Analysis of a Biopsy-Based Genomic Classifier in High-Risk Prostate Cancer: Meta-Analysis of the NRG Oncology/Radiation Therapy Oncology Group 9202, 9413, and 9902 Phase 3 Randomized Trials

Beyond the status quo: when disease volume and metastatic timing are not enough to personalize treatment in mHSPC

This review explores the complexities of treatment intensification in metastatic hormone-sensitive prostate cancer (mHSPC), emphasizing the limitations of using disease volume and metastatic timing as sole prognostic factors. Current algorithms focus on clinical factors like ECOG, comorbidities, and patient preferences, yet lack biomarkers for more individualized therapy. By examining prognostic indicators - clinical, analytical, pathological, molecular, and imaging - this article highlights the importance of a personalized approach. Multimodal strategies and predictive biomarkers are proposed to optimize therapy selection between doublet and triplet regimens, ultimately improving patient outcomes. Future trials incorporating emerging biomarkers may provide the basis for precision treatment in mHSPC, shifting management beyond conventional classifications.

Biomarkers in prostate cancer: current status and future directions in radiotherapy-statement from the Prostate Cancer Working Group of the German Society of Radiation Oncology (DEGRO)

PURPOSE

Prostate cancer (PCa) is the most frequently diagnosed malignancy among men in Germany. Advances in diagnostics and treatment have transformed PCa into a chronic disease. Given the heterogeneity of PCa, there is a need for additional stratification tools. This review focuses on updating the evidence for genomic classifiers (GC; Decipher [Veracyte Inc. San Diego, CA, USA], Prolaris [Myriad Genetics, Inc., Salt Lake City, UT], and Oncotype DX [Exact Sciences, Madison, WI, USA] tests) and artificial intelligence (AI)-based digital histopathology biomarkers (ArteraAI Prostate Test) in the context of radiotherapy (RT) for PCa.

METHODS

The members of the Prostate Cancer Working Group of the German Society of Radiation Oncology (DEGRO) conducted an updated literature search on GCs and histopathological biomarkers in PCa, covering original articles published between January 2022 and February 2024 in the PubMed database.

RESULTS

In addition to previous reviews, 11 relevant studies were identified, of which nine studies analyzed biomarkers within prospective phase II or III trials. Eight trials focused on genomic biomarkers, of which three addressed GCs in primary localized PCa, three in recurrent PCa in the setting of salvage RT, and two in metastatic castration-sensitive PCa. In localized PCa, GCs could be validated in a retrospective analysis of randomized controlled trials. Additionally, three studies reported on AI-based histopathology biomarkers.

CONCLUSION

Genomic classifiers and AI-based digital histopathology models might have superior prognostic and predictive value compared to established clinical and pathological parameters in localized, recurrent, and metastatic PCa. Despite promising results, prospective validation of these biomarkers in randomized trials remains limited. This review underscores the need for further prospective trials to confirm the usefulness of these biomarkers in PCa.

« Augmented radiotherapy » in the management of high-risk prostate cancer (PCa): A systematic review

BACKGROUND

In patients with high-risk (HR) prostate cancer (PCa) treated with radiotherapy and androgen deprivation therapy (ADT), intensification with androgen receptor pathway inhibitor (ARPI) improves overall survival (OS), at the cost of significant side-effects. We hypothesized that "augmented RT" schedules (defined as either dose-escalation on the prostate gland over 78 Gy and/or addition of whole pelvic radiotherapy (WPRT)), combined with long-term ADT can reach excellent prostate cancer specific survival (PCSS) in this population with little detrimental impact on quality of life.

METHODS

We searched Pubmed database until February 8, 2024. Studies reporting both oncological and toxicity outcomes after "augmented RT" were deemed eligible. Studies without ADT or with ARPI intensification were deemed ineligible.

RESULTS

Dose-escalation within the prostate gland at doses over 78 Gy halved the risk of biochemical recurrence at 5 years, with however no impact on PCSS. The addition of WPRT provides a 5-year disease-free survival (DFS) reaching 89.5 % at 5 years, with no significant increase in late grade≥ 2 genito-urinary (GU) or gastrointestinal (GI) toxicity. Combined approaches result in 9-year PCSS ranging between 96.1 % and 100 %. Most approaches demonstrated excellent safety profiles.

CONCLUSIONS

"Augmented RT" reached excellent oncological outcomes, with minimal additional toxicity. The development of biomarkers might lead to further treatment personalization, in the rapidly evolving landscape of systemic therapies.

Genomic classifiers and prognosis of localized prostate cancer: a systematic review

BACKGROUND

Refinement of the risk classification for localized prostate cancer is warranted to aid in clinical decision making. A systematic analysis was undertaken to evaluate the prognostic ability of three genomic classifiers, Decipher, GPS, and Prolaris, for biochemical recurrence, development of metastases and prostate cancer-specific mortality in patients with localized prostate cancer.

METHODS

Data sources: MEDLINE, Embase, and Web of Science were queried for reports published from January 2010 to April 2022.

STUDY SELECTION

prospective or retrospective studies reporting prognosis for patients with localized prostate cancer.

DATA EXTRACTION

relevant data were extracted into a customized database by one researcher with a second overreading. Risk of bias was assessed using a validated tool for prognostic studies, Quality in Prognosis Studies (QUIPS). Disagreements were resolved by consensus or by input from a third reviewer. We assessed the certainty of evidence by GRADE incorporating adaptation for prognostic studies.

RESULTS

Data synthesis: a total of 39 studies (37 retrospective) involving over 10,000 patients were identified. Twenty-two assessed Decipher, 5 GPS, and 14 Prolaris. Thirty-four studies included patients who underwent prostatectomy. Based on very low to low certainty of evidence, each of the three genomic classifiers modestly improved upon the prognostic ability for biochemical recurrence, development of metastases, and prostate cancer-specific mortality compared to standard clinical risk-classification schemes.

LIMITATIONS

downgrading of confidence in the evidence stemmed largely from bias due to the retrospective nature of the studies, heterogeneity in treatment received, and era in which patients were treated (i.e., prior to the 2000s).

CONCLUSIONS

Genomic classifiers provide a small but consistent improvement upon the prognostic ability of clinical classification schemes, which may be helpful when treatment decisions are uncertain. However, evidence from current management-era data and of the predictive ability of these tests is needed.

Evaluation of clinical risk stratification to determine benefit from long-term versus short-term androgen deprivation in high-risk localized prostate cancer

BACKGROUND

Patients treated with RT and long-term androgen deprivation therapy (ltADT) for high-risk localized prostate cancer (HRLPC) with 1 high-risk factor (any of Gleason ≥8, PSA > 20 ng/mL, ≥cT3; "high-risk") have better outcomes than those with 2-3 factors and/or cN1 disease ("very high risk"). We evaluated whether this risk stratification could determine benefit from ltADT versus short-term (stADT).

METHODS

The Intermediate Clinical Endpoints in Cancer of the Prostate (ICECaP) repository of randomized trials was queried to identify eligible patients and trials. The key outcomes of interest were metastasis-free survival (MFS), overall survival (OS), time to metastasis (TTM) and prostate cancer-specific mortality (PCSM). Stratified Cox and Gray's regression were used to obtain the overall treatment effect for outcomes and risk groups, and the Wald interaction test to estimate whether treatment benefit differed by risk group or trial. Heterogeneity of studies was assessed by Cochran's Q and I2.

RESULTS

2780 patients from 3 trials were included. Patients with very-high risk disease had greater benefit with ltADT compared to high-risk disease (MFS HR 0.77 [0.68-0.88] vs. 0.89 [0.76-1.03]; TTM 0.61 [0.51-0.74] vs. 0.77 [0.59-0.99]; PCSM 0.71 [0.56-0.90] vs. 0.82 [0.59-1.14]; OS 0.87 [0.76-1.00] vs. 0.93 [0.79-1.08]), but there was no statistically significant difference in treatment effect by risk group (p-interaction >0.1). Heterogeneity for treatment effect across trials was low in the very high-risk group and moderate in the high-risk group.

CONCLUSIONS

Clinical risk stratification merits further evaluation in clinical trials to identify which patients with HRLPC may benefit from ltADT versus stADT.

Integration of Genomic Tests in Prostate Cancer Care: Implications for Clinical Practice and Patient Outcomes

Prostate cancer (PCa) is a common malignancy in men and is among the leading causes of cancer-related death worldwide. Genomic tests assess disease aggressiveness and guide treatment, particularly in low- and intermediate-risk PCa. We reviewed the literature on the use of four genomic tests (Prolaris®, Promark®, Oncotype DX®, and Decipher®) in assessing the prognosis of PCa and their use in treatment decision-making. Most of the studies showed that Prolaris® has a strong correlation with biochemical recurrence, metastasis risk, PCa-specific mortality (PCSM), and pathological features. Similarly, three studies on Promark® indicated a connection between results and pathological features in the subsequent prostatectomy, time to metastasis, and biochemical recurrence. Fourteen studies on Oncotype DX® showed a clear correlation between high scores, death, and PCSM. One study found that routine biopsy pathology reports, combined with serum PSA levels, provide a risk assessment comparable to Oncotype DX® testing. Results from 22 studies on Decipher® were controversial. The test was associated with conservative management, suggesting that patients with a high GC score are more likely to need radiation after surgery. Comparative studies indicated that Oncotype DX® is preferable for assessing PCSM, Decipher® for predicting metastasis, and Prolaris® for predicting recurrence. With the incidence rate of PCa dramatically increasing, genomic tests appear to be useful adjunctive precision medicine tools with significant potential in improving prognostic discrimination, facilitating better risk stratification, and guiding personalized treatment, especially in the intermediate-risk patient group. Large-scale, prospective, multi-sectional studies are required to validate the utility of these tests prior to their integration into clinical practice.

Biopsy-based Basal-luminal Subtyping Classifier in High-risk Prostate Cancer: A Combined Analysis of the NRG Oncology/RTOG 9202, 9413, and 9902 Phase 3 Trials

BACKGROUND AND OBJECTIVE

Long-term (LT) androgen deprivation therapy (ADT) has been found to be beneficial to patients with high-risk prostate cancer (PCa). However, administration of LT-ADT to all patients with high-risk PCa may lead to overtreatment. Enhanced risk stratification using genomic classifiers (such as the recently developed prostate subtyping classifier [PSC]) might be useful. This study aims to characterize the prognostic and predictive ability of the PSC in patients with high-risk PCa undergoing radiotherapy long-term (LT; 24-28 mo) versus short-term (ST; 4 mo) ADT.

METHODS

Biopsy samples from three randomized, phase 3 trials-NRG/RTOG 9202, 9413, and 9902-were classified as either PSC basal or luminal. The prognostic and predictive values of PSC for each oncologic endpoint (biochemical failure [BF], distant metastasis [DM], metastasis-free survival [MFS], PCa-specific mortality [PCSM], overall survival [OS]) and other cause-mortality (OCM) were assessed with Cox proportional hazards (MFS, OCM, and OS), Fine-Gray (BF, DM, and PCSM), and restricted mean survival time (RMST) models.

KEY FINDINGS AND LIMITATIONS

On a multivariable analysis, the basal subtype was found to have a worse prognosis for MFS (hazard ratio [HR] 1.8 [1.3-2.5], p < 0.001), PCSM (subdistribution HR 2.4 [95% confidence interval {CI} 1.4-4.1], p = 0.001), and OS (HR 1.8 [1.3-2.6], p < 0.001). Ten-year PCSM was 15% better for the luminal subtype than for the basal subtype (11% [95% CI 6-15%] vs 26% [95% CI 17-35%]). A significant interaction between ADT duration (LT vs ST) and PSC subtype (basal vs luminal) was observed for PCSM (pinteraction = 0.008), leading to the observation that 10-yr PCSM was improved with LT-ADT only in patients with basal-type tumors (5% [95% CI 0-11%] vs 42% [29-56%], p < 0.001). Improvements in 10-yr RMST with LT-ADT were greater for basal tumors for oncologic endpoints with the exception of OCM.

CONCLUSIONS AND CLINICAL IMPLICATIONS

PSC is both a prognostic and a predictive biomarker for patients who benefit from LT-ADT. PSC subtypes may be used to personalize ADT recommendations for patients with high-risk PCa, pending further validation in a prospective study.

PATIENT SUMMARY

In this study, we tried to understand the usefulness of a new genomic test in patients with high-risk, nonmetastatic prostate cancer who underwent radiation therapy and hormonal therapy (HT). We found that this test can help determine a patient's prognosis (eg, a patient's chance of having the cancer return) and, more importantly, personalize treatment decisions by understanding which patients may benefit from long-term HT. This has the potential to save many patients who may not benefit from prolonged HT from "overtreatment" or the unnecessary side effects of such treatment.

The role of NOP58 in prostate cancer progression through SUMOylation regulation and drug response

Background

Prostate cancer is one of the leading causes of cancer-related deaths in men. Its molecular pathogenesis is closely linked to various genetic and epigenetic alterations, including posttranslational modifications like SUMOylation. Identifying biomarkers that predict outcomes and specific therapeutic targets depends on a comprehensive understanding of these processes. With growing interest in SUMOylation as a mechanism affecting prostate cancer-related genes, this study aimed to investigate the central role of SUMOylation in prostate cancer prognostics, focusing on the significance of NOP58.

Methods

We conducted a comprehensive bioinformatics analysis, integrating differential expression analysis, survival analysis, gene set enrichment analysis (GSEA), and single-cell transcriptomic analyses using data from The Cancer Genome Atlas (TCGA). Key genes were identified through intersections of Venn diagrams, Boralta algorithm signatures, and machine learning models. These signaling mechanisms were validated through experimental studies, including immunohistochemical staining and gene ontology analyses.

Results

The dual-gene molecular subtype analysis with SUMO1, SUMO2, and XPO1 genes revealed significant differences in survival outcomes across molecular subtypes, further emphasizing the potential impact of NOP58 on SUMOylation, a key post-translational modification, in prostate cancer. NOP58 overexpression was strongly associated with shorter overall survival (OS), progression-free interval (PFI), and disease-specific death in prostate cancer patients. Immunohistochemical analysis confirmed that NOP58 was significantly overexpressed in prostate cancer tissues compared to normal tissues. ROC curve analysis demonstrated that NOP58 could distinguish prostate cancer from control samples with high diagnostic accuracy. Gene Ontology analysis, along with GSVA and GSEA, suggested that NOP58 may be involved in cell cycle regulation and DNA repair pathways. Moreover, NOP58 knockdown led to increased BCL2 expression and decreased Ki67 levels, promoting apoptosis and inhibiting cell proliferation. Colony formation assays further showed that NOP58 knockdown inhibited, while its overexpression promoted, colony formation, highlighting the critical role of NOP58 in prostate cancer cell growth and survival. Additionally, NOP58 was linked to drug responses, including Methotrexate, Rapamycin, Sorafenib, and Vorinostat.

Conclusion

NOP58 is a key regulator of prostate cancer progression through its mediation of the SUMOylation pathway. Its expression level serves as a reliable prognostic biomarker and an actionable therapeutic target, advancing precision medicine for prostate cancer. Targeting NOP58 may enhance therapeutic efficacy and improve outcomes in oncology.

Volumetric Modulated Arc Therapy for High-Risk and Very High-Risk Locoregional Prostate Cancer in the Modern Era: Real-World Experience from an Asian Cohort

This study retrospectively evaluates the clinical outcomes of definitive volumetric modulated arc therapy (VMAT) for high-risk or very high-risk locoregional prostate cancer patients from an Asian institution. Consecutive patients who received VMAT (76 Gy in 38 fractions) between January 2017 and June 2022 were included. Whole pelvic radiotherapy (WPRT) (46 Gy in 23 fractions) was employed for clinically node-negative disease (cN0) and a Roach estimated risk of ≥15%, as well as simultaneous integrated boost (SIB) of 55-57.5 Gy to node-positive (cN1) disease. The primary endpoint was biochemical relapse-free survival (BRFS). Secondary endpoints included radiographic relapse-free survival (RRFS), metastasis-free survival (MFS) and prostate cancer-specific survival (PCSS). A total of 209 patients were identified. After a median follow-up of 47.5 months, the 4-year actuarial BRFS, RRFS, MFS and PCSS were 85.2%, 96.8%, 96.8% and 100%, respectively. The incidence of late grade ≥ 2 genitourinary (GU) and gastrointestinal (GI) toxicity were 15.8% and 11.0%, respectively. No significant difference in cancer outcomes or toxicity was observed between WPRT and prostate-only radiotherapy for cN0 patients. SIB to the involved nodes did not result in increased toxicity. International Society of Urological Pathology (ISUP) group 5 and cN1 stage were associated with worse RRFS (p < 0.05). PSMA PET-CT compared to conventional imaging staging was associated with better BRFS in patients with ISUP grade group 5 (p = 0.039). Five-year local experience demonstrates excellent clinical outcomes. PSMA PET-CT staging for high-grade disease and tailored pelvic irradiation based on nodal risk should be considered to maximize clinical benefit.

Association Between the Decipher Genomic Classifier and Prostate Cancer Outcome in the Real-world Setting

BACKGROUND AND OBJECTIVE

Although the prognostic significance of the Decipher prostate cancer genomic classifier (GC) has been established largely from analyses of archival tissue, less is known about the associations between the results of Decipher testing and oncologic outcomes among patients receiving contemporaneous testing and treatment in the real-world practice setting. Our objective was to assess the associations between the Decipher GC and risks of metastasis and biochemical recurrence (BCR) following prostate biopsy and radical prostatectomy (RP) among patients tested and treated in the real-world setting.

METHODS

A retrospective cohort study was conducted using a novel longitudinal linkage of transcriptomic data from the Decipher GC and real-world clinical data (RWD) aggregated from insurance claims, pharmacy records, and electronic health record data across payors and sites of care. Kaplan-Meier and Cox proportional hazards regressions were used to examine the associations between the GC and study outcomes, adjusting for clinical and pathologic factors.

KEY FINDINGS AND LIMITATIONS

Metastasis from prostate cancer and BCR after radical prostatectomy, Decipher GC continuous score, and risk categories were evaluated. We identified 58 935 participants who underwent Decipher testing, including 33 379 on a biopsy specimen and 25 556 on an RP specimen. The median age was 67 yr (interquartile range [IQR] 62-72) at biopsy testing and 65 yr (IQR 59-69) at RP. The median GC score was 0.43 (IQR 0.27-0.66) among biopsy-tested patients and 0.54 (0.32-0.79) among RP-tested patients. The GC was independently associated with the risk of metastasis among biopsy-tested (hazard ratio [HR] per 0.1 unit increase in GC 1.21 [95% confidence interval {CI} 1.16-1.27], p < 0.001) and RP-tested (HR 1.20 [95% CI 1.17-1.24], p < 0.001) patients after adjusting for baseline clinical and pathologic risk factors. In addition, the GC was associated with the risk of BCR among RP-tested patients (HR 1.12 [95% CI 1.10-1.14], p < 0.001) in models adjusted for age and Cancer of the Prostate Risk Assessment postsurgical score.

CONCLUSIONS AND CLINICAL IMPLICATIONS

This real-world study of a novel transcriptomic linkage conducted at a national scale supports the external prognostic validity of the Decipher GC among patients managed in contemporary practice.

PATIENT SUMMARY

This study looked at the use of the Decipher genomic classifier, a test used to help understand the aggressiveness of a patient's prostate cancer. Looking at the results of 58 935 participants who underwent testing, we found that the Decipher test helped estimate the risk of cancer recurrence and metastasis.

Transcriptomic Profiling of Primary Prostate Cancers and Nonlocalized Disease on Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography: A Multicenter Retrospective Study

PURPOSE

To characterize the relationship between Decipher genomic classifier scores and prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT)-based metastatic spread.

MATERIALS AND METHODS

We identified patients from four institutions who underwent PSMA PET/CT scans pretreatment for primary staging or postradical prostatectomy (RP) for suspected recurrence and had Decipher transcriptomic data available from biopsy or RP specimens. PSMA PET/CT-based patterns of spread were classified as localized (miT + N0M0) or nonlocalized (miN1M0 or miM1a-c). We calculated the association between Decipher scores and the risk of nonlocalized disease on PSMA PET/CT using multivariable logistic regression for pretreatment patients and multivariable Cox regression for post-RP patients. We also compared select transcriptomic signatures between patients with localized and nonlocalized diseases.

RESULTS

Five hundred eighty-six patients were included (pretreatment: n = 329; post-RP: n = 257). Higher Decipher scores were associated with nonlocalized disease on PSMA PET/CT both pretreatment (odds ratio, 1.18 [95% CI, 1.03 to 1.36] per 0.1 increase in Decipher score, P = .02) and post-RP (hazard ratio, 1.15 [95% CI, 1.05 to 1.27] per 0.1 increase in Decipher score, P = .003). In the pretreatment setting, nonlocalized disease was associated with higher rates of TP53 mutations and lower rates of PAM50 luminal A subtype compared with localized disease. In the post-RP setting, overexpression of signatures related to metabolism, DNA repair, and androgen receptor signaling were associated with higher rates of nonlocalized disease.

CONCLUSION

Higher Decipher scores were associated with nonlocalized disease identified on PSMA PET/CT both pretreatment and post-RP. There were several transcriptomic differences between localized and nonlocalized diseases in both settings.

Development of a Longitudinal Prostate Cancer Transcriptomic and Clinical Data Linkage

Importance

Although tissue-based gene expression testing has become widely used for prostate cancer risk stratification, its prognostic performance in the setting of clinical care is not well understood.

Objective

To develop a linkage between a prostate genomic classifier (GC) and clinical data across payers and sites of care in the US.

Design, Setting, and Participants

In this cohort study, clinical and transcriptomic data from clinical use of a prostate GC between 2016 and 2022 were linked with data aggregated from insurance claims, pharmacy records, and electronic health record (EHR) data. Participants were anonymously linked between datasets by deterministic methods through a deidentification engine using encrypted tokens. Algorithms were developed and refined for identifying prostate cancer diagnoses, treatment timing, and clinical outcomes using diagnosis codes, Common Procedural Terminology codes, pharmacy codes, Systematized Medical Nomenclature for Medicine clinical terms, and unstructured text in the EHR. Data analysis was performed from January 2023 to January 2024.

Exposure

Diagnosis of prostate cancer.

Main Outcomes and Measures

The primary outcomes were biochemical recurrence and development of prostate cancer metastases after diagnosis or radical prostatectomy (RP). The sensitivity of the linkage and identification algorithms for clinical and administrative data were calculated relative to clinical and pathological information obtained during the GC testing process as the reference standard.

Results

A total of 92 976 of 95 578 (97.2%) participants who underwent prostate GC testing were successfully linked to administrative and clinical data, including 53 871 who underwent biopsy testing and 39 105 who underwent RP testing. The median (IQR) age at GC testing was 66.4 (61.0-71.0) years. The sensitivity of the EHR linkage data for prostate cancer diagnoses was 85.0% (95% CI, 84.7%-85.2%), including 80.8% (95% CI, 80.4%-81.1%) for biopsy-tested participants and 90.8% (95% CI, 90.5%-91.0%) for RP-tested participants. Year of treatment was concordant in 97.9% (95% CI, 97.7%-98.1%) of those undergoing GC testing at RP, and 86.0% (95% CI, 85.6%-86.4%) among participants undergoing biopsy testing. The sensitivity of the linkage was 48.6% (95% CI, 48.1%-49.1%) for identifying RP and 50.1% (95% CI, 49.7%-50.5%) for identifying prostate biopsy.

Conclusions and Relevance

This study established a national-scale linkage of transcriptomic and longitudinal clinical data yielding high accuracy for identifying key clinical junctures, including diagnosis, treatment, and early cancer outcome. This resource can be leveraged to enhance understandings of disease biology, patterns of care, and treatment effectiveness.

Transcriptome-Based Prognostic and Predictive Biomarker Analysis of ENACT: A Randomized Controlled Trial of Enzalutamide in Men Undergoing Active Surveillance

PURPOSE

Few studies have explored the potential for pharmacological interventions to delay disease progression in patients undergoing active surveillance (AS). This preplanned transcriptomic analysis of patient samples from the ENACT trial aims to identify biomarkers in patients on AS who are at increased risk for disease progression or who may derive the greatest benefit from enzalutamide treatment.

PATIENTS AND METHODS

In the phase II ENACT (ClinicalTrials.gov identifier: NCT02799745) trial, patients on AS were randomly assigned 1:1 to 160 mg orally once daily enzalutamide monotherapy or continued AS for 1 year. Transcriptional analyses were conducted on biopsies collected at trial screening, year 1, and year 2. Three gene expression signatures were evaluated in samples collected at screening and in available samples from patients on AS at any time during surveillance (expanded cohort): Decipher genomic classifier, androgen receptor activity (AR-A) score, and Prediction Analysis of Microarray 50 (PAM50) cell subtype signature.

RESULTS

The Decipher genomic classifier score was prognostic; higher scores were associated with disease progression in the expanded cohort and AS arm of the expanded cohort. Patients with higher Decipher scores had greater positive treatment effect from enzalutamide as measured by time to secondary rise in prostate-specific antigen >25% above baseline. In patients treated with enzalutamide, higher AR-A scores and PAM50 luminal subtypes were associated with a greater likelihood of negative biopsy incidence at year 2.

CONCLUSION

This analysis suggests that the Decipher genomic classifier may be prognostic for disease progression in AS patients with low- to intermediate-risk prostate cancer. Higher Decipher and AR-A scores, as well as PAM50 luminal subtypes, may also serve as biomarkers for treatment response.

Genomic Classifier Performance in Intermediate-Risk Prostate Cancer: Results From NRG Oncology/RTOG 0126 Randomized Phase 3 Trial

PURPOSE

Intermediate-risk prostate cancer is a heterogeneous disease state with diverse treatment options. The 22-gene Decipher genomic classifier (GC) retrospectively has shown to improve risk stratification in these patients. We assessed the performance of the GC in men with intermediate-risk disease enrolled in NRG Oncology/RTOG 01-26 with updated follow-up.

METHODS AND MATERIALS

After National Cancer Institute approval, biopsy slides were collected from NRG Oncology/RTOG 01-26, a randomized phase 3 trial of men with intermediate-risk prostate cancer randomized to 70.2 Gy versus 79.2 Gy of radiation therapy without androgen deprivation therapy. RNA was extracted from the highest-grade tumor foci to generate the locked 22-gene GC model. The primary endpoint for this ancillary project was disease progression (composite of biochemical failure, local failure, distant metastasis, prostate cancer-specific mortality, and use of salvage therapy). Individual endpoints were also assessed. Fine-Gray or cause-specific Cox multivariable models were constructed adjusting for randomization arm and trial stratification factors.

RESULTS

Two-hundred fifteen patient samples passed quality control for analysis. The median follow-up was 12.8 years (range, 2.4-17.7). On multivariable analysis, the 22-gene GC (per 0.1 unit) was independently prognostic for disease progression (subdistribution hazard ratio [sHR], 1.12; 95% confidence interval [CI], 1.00-1.26; P = .04), biochemical failure (sHR, 1.22; 95% CI, 1.10-1.37; P < .001), distant metastasis (sHR, 1.28; 95% CI, 1.06-1.55; P = .01), and prostate cancer-specific mortality (sHR, 1.45; 95% CI, 1.20-1.76; P < .001). Ten-year distant metastasis in GC low-risk patients was 4% compared with 16% for GC high-risk patients. In patients with lower GC scores, the 10-year difference in metastasis-free survival rate between arms was -7%, compared with 21% for higher GC patients (P-interaction = .04).

CONCLUSIONS

This study represents the first validation of a biopsy-based gene expression classifier, assessing both its prognostic and predictive value, using data from a randomized phase 3 trial of intermediate-risk prostate cancer. Decipher improves risk stratification and can aid in treatment decision-making in men with intermediate-risk disease.

Analysing the tumor transcriptome of prostate cancer to predict efficacy of Lu-PSMA therapy

RATIONALE

177Lu-PSMA ([177Lu]Lutetium-PSMA-617) therapy is an effective treatment option for patients with prostate specific membrane antigen (PSMA)-positive metastatic castration-resistant prostate cancer, but still shows a non-responder rate of approximately 30%. Combination regimes of programmed death-ligand 1 (PD-L1) inhibition and concomitant 177Lu-PSMA therapy have been proposed to increase the response rate. However, the interplay of immune landscape and 177Lu-PSMA therapy efficacy is poorly understood.

METHODS

Between March 2018 and December 2021, a total of 168 patients were referred to 177Lu-PSMA therapy in our department and received a mean total dose of 21.9 GBq (three cycles in mean). All patients received baseline PSMA positron emission tomography to assess the PSMA uptake. The histopathological specimen of the primary prostate tumor was available with sufficient RNA passing quality control steps for genomic analysis in n=23 patients. In this subset of patients, tumor RNA transcriptomic analyses assessed 74 immune-related features in total, out of which n=24 signatures were not co-correlated and investigated further for outcome prognostication.

RESULTS

In the subset of patients who received 177Lu-PSMA therapy, PD-L1 was not significantly associated with OS (HR per SD change (95% CI) 0.74 (0.42 to 1.30); SD: 0.18; p=0.29). In contrast, PD-L2 signature was positively associated with longer OS (HR per SD change 0.46 (95% CI 0.29 to 0.74); SD: 0.24; p=0.001; median OS 17.2 vs 5.7 months in higher vs lower PD-L2 patients). In addition, PD-L2 signature correlated with PSA-response (ϱ=-0.46; p=0.04). The PD-L2 signature association with OS was significantly moderated by L-Lactatdehydrogenase (LDH) levels (Cox model interaction p=0.01).

CONCLUSION

Higher PD-L2 signature might be associated with a better response to 177Lu-PSMA therapy and warrants further studies investigating additional immunotherapy. In contrast, PD-L1 was not associated with outcome. The protective effect of PD-L2 signature might be present only in men with lower LDH levels.

Transcriptomic Signatures Associated With Outcomes in Recurrent Prostate Cancer Treated With Salvage Radiation, Androgen-Deprivation Therapy, and Enzalutamide: Correlative Analysis of the STREAM Trial

PURPOSE

Men with rising prostate-specific antigen (PSA) after radical prostatectomy (RP) may progress despite radiation and androgen-deprivation therapy (ADT). Tissue-based transcriptomic signatures can identify who may benefit from a more aggressive systemic approach.

METHODS

We performed a retrospective analysis of a prospective phase II multicenter trial of enzalutamide, ADT, and salvage radiotherapy in men with rising PSA after RP. Tumor tissue was analyzed using the Decipher platform for gene expression, including a novel prostate subtyping classifier, PTEN loss, homologous recombination deficiency (HRD), and ADT response. Cox models were used to associate signature scores with progression-free survival (PFS).

RESULTS

Of the 38 men enrolled, 31 had tissue with sufficient-quality RNA for genomic analysis. Luminal differentiated (LD) subtype tumors had the longest 3-year PFS at 89% compared with 19% in the luminal proliferating subtype. Men with signatures of PTEN loss (hazard ratio [HR], 1.32; 95% CI, 1.07 to 1.64; P = .01) or HRD (HR, 1.21; 95% CI, 1.05 to 1.39; P = .009) had worse PFS, while those with higher ADT response signature scores (HR, 0.75; 95% CI, 0.61 to 0.94; P = .01) were associated with improved PFS. Analysis of these signatures in a large cohort (n = 5,330) of RP samples from patients with biochemical recurrence found that these signatures provide complementary information related to outcomes with salvage radiation.

CONCLUSION

Despite aggressive systemic therapy with salvage radiation, nearly 50% of high-risk men relapse within 3 years. We show that LD and higher ADT sensitivity tumors had favorable outcomes. Those with a luminal proliferating subtype, PTEN loss, and/or HRD signatures had poor outcomes despite ADT/radiation and enzalutamide and may benefit from alternative approaches.