STATE OF THE ART

 

Metastatic prostate cancer and the evolving therapeutic landscape

     Prostate cancer is the most commonly diagnosed cancer in European men. Every year more than 400,000 men are diagnosed and about 107,000 die of prostate cancer upon development or newly diagnosis of metastatic disease. In men with metastatic hormone-sensitive prostate cancer (mHSPC), androgen deprivation therapy (ADT) has been standard-of-care (SOC) the last 70 years. Although ADT was initially used as monotherapy, the therapeutic field has moved towards the use of earlier treatment intensification. Nowadays, backbone ADT is combined with other systemic agents, such novel hormonal agents (NHA) and taxane-based chemotherapy, which has resulted in improved SOC and patient outcome. However, eventually all men will progress and develop metastatic castration-resistant prostate cancer (mCRPC). The last decade, the introduction of new agents and treatment sequencing regimens have improved the SOC. However, regardless in which stage of the disease, drug selection is typically driven by availability, reimbursement criteria, and clinical judgment. Although these drugs are beneficial for the overal patient population on average, their unselected usage in daily clinical practice can and will lead to ineffective trial-and-error treatment decisions, and will increase the socio-economic burden on the health care system, since:

  • These drugs are expensive.

  • The response rates can vary considerably (not all patients have a long-term benefit from all drug classes).

  • There are no predictive treatment markers that can inform which patient could benefit more from which therapy.

Inferring Biomarker Signatures using comprehensive genomics profiling

     Multiple studies have reported on the genomic alteration landscape in metastatic hormone-sensitive (mHSPC) and castration-resistant prostate cancer (mCRPC), focusing on the alteration frequencies across different disease states and clinical phenotypes, and the potential clinical implications in terms of prognosis and treatment-predictive value. Although molecular analysis of archival primary biopsy/resection material is worthwhile to perform, the biomarker discovery in metastatic prostate cancer has been hampered by low success rates in obtaining metastatic tissue for downstream molecular profiling. Also, profiling a single metastatic lesion is not capable of providing the full spectrum of the molecular heterogeneity that exists within the patient. A liquid biopsy, e.g. tumour-derived cell-free DNA (cfDNA), is an attractive real-time alternative. During ProBio, biomarker signatures will be inferred by comprehensive genomic profiling from tissue-derived and circulating tumor DNA, using a gene panel specifically designed for prostate cancer. Alterations in the following genes/pathways or combinations thereof constitute the initial biomarker signatures:

  • Androgen receptor

  • Homologous recombination deficiency.

  • TP53

  • TMPRSS2-ERG gene fusion

  • Other biomarker signatures will be added upon drug availability and protocol amendment

Novel statistical trial designs

     ProBio will use outcome-adaptive randomisation, adapting the randomisation based on progression free survival within combinations of treatment classes and biomarker signatures. Treatments will initially be assigned to all biomarker signatures where they might be effective. The trial will be analysed within a Bayesian framework, which allows for calculations of the probability for each treatment that it is superior to standard of care within a given signature. Each experimental arm will be evaluated relative to patients in the control arm with the same biomarker signature. Participants and treating physicians will be blinded to the biomarker signature in the control arm. This information will thus not influence treatment choice among controls (reflecting today’s standard of care). Further, ProBio will use the sequential multiple assignments trial (SMART) concept, where each patient who progresses within the trial will be re-assigned to another treatment based on the patient’s current biomarker signature profile. The randomisation probabilities within the experimental arm are defined in proportion to the probability that each treatment class is superior to standard of care for a given biomarker signature, and therefore change as data accumulates in the trial and knowledge accumulates for what biomarker signature specific treatments are more probable to be effective. ProBio is a platform study, which means that new treatments and biomarker profiles can be added to the experimental arm in the future. This will be done after protocol amendments.

STUDY DESIGN

General overview and hypothesis

      The proposed hypothesis is that treatment decisions based on biomarker signatures identified by sequencing tumour tissue and/or circulating tumour DNA significantly will increase the progression free survival (PFS) in patients with metastatic prostate cancer compared to current clinical standard-of-care (Primary analysis). This hypothesis will be tested in a large, international, multi-centre, randomised controlled platform trial with an outcome-adaptive and biomarker-driven design in male patients, aged above 18 years, with histologically confirmed prostate adenocarcinoma, initiating systemic therapy for metastatic disease, encompassing:

  • Newly diagnosed (i.e. de novo) metastatic hormone-sensitive prostate cancer (mHSPC) or 

  • First-line metastatic castration-resistant prostate cancer (mCRPC), i.e. first evidence of progressive metastatic prostate cancer under castrate levels (<50 ng/dL) of serum testosterone, as defined by the EAU guidelines.


ProBio trial design

mHSPC: metastatic hormone-sensitive prostate cancer. mCRPC: metastatic castration-resistant prostate cancer. ctDNA: circulating tumour DNA. SOC: standard-of-care, BS: biomarker signature, HRD: homologous recombination repair deficiency, ADT: androgen deprivation therapy, AR: androgen receptor, wt: wild type. * adaptive randomisation, § local treatment allowed across all treatment arms, ¶ avoiding taxane-taxane or ARSi-ARSi sequence when patients experienced short progression-free interval, # AR signalling inhibitor (ARSi) based on availability and reimbursement, ∞ taxane-based chemotherapy (CT) based on availability and reimbursement.

Treatments

      Patients in the experimental arm can be randomised to the following treatment classes, depending on national guidelines, availability and reimbursement criteria:

        For mHSPC 

  1.  AR signalling inhibitors

    • Abiraterone acetate plus prednisone​

    • Apalutamide

    • Other ARSi upon approval from authorities and protocol amendment

  2. Taxane-based chemotherapy

    • Docetaxel​

  3. Other investigational agent(s) sponsored by pharmaceutical company

    • Niraparib plus abiraterone acetate plus prednisone

       For mCRPC

  1. AR signalling inhibitors

    • Enzalutamide

    • Abiraterone acetate plus prednisone

  2. Taxane-based chemotherapy

    • Docetaxel

    • Cabazitaxel

  3. Platinum-based chemotherapy

    • Carboplatin​

  4. Other investigational agent(s) sponsored by pharmaceutical company:

    • Niraparib plus abiraterone acetate plus prednisone

Treatment randomisation procedures and patient pathways

      ProBio patients can follow different pathways within the trial, which not only depends on their biomarker subgroup combinations, but also on the timing of randomisation and in which arm the patient was initially randomised to. Patients may enter the metastatic hormone-sensitive prostate cancer (mHSPC) phase of the ProBio trial, and will be followed till metastatic castration-resistant prostate cancer (mCRPC) onset, and during 2 lines of systemic therapy in mCRPC. Alternatively, patients previously treated within the SOC outside of ProBio and that have developed mCRPC can immediately enter the mCRPC phase of the ProBio trial, and will be followed during 2 lines of systemic therapy in mCRPC. Patients are excluded if their biomarker signature cannot be inferred. Patients will be randomised either to the control group (SOC) or one of the experimental biomarker signature-therapy combination arms. As patients might be unfit or unwilling to continue the trial, both the patient and treating physician might choose to discontinue the patient and exit the trial. Upon progressive disease, patients initially randomised to one of the biomarker signature-therapy combination arms will be rerandomised to another biomarker signature-therapy combination arm after a new liquid biopsy profile was generated. During the 12-15 day turnaround time to generate a new liquid biopsy profile it is at the discretion of the treating physician to completely stop or continue the prior systemic therapy on which the patient is currently progressive. In contrast, patients initially randomised to the control group will remain in their arm upon progression (unless graduated biomarker signatures-therapy combinations are available) and will immediately receive a new line of physicians' choice SOC therapy. In the later stage of the trial, if the biomarker subgroup combination of a new patient belongs to one of the graduating biomarker signatures, the patient will enter the confirmatory trial with fixed randomisation to the control (SOC) or the graduating active treatment. Finally, upon progressive disease after the second or third randomisation, depending if the patient entered ProBio in the mCRPC or mHSPC setting respectively, all patients will discontinue and exit the ProBio trial for the PFS endpoints. Long-term follow for overall survival (OS) analysis will take place via the national cancer registries by biannual communication with the coordinating and/or site principal investigators.

NEW FIGURE 3-1.png
 
NEW FIGURE 2-1.png

STUDY OBJECTIVES

Primary objective and endpoint

Objective

Evaluation of the clinical effectiveness of treatment class selection based on a biomarker signature derived from circulating tumor DNA (ctDNA) or tumor tissue DNA by improving Progression Free Survival (PFS) compared to standard-of-care (SOC) in patients with metastatic hormone-sensitive and castration-resistant prostate cancer. The goal is to early identify in which biomarker signature a therapy class is superior to SOC, by comparing biomarker signature-therapy class combinations with respect to superiority in PFS to a common control group (SOC) (Primary analysis)

Endpoint

Progression-free survival, where progression is defined according to disease stage at trial entry:

  • For mHSPC: Time to development of castration-resistance (European Association of Urology [EAU] guidelines)

  • For mCRPC: Time to no longer clinical benefiting (NLCB) (Prostate Cancer Working Group [PCWG3] guidelines)

probio primary.png

Secondary objectives and endpoints

Objective

Evaluating whether treatment class selection based on biomarker signatures can, compared to standard of care, improve the PFS distribution of the experimental arm altogether versus the control group (key secondary analysis 1).

Endpoint

Progression-free survival,  where progression is defined according to disease stage at trial entry (see endpoint of primary analysis).

NEW FIGURE 5-1.png

Objective

To determine whether a certain treatment class is superior for a certain biomarker signature compared to other treatment classes, by comparing experimental arms against each other (efficacy analysis) within any biomarker signature across experimental arms (key secondary analysis 2)

Endpoint

Progression-free survival,  where progression is defined according to disease stage at trial entry (see endpoint of primary analysis)

NEW FIGURE 6-1.png

Objective

Evaluating whether treatment class selection based on biomarker signatures can, compared to standard of care, improve treatment class response rate (RR) after 2-4 months of treatment.

Evaluating whether treatment class selection based on biomarker signatures can, compared to standard of care, improve time to biochemical progression

Evaluating whether treatment class selection based on biomarker signatures can, compared to standard of care, improve time to radiological progression.

Evaluating whether treatment class selection based on biomarker signatures can, compared to standard of care, improve the time from the initial study randomisation to the 2nd progression or death from any cause

Evaluating whether treatment class selection based on biomarker signatures can, compared to standard of care, improve the time from the initial study randomisation to death from any cause.

Evaluating whether treatment class selection based on biomarker signatures can, compared to standard of care, improve quality of life

Evaluating whether treatment class selection based on biomarker signatures can, compared to standard of care, improve health economy

Evaluating whether treatment class selection based on biomarker signatures, compared to standard of care, does not increase toxicity (i.e drug safety)

To identify additional predictive and prognostic biomarkers. 

Identify superior treatment sequencing regimens (i.e. is treatment A followed by treatment B superior to treatment B followed by treatment A given a biomarker signature)

Endpoint

Treatment class response rate (RR) 

  • RECIST v1.1 objective response


  • PSA response


  • Composite overall response


PSA-PFS

rPFS

PFS2

Overall Survival (OS)

Quality of life assessed by 

  • EORTC-QLQ-C30


  • EQ-5D-5L


  • BPI-SF


Cost effectiveness will be assessed by using the EQ-5D-5L instrument to estimate health utilities. Treatment costs will be based on drug costs and reimbursement dataRec

Frequency and severity of adverse events (AE) using Common Terminology Criteria for Adverse Events (CTCAE v5.0)

 
 

IMPACT

Short and long-term effects on patient management

     The molecular characteristics of a patient’s tumour will become an essential prerequisite of routine diagnostics to prognosticate the patient and to define the treatment management by predictive biomarker assessment.

  In the short term our study will:

  • introduce genomic profiling in the daily practice of treating physicians 

  • allow for better patient monitoring and management

  • potentially provide longer benefit for those recruited patients that will be randomised to a biomarker signature-driven treatment arm 

  Since we envision treatment will become patient-tailored, aiming towards a maximal response probability of the actual treatment that is being prescribed, our study will in the long term:

  • introduce the use of predictive tissue- and/or blood-based molecular signatures in standard-of-care 

  • result in the identification of a subpopulation of patients who would not benefit from standard-of-care therapy and immediately direct these patients to more novel drugs or experimental trials 

  • introduce true precision urologic oncology in metastatic prostate cancer, aiming to maximise quality-of-life and prognosis in this rapidly expanding patient population. 

Valorisation strategy and future vision

     ProBio’s future vision is a molecularly-driven selection of a (systemic) therapy that benefits the patient the most. Hence, ProBio aims to valorise its results and brings these as rapid as possible to the relevant patient group in daily practice. Our valorisation strategy encompasses:

  • Implementing a validation arm in our trial design to test graduated biomarker signature/therapy combinations in standard-of-care 

  • Actively involve the Ministries of Healthcare to discuss reimbursement strategies of the ProBio genomic profiling test 

  • Development of a centralised ProBio laboratory on a national level 

  • Organise knowledge diffusion symposia for clinicians, general practitioners and patient organisations

  • Publishing our results in both national and international journals 

  • Attend scientific conferences to discuss the results 

WHAT ARE OUR EXPLORATORY SUBSTUDIES?

  1. Can ctDNA fraction dynamics replace PCWG3 for therapy response assessment?

  2. Can ctDNA fraction bursts predict therapy response?

  3. Retrospective analysis of the ctDNA profile to identify new biomarker signature - treatment associations

  4. Analysis of cell-free DNA methylomes

  5. Analysis of cell-free RNA

  6. RNA Analysis of thrombocytes

  7. Prospective DNA analysis of CTCs

  8. RNA analysis of CTCs

  9. cfRNA and cfDNA analysis of urine

  10. Prospective evaluation of clinical validity of PSMA-PET/CT-scan in mCRPC (CUTR-01 study)

  11. Development of a new Patient Reported Outcome Measure (PROM) instrument to evaluate the Quality of Life (QoL) of patients with advanced prostate cancer

  12. Quantitative analysis of androgen receptor perturbations using a blood-based liquid biopsy as a treatment-predictive biomarker for men with metastatic castration- resistant prostate cancer.