. Biopsies are still required in the follow-up, which can be personalized according to risk patterns. The pathologist must identify the cribriform or intraductal histology on biopsies in order to exclude these patients from AS, in the same way as with patients with alterations in DNA repair genes.

CONCLUSIONS

Controversial indications such as the inclusion of patients from intermediate-risk groups, or the transition to active treatment due to exclusive progression in tumor volume, should be further optimized. It is possible that the future competition of tissue biomarkers, the refinement of objective parameters of mpMRI and the validation of PSA kinetics calculators may sub-stratify risk groups.

Analysis of Serum Markers with Regard to Treatment Procedures in Advanced Stage Prostate Cancer Patients

Background

Biomarkers predicting the efficacy of treatment for locally limited prostate cancer are greatly needed. This knowledge could improve the classification of patients for different methods of treatment and enable better recognition of groups with higher risk of biological recurrence. We prospectively assessed serial blood levels of apoptotic biomarkers and correlated them with response to treatment and clinical factors.

Material/Methods

Blood was collected from 25 patients with prostate cancer before and after surgery, 16 healthy volunteers with benign prostatic hyperplasia (BPH), and 14 patients with metastasized disease. Immunoenzymatic methods were used to determine circulating apoptotic and inflammatory mediators, including tumor necrosis factor α (TNF-α), type I receptor (TNFRI), and type II receptor (TNFRII); FAS ligand (FasL); TNF-related apoptosis-inducing ligand (TRIAL); caspase 8 (Cas8); caspase 9 (Cas9); DNA methylation (metDNA); P-selectin; and high-sensitivity C-reactive protein. The total circulating fragments of cell-free DNA (cfDNA) were measured directly in serum.

Results

Peripheral serum prostate-specific antigen increased rapidly together with cfDNA. A negative correlation was noted between tumor volume and TNFRI and TNFRII. Postsurgery P-selectin level was decreased, and metDNA and TNFRII levels were increased. Three comparisons were made between patient groups: surgical vs. BPH; surgical vs. palliative; and palliative vs. BPH. TNFRI, TNFRII, metDNA, P-selectin, Cas8, and FasL were shown to have significant roles.

Conclusions

The study indicated significant roles for cfDNA, both TNF receptors, metDNA, and P-selectin as serum biomarkers in patients with prostate cancer.

Molecular pathology of prostate cancer: a practical approach

While localised prostate cancer can be cured by local treatment, 'high-risk' prostate cancer often progresses to castration resistant disease and remains incurable with a dismal prognosis. In recent years, technical advances and development of novel methodologies have largely contributed to a better understanding of underlying molecular mechanisms that promote tumour growth and progression. Consecutively, novel therapeutic strategies for treatment of prostate cancer have emerged during the last decade, calling for the identification of predictive biomarkers. The concept of personalised medicine is to tailor treatment according to the specific tumour profile of an individual patient. Moreover, acquired molecular changes during tumour evolution and in response to therapy selection pressure require adapted predictive marker testing at different time points during the disease. In this setting, the pathologist plays a critical role in patient management and treatment selection. In this review, we provide a comprehensive overview of the current knowledge of molecular aspects of prostate cancer and their potential utility in the context of different therapeutic approaches. Furthermore, we discuss methods for molecular marker testing in routine clinical practice, with a focus on castration resistant prostate cancer.

Tailoring Intensity of Active Surveillance for Low-Risk Prostate Cancer Based on Individualized Prediction of Risk Stability

Importance

Active surveillance is increasingly recognized as the preferred standard of care for men with low-risk prostate cancer. However, active surveillance requires repeated assessments, including prostate-specific antigen tests and biopsies that may increase anxiety, risk of complications, and cost.

Objective

To identify and validate clinical parameters that can identify men who can safely defer follow-up prostate cancer assessments.

Design, Setting, and Participants

The Canary Prostate Active Surveillance Study (PASS) is a multicenter, prospective active surveillance cohort study initiated in July 2008, with ongoing accrual and a median follow-up period of 4.1 years. Men with prostate cancer managed with active surveillance from 9 North American academic medical centers were enrolled. Blood tests and biopsies were conducted on a defined schedule for least 5 years after enrollment. Model validation was performed among men at the University of California, San Francisco (UCSF) who did not enroll in PASS. Men with Gleason grade group 1 prostate cancer diagnosed since 2003 and enrolled in PASS before 2017 with at least 1 confirmatory biopsy after diagnosis were included. A total of 850 men met these criteria and had adequate follow-up. For the UCSF validation study, 533 active surveillance patients meeting the same criteria were identified. Exclusion criteria were treatment within 6 months of diagnosis, diagnosis before 2003, Gleason grade score of at least 2 at diagnosis or first surveillance biopsy, no surveillance biopsy, or missing data.

Exposures

Active surveillance for prostate cancer.

Main Outcomes and Measures

Time from confirmatory biopsy to reclassification, defined as Gleason grade group 2 or higher on subsequent biopsy.

Results

A total of 850 men (median [interquartile range] age, 64 [58-68] years; 774 [91%] White) were included in the PASS cohort. A total of 533 men (median [interquartile range] age, 61 [57-65] years; 422 [79%] White) were included in the UCSF cohort. Parameters predictive of reclassification on multivariable analysis included maximum percent positive cores (hazard ratio [HR], 1.30 [95% CI, 1.09-1.56]; P = .004), history of any negative biopsy after diagnosis (1 vs 0: HR, 0.52 [95% CI, 0.38-0.71]; P < .001 and ≥2 vs 0: HR, 0.18 [95% CI, 0.08-0.4]; P < .001), time since diagnosis (HR, 1.62 [95% CI, 1.28-2.05]; P < .001), body mass index (HR, 1.08 [95% CI, 1.05-1.12]; P < .001), prostate size (HR, 0.40 [95% CI, 0.25-0.62]; P < .001), prostate-specific antigen at diagnosis (HR, 1.51 [95% CI, 1.15-1.98]; P = .003), and prostate-specific antigen kinetics (HR, 1.46 [95% CI, 1.23-1.73]; P < .001). For prediction of nonreclassification at 4 years, the area under the receiver operating curve was 0.70 for the PASS cohort and 0.70 for the UCSF validation cohort. This model achieved a negative predictive value of 0.88 (95% CI, 0.83-0.94) for those in the bottom 25th percentile of risk and of 0.95 (95% CI, 0.89-1.00) for those in the bottom 10th percentile.

Conclusions and Relevance

In this study, among men with low-risk prostate cancer, heterogeneity prevailed in risk of subsequent disease reclassification. These findings suggest that active surveillance intensity can be modulated based on an individual's risk parameters and that many men may be safely monitored with a substantially less intensive surveillance regimen.