Citations

The intestinal epithelium is exposed to diverse combinations of microbiota-derived compounds; however, the mechanisms by which the host integrates these signals remain poorly defined. Studying two highly abundant microbial metabolites, we identified the purine metabolite hypoxanthine as an effector metabolite that directly drives signaling and the short-chain fatty acid butyrate as a regulatory metabolite that conditions host responsiveness. Specifically, hypoxanthine activates the adenosine A1 receptor–TRPC4 axis in enterochromaffin (EC) cells, triggering calcium influx and serotonin release resulting in accelerated gastrointestinal transit locally and increased platelet activation systemically. In contrast, butyrate epigenetically upregulates specific G protein–coupled receptors and ion channels to enhance response to hypoxanthine and the neurotransmitters norepinephrine and dopamine. These findings define a cooperative signaling framework and highlight the role of EC cells as a distinct epithelial signaling hub that senses and integrates microbial metabolite signals to drive physiological responses. Our findings provide a mechanistic foundation for therapeutic strategies that leverage combinatorial microbial signaling.

Gut microbiota regulate the intestinal expression of drug-metabolizing enzymes, transporters, and barrier properties that determine oral drug absorption and disposition. This study compares germ-free Swiss Webster mice to mice colonized with fecal microbiota from a single human donor, evaluating microbiota-driven differences in colonic gene expression and P-gp protein expression, as well as small intestinal mucosal permeability. Transcriptomic analysis of colonic tissue revealed microbiota-induced upregulation of genes encoding P-gp and other drug transporters, including MCT1 and OCTN2. Immunofluorescence also indicated greater P-gp expression and apical localization in colonized mice. Gene expression of drug-metabolizing enzymes was also higher in colonized mice, including phase I enzymes (carboxylesterase 2 paralogs), phase II enzymes (UDP-glucuronosyltransferases and glutathione S-transferases), and enzymes responsible for synthesizing their co-substrates, UDP-glucuronic acid and glutathione. Small intestinal mucosal explants demonstrated lower permeability to 14C-labeled polyethylene glycol 4000 in colonized mice compared to germ-free mice. In the colon, transcriptomic analysis identified microbiota-dependent changes in genes regulating paracellular tight junctions and actomyosin contractility. These results show that human-derived gut microbiota alter gene expression in the mouse colon, identifying candidate microbiota-responsive genes relevant to oral drug absorption and disposition.

Background Tumor-infiltrating lymphocytes (TILs) are established determinants of clinical outcomes in breast cancer. 1–6 While stromal TILs (sTILs) are commonly evaluated due to easier scoring and higher interobserver reproducibility, intraepithelial TILs may provide additional insights into anti-tumor immunity. 7 We aimed to comprehensively characterize immunotype-associated cellular landscapes in triple-negative breast cancer (TNBC) and identify features associated with clinical outcomes. Methods 212 TNBC tumors were classified into three immunotypes based on immune infiltrate location and density: immune desert (ID), immune excluded (IE), and immune inflamed (IN). 8 Single-cell spatial transcriptomics was performed on 75 tumors to define the cellular composition and functional states of the tumor microenvironment across immunotypes. Findings were validated and integrated with bulk RNA sequencing data and clinical outcome datasets from FinXX, CALGB-40603, I-SPY 2, and Real-World Clinico-Genomic Data (RWCGD) cohorts. Results Patients with IN tumors had significantly improved outcomes compared with ID tumors. Despite high sTILs, IE tumors showed poor outcomes similar to ID tumors. Single-cell spatial analysis revealed that ID and IE tumors exhibited reduced major histocompatibility complex I/II expression and fewer tumor-resident plasmacytoid dendritic cells (pDCs) compared with IN tumors, which were enriched for interferon-alpha (IFNα) and interferon-gamma (IFNγ) responses. High IFN response scores were associated with favorable outcomes across multiple therapy types in independent datasets. Deconvolution of RWCGD bulk RNA-seq data confirmed that pDC abundance correlated with improved outcomes specifically in hormone receptor–negative subtypes. Conclusions Our study highlights pDCs and IFN signaling as hallmarks of effective anti-tumor immunity in TNBC. Immunotype-based profiling underscores the limited prognostic value of sTILs alone in immune-excluded tumors and supports pDCs and IFN pathways as potential biomarkers for prognosis and therapeutic development in TNBC.

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.

Abstract Significance: Emergence of resistance to endocrine therapies represents a major challenge in theclinical management of estrogen receptor positive (ER+) breast tumors. CDK4/6 inhibitors(palbociclib, ribociclib, abemaciclib) have improved survival when combined with endocrine therapy. Nonetheless, resistance to CDK4/6 inhibitors eventually occurs. One of the emerging mechanisms ofresistance toward endocrine therapy and CDK4/6 inhibitors is characterized by the enrichment ofbreast cancer stem cells (CSCs) that show stem-like features such as self-renewal capacity, highCD44 expression and ALDH activity. We have demonstrated that Aurora-A kinase (AURKA) has apivotal role in promoting cancer cellular plasticity and clonal expansion of endocrine resistantCD44high/ALDHhigh CSCs. Our preclinical studies on AURKA-driven tumor stemness provided thetherapeutic foundation for a Phase-II clinical trial (TBCRC041) of the AURKA inhibitor, alisertib, whichdemonstrated clinically meaningful activity in patients with endocrine and CDK4/6 inhibitors resistantER+ metastatic breast cancer (MBC). Despite such activity, alisertib resistance finally occurred. Therefore, we hypothesize that up-regulation of IL6R/STAT3 and PR stemness oncogenic pathwaysmay sustain the clonal expansion of CD44high/ALDHhigh CSCs after tumor progression on AURKAinhibitors. Experimental Design: We used variant MCF-7 breast cancer models that show resistance toendocrine therapy (letrozole and fulvestrant) and alisertib (MCF-7 LR/FR, MCF-7 LR/FR-AlisR) todefine in vitro and in vivo the efficacy of stemness-targeted therapies to enhance alisertib activity byimpairing the enrichment of hormone refractory CD44High/ALDHHigh CSCs. Parental MCF-7 cells wereused as control. We employed exclusive PDX-derived 3D-Mammospheres (MPS) that wereestablished from the Phase-II clinical trial TBCRC041 to test the efficacy of stemness-targetedtherapies in enhancing the therapeutic activity of alisertib. In Vitro Studies: Immunofluorescence andimmunoblot assays were used to assess the expression of breast cancer stemness biomarkers. Enrichment of ALDHHigh CSCs was measured using Red-Aldefluor kit. Cell proliferation and Red-Annexin-VHigh apoptotic cells were quantified in real-time using IncuCyte S3. In Vivo Studies: 1x106breast cancer cells were injected into the mammary fat pad of NSG-female mice and treated withfulvestrant, alisertib and tocilizumab as monotherapy or in combination. Control groups were treatedwith saline solution placebo. Drug Treatments: Tocilizumab and Onapristone were used to inhibit theIL6R/STAT3 and PR stemness pathways, respectively. Results: Our study demonstrates for the first time that nuclear STAT3/PR complex mediatesAURKA-induced expression of KLF4 stemness gene and enrichment of endocrine resistantCD44high/ALDHhigh CSCs. Alisertib resistant MCF-7 LR/FR cells showed increased expression ofIL6R, T288-AURKA, S727-STAT3 and S294-PR compared to alisertib naïve cells. MCF-7 LR/FR-AlisR-derived 3D-MPS had increased KLF4 and CD44 expression. Alisertib resistant PDX modelsalso showed high levels of CD44, IL6R/STAT3 and KLF4 expression. Remarkable, pharmacologicalblockade of PR and STAT3 transcriptional regulatory networks enhanced the efficacy of alisertib byreducing the enrichment of CD44High/ALDHHigh CSCs. Conclusions: These findings provide the strong preclinical rationale for the development of novelcombinatorial therapeutic strategies targeting IL6R/STAT3 and PR stemness pathways to enhancethe efficacy of AURKA inhibitors that will result in the selective eradication of CD44High/ALDHHighCSCs with consequent benefits on the overall survival of patients with advanced ER+ breast tumorsrefractory to endocrine therapies and CDK4/6 inhibitors.輀 Citation Format: A. B. D'ASSORO, M. Drago, T. Haddad, M. GOETZ, K. Giridhar, K. Kalari, L. Manzella, P. Vigneri, F. Drago, C. Vancheri, C. Lange, J. Ingle. Stemness-targeted therapies to enhance the efficacy of AURKA inhibitors in endocrine resistant er+ breast cancer [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 PS2-11-08.

Abstract Background: Tumor-infiltrating lymphocytes (TILs) in HER2+ and triple-negative breast cancer (BC) are prognostic and associated with therapy response; however, there are few data regarding distribution and significance of TIL values in ER+ HER2-negative (HER2-) MBC patients (pts) treated with CDK4/6 inhibitors (CDK4/6i). CDK4/6 inhibition may promote antitumor immunity by production of type III interferons and tumor antigen presentation, and by inhibition of regulatory T cells (Goel, Nature 2017). Further, the addition of immune checkpoint therapy to palbociclib numerically prolonged PFS in the 2nd line (2L) setting (Mayer, JCO 2024). We aimed to investigate the prognostic role of TILs derived from fresh metastatic tumor biopsies in pts with ER+HER2- MBC prior to starting CDK4/6i and endocrine therapy (ET) in the first line (1L) and 2L setting. Methods: PROMISE (NCT0281902) is a multicenter, prospective study that enrolled women commencing the CDK4/6i palbociclib (Pb) with letrozole (1L) or fulvestrant (2L) for HR+HER2- MBC. The primary goal was to identify novel genomic variants and pathways associated with PFS. Here, we performed a secondary analysis to quantitate stromal TILs using protocol mandated pretreatment tumor biopsies and determine their association with PFS. Using the Kaplan-Meier method, we reported median PFS (mPFS) and 3-year PFS percentage (%) (95% confidence intervals [CIs]) by TILs [≥20% vs <20%] separately within 1L and 2L. As sample TIL values were generally concentrated at zero (27/58 = 46.6%), coupled with wide spread of sample TIL values ≥20% [range: 20%- 80%], we applied a ≥20% threshold for PFS analysis (high vs low TIL group) as described by Luen, Salgado et al. Lancet Oncol 2017. Statistical significance was based on the Wilcoxon test of the null hypothesis that there was no difference in the PFS curves by TILs. PFS is reported at median follow-up of 21 months. Results: Pretreatment tumor biopsies from 58/68 (85.3 %) pts were evaluable (42 in 1L and 16 in 2L). Median [Q1, Q2] TIL values were higher in 1L (5% [0, 10]) vs 2L (0% [0, 15]). The most common biopsy sites were bone (44.8%), lymph node (17.2%), liver (17.2%) and breast (12%). Overall, TILs frequency (>20%) by the 4 most common biopsy sites were bone (2/20, 10%), lymph node (4/7, 57%), liver (2/6, 33%), and breast (1/7, 14%). In 1L, although PFS was not significantly different (P = 0.237), mPFS (44 vs 34 months) and 3-year PFS 75.0%, [95% CI: 50.3%, 100%] vs 46.4% [95% CI: 31.0%, 69.5%]) were longer in pts with high versus low TILS, respectively. In 2L, the 3-year PFS was numerically similar comparing high and low TILs groups, (25.0%, [95% CI: 4.6%, 100%] vs 22.5% [95% CI: 6.7%, 76.1%]) with no significant difference in PFS (P = 0.761). Conclusions: In pts with ER+HER2- MBC treated with Pb and ET, PFS was numerically longer comparing high vs low TIL values in 1L but not 2L settings. Future studies evaluating TILs in larger datasets are needed to validate these findings. Genomic analysis (DNA/RNA) and its association with TIL levels is underway and will be presented at the meeting. Funding: The Center for Individualized Medicine, Mayo Clinic; Mayo Clinic Breast Specialized Program of Research Excellence (SPORE P50CA116201); Mayo Clinic Cancer Center (CA15083-40A2); TEMPUS (https://www.tempus.com/) and Conquer Cancer Foundation of ASCO (Career Development Award 2018, Dr. O’Sullivan) Citation Format: C. C. O'Sullivan, A. M. Moyer, A. Nassar, D. M. Zahrieh, V. Suman, X. Tang, K. J. Thompson, R. C. Hentz, J. J. Harrington, A. Moreno-Aspitia, D. W. Northfelt, T. C. Haddad, S. Chumsri, P. P. Peethambaram, K. J. Ruddy, K. V. Giridhar, R. A. Leon-Ferre, R. Weinshilboum, L. Wang, K. R. Kalari, M. P. Goetz. Tumor-infiltrating lymphocytes in advanced ER-positive, HER2-negative breast cancer prior to treatment with palbociclib and endocrine therapy: a retrospective analysis of the PROMISE study [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 PS1-10-22.

Integrating artificial intelligence (AI) with healthcare data is rapidly transforming medical diagnostics and driving progress toward precision medicine. However, effectively leveraging multimodal data, particularly digital pathology whole slide images (WSIs) and genomic sequencing, remains a significant challenge due to the intrinsic heterogeneity of these modalities and the need for scalable and interpretable frameworks. Existing diagnostic models typically operate on unimodal data, overlooking critical cross-modal interactions that can yield richer clinical insights. We introduce MarbliX (Multimodal Association and Retrieval with Binary Latent Indexed matriX), a self-supervised framework that learns to embed WSIs and immunogenomic profiles into compact, scalable binary codes, termed “monogram.” By optimizing a triplet contrastive objective across modalities, MarbliX captures high-resolution patient similarity in a unified latent space, enabling efficient retrieval of clinically relevant cases and facilitating case-based reasoning. In lung cancer, MarbliX achieves 85%–89% across all evaluation metrics, outperforming histopathology (69%–71%) and immunogenomics (73%–76%). In kidney cancer, real-valued monograms yield the strongest performance (F1: 80%–83%, Accuracy: 87%–90%), with binary monograms slightly lower (F1: 78%–82%).

Abstract Background Brain insulin resistance and cerebrovascular dysfunction emerge early in late-onset Alzheimer’s disease, but how amyloid-β (Aβ) disrupts insulin signaling at the cerebrovascular blood–brain barrier—a major site of insulin receptor signaling and transport into the brain—remains unclear. Methods We exposed two distinct human blood-brain-barrier endothelial cell models to soluble Aβ40 or Aβ42 for 1 h, followed by 100 nM insulin for 10 min. Protein and phosphoprotein responses were quantified by reverse-phase protein array, and differential expression was evaluated using linear models. Results Aβ40 reduced insulin-stimulated Akt activation and converted insulin’s normal inhibition of AMPK into modest stimulation. Aβ42 did not alter insulin-stimulated Akt signaling but moderately suppressed basal Akt activation. Conclusions These findings suggest that Aβ40 acutely impairs insulin signal transduction in BBB endothelial cells, supporting a model in which vascular Aβ exposure contributes directly to the early development of brain insulin resistance in AD.

Abstract Cutaneous squamous cell carcinoma (cSCC) poses significant clinical challenges due to its rising incidence and potential for metastasis. Histopathologic risk stratification is further limited by substantial inter-observer variability. Unsupervised AI approaches based on content-based image retrieval offer scalable and interpretable decision support for diagnostic pathology. The objective of this study was to evaluate the use of image retrieval within histopathology atlases to stratify cSCC tumor differentiation from whole-slide images (WSIs), while comparing different patch selection and feature extraction strategies. This retrospective study included 552 archived WSIs comprising 385 well-differentiated, 102 moderately differentiated, and 66 poorly differentiated cases collected across Mayo Clinic sites in Arizona, Florida, and Minnesota. Image atlases were constructed using multiple patch aggregation strategies (Mosaic, Collage, and Montage) and deep learning encoders (KimiaNet, PathDino, and H-Optimus-0). A leave-one-WSI-out evaluation framework was used to assess differentiation classification performance using accuracy, specificity, sensitivity, and F1 score. Mosaic combined with KimiaNet achieved the highest Top-1 accuracy (74.9%) and specificity (92.6%), while Mosaic with H-Optimus-0 yielded the best Top-5 accuracy (79.0%) and macro-F1 score (62.6%). Collage combined with KimiaNet produced the highest Top-5 specificity (99.5%). The generalizability of the evaluated AI models varied across hospitals, reflecting differences in imaging protocols, staining practices, and patient populations. Overall, unsupervised image search and retrieval provides effective, annotation-free support for cSCC differentiation and has the potential to enhance dermatopathology workflows when appropriate combinations of patch selection and feature ex-traction methods are employed.