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      string(257) "NCT01715285 - A Randomized, Double-blind, Comparative Study of Abiraterone Acetate Plus Low-Dose Prednisone Plus Androgen Deprivation Therapy (ADT) Versus ADT Alone in Newly Diagnosed Subjects With High-Risk, Metastatic Hormone-naive Prostate Cancer (mHNPC)"
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  ["project_title"]=>
  string(106) "Optimizing the therapeutic index of AR pathway inhibition in men with advanced prostate cancer (Optima-AR)"
  ["project_narrative_summary"]=>
  string(844) "The goal of this project is to personalize treatment for patients with advanced prostate cancer by accounting for both tumor biology and patient susceptibility. We aim to identify tumor- and patient-related factors that place individuals into one of three groups: (1) tumors that do not respond to androgen receptor pathway inhibitors (ARPIs); (2) tumors that respond well to ARPIs in patients without increased vulnerability to these drugs; or (3) tumors that respond to ARPIs in patients with inherited susceptibility to ARPI-related side effects.



Using a pooled cohort of patients treated with ARPIs, we will test two hypotheses: first, that molecularly defined tumors achieve durable disease control with ARPI therapy; and second, that inherited patient factors predict clinically meaningful, on-target side effects of ARPIs."
  ["project_learn_source"]=>
  string(11) "data_holder"
  ["principal_investigator"]=>
  array(7) {
    ["first_name"]=>
    string(6) "Andrew"
    ["last_name"]=>
    string(4) "Hahn"
    ["degree"]=>
    string(2) "MD"
    ["primary_affiliation"]=>
    string(49) "The University of Texas MD Anderson Cancer Center"
    ["email"]=>
    string(20) "ahahn@mdanderson.org"
    ["state_or_province"]=>
    string(2) "TX"
    ["country"]=>
    string(13) "United States"
  }
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      ["p_pers_f_name"]=>
      string(7) "Rebecca"
      ["p_pers_l_name"]=>
      string(7) "Tidwell"
      ["p_pers_degree"]=>
      string(2) "MS"
      ["p_pers_pr_affil"]=>
      string(49) "The University of Texas MD Anderson Cancer Center"
      ["p_pers_scop_id"]=>
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      ["requires_data_access"]=>
      string(3) "yes"
    }
    [1]=>
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      ["p_pers_f_name"]=>
      string(4) "Chad"
      ["p_pers_l_name"]=>
      string(4) "Huff"
      ["p_pers_degree"]=>
      string(3) "PhD"
      ["p_pers_pr_affil"]=>
      string(49) "The University of Texas MD Anderson Cancer Center"
      ["p_pers_scop_id"]=>
      string(0) ""
      ["requires_data_access"]=>
      string(2) "no"
    }
  }
  ["project_ext_grants"]=>
  array(2) {
    ["value"]=>
    string(2) "no"
    ["label"]=>
    string(68) "No external grants or funds are being used to support this research."
  }
  ["project_date_type"]=>
  string(18) "full_crs_supp_docs"
  ["property_scientific_abstract"]=>
  string(1665) "Background: The addition of androgen receptor (AR) pathway inhibitors (APRIs) to androgen deprivation therapy (ADT) has not produced the expected proportional increases in life expectancy in real-world patients in the United States. This raises the possibility that the life-prolonging effects of ARPI are limited by on-target side effects.



Objective: To identify and validate tumor and host variables that place patients with mHSPC into 1 of 3 groups to inform future treatment strategy.



Study Design: We will use individual patient data to create 3 cohorts that each have a distinct study design: 

1) germline DNA- Men with metastatic HSPC who have germline DNA WES or WGS completed and CV risk factors from baseline and ~ 6-12 months after. 

2) Gene expression- Men with gene expression available prior to treatment and efficacy outcomes

3) Pooled cohort



Participants: Men with mHSPC with clinical outcomes available for treatment with ADT +/- ARPI and either germline DNA WES/WGS or gene expression of tumor



Primary outcome measure: Change in cholesterol panel and ASCVD risk score based on genotype

Secondary outcome measure: Radiographic PFS and PSA at 6 months based upon gene expression groupings



Statistical analysis: Predictors of cardiometabolic toxicity will be identified using a logistic regression classification and regression tree (CART) analysis with leave one out validation for the defined cohort.  Predictors of PFS  will be identified similarly using a Cox regression CART analysis with leave one out validation within the defined cohort.  "
  ["project_brief_bg"]=>
  string(3151) "In clinical trial populations, the addition of androgen receptor (AR) pathway inhibitors (APRIs) to androgen deprivation therapy (ADT) significantly improved survival for men with metastatic hormone sensitive prostate cancer (mHSPC) and non-metastatic castration-resistant prostate cancer (nmCRPC).1-3 However, this strategy has not produced the expected proportional increases in life expectancy in real-world patients in the United States.4,5 This raises the possibility that the life-prolonging effects of ARPI are limited by on-target side effects. Prostate cancer is a disease of older age, with a median age at diagnosis of 67 years and a median age at death from prostate cancer of 79.5 years.6,7 Men with advanced prostate cancer have a high burden of cardiometabolic and bone health comorbidities.8-10 These age-related illnesses are associated with low testosterone levels, and in a subset of men, ARPI exacerbates these concurrent illnesses. These observations support the perspective that therapies directed exclusively toward the cancer, without considering the effects on the patient, may limit efficacy in this age group. 



There is an unmet need to prospectively identify patients with potentially lethal prostate cancer whose outcomes will be improved by accounting for the vulnerability of the individual host to on-target side effects (germline) and the effectiveness of ARPI on an individual’s cancer (somatic and transcriptomic) to ultimately de-intensify treatment. Translational studies have demonstrated that specific alterations in a tumor’s somatic DNA and gene expression pathways are associated with the effectiveness of ARPI. In somatic DNA, SPOP alterations are associated with response to ARPI, and the aggressive variant molecular signature (loss of 2/3 of PTEN, RB1, or TP53) is associated with resistance to ARPI.11,12 In bulk RNA sequencing, our group and others have shown that upregulation of cell cycle and DNA damage repair pathways is associated with resistance to ARPI.13,14 Previously, it was challenging to objectively measure on-target side effects with ARPI. Our group has pioneered using objective measures of cardiometabolic health, including body composition and lipid profiles, to identify inherited vulnerabilities and clinical factors associated with differential harm from ARPI.15,16 In these studies, we have demonstrated that inherited polymorphisms in steroidogenic genes and type II diabetes mellitus are associated with differential body composition toxicity after hormone therapy.



The overarching goal of this proposal is to identify and validate tumor and host variables that place patients into one of the following groups and inform treatment strategy. We will identify men with tumors resistant to ARPI who will benefit from further intensification. We will identify men with tumor's responsive to ARPI who are not vulnerable to CV complications and are ideal candidates for prolonged ADT + ARPI. We will finally identify men with tumor's response to ARPI but vulnerable to CV complications and are ideal for finite ADT + ARPI or eugonadal, novel therapies"
  ["project_specific_aims"]=>
  string(691) "Primary Aims

•	Determine whether inherited polymorphisms in steroidogenic genes are associated with differential cardiometabolic toxicity in men treated with ADT +/- ARPI

•	Evaluate whether increased gene expression of cell cycle pathways is associated with inferior PFS to ADT +/- ARPI



Secondary Aims

•	Identify additional inherited polymorphisms associated with differential cardiometabolic toxicity with ADT +/- ARPI

•	Test whether established somatic DNA alterations are associated with PFS to ADT +/- ARPI

•	Determine how expression of cell cycle pathways is associated with Decipher score in men with advanced prostate cancer"
  ["project_study_design"]=>
  array(2) {
    ["value"]=>
    string(7) "meta_an"
    ["label"]=>
    string(52) "Meta-analysis (analysis of multiple trials together)"
  }
  ["project_purposes"]=>
  array(4) {
    [0]=>
    array(2) {
      ["value"]=>
      string(56) "new_research_question_to_examine_treatment_effectiveness"
      ["label"]=>
      string(114) "New research question to examine treatment effectiveness on secondary endpoints and/or within subgroup populations"
    }
    [1]=>
    array(2) {
      ["value"]=>
      string(49) "new_research_question_to_examine_treatment_safety"
      ["label"]=>
      string(49) "New research question to examine treatment safety"
    }
    [2]=>
    array(2) {
      ["value"]=>
      string(22) "participant_level_data"
      ["label"]=>
      string(36) "Participant-level data meta-analysis"
    }
    [3]=>
    array(2) {
      ["value"]=>
      string(37) "participant_level_data_only_from_yoda"
      ["label"]=>
      string(51) "Meta-analysis using only data from the YODA Project"
    }
  }
  ["project_research_methods"]=>
  string(802) "Data source: Up to 3 trials in the same disease space from the YODA project.



Inclusion criteria

•	Metastatic hormone-sensitive prostate cancer (HSPC)

•	Hormone naïve disease at initial enrollment, specifically no prior ARPI and ≤ 2 months of ADT

•	Efficacy outcomes available for treatment with ADT +/- ARPI

•	Availability of germline DNA whole exome or whole genome sequencing OR gene expression of tumor at baseline of study entry

•	For the germline cohort, must have lipid panels, blood pressure, and glycemic control data



Exclusion criteria

- > 2 months of ADT at trial enrollment

- Missing efficacy and CV outcome measure data (1 of these 2 will remain eligible)

- Receipt of taxane chemotherapy"
  ["project_main_outcome_measure"]=>
  string(1056) "The primary outcome measure will be change in cholesterol/lipid panel and ASCVD risk score based on steroidogenic genotype of cardiometabolic toxicity. These will be measure at baseline and after 6-12 months of treatment. We will test how pre-specific inherited polymorphisms are associated with differences in these outcomes at 6-12 month time point adjusting for baseline value in this measure. We will use a directed acyclic graph to clearly depict confounding and mediating variables and adjust accordingly.



Secondary outcome measures will include evaluation of efficacy by radiographic PFS and PSA response after 6 months of therapy. We will perform supervised gene set enrichment analyses by PFS with a focus on select Hallmark pathways. Additionally, we will test AR activity signature, PTEN activity, and select other gene expression pathways of interest. Additionally, we will have secondary outcome measures for the germline and CV risk analysis that include treatment-emergent HTN, blood pressure, and markers of glycemic control."
  ["project_main_predictor_indep"]=>
  string(248) "For germline DNA studies, the exposure of interest is inherited genotype in pre-specified genes of steroidogenesis

For bulk RNA sequencing studies, we will test select Hallmark gene pathways associated with DDR, cell cycle, and AR activity. "
  ["project_other_variables_interest"]=>
  string(168) "In addition to the primary and secondary outcome measures listed above, we will evaluate overall survival in the pooled cohort as proof-of-principle of the 3 groupings."
  ["project_stat_analysis_plan"]=>
  string(2000) "Patient, tumor, and genetic characteristics will be presented separately by cohort.  Predictors of cardiometabolic toxicity will be identified using a logistic regression classification and regression tree (CART) analysis with leave one out validation for the defined cohort.  Predictors of PFS  will be identified similarly using a Cox regression CART analysis with leave one out validation within the defined cohort.  The predictors identified in cohorts 1 and 2 will be validated further in cohort 3 using the identified predictors to model the combined outcome of cardiometabolic toxicity and/or long PFS.  The agreement κ between medical record (gold standard) and model prediction from the selected model will be reported with a 95% confidence interval.  Additional model refinement may be implemented as needed to improve prediction.



Assuming 2000 patients to start and allowing for some patients to not meet any cohort completely, sample sizes within each cohort assume 600 patients available.  Cohort 1: For an individual logistic regression model of cardiometabolic toxicity (Y) on a binary predictor X (i.e. a polymorphism) assuming 50% are in the group X=No and 50% are in the group X=Yes) achieves 84.1% power at a 5% significance level to detect a change in Prob(Y=1) from the baseline value of 0.35 to 0.52. This change corresponds to an odds ratio of 2.0, assuming other independent variables in the logistic regression obtained an R-Squared of 0.50. Cohort 2: For an individual Cox regression model of the log hazard ratio for PFS on any covariate with a standard deviation of 1.0, achieves 84.8% power at a 5% significance level to detect a regression coefficient equal to -0.2877 (i.e. hazard ratio =0.75), assuming other covariates in the Cox regression have an R-Squared of 0.7. The calculation was adjusted for an anticipated event rate of 60%. Cohort 3: The two-sided 95% confidence interval will have a width of 0.096 if the standard deviation SD(κ), is 0.60."
  ["project_software_used"]=>
  array(2) {
    [0]=>
    array(2) {
      ["value"]=>
      string(1) "r"
      ["label"]=>
      string(1) "R"
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    [1]=>
    array(2) {
      ["value"]=>
      string(5) "stata"
      ["label"]=>
      string(5) "STATA"
    }
  }
  ["project_timeline"]=>
  string(222) "Project start date: April 2026

Analysis completion date: June 2027 for germline DNA and gene expression studies. April 2028 for pooled analysis

Manuscript drafted: Will be 2-3 papers with first in Spring 2027"
  ["project_dissemination_plan"]=>
  string(340) "If our results were positive, we believe these results would be of interest to clinical and translational oncology audiences including: 1) ASCO GU Cancer Symposium, ASCO Annual Meeting or ESMO Congress and manuscripts top target would be Nature Medicine or Journal of Clinical Oncology with many lower potentials depending upon our results."
  ["project_bibliography"]=>
  string(2756) "

Chi KN, Chowdhury S, Bjartell A, et al. Apalutamide in Patients With Metastatic Castration-Sensitive Prostate Cancer: Final Survival Analysis of the Randomized, Double-Blind, Phase III TITAN Study. J Clin Oncol 2021;39:2294-303.
Smith MR, Saad F, Chowdhury S, et al. Apalutamide and Overall Survival in Prostate Cancer. Eur Urol 2021;79:150-8.
James ND, de Bono JS, Spears MR, et al. Abiraterone for Prostate Cancer Not Previously Treated with Hormone Therapy. N Engl J Med 2017;377:338-51.
Siegel R, Ward E, Brawley O, Jemal A. Cancer statistics, 2011. CA: A Cancer Journal for Clinicians 2011;61:212-36.
Siegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA Cancer J Clin 2024;74:12-49.
Droz JP, Albrand G, Gillessen S, et al. Management of Prostate Cancer in Elderly Patients: Recommendations of a Task Force of the International Society of Geriatric Oncology. Eur Urol 2017;72:521-31.
Clark R, Vesprini D, Narod SA. The Effect of Age on Prostate Cancer Survival. Cancers (Basel) 2022;14.
Leong DP, Fradet V, Shayegan B, et al. Cardiovascular Risk in Men with Prostate Cancer: Insights from the RADICAL PC Study. J Urol 2020;203:1109-16.
Hahn AW, Thoman W, Koutroumpakis E, et al. Cardiometabolic healthcare for men with prostate cancer: an MD Anderson Cancer Center experience. Cardiooncology 2023;9:33.
Morgans AK, Renzulli J, 2nd, Olivier K, Shore ND. Risk of Cognitive Effects in Comorbid Patients With Prostate Cancer Treated With Androgen Receptor Inhibitors. Clin Genitourin Cancer 2021;19:467.e1-.e11.
Swami U, Graf RP, Nussenzveig RH, et al. SPOP Mutations as a Predictive Biomarker for Androgen Receptor Axis-Targeted Therapy in De Novo Metastatic Castration-Sensitive Prostate Cancer. Clin Cancer Res 2022;28:4917-25.
Aparicio AM, Shen L, Tapia EL, et al. Combined Tumor Suppressor Defects Characterize Clinically Defined Aggressive Variant Prostate Cancers. Clin Cancer Res 2016;22:1520-30.
Hahn AW, Manyam GC, Chapin BF, et al. A phase II trial of apalutamide for intermediate-risk prostate cancer and molecular correlates. BJU Int 2024;134:449-58.
Alumkal JJ, Sun D, Lu E, et al. Transcriptional profiling identifies an androgen receptor activity-low, stemness program associated with enzalutamide resistance. Proc Natl Acad Sci U S A 2020;117:12315-23.
Hahn AW, Tidwell RS, Pilie PG, et al. Body composition as a determinant of the therapeutic index with androgen signaling inhibition. Prostate Cancer Prostatic Dis 2024.
Venkatesh N, Tidwell RS, Yu Y, et al. Body composition in recurrent prostate cancer and the role of steroidogenic genotype. Endocr Relat Cancer 2024;31.

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data partner
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}


pi country
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}


pi affil
array(0) {
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products
array(0) {
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num of trials
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res
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}