The Clinical Cell-Cycle Risk (CCR) Score Is Associated With Metastasis After Radiation Therapy and Provides Guidance on When to Forgo Combined Androgen Deprivation Therapy With Dose-Escalated Radiation

Active surveillance selection and 3-year durability in intermediate-risk prostate cancer following genomic testing

BACKGROUND

Genomic testing can add risk stratification information to clinicopathological features in prostate cancer, aiding in shared medical decision-making between the clinician and patient regarding whether active surveillance (AS) or definitive treatment (DT) is most appropriate. Here we examined initial AS selection and 3-year AS durability in patients diagnosed with localized intermediate-risk prostate cancer who underwent Prolaris testing before treatment decision-making.

METHODS

This retrospective observational cohort study included 3208 patients from 10 study sites who underwent Prolaris testing at diagnosis from September 2015 to December 2018. Prolaris utilizes a combined clinical cell cycle risk score calculated at diagnostic biopsy to stratify patients by the Prolaris AS threshold (below threshold, patient recommended to AS or above threshold, patient recommended to DT). AS selection rates and 3-year AS durability were compared in patients recommended to AS or DT by Prolaris testing. Univariable and multivariable logistic regression models and Cox proportional hazard models were used with molecular and clinical variables as predictors of initial treatment decision and AS durability, respectively.

RESULTS

AS selection was ~2 times higher in patients recommended to AS by Prolaris testing than in those recommended to DT (p < 0.0001). Three-year AS durability was ~1.5 times higher in patients recommended to AS by Prolaris testing than in those recommended to DT (p < 0.0001). Prolaris treatment recommendation remained a statistically significant predictor of initial AS selection and AS durability after accounting for CAPRA or Gleason scores.

CONCLUSIONS

Prolaris added significant information to clinical risk stratification to aid in treatment decision making. Intermediate-risk prostate cancer patients who were recommended to AS by Prolaris were more likely to initially pursue AS and were more likely to remain on AS at 3 years post-diagnosis than patients recommended to DT.

Genistein: A promising ally in combating neurodegenerative disorders

Neurodegenerative disorders arise when nerve cells in the brain or peripheral nervous system gradually lose functions and eventually die. Although certain therapies may alleviate some of the physical and mental symptoms associated with neurodegenerative disorders, hence slowing their progression, but no sure-shot treatment is currently available. It was shown that the rise in life expectancy and the number of elderly people in the community led to an increasing trend in the incidence and prevalence of neurodegenerative disease. Phytomolecules are demonstrating their effectiveness in combating, regression, and delaying various diseases. Genistein is one of soy isoflavone with antioxidant, anti-inflammatory, and estrogenic effects. Researchers demonstrated that Genistein treatment significantly reduced hyperglycemia, improved cognitive performance by modulating acetylcholinesterase activity and oxidative stress, and alleviated neuroinflammatory conditions in mice. This paper evaluates (in vivo and in vitro) various molecular targets of isoflavones and their ability to effectively counter several neurodegenerative disorders such as Parkinson's, Alzheimer's, and Huntington's diseases and amyotrophic lateral sclerosis. In this review, we aim to provide an overview of the role that genistein plays in delaying the development of neurodegenerative disorders.

A Phase 2 Trial of Radium223 and Stereotactic Ablative Radiation Therapy in Hormone-Naïve Men with Oligometastatic Prostate Cancer to Bone: The RadSABR Study

PURPOSE

We hypothesized that treatment with Radium223 (Ra223) and Stereotactic ablative radiotherapy (SABR) in patients with bone-only metachronous oligometastastic hormone-sensitive prostate cancer (moHSPC) could safely delay the start of androgen deprivation therapy (ADT) and maintain quality of life (QoL).

METHODS AND MATERIALS

This prospective trial included 20 men with moHSPC and ≤5 bone-only metastases who previously had definitive treatment to the prostate and pelvic lymph nodes. Eligibility criteria were testosterone ≥ 100 ng/dL and metastases validated by conventional imaging. Exclusion criteria were postinitial treatment (LHRH) therapy or N1 disease at bone metastasis diagnosis. Treatment included 6 cycles of Ra223 and SABR (30 Gy in 5 fractions). Bone scans and Prostate Specific Antigen (PSA) levels were monitored regularly. The primary endpoint was freedom from ADT use at 15 months in ≥20% of patients. Patients were followed for 2 years, with clinically significant patient-reported outcome changes defined as >1/2 standard deviation from baseline. Statistical analyses used Wilcoxon rank sum, Pearson's χ2 tests, and univariate Cox regression, with significance set at P < .05 RESULTS: The median number of Ra223 cycles was 6. Freedom from ADT at 15 and 24 months was 50.0% and 40.0%, respectively (P < .001). Eleven (55%) and 5 (25%) patients had PSA declines exceeding 50% and 90%, respectively, with 2 patients achieving undetectable PSA levels (<0.01) at 2 years. No significant changes were observed in any patient-reported outcome QoL domains. Two patients had grade 3 skeletal-related events, and grade 2+ events attributed to Ra223 and SABR were observed in 4 and 2 patients, respectively.

CONCLUSIONS

In this phase 2 trial, the initial use of Ra223 and SABR for moHSPC significantly delayed ADT use compared with historical controls. The therapy is well tolerated, preserves QoL, and can lead to undetectable PSA levels at 2 years.

Prostate Cancer Risk Stratification in NRG Oncology Phase III Randomized Trials Using Multimodal Deep Learning With Digital Histopathology

PURPOSE

Current clinical risk stratification methods for localized prostate cancer are suboptimal, leading to over- and undertreatment. Recently, machine learning approaches using digital histopathology have shown superior prognostic ability in phase III trials. This study aims to develop a clinically usable risk grouping system using multimodal artificial intelligence (MMAI) models that outperform current National Comprehensive Cancer Network (NCCN) risk groups.

MATERIALS AND METHODS

The cohort comprised 9,787 patients with localized prostate cancer from eight NRG Oncology randomized phase III trials, treated with radiation therapy, androgen deprivation therapy, and/or chemotherapy. Locked MMAI models, which used digital histopathology images and clinical data, were applied to each patient. Expert consensus on cut points defined low-, intermediate-, and high-risk groups on the basis of 10-year distant metastasis rates of 3% and 10%, respectively. The MMAI's reclassification and prognostic performance were compared with the three-tier NCCN risk groups.

RESULTS

The median follow-up for censored patients was 7.9 years. According to NCCN risk categories, 30.4% of patients were low-risk, 25.5% intermediate-risk, and 44.1% high-risk. The MMAI risk classification identified 43.5% of patients as low-risk, 34.6% as intermediate-risk, and 21.8% as high-risk. MMAI reclassified 1,039 (42.0%) patients initially categorized by NCCN. Despite the MMAI low-risk group being larger than the NCCN low-risk group, the 10-year metastasis risks were comparable: 1.7% (95% CI, 0.2 to 3.2) for NCCN and 3.2% (95% CI, 1.7 to 4.7) for MMAI. The overall 10-year metastasis risk for NCCN high-risk patients was 16.6%, with MMAI further stratifying this group into low-, intermediate-, and high-risk, showing metastasis rates of 3.4%, 8.2%, and 26.3%, respectively.

CONCLUSION

The MMAI risk grouping system expands the population of men identified as having low metastatic risk and accurately pinpoints a high-risk subset with elevated metastasis rates. This approach aims to prevent both overtreatment and undertreatment in localized prostate cancer, facilitating shared decision making.

Molecular analysis of archival diagnostic prostate cancer biopsies identifies genomic similarities in cases with progression post-radiotherapy, and those with de novo metastatic disease

BACKGROUND

It is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin-fixed paraffin-embedded (FFPE) prostate biopsies from cohorts with post-radiotherapy (RT) long-term clinical follow-up has been limited. Utilizing parallel sequencing modalities, we performed a proof-of-principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with (i) stable PCa (sPCa) postprimary or salvage RT, (ii) progressing PCa (pPCa) post-RT, and (iii) de novo metastatic PCa (mPCa).

METHODS

A cohort of 19 patients with diagnostic prostate biopsies (n = 6 sPCa, n = 5 pPCa, n = 8 mPCa) and mean 4 years 10 months follow-up (diagnosed 2009-2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3'RNA sequencing (3'RNAseq) (n = 19), nanoString analysis (n = 12), and Illumina 850k methylation (n = 8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes and methylated genomic regions (MGRs).

RESULTS

Eighteen of 19 samples provided useable 3'RNAseq data. Principal component analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified ~600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression-free survival post-RT (p < 0.0001) in an external cohort.

CONCLUSIONS

3'RNAseq, nanoString and 850k-methylation analyses are each achievable from historical FFPE diagnostic pretreatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation.

Using the Cell-Cycle Risk Score to Predict the Benefit of Androgen-Deprivation Therapy Added to Radiation Therapy in Patients With Newly Diagnosed Prostate Cancer

PURPOSE

Guidelines recommend adding androgen-deprivation therapy (ADT) to radiation therapy (RT) in certain patients with localized prostate cancer. Individualized genomic testing may improve the prognostic accuracy of risk assessments. Herein, we describe a mathematical model of the benefit of adding ADT to RT as a function of the personalized clinical cell-cycle risk (CCR) score to inform 10-year metastasis risk.

METHODS

A model of absolute risk reduction (ARR) was built using a retrospective cohort of men tested with Prolaris who received RT alone (N = 467). The relative benefit of ADT added to RT to reduce distant metastasis was estimated at 41% on the basis of a meta-analysis of randomized trials. The ARR and number needed to treat (NNT) were computationally derived in patients clinically tested with Prolaris between January 1, 2020, and October 31, 2022 (N = 56,485). Risks were predicted using a cause-specific Cox proportional hazards model with CCR score predicting time to metastasis. A CCR score of 2.112 represents the validated multimodal treatment (MMT) threshold.

RESULTS

The ARR from ADT increased from almost zero at low CCR scores to 17.1% at CCR = 3.690 with the corresponding NNT = 6, indicating that adding ADT to RT would prevent metastasis within 10 years for one of every six treated individuals. In the clinical cohort, the average ARR was 0.86% in individuals under the MMT threshold (NNT = 116). The average ARR was 8.19% in individuals above the MMT threshold (NNT = 12). Broad ranges of ADT benefit were observed within National Comprehensive Cancer Network risk categories.

CONCLUSION

The precise and personalized risk estimate of metastasis provided by the CCR score can help inform patients and physicians when considering treatment intensification.

Validation of the Combined Clinical Cell-Cycle Risk Score to Prognosticate Early Prostate Cancer Metastasis From Biopsy Specimens and Comparison With Other Routinely Used Risk Classifiers

PURPOSE

We aim to independently validate the prognostic utility of the combined cell-cycle risk (CCR) multimodality threshold to estimate risk of early metastasis after definitive treatment of prostate cancer and compare this prognostic ability with other validated biomarkers.

METHODS

Patients diagnosed with localized prostate cancer were enrolled into a single-institutional registry for the prospective observational cohort study. The primary end point was risk of metastasis within 3 years of diagnostic biopsy. Secondary end points included time to definitive treatment, time to subsequent therapy, and metastasis after completion of initial definitive treatment. Multivariable cause-specific Cox proportional hazards regression models were produced accounting for competing risk of death and stratified on the basis of the CCR active surveillance and multimodality (MM) thresholds. Time-dependent areas under the receiver operating characteristic curve were calculated.

RESULTS

The cohort consisted of 554 men with prostate cancer and available CCR score from biopsy. The CCR score was prognostic for metastasis (hazard ratio [HR], 2.32 [95% CI, 1.17 to 4.59]; P = .02), with scores above the MM threshold having a higher risk than those below the threshold (HR, 5.44 [95% CI, 2.72 to 10.91]; P < .001). The AUC for 3-year risk of metastasis on the basis of CCR was 0.736. When men with CCR above the MM threshold received MM therapy, their 3-year risk of metastasis was significantly lower than those receiving single-modality therapy (3% v 14%). Similarly, a CCR score above the active surveillance threshold portended a faster time to first definitive treatment.

CONCLUSION

CCR outperforms other commonly used biomarkers for prediction of early metastasis. We illustrate the clinical utility of the CCR active surveillance and multimodality thresholds. Molecular genomic tests can inform patient selection and personalization of treatment for localized prostate cancer.

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.

Can We Predict Prostate Cancer Metastasis Based on Biomarkers? Where Are We Now?

The incidence of prostate cancer (PC) has risen annually. PC mortality is explained by the metastatic disease (mPC). There is an intermediate scenario in which patients have non-mPC but have initiated a metastatic cascade through epithelial-mesenchymal transition. There is indeed a need for more and better tools to predict which patients will progress in the future to non-localized clinical disease or already have micrometastatic disease and, therefore, will clinically progress after primary treatment. Biomarkers for the prediction of mPC are still under development; there are few studies and not much evidence of their usefulness. This review is focused on tissue-based genomic biomarkers (TBGB) for the prediction of metastatic disease. We develop four main research questions that we attempt to answer according to the current evidence. Why is it important to predict metastatic disease? Which tests are available to predict metastatic disease? What impact should there be on clinical guidelines and clinical practice in predicting metastatic disease? What are the current prostate cancer treatments? The importance of predicting metastasis is fundamental given that, once metastasis is diagnosed, quality of life (QoL) and survival drop dramatically. There is still a need and space for more cost-effective TBGB tests that predict mPC disease.

Genetic and Genomic Testing for Prostate Cancer: Beyond DNA Repair

Significant progress has been made in genetic and genomic testing for prostate cancer across the disease spectrum. Molecular profiling is increasingly relevant for routine clinical management, fueled in part by advancements in testing technology and integration of biomarkers into clinical trials. In metastatic prostate cancer, defects in DNA damage response genes are now established predictors of benefit to US Food and Drug Administration-approved poly (ADP-ribose) polymerase inhibitors and immune checkpoint inhibitors, and trials are actively investigating these and other targeted treatment strategies in earlier disease states. Excitingly, opportunities for molecularly informed management beyond DNA damage response genes are also maturing. Germline genetic variants (eg, BRCA2 or MSH2/6) and polygenic germline risk scores are being investigated to inform cancer screening and active surveillance in at-risk carriers. RNA expression tests have recently gained traction in localized prostate cancer, enabling patient risk stratification and tailored treatment intensification via radiotherapy and/or androgen deprivation therapy for localized or salvage treatment. Finally, emerging minimally invasive circulating tumor DNA technology promises to enhance biomarker testing in advanced disease pending additional methodological and clinical validation. Collectively, genetic and genomic tests are rapidly becoming indispensable tools for informing the optimal clinical management of prostate cancer.

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

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

High Dose “HDR-Like” Prostate SBRT: PSA 10-Year Results From a Mature, Multi-Institutional Clinical Trial

Purpose/Objective(s)

Although ample intermediate-term prostate stereotactic body radiotherapy (SBRT) outcomes have been reported, 10-year results remain relatively sparse.

Materials/Methods

Eighteen institutions enrolled 259 low- and intermediate-risk patients. Median follow-up is 5.5 years, with 66 patients followed ≥ 10 years. This SBRT regimen specifically emulated an existing HDR brachytherapy dose schedule and isodose morphology, prescribed to 38 Gy/4 fractions, delivered daily by robotic SBRT, mandating > 150% dose escalation in the peripheral zone. Androgen deprivation therapy was not allowed, and a hydrogel spacer was not available at that time.

Results

Median pre-SBRT PSA 5.12 ng/mL decreased to 0.1 ng/mL by 3.5 years, with further decrease to a nadir of < 0.1 ng/mL by 7 years, maintained through 10 years. Ten-year freedom from biochemical recurrence measured 100% for low-risk, 84.3% for favorable intermediate risk (FIR), and 68.4% for unfavorable intermediate (UIR) cases. Multivariable analysis revealed that the UIR group bifurcated into two distinct prognostic subgroups. Those so classified by having Gleason score 4 + 3 and/or clinical stage T2 (versus T1b/T1c) had a significantly poorer 10 year freedom from biochemical recurrence rate, 54.8% if either or both factors were present, while UIR patients without these specific factors had a 94.4% 10-year freedom from biochemical recurrence rate. The cumulative incidence of grade 2 GU toxicity modestly increased over time – 16.3% at 5 years increased to 19.2% at 10 years-- while the incidence of grade 3+ GU and GI toxicity remained low and stable to 10 years - 2.6% and 0%, respectively. The grade 2 GI toxicity incidence also remained low and stable to 10 years – 4.1% with no further events after year 5.

Conclusion

This HDR-like SBRT regimen prescribing 38 Gy/4 fractions but delivering much higher intraprostatic doses on a daily basis is safe and effective. This treatment achieves a median PSA nadir of <0.1 ng/mL and provides high long-term disease control rates without ADT except for a subgroup of unfavorable intermediate-risk patients.

Development and validation of a cell cycle progression signature for decentralized testing of men with prostate cancer

Aim: The 46-gene Prolaris^® cell cycle progression test provides information on the risk of prostate cancer progression. Here we developed and validated a 16-gene kit-based version. Methods: RNA was extracted from prostate cancer biopsy tissue. Amplification efficiency, minimum tumor content, repeatability, reproducibility and equivalence with the 46-gene test were evaluated. Results: Amplification efficiencies for all genes were within the acceptable range (90-110%), and samples with ≥50% tumor content were appropriate for the 16-gene test. Results were repeatable (standard deviation: 0.085) and reproducible (standard deviation: 0.115). Instrument, operator and kit lot had minimal impact on results. Cell cycle progression scores from the 46- and 16-gene tests were highly correlated (r = 0.969; bias = 0.217). Conclusion: The 16-gene test performs consistently and similarly to the 46-gene test.