Bédard, Philippe L.

Abstract INTRODUCTION: Prostate cancer (PC) shows marked heterogeneity in clinical outcomes, from indolent to highly aggressive disease. Alterations in TP53, PTEN, RB1, and DNA damage repair genes are linked to poor patient outcomes, yet how the interaction and co-occurrence of these alterations impact prognosis remains unclear. We leveraged the AACR Project GENIE prostate cancer cohort to assess the prognostic impact of individual and concomitant gene alterations, focusing on key PC drivers (BRCA2, TP53, PTEN, RB1). METHODS: the study was conducted in two stages: (i) identification of candidate alterations at individual gene level through a systematic literature review, followed by analyzing the prevalence and co-occurrence of genes in the AACR Project GENIE Public Release (PR) dataset. (ii) Prognostic analysis of the pre-selected biomarkers in the AACR Project GENIE Biopharma Collaborative (BPC) cohort. Analyses were performed in three clinical settings (entire BPC cohort, n=1114; subgroup of patients with localized disease at diagnosis, n=837; and subgroup of patients with metastatic PC with a biopsy collected before or at the time of mPC, n=455) using two statistical approaches: univariate analysis (UA) and inverse probability weighting using propensity scores (PS). Cox models were applied to estimate overall survival hazard ratios (HRs). RESULTS: after integrating the findings from the systematic review with the analysis of the GENIE PR (n=5684), 107 individual genes and 122 co-occurring alterations were selected for study. In the GENIE BPC (n=1114 patients) 75% were M0 at diagnosis, and 67% presented metastatic PC at any time. Alteration prevalence was: TP53, 25%; PTEN, 15%; BRCA2, 4%; RB1, 4%; co-alterations included, PTEN-TP53 (6.4%), RB1-TP53 (2.1%), PTEN-RB1 (1.3%), and BRCA2-TP53 (1.2%). All four key genes showed a statistically significant prognostic impact in the entire cohort with UA (BRCA2, HR:1.9; TP53, HR:2.6; PTEN, HR:2.4; RB1, HR:4.1, all p<0.001). Results were consistent in the subgroup analysis and when using PS. Additional genes such as FANCA, PIK3CA, and MYC were also associated with poor outcomes. Among co-alterations, BRCA2-TP53 (HR:2.0, p=0.05), RB1-TP53 (HR:3.6, p<0.001), PTEN-TP53 (HR:2.4, p<0.001); PTEN-RB1 (HR:5.5, p<0.001), and PTEN-TP53-RB1 (HR:9.0, p<0.001) were the strongest predictors of poor survival, with consistent effects across subgroups and analytical methods. Other combinations including MYC-TP53 (HR 2.2, p<0.001) and PIK3CA-TP53 (HR 3.2, p<0.001), also showed independent prognostic value. CONCLUSIONS: Genomic alterations in TP53, PTEN, RB1, and BRCA2, alone and in combination, independently associate with poor prognosis. Co-alteration patterns such as PTEN-TP53-RB1 define aggressive molecular subsets. This evidence supports integrating genomic interaction patterns for enhancing clinical risk models and guiding precision patient management. Furthermore, this study highlights the potential of AACR Project GENIE to enable data-driven development of biomarker-informed patient care strategies. Citation Format: Pablo Cresta Morgado, Victor Navarro, Guillermo Vilacampa, Haitham Alatoom, Manuel Ramos del Rio, Irbaz Riaz, Shawn Sweeney, Nikolaus Schultz, Ken Kehl, Gregory Riely, Wasim Abida, Katherine Panageas, Deborah Schrag, Philippe Bedard, Christine Micheel, Xindi Guo, Chelsea Nayan, Rodrigo Dientsmann, Joaquin Mateo. Genomic prognostic biomarkers in prostate cancer from the AACR GENIE cohort [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr A013.

Importance Molecular analyses of biospecimens collected from study participants are essential for identifying biomarkers that can tailor treatments to specific subsets of patients who are most likely to benefit. Sharing of data and biospecimens from clinical trials enables personalized, patient-centric use of cancer therapies and accelerates the development of new treatments. Objective To describe obstacles to sharing data and biospecimens and to propose strategies to enhance access and collaboration. Evidence Review This is a Special Communication authored by 53 academic investigators and patient representatives from the breast cancer community with extensive experience in conducting clinical and translational research. The article also evaluates the impact of biomarker research on specifying responsive subpopulations in the 29 registrational clinical trials that have led to approval of a new drug for treatment of breast cancer between 2017 and 2024. Findings Clinical trial participants are increasingly asked to provide tissue and/or body fluid biospecimens for biomarker research that is typically controlled by the sponsoring pharmaceutical company, but published biomarker studies are rare. Among 29 breast cancer registrational studies reported in the past 8 years, none resulted in biomarker research that restricted a drug’s approved indication. Herein, strategies to maximize the value of clinical data and biospecimens contributed by participants are proposed, thereby supporting the shared goals of the pharmaceutical industry and academia to improve patient care. These strategies include (1) establishing coleadership structures involving academia and patients in clinical trial design and conduct, (2) ensuring that informed consent forms state that data and biospecimens will be shared with academia for future research, (3) requiring the sharing of clinical data as a condition for regulatory approval, and (4) enabling access to biospecimens and translational research data for independent studies on biomarkers that may indicate drug efficacy and toxicity. Conclusions and Relevance Data and biospecimen sharing from registrational trials has been suboptimal. Improving clinical data, biospecimens, and biospecimens’ related data sharing requires concrete actions and a multidimensional stakeholder approach to accelerate the impact of clinical cancer research on the quality of patient care.

Abstract Background Metformin has been associated with lower breast cancer (BC) risk and improved outcomes in observational studies. Multiple biologic mechanisms have been proposed, including a recent report of altered sex hormones. We evaluated the effect of metformin on sex hormones in MA.32, a phase III trial of nondiabetic BC subjects who were randomly assigned to metformin or placebo. Methods We studied the subgroup of postmenopausal hormone receptor-negative BC subjects not receiving endocrine treatment who provided fasting blood at baseline and at 6 months after being randomly assigned. Sex hormone-binding globulin, bioavailable testosterone, and estradiol levels were assayed using electrochemiluminescence immunoassay. Change from baseline to 6 months between study arms was compared using Wilcoxon sum rank tests and regression models. Results 312 women were eligible (141 metformin vs 171 placebo); the majority of subjects in each arm had T1/2, N0, HER2-negative BC and had received (neo)adjuvant chemotherapy. Mean age was 58.1 (SD=6.9) vs 57.5 (SD=7.9) years, mean body mass index (BMI) was 27.3 (SD=5.5) vs 28.9 (SD=6.4) kg/m2 for metformin vs placebo, respectively. Median estradiol decreased between baseline and 6 months on metformin vs placebo (−5.7 vs 0 pmol/L; P < .001) in univariable analysis and after controlling for baseline BMI and BMI change (P < .001). There was no change in sex hormone-binding globulin or bioavailable testosterone. Conclusion Metformin lowered estradiol levels, independent of BMI. This observation suggests a new metformin effect that has potential relevance to estrogen sensitive cancers.

Abstract Introduction: MutHER is a phase II trial that demonstrated the anti-tumor activity of the pan-HER inhibitor neratinib in HER2mut, non-amplified MBC. The major challenges to accrue to this trial were the large number of pts to screen for the 2-3% HER2mut population and the high rate (24%) of poor quality tumor DNA for sequencing. The goals of this ctDNA study were: 1) the concordance of HER2mut detected by ctDNA versus tumor testing; 2) the incidence of ctDNA HER2mut in HER2 non-amplified MBC; 3) changes in HER2mut variant allele frequency (VAF) on neratinib therapy. Methods: A sample size of 30 negative (neg) controls was needed to ensure 90% confidence if ctDNA testing has >90% specificity in detecting HER2mut. Thus, plasma from MBC pts obtained at screening for MutHER trial (Neg control: 40 pts without HER2mut on tumor testing; Positive (pos) control: 14 pts with known HER2mut who received neratinib) were subjected to Guardant360 ctDNA 70-gene panel sequencing (all exons of HER2 included). ctDNA from the 14 neratinib treated pts were also analyzed at week (wk) 4 and upon progression. ctDNA data from MBC pts clinically tested at Guardant Health were interrogated for HER2mut incidence. Results: Among the 14 pts with tumor pos for HER2mut, ctDNA sequencing identified the same HER2mut in 11, discrepant HER2mut in 1, and neg in 2. The 2 pts with ctDNA neg for HER2mut had progressive disease (PD) and stable disease (SD > 6 months) on neratinib, respectively. Among the 40 neg controls, 8 were not evaluable (no detectable ctDNA or assay unsuccessful) and all 32 successfully sequenced cases were neg for HER2mut. The sensitivity and specificity of ctDNA for HER2mut detection was 11/14 (79%, 90% CI: 53-94%) and 32/32 (100%, 90% CI: 91-100%), respectively. Among the 11 paired baseline and wk 4 samples, 9 (82%) had lower HER2mut VAFs at wk 4 than at baseline, with 1 complete response (CR), 1 partial response (PR), 5 SD, and 4 PD at wk 8 as best tumor response. Two pts had higher wk 4 ctDNA HER2mut VAFs and both had radiographic PD at wk 8. The absolute HER2mut VAF levels at wk 4 were significantly associated with TTP (Spearman rho=-0.69, p=0.02) and tumor size change (rho=0.67, p=0.05). The HER2mut VAFs were significantly higher at progression than wk 4 in all pts (p<0.01). One pt acquired a new HER2mut T798I, which is analogous to the gate-keeper mutation EGFR T790M. The incidence of HER2mut without amplification in unselected consecutive MBC clinically tested by Guardant360 was 3% (48/1,584), with mutation pattern similar to published tumor testing data. Conclusions: ctDNA sequencing is sensitive and highly specific in detecting HER2mut, offering a non-invasive method to identify pts for trials of HER2mut-targeted therapy. Decreased HER2mut VAFs at wk 4 was observed in 82% of cases, consistent with the on-target effect of neratinib. Increased HER2mut VAFs at wk 4 is a potential early marker of progression. Citation Format: Cynthia Ma, Ron Bose, Feng Gao, Rachel Freedman, Melinda Telli, Gretchen Kimmick, Eric Winer, Michael Naughton, Matthew Goetz, Christy Russell, Debu Tripathy, Melody Cobleigh, Andres Forero, Timothy Pluard, Carey Anders, Shana Thomas, Jill Anderson, Caroline Bumb, Kimberly Banks, Richard Lanman, Richard Bryce, Alshad Lalani, John Pfeifer, Daniel Hays, Mark Pegram, Kimberly Blackwell, Philippe Bedard, Hussam Al-Kateb, Matthew Ellis. Circulating tumor DNA (ctDNA) sequencing for HER2 mutation (HER2mut) screening and response monitoring to neratinib in metastatic breast cancer (MBC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr CT011. doi:10.1158/1538-7445.AM2017-CT011

Abstract Purpose: Based on promising preclinical data, we conducted a single-arm phase II trial to assess the clinical benefit rate (CBR) of neratinib, defined as complete/partial response (CR/PR) or stable disease (SD) ≥24 weeks, in HER2mut nonamplified metastatic breast cancer (MBC). Secondary endpoints included progression-free survival (PFS), toxicity, and circulating tumor DNA (ctDNA) HER2mut detection. Experimental Design: Tumor tissue positive for HER2mut was required for eligibility. Neratinib was administered 240 mg daily with prophylactic loperamide. ctDNA sequencing was performed retrospectively for 54 patients (14 positive and 40 negative for tumor HER2mut). Results: Nine of 381 tumors (2.4%) sequenced centrally harbored HER2mut (lobular 7.8% vs. ductal 1.6%; P = 0.026). Thirteen additional HER2mut cases were identified locally. Twenty-one of these 22 HER2mut cases were estrogen receptor positive. Sixteen patients [median age 58 (31–74) years and three (2–10) prior metastatic regimens] received neratinib. The CBR was 31% [90% confidence interval (CI), 13%–55%], including one CR, one PR, and three SD ≥24 weeks. Median PFS was 16 (90% CI, 8–31) weeks. Diarrhea (grade 2, 44%; grade 3, 25%) was the most common adverse event. Baseline ctDNA sequencing identified the same HER2mut in 11 of 14 tumor-positive cases (sensitivity, 79%; 90% CI, 53%–94%) and correctly assigned 32 of 32 informative negative cases (specificity, 100%; 90% CI, 91%–100%). In addition, ctDNA HER2mut variant allele frequency decreased in nine of 11 paired samples at week 4, followed by an increase upon progression. Conclusions: Neratinib is active in HER2mut, nonamplified MBC. ctDNA sequencing offers a noninvasive strategy to identify patients with HER2mut cancers for clinical trial participation. Clin Cancer Res; 23(19); 5687–95. ©2017 AACR.