Kalari, K. R.

Abstract Background: The increasing volume and diversity of clinical genomic reports pose a significant challenge across healthcare institutions for the interpretation and proper implementation of precision oncology research. Reports from multiple different vendors (e.g., Invitae, Ambry Genetics, Foundation Medicine) are typically PDFs and exhibit substantial heterogeneity in panel design, gene coverage, and reporting standards, which hinders efficient retrospective data mining and patient cohort identification within the electronic medical records. We sought to develop a framework to interrogate all of these reports. Methods: We extracted genomic reports from patients with breast cancer treated with neoadjuvant chemotherapy and developed MolHarmonizer, a novel, scalable framework leveraging Python and Gemini LLMs, designed to process and harmonize genomic data from disparate multi-vendor reports. Gemini LLMs are employed explicitly for robust information extraction, normalization, and structuring of key genomic features, transforming unstructured data into a unified, queryable dataset. Results: Our MolHarmonizer framework successfully processed 1,147 genomic reports from 1703 breast cancer patients (2006-2023) from 23 different companies, demonstrating robust capability to extract and standardize critical actionable biomarkers. Data sources included Invitae (n=554), Ambry Genetics (n=189), Natera (n=95), Mayo Clinic (n=88), Tempus (n=63), Guardant Health (n=47), and Foundation Medicine (n=37), with others contributing less than 20 reports. Of the samples, 827/1147 (72.1%) were germline (blood/saliva). A majority of the patients were tested using the panels due to a personal/family history (n=925). Overall, 413/1147 (36.0%) reports identified at least one mutation. For breast cancer, 75 reports showed BRCA1/2 mutations (37 BRCA1, 37 BRCA2, and one patient with both BRCA1 and 2). Other mutations identified included: PIK3CA (n=40), TP53 (n=96), PTEN (n=21), ESR1 (n=13) and AKT1/2 (n=8). Conclusion: MolHarmonizer, a powerful framework leveraging Gemini LLMs, effectively addresses genomic data heterogeneity by automating biomarker extraction and harmonization. This enables rapid cohort identification and deep retrospective analyses for clinical insights, biomarker discovery, understanding disease history, facilitating novel pattern discovery, e.g., predicting BRCA1 mutations from WSI, and accelerating research within our neoadjuvant BC cohort. Future plans include expanding to include over 20,000 breast cancer patients, developing a user-friendly chatbot, and ensuring inter-institutional adaptability for a variety of complex diseases. Citation Format: Krishna Rani Kalari, Xiaojia Tang, Thanmayee Boyapati, Tanya L. Hoskin, Sumathilatha Myla, Sumedha G. Penheiter, Richard M. Weinshilboum, Liewei Wang, Hamid R. Tizhoosh, Karthik Vikram Giridhar, Matthew P. Goetz, Judy C. Boughey. Development of an LLM framework for analysis of heterogeneous breast cancer patients genomic reports [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2756.

Abstract Background: DNA methyltransferase (DNMT) isoforms 1, 3A and 3B are enzymes that regulate DNA methylation, controlling gene expression, chromatin stability and genetic imprinting. We have previously shown that DNMT3A protein expression in early triple negative breast cancer (TNBC) is associated with more aggressive clinicopathologic features (higher tumor grade, tumor proliferation and frequency of nodal metastases) and worse clinical outcomes in the absence of chemotherapy (Leon-Ferre et al, SABCS 2024). Pre-clinically, we have shown that DNMT3A protein expression predicts sensitivity to DNMT inhibitors (Yu J et al., J Clin Invest 2018), and that DNMT inhibitor treatment leads to downregulation of DNMT3A, enhanced expression of immune-related pathways, and halted tumor growth, particularly in combination with immunotherapy and paclitaxel. Methods: This is a phase 1, open-label, multicenter study evaluating the safety and recommended phase 2 dose (RP2D) of the oral DNMT inhibitor ASTX727 + paclitaxel + pembrolizumab in metastatic TNBC. ASTX727 is an oral fixed dose combination (FDC) tablet of 35 mg decitabine (active agent) and 100 mg cedazuridine (a cytidine deaminase inhibitor that prevents decitabine degradation in the bowel and liver, allowing oral delivery). The study consists of two parts: Part 1 is a dose-finding cohort, using a 3+3 design, with 5 dose levels (Table), and its primary objective is to determine the RP2D. Part 2 is an expansion cohort (n=6), with the primary objective to confirm tolerability of the regimen at the RP2D. Secondary objectives are to record the antitumor activity of the regimen, describe the AE profile, explore the association of baseline gene expression profiles with clinical benefit, and to evaluate impact of treatment on tumor and ctDNA methylation. Exploratory objectives will evaluate the association of baseline DNMT3A protein expression and antitumor activity, and the impact of treatment on the tumor and peripheral blood immune phenotype. Eligible patients are adults 18 years or older with metastatic TNBC (ER/PR ≤10%, and HER2-negative per ASCO/CAP guidelines), independent of PD-L1 expression. Patients are allowed to have received 0-3 prior lines of systemic therapy in the metastatic setting, including prior immune checkpoint inhibitors in the early and/or metastatic settings. Patients must be eligible for taxanes and have adequate organ and bone marrow function. Patients with treated brain metastases are eligible if previously treated without evidence of progression after 4 weeks. Leptomeningeal carcinomatosis is not allowed. Patients must have an ECOG performance status of ≤2 and have no gastrointestinal disorders impacting absorption of oral medications. As of June 20, 2025, the study is enrolling patients, with 10 patients dosed in the dose-finding phase. Citation Format: R. Leon-Ferre, D. M. Zahrieh, P. P. Advani, D. Quiroga, K. V. Giridhar, P. J. Dizona, D. Stover, X. Wang, A. J. Tevaarwerk, G. M. Choong, S. Yasir, K. R. Kalari, J. Foldi, R. Parajuli, M. H. Hackney, H. K. Chew, R. Wajeeha, H. Bear, E. Sharon, B. Ko, G. I. Shapiro, S. Gore, L. Pelosof, L. Wang, M. P. Goetz. Trial in progress: Phase 1 Study Targeting DNA Methyltransferases in Metastatic Triple-Negative Breast Cancer (NCI Protocol #10546) [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS5-07-20.