The ProBio trial: molecular biomarkers for advancing personalized treatment decision in patients with metastatic castration-resistant prostate cancer

Prostate cancer and liquid biopsies: Clinical applications and challenges

Liquid biopsy has emerged as a valuable and minimally invasive tool for real-time detection of clinically actionable abnormalities across various cancer types. Its applicability is particularly compelling in the realm of prostate cancer, where novel therapeutic agents, including those targeting DNA repair systems, are under development. Despite these advancements, challenges persist in effectively screening for prostate cancer, enhancing risk stratification, and determining optimal approaches for treating advanced disease. Consequently, there is a pressing need for improved biomarkers to aid clinicians in decision-making within these contexts. Cell-free DNA and extracellular vesicle analysis have demonstrated promise in diagnosis, prognostication, assessment of treatment responses, and identification of emerging mechanisms of resistance. Nevertheless, obstacles must be addressed before liquid biopsies can be integrated into routine clinical practice. These challenges encompass preanalytical considerations such as sample collection and storage, methods of extracellular vesicle isolation and enrichment, and the need for enhanced interpretation of generated sequencing data. This review provides a comprehensive overview of current clinical opportunities in managing prostate cancer through blood-based liquid biopsy, highlighting the progress made, and acknowledging the challenges that remain. Additionally, we discuss the next steps required for the effective implementation of liquid biopsies in guiding personalized treatment strategies for prostate cancer.

Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine-learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org ). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

Flexible evaluation of surrogacy in platform studies

Trial-level surrogates are useful tools for improving the speed and cost effectiveness of trials but surrogates that have not been properly evaluated can cause misleading results. The evaluation procedure is often contextual and depends on the type of trial setting. There have been many proposed methods for trial-level surrogate evaluation, but none, to our knowledge, for the specific setting of platform studies. As platform studies are becoming more popular, methods for surrogate evaluation using them are needed. These studies also offer a rich data resource for surrogate evaluation that would not normally be possible. However, they also offer a set of statistical issues including heterogeneity of the study population, treatments, implementation, and even potentially the quality of the surrogate. We propose the use of a hierarchical Bayesian semiparametric model for the evaluation of potential surrogates using nonparametric priors for the distribution of true effects based on Dirichlet process mixtures. The motivation for this approach is to flexibly model relationships between the treatment effect on the surrogate and the treatment effect on the outcome and also to identify potential clusters with differential surrogate value in a data-driven manner so that treatment effects on the surrogate can be used to reliably predict treatment effects on the clinical outcome. In simulations, we find that our proposed method is superior to a simple, but fairly standard, hierarchical Bayesian method. We demonstrate how our method can be used in a simulated illustrative example (based on the ProBio trial), in which we are able to identify clusters where the surrogate is, and is not useful. We plan to apply our method to the ProBio trial, once it is completed.

Treatment landscape and burden of disease in metastatic castration-resistant prostate cancer: systematic and structured literature reviews

Purpose

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal disease that imposes a major burden on patients and healthcare systems. Three structured literature reviews (treatment guidelines, treatment landscape, and human/clinical/patient burden) and one systematic literature review (economic burden) were conducted to better understand the disease burden and unmet needs for patients with late-stage mCRPC, for whom optimal treatment options are unclear.

Methods

Embase®, MEDLINE®, MEDLINE® In-Process, the CENTRAL database (structured and systematic reviews), and the Centre for Reviews and Dissemination database (systematic review only) were searched for English-language records from 2009 to 2021 to identify mCRPC treatment guidelines and studies related to the treatment landscape and the humanistic/economic burden of mCRPC in adult men (aged ≥18 years) of any ethnicity.

Results

In total, six records were included for the treatment patterns review, 14 records for humanistic burden, nine records for economic burden, three records (two studies) for efficacy, and eight records for safety. Real-world treatment patterns were broadly aligned with treatment guidelines and provided no optimal treatment sequencing beyond second line other than palliative care. Current post-docetaxel treatments in mCRPC are associated with adverse events that cause relatively high rates of treatment discontinuation or disruption. The humanistic and economic burdens associated with mCRPC are high.

Conclusion

The findings highlight a lack of treatment options with novel mechanisms of action and more tolerable safety profiles that satisfy a risk-to-benefit ratio aligned with patient needs and preferences for patients with late-stage mCRPC. Treatment approaches that improve survival and health-related quality of life are needed, ideally while simultaneously reducing costs and healthcare resource utilization.

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.

Confirmatory prediction-driven RCTs in comparative effectiveness settings for cancer treatment

BACKGROUND

Medical advances in the treatment of cancer have allowed the development of multiple approved treatments and prognostic and predictive biomarkers for many types of cancer. Identifying improved treatment strategies among approved treatment options, the study of which is termed comparative effectiveness, using predictive biomarkers is becoming more common. RCTs that incorporate predictive biomarkers into the study design, called prediction-driven RCTs, are needed to rigorously evaluate these treatment strategies. Although researched extensively in the experimental treatment setting, literature is lacking in providing guidance about prediction-driven RCTs in the comparative effectiveness setting.

METHODS

Realistic simulations with time-to-event endpoints are used to compare contrasts of clinical utility and provide examples of simulated prediction-driven RCTs in the comparative effectiveness setting.

RESULTS

Our proposed contrast for clinical utility accurately estimates the true clinical utility in the comparative effectiveness setting while in some scenarios, the contrast used in current literature does not.

DISCUSSION

It is important to properly define contrasts of interest according to the treatment setting. Realistic simulations should be used to choose and evaluate the RCT design(s) able to directly estimate that contrast. In the comparative effectiveness setting, our proposed contrast for clinical utility should be used.

Clinical Trial Protocol for ProBio: An Outcome-adaptive and Randomised Multiarm Biomarker-driven Study in Patients with Metastatic Prostate Cancer

ProBio is an outcome-adaptive, multiarm, multiple-assignment randomised, biomarker-driven platform trial in men with metastatic castration-resistant prostate cancer. Here we describe the amended clinical protocol, focusing on expansion of the trial to include patients with de novo metastatic hormone-sensitive prostate cancer.

Androgen receptor genomic alterations and treatment resistance in metastatic prostate cancer

BACKGROUND

Genomic alterations to the androgen receptor (AR) are common in metastatic castration-resistant prostate cancer (mCRPC). AR copy number amplifications, ligand-binding domain missense mutations, and intronic structural rearrangements can all drive resistance to approved AR pathway inhibitors and their detection via tissue or liquid biopsy is linked to clinical outcomes. With an increasingly crowded treatment landscape, there is hope that AR genomic alterations can act as prognostic and/or predictive biomarkers to guide patient management.

METHODS

In this review, we evaluate the current evidence for AR genomic alterations as clinical biomarkers in mCRPC, focusing on correlative studies that have used plasma circulating tumor DNA to characterize AR genotype.

RESULTS

We highlight data that demonstrates the complexity of AR genotype within individual patients, and suggest that future studies should account for cancer clonal heterogeneity and variable tumor content in liquid biopsy samples. Given the potential for cooccurrence of multiple AR genomic alterations in the same or competing subclones of a patient, it is distinctly challenging to attribute blanket clinical significance to any individual alteration. This challenge is further complicated by the varied treatment exposures in contemporary patients, and the fact that AR genotype continues to evolve in the mCRPC setting across sequential lines of systemic therapy.

CONCLUSIONS

As treatment access and liquid biopsy technology continues to improve, we posit that real-time measures of AR biology are likely to play a key role in emerging precision oncology strategies for metastatic prostate cancer.

Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

Sequencing of cell-free DNA (cfDNA) is currently being used to detect cancer by searching both for mutational and non-mutational alterations. Recent work has shown that the length distribution of cfDNA fragments from a cancer patient can inform tumor load and type. Here, we propose non-negative matrix factorization (NMF) of fragment length distributions as a novel and completely unsupervised method for studying fragment length patterns in cfDNA. Using shallow whole-genome sequencing (sWGS) of cfDNA from a cohort of patients with metastatic castration-resistant prostate cancer (mCRPC), we demonstrate how NMF accurately infers the true tumor fragment length distribution as an NMF component - and that the sample weights of this component correlate with ctDNA levels (r=0.75). We further demonstrate how using several NMF components enables accurate cancer detection on data from various early stage cancers (AUC=0.96). Finally, we show that NMF, when applied across genomic regions, can be used to discover fragment length signatures associated with open chromatin.

Detection of von Hippel-Lindau gene mutation in circulating cell-free DNA for clear cell renal cell carcinoma

The therapeutic landscape of metastatic clear cell renal cell carcinoma (ccRCC) has rapidly expanded, and there is an urgent need to develop noninvasive biomarkers that can select an optimal therapy or evaluate the response in real time. To evaluate the clinical utility of circulating tumor DNA (ctDNA) analysis in ccRCC, we established a highly sensitive assay to detect mutations in von Hippel‐Lindau gene (VHL) using a combination of digital PCR and multiplex PCR–based targeted sequencing. The unique assay could detect VHL mutations with a variant allele frequency (VAF) <1.0%. Further, we profiled the mutation status of VHL in 76 cell‐free DNA (cfDNA) and 50 tumor tissues from 56 patients with ccRCC using the assay. Thirteen VHL mutations were identified in cfDNA from 12 (21.4%) patients with a median VAF of 0.78% (range, 0.13%‐4.20%). Of the 28 patients with VHL mutations in matched tumor tissues, eight (28.6%) also had VHL mutation in cfDNA with a median VAF of 0.47% (range, 0.13%‐2.88%). In serial ctDNA analysis from one patient, we confirmed that the VAF of VHL mutation changed consistent with tumor size by radiographic imaging during systemic treatment. In conclusion, VHL mutation in cfDNA was detected only in a small number of patients even using the highly sensitive assay; nevertheless, we showed the potential of ctDNA analysis as a novel biomarker in ccRCC.

Clinical implications of genomic alterations in metastatic prostate cancer

There has been a rapid expansion in treatment options for the management of metastatic prostate cancer, but individual patient outcomes can be variable due to inter-patient tumor heterogeneity. Fortunately, the disease can be stratified on the basis of common somatic features, providing potential for the development of clinically useful prognostic and predictive biomarkers. Tissue biopsy programs and studies leveraging circulating tumor DNA (ctDNA) have revealed specific genomic alterations that are associated with aggressive disease biology. In this review, we discuss the potential for genomic subtyping to improve prognostication and to help guide treatment selection. We summarize data on associations between AR pathway alterations and patient response to AR signaling inhibitors and other standards of care. We describe the links between detection of different types of DNA damage repair defects and clinical outcomes with targeted therapies such as poly(adenosine diphosphate-ribose) polymerase (PARP) inhibitors or immune checkpoint inhibitors. PI3K signaling pathway inhibitors are also in advanced clinical development and we report upon the potential for these and other novel targeted therapies to have impact in specific molecular subsets of metastatic prostate cancer. Finally, we discuss the growing use of blood-based analytes for prognostic and predictive biomarker development, and summarize ongoing prospective biomarker-driven clinical trials.

Resistance to second-generation androgen receptor antagonists in prostate cancer

The introduction of second-generation androgen receptor antagonists (SG-ARAs) has greatly impacted the treatment of metastatic prostate cancer, providing tolerable and efficacious alternatives to chemotherapy. SG-ARAs provide similar therapeutic benefit to abiraterone, a potent CYP17 inhibitor, and do not require the co-administration of prednisone. Despite considerable improvements in clinical outcomes in the settings of both castration sensitivity and castration resistance, the durability of clinical response to the SG-ARAs enzalutamide, apalutamide and darolutamide, similar to abiraterone, is limited by inevitable acquired resistance. Genomic aberrations that confer resistance to SG-ARAs or provide potential alternative treatment modalities have been identified in numerous studies, including alterations of the androgen receptor, DNA repair, cell cycle, PI3K-AKT-mTOR and Wnt-β-catenin pathways. To combat resistance, researchers have explored approaches to optimizing the utility of available treatments, as well as the use of alternative agents with a variety of targets, including AR-V7, AKT, EZH2 and HIF1α. Ongoing research to establish predictive biomarkers for the treatment of tumours with resistance to SG-ARAs led to the approval of the PARP inhibitors olaparib and rucaparib in pre-treated metastatic castration-resistant prostate cancer. The results of ongoing studies will help to shape precision medicine in prostate cancer and further optimize treatment paradigms to maximize clinical outcomes.

Increased Pathway Complexity Is a Prognostic Biomarker in Metastatic Castration-Resistant Prostate Cancer

Simple Summary

Circulating tumour DNA profiling can cost-efficiently accelerate biomarker discovery within oncology trials. However, biomarker identification in metastatic castration-resistant prostate cancer is confounded by a heterogeneous genomic landscape with few commonly-perturbed genes and a large number of infrequently mutated, yet potentially biologically-relevant, cancer drivers. Hence, large sample sizes are required for the stratified evaluation of these infrequent perturbations. To circumvent this issue, we investigated whether grouping genomic alterations with other events within the same cellular pathways would offer increased precision for biomarker discovery. We undertook an individual patient-level pooled analysis of 342 patients with metastatic castration-resistant prostate cancer-initiating abiraterone acetate or enzalutamide. We found that the total number of altered pathways, which we termed the pathway complexity index (PCI) was associated with a poor prognosis. Since genomic profiling is now standard practice in interventional oncology trials, our findings highlight the importance of comprehensive genomic profiling for biomarker discovery and utilization.

Abstract

Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease, characterized by common and rare driver gene alterations that provide a selective growth advantage for progressing tumour cells. We hypothesized that the number of distinct gene driver alteration-affected pathways or gene classes was associated with poor prognosis in patients initiating androgen receptor signalling inhibitors (ARSi). We performed a post hoc analysis of an amalgamated baseline circulating tumour DNA (ctDNA) mutational landscape dataset of ARSi-treated men with mCRPC (n = 342). We associated the detected hotspot, pathogenic, and/or high impact protein function-affecting perturbations in 39 genes into 13 pathways. Progression-free (PFS) and overall survival (OS) were analysed using Kaplan–Meier curves and multivariate Cox regression models. Driver gene alterations were detected in 192/342 (56.1%) evaluable patients. An increased number of affected pathways, coined pathway complexity index (PCI), resulted in a decremental PFS and OS, and was independently associated with prognosis once ≥3 pathway or gene classes were affected (PFS HR (95%CI): 1.7 (1.02–2.84), p = 0.04, and OS HR (95%CI): 2.5 (1.06–5.71), p = 0.04). Additionally, visceral disease and baseline PSA and plasma ctDNA levels were independently associated with poor prognosis. Elevated PCI is associated with poor ARSi outcome and supports comprehensive genomic profiling to better infer mCRPC prognosis.

AZGP1 Protein Expression in Hormone-Naïve Advanced Prostate Cancer Treated with Primary Androgen Deprivation Therapy

Biomarkers for predicting the risk of castration-resistant prostate cancer (CRPC) in men treated with primary androgen deprivation therapy (ADT) are lacking. We investigated whether Zinc-alpha 2 glycoprotein (AZGP1) expression in the diagnostic biopsies of men with hormone-naïve prostate cancer (PCa) undergoing primary ADT was predictive of the development of CRPC and PCa-specific mortality. The study included 191 patients who commenced ADT from 2000 to 2011. The AZGP1 expression was evaluated using immunohistochemistry and scored as high or low expression. The risks of CRPC and PCa-specific mortality were analyzed using stratified cumulative incidences and a cause-specific COX regression analysis for competing risk assessment. The median follow-up time was 9.8 (IQR: 6.1–12.7) years. In total, 94 and 97 patients presented with low and high AZGP1 expression, respectively. A low AZGP1 expression was found to be associated with a shorter time to CRPC when compared to patients with a high AZGP1 expression (HR: 1.5; 95% CI: 1.0–2.1; p = 0.03). However, the multivariable analysis demonstrated no added benefit by adding the AZGP1 expression to prediction models for CRPC. No differences for PCa-specific mortality between the AZGP1 groups were observed. In conclusion, a low AZGP1 expression was associated with a shorter time to CRPC for PCa patients treated with first-line ADT but did not add any predictive information besides well-established clinicopathological variables.