Citations

Abstract Background: Endometrial cancer (EC) remains a major gynecologic malignancy driven in part by aberrant estrogen receptor (ER) signaling. The active tamoxifen metabolite (Z)-endoxifen exhibits dual SERM/SERD-like activity, modulating ER function while exerting additional noncanonical antiproliferative effects. Understanding (Z)-endoxifen’s mechanisms of action and its interaction with cell-cycle regulators is critical to optimizing targeted therapy in EC. This study investigated the molecular and functional effects of (Z)-endoxifen, alone and in combination with the CDK4/6 inhibitor abemaciclib, across diverse EC models to define mechanistic activity and translational potential. Methods: ER+ (Ishikawa, HCI-EC23, patient derived organoid U1561.005) and ER-variable (ARK1, ARK2) EC models were treated with estrogen (0-10 nM), (Z)-endoxifen (125 nM-10 µM) or fulvestrant (0-2.5 μM), and abemaciclib (0-10 μM), as single agents or in combination. Cell viability was assessed using luminescence-based assays. Dose-response analyses and combinatorial synergy were evaluated to determine endocrine sensitivity, ER dependency, and downstream cell-cycle effects. Results: Estrogen induced biphasic proliferative responses in ER+ models, confirming ligand-driven mitogenic signaling. (Z)-Endoxifen monotherapy suppressed viability across all cell lines, demonstrating superior potency to fulvestrant and activity independent of ER expression status. Mechanistically, (Z)-endoxifen abrogated estrogen-induced proliferative peaks, consistent with ER antagonism and potential receptor degradation, while also exerting ER-independent effects suggestive of cell-cycle modulation. Abemaciclib monotherapy inhibited viability in both ER+ and ER− models, and its combination with (Z)-endoxifen yielded strong synergistic activity (Chou-Talalay combination index < 1), including in ER-negative ARK2 and the ER+ U1561.005 organoid. This synergy likely arises from concurrent disruption of ER signaling and CDK4/6-cyclin D regulatory pathways. Conclusions: (Z)-Endoxifen demonstrates dual ER-dependent and ER-independent activity in EC preclinical models. Synergy was observed in combination a CDK 4/6 inhibitor. These findings broaden the current understanding of (Z)-endoxifen’s efficacy and support further exploration of its potential therapeutic role in ER-driven and mixed-phenotype EC, including evaluation of responses across ER expression levels. Citation Format: Grace Choong, Xiaonan Hou, Sandra Suarez Hammer, Scott M. Blackburn, John Weroha, Steven C. Quay. (Z)-endoxifen modulates estrogen receptor and cell-cycle signaling to induce synergistic antiproliferative effects with CDK4/6 inhibition in endometrial cancer models [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 405.

Abstract Background: Digital Drug Assignment (DDA) is a computational reasoning model that scores cancer therapies based on the complete molecular profile of a tumor, and stratifies them by predicted efficacy (Petak et al., 2021). In a prior study of 111 lung cancer patients, DDA-derived high-score molecularly targeted agents (MTAs) were associated with improved clinical outcomes (Dirner et al., 2025). Here, we extend this analysis to the GENIE BPC NSCLC cohort to assess the broader clinical validity of DDA. Methods: From the GENIE BPC NSCLC cohort data available on Synapse, we included 1,078 patients with a single-sample genomic profile, available primary treatment data and survival outcomes (total 2,103 treatment lines, therapies included: afatinib, erlotinib, osimertinib, crizotinib, nivolumab, pembrolizumab, atezolizumab, bevacizumab+chemo, ramucirumab+chemo; and chemotherapy alone). DDA scores were generated for all cases, and the individual score of the administered MTAs (incl. immune checkpoint inhibitors) was used to stratify outcomes into low (<0), intermediate, and high DDA-score (≥1000) tiers. Progression-free survival (PFS, by imaging) and overall survival (OS) were analyzed using Kaplan-Meier statistics. Results: Median PFS and OS differed significantly across DDA score tiers, increasing with higher scores (see table). Intermediate-tier drugs had similar mPFS values as chemotherapies (3.9 vs 4.2 months). Six-month PFS and twelve-month OS rates increased with DDA-tiers and were all significantly different by χ2 test. DDA-high therapies provided greater benefit across treatment types than lower-score counterparts. Conclusions: Across a large, real-world NSCLC cohort, DDA effectively distinguished therapies with higher clinical efficacy based on the full molecular profile of each patient. These results reinforce the potential of DDA to enhance personalized treatment selection based on NGS diagnostics in precision oncology. Citation Format: Barbara Vodicska, Eniko Kispeter, Dora Lakatos, Gabor Gy Kalmar, Robert Doczi, Dora Gorog-Tihanyi, Anna Dirner, Reka Szalkai-Denes, William T. Beck, Arkadiusz Z. Dudek, Christophe Le Tourneau, Istvan Petak. Molecularly-informed prediction of treatment efficacy in the GENIE BPC NSCLC cohort using computational reasoning [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 7.

Abstract Lung cancer remains the leading cause of cancer-related deaths worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. Despite advances in targeted and immuno-therapies, overall survival for NSCLC remains below 25%, due to late-stage detection and therapeutic resistance. Cancer stem cells (CSCs), a highly tumorigenic subpopulation within NSCLC, drive relapse, metastasis, and treatment failure. Understanding the mechanisms by which CSCs promote the aggressiveness of NSCLC may reveal new diagnostic and therapeutic opportunities. CSCs establish an intercellular communication network through the secretion of extracellular vesicles (EVs), membrane-bound nanoparticles that transport proteins, lipids, and nucleic acids that can influence recipient cell behavior. Our previous work demonstrated that CSCs secrete significantly more EVs compared to bulk cancer cells (BCCs) and induce an enhanced tumorigenic phenotype in BCCs. However, the EV protein cargo that mediates these CSC-driven phenotypes and the signaling they promote remain poorly understood. This study aimed to identify and characterize CSC-derived EV protein cargo that contributes to NSCLC growth and metastasis. CSC- and BCC-derived EVs were isolated using tangential flow filtration and characterized according to MISEV guidelines. Mass spectrometry and pathway analysis were performed to compare the proteome of CSC- and BCC-derived EVs, followed by functional characterization in vitro and in vivo. Our results showed that EVs exhibited expected morphological, biochemical, and physical properties. Pathway analyses showed that CSC-derived EVs were enriched in proteins that localize to exosomes and associate with metabolism and cell adhesion. Comparison of BCC and CSC-derived EVs revealed Desmoglein-2 (DSG2) as one of the proteins exclusively detected in CSC-derived EVs. shRNA-mediated knockdown of DSG2 significantly reduced invasion, clonal expansion, and transformed growth in vitro and decreased tumor growth and metastasis in vivo. Furthermore, DSG2-competent EVs partially rescued the effects of DSG2 knockdown on CSC tumor growth in vivo. Together, these findings identify DSG2 as a key CSC-specific EV protein cargo that promotes an enhanced tumorigenic phenotype and NSCLC tumor growth. This work highlights the role of CSC-derived EV proteins as mediators of NSCLC aggressiveness and as candidates for biomarker and therapeutic development. Citation Format: Prita Pandya, Aamena Ahmed, Nayya Murray, Dania S. Al-Qasrawi, Anaya Y. Clarke, Reagan Carris, Verline Justilien. Desmoglein-2 carrying cancer stem cell-derived extracellular vesicles promote lung cancer aggressiveness [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 833.

Abstract Therapeutic resistance to chemotherapy is frequently the proximate cause of increased tumor burden, cancer treatment failure, and ultimately, patient mortality. The most successful therapy strategy derived from evolutionary practices to date, Adaptive Therapy (AT), leverages the fitness cost of developing therapeutic resistance. AT avoids treating cancer cells with the Maximum Tolerated Dose (MTD) of therapeutic drugs and instead incorporates a series of adaptive dosing schedules. Treatment-sensitive cells are bolstered by modulating or pausing treatment to out-compete and suppress treatment-resistant cell growth. We are evaluating AT for the first time in colorectal cancer, using a syngeneic orthotopic xenograft model. This work represents several key advances: it is the first to longitudinally and non-invasively track sensitive and resistant clones in vivo, to evaluate adaptive therapy in an immunocompetent mouse model, to incorporate multi-drug treatment regimens, and to integrate a targeted therapeutic agent. The dual-bioluminescent sensitive and resistant CT26 cell lines developed for this study allow real-time visualization and quantification of each population throughout tumor progression and treatment. Together, these advances establish a robust and clinically relevant platform for characterizing resistance dynamics and refining adaptive therapy strategies aimed at improving treatment outcomes in colorectal cancer. Citation Format: Harley I. Richker, Bailey Sierra Kane, Gissel Marquez Alcaraz, Ellie Pahl, Ryan Carr, Nagarajan Kannan, Carlo C. Maley. Harnessing clonal dynamics to overcome resistance: An adaptive therapy framework in colorectal cancer [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 702.

Abstract Introduction: Ewing sarcoma (EwS) is a FET::ETS family member-driven primary bone cancer demonstrating vast heterogeneity. Between a patient’s primary diagnosis and disease progression, tumor cell state adaptation, microenvironment changes, and the landscape of evolving therapeutic vulnerabilities remain poorly understood. To address these gaps, the Sean Karl Cohort was established in 2025 to conduct the largest single-cell transcriptomic analysis of retrospective paired tumor samples from patients with EwS. Here, we present data from the five analytic teams, and through shared SOPs now expand this cohort to Europe. Methods: Common sample processing SOPs were established to isolate cells from FFPE material from paired patient EwS samples. Single-cell (sc) RNAseq was generated using the GEM-X Flex Gene Expression protocol (10x Genomics). Alex’s Lemonade Stand Foundation (ALSF) Data Lab established a common data processing and integration pipeline with an EwS-specific cell annotation workflow to create a harmonized dataset for downstream analyses. Analytic teams were created to define tumor cell subpopulations and their therapeutic vulnerabilities and to characterize the tumor microenvironment. Data: We demonstrate the feasibility of generating high-quality scRNAseq profiles from retrospective FFPE-preserved EwS tumors. To date, 116 samples have yielded ∼800,000 cells. Integrated analysis reveals reproducible EwS tumor cell states shared across patients with regulatory network analyses nominating candidate therapeutic vulnerabilities. The scale of this international cohort enables saturation analysis for rare cell populations. Paired and longitudinal samples further allow correlation of emergent cell states with therapy resistance and metastatic progression. For example, immune-focused analyses show increases in T cell and macrophage populations in post-therapy samples. A novel, standardized EwS-specific cell annotation workflow has been developed to harmonize analyses and findings. These data will be openly shared with the community through the ALSF Single-cell Pediatric Cancer Atlas Portal. Conclusion: Large-scale international collaborative sample sharing, standardized processing pipelines, and harmonized EwS-specific annotations now enable deep single-cell analyses to characterize tumor heterogeneity in this rare pediatric and adolescent cancer. An in vivo expansion of the Sean Karl Cohort is underway to assess conservation of EwS tumor cell states and regulatory vulnerabilities identified in human tumors pre- and post-therapy in preclinical models, further supporting translation of these findings toward therapeutic strategies. Citation Format: Abbe Pannucci, Elina Mukherjee, Jessica D. Daley, Shireen Sita Ganapathi, Elissa Boguslawski, Lea Surrey, Lauren Gutstein, Patrick Azar, Emily Stockfisch, Azfar Neyaz, Ivy John, Jennifer Picarsic, Yutaro Tanaka, Byron Butaney, Riaz Gillani, Brian D. Crompton, Katherine A. Janeway, Jaclyln Taroni, Jessica Davis, Damon Reed, Adam Shlien, Theodore W. Laetsch, Rajen Mody, Clémence Henon, Thomas G. Grünewald, Elizabeth R. Lawlor, Filemon Dela Cruz, Patrick J. Grohar, Jovana Pavisic, Ally Hawkins, Anthony R. Cillo, Kelly M. Bailey. The Sean Karl Cohort: An international single-cell RNAseq study of paired patient Ewing sarcoma specimens [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 643.

Abstract Breast cancer is the most common female malignancy in the U.S. and the leading cause of cancer-related deaths in women worldwide. Nearly 80% of breast tumors express estrogen receptor alpha (ERα) which drives tumor progression. While endocrine therapies and CDK4/6 inhibitors have increased overall survival, many patients experience recurrence of metastatic disease that is largely refractory to additional lines of endocrine therapy. Metastatic disease remains incurable, highlighting the need for alternative treatment approaches. Through a genome-wide CRISPR knockout screen, we identified Lemur Tail Kinase 2 (LMTK2) as the top hit exhibiting synthetic lethality in the presence of the endocrine therapy, endoxifen, in both endocrine-sensitive and -resistant cell line models. Using publicly available patient tumor databases we identified LMTK2 copy number gain/amplification in 67% of ERα+ human metastatic breast tumors, while only 1% of primary tumors harbored these genomic alterations. Elevated LMTK2 expression in early-stage primary breast tumors was associated with worse recurrence-free survival and overall survival. We discovered that LMTK2 mRNA and protein levels were substantially elevated in nearly all cell-line and patient-derived models of endocrine and CDK4/6i resistance. Utilizing siRNAs and dox-inducible shRNA expressing cell lines, we found that knockdown of LMTK2 enhanced the efficacy of multiple endocrine therapies in treatment naïve models and resensitized resistant models to their respective treatment. LMTK2 overexpression was found to be sufficient for conferring resistance to all standard of care therapies tested including endocrine agents, CDK4/6i, and PI3K inhibitors. RNAseq and global proteomics of LMTK2 overexpressing and knockout models revealed the PI3K/AKT pathway and estrogen signaling as highly regulated pathways by LMTK2. Confirmatory western blot studies demonstrated that LMTK2 overexpression results in dramatic increases in AKT and ERα phosphorylation and activity, while knockout of LMTK2 diminishes these effects. Attempts to completely ablate LMTK2 in endocrine/CDK4/6i-resistant models via CRISPR were not successful, and continuous siRNA or shRNA-mediated knockdown was lethal in resistant cell lines, confirming its essentiality in this setting. In summary we have uncovered LMTK2 as a novel mediator of endocrine/CDK4/6i resistance that is mechanistically linked to the PI3K/AKT pathway among others. Genetic manipulation of LMTK2 has validated it as an ideal therapeutic target for both advanced and newly diagnosed forms of ERα+ breast cancer. Citation Format: Anna Detry, Sofia Marigliano, Jenna Heinen, Adam Bass, Calley Jones, Rajeev Muthyala, Matthew Goetz, John Hawse. LMTK2: A novel driver of endocrine resistance in ERα+ breast cancer [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 443.

Abstract Background: Small cell lung cancer (SCLC) remains an aggressive malignancy with limited treatment options and a 5-year survival rate under 10%. Delta-like ligand 3 (DLL3), expressed in >85% of SCLC but absent from normal tissue, represents an attractive therapeutic target. Existing DLL3-directed antibody-drug conjugates suffer from poor payload stability and limited tumor penetration. To overcome these limitations, we engineered a DLL3-targeted nano-immunoconjugate (NIC) of SN38, the active metabolite of irinotecan, using an albumin-based nanoscaffold. Methods: SN38 was encapsulated in a human serum albumin (HSA) matrix and non-covalently coated with a recombinant anti-DLL3 monoclonal antibody to yield DLL3-SN38-NIC. Stable conjugation was confirmed by HSA-IgG interactions and zeta-potential shift. Binding kinetics were evaluated using Biacore surface plasmon resonance (SPR) and Octet bio-layer interferometry (BLI) employing AHC biosensors to determine DLL3-antibody affinity and specificity. Cytotoxicity was assessed using IncuCyte live-cell imaging across five SCLC cell lines (DMS454, SHP77, NCI-H82, NCI-H889, and NCI-H211) with varying DLL3 expression. Results: DLL3-SN38-NIC retained high-affinity DLL3 binding (KD ≈ 3 × 10-10 M) and demonstrated potent cytotoxicity in SCLC cell lines. NIC formation did not reduce cytotoxic activity compared with free SN38, confirming preserved potency. Cytotoxicity trends were consistent across lines with variable DLL3 expression, and DLL3 antibody alone exhibited negligible cytotoxicity. These findings confirm that nano-immunoconjugate formation maintains drug activity and DLL3 binding; additional in-vivo studies are underway to evaluate pharmacokinetics and tumor selectivity. Conclusions: Albumin-based DLL3-SN38-NICs represent a novel nano-oncologic platform that preserves SN38 potency and achieves high-affinity DLL3 engagement. Ongoing studies will assess in-vivo selectivity, biodistribution, and therapeutic potential in DLL3-positive SCLC and other neuroendocrine malignancies. Citation Format: Mohamed Shanshal, Lin Yang, Liyi Geng, Wendy Nevala, Aaron S. Mansfield, Bharath Wootla, Konstantinos Leventakos, Kyle Korshavn, Svetomir N. Markovic. Albumin-based DLL3-targeted nano-immunoconjugates of SN38 preserve potency and demonstrate high-affinity DLL3 binding in small cell lung cancer [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 449.

Abstract Background: Spatial cellular ecosystems in the tumor microenvironment (TME) form dynamic signaling hubs that critically influence cancer disease progression and response to therapy, including response to immune checkpoint inhibitors (ICIs). However, tumor sampling bias and the impracticality of acquiring serial tumor biopsies have made it challenging to profile the TME clinically. To address this challenge, we developed Liquid EcoTyper, a multi-analyte AI framework to quantify TME spatial cellular ecosystems—termed spatial ecotypes (SEs)—noninvasively from cell-free DNA (cfDNA) methylation data. Methods: In previous work, we discovered nine spatial ecotypes, including SEs associated with ICI response (e.g., SE7 with benefit, SE4 with resistance), and quantified them from 1,249 bulk tumor RNA-seq profiles of melanoma, non-small cell lung cancer (NSCLC), and bladder cancer (BC) patients (Cancer Res (2025) 85 (8_Supplement_1): 153). Here we trained Liquid EcoTyper, an interpretable deep learning model, to transfer SE profiling to cell-free DNA using CpG methylation profiles. Performance was quantified using simulated and real data, including methylation profiles (EM-seq) of plasma cfDNA paired with tumor biopsy-derived SE levels determined by EM-seq (n=20 pairs) or 10x Visium (n=15 pairs). Clinical outcome prediction was evaluated using pretreatment plasma from patients treated with ICI alone (n=78 melanoma pts), chemotherapy and ICI (n=25 NSCLC pts), and enfortumab vedotin and ICI (n=10 localized muscle-invasive BC (MIBC) pts). Tumor mutational burden (TMB), tumor PD-L1, or circulating tumor DNA (ctDNA) were profiled as a comparator where possible. Results: We observed striking concordance between plasma-derived SE levels and tumor biopsy-confirmed SE levels from the same patients, demonstrating that liquid biopsy analysis of cfDNA methylomes can recapitulate TME spatial biology. Underscoring specificity, no reliable SE signal was detectable from peripheral blood mononuclear cells. In pre-ICI plasma, liquid SE levels were significantly associated with ICI-based response (SE7) versus resistance (SE4) in patients with melanoma, NSCLC, and MIBC, with a mean cross-cancer area under the curve (AUC) of 0.87 for SE7 (range 0.8-0.97) and 0.81 for SE4 (range 0.76-0.85)—far surpassing TMB, tumor PD-L1, and ctDNA in evaluable patients, both in binary analyses of response and multivariable models of survival. Our results also showed potential to predict pathologic complete response in the neoadjuvant setting. Conclusion: Liquid EcoTyper is a scalable noninvasive AI-based framework for spatiotemporal assessment of the TME. By enabling TME-informed risk stratification without surgical biopsies, Liquid EcoTyper has potential to enable more precise and actionable decision making in patients with solid tumors. Citation Format: Erin L. Brown, Wubing Zhang, Abul Usmani, Noah Earland, Ayesha Hashmi, Chibuzor Olelewe, Anushka Viswanathan, Pradeep S. Chauhan, Minji Kang, Chloé B. Steen, Hyun Soo Jeon, Susanna Avagyan, Irfan Alahi, Nicholas P. Semenkovich, Matteo Bergsagel, Janella C. Schwab, Chloe M. Sachs, Faridi Qaium, Peter K. Harris, Antonella Bacchiocchi, Qingyuan Cai, Andrew J. Gentles, Rondell P. Graham, Peter C. Lucas, Ryan C. Fields, Jacob J. Orme, Aaron S. Mansfield, Mario Sznol, Ruth Halaban, David Y. Chen, Aaron M. Newman, Aadel A. Chaudhuri. Liquid biopsy profiling of the tumor microenvironment to determine response to immunotherapy regimens across solid tumors [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 94.

Abstract Background: Despite the decline in overall mortality and incidence of cancer in the US population, the burden of cancer is still high, especially in underserved and under-researched populations. A major contributor to poor cancer outcomes is the absence of dedicated efforts utilizing scientifically rigorous approaches and implementation strategies to optimize participant enrollment and accrual in clinical trials. The Connecting Patient Populations to Clinical Trials (CP2CT) program implements innovative multilevel interventions to enhance clinical trial awareness and optimize referral pathways that facilitate patient enrollment. The CP2CT Data, Evaluation, and Coordinating Center (DECC) supports its data and evaluation activities, and coordinates a learning collaborative towards mitigating the key barriers of cancer burden in all populations. Methods: Using an implementation science-informed approach, the DECC deployed coordinated strategies over three years: (1) administrative structuring through streamlined governance, centralized reporting, and stakeholder integration; (2) data standardization via Common Data Elements (CDEs), a cross-network REDCap system, and a multi-institution Data Transfer Agreement (DTA); (3) evaluation infrastructure through a Network Logic Model, evaluation plan, standardized constructs, and a Process Evaluation Plan with tools; (4) learning supports through an internal website and expanded Speaker Series; and (5) site-level implementation facilitation through structured visits. Results: In collaboration with the CP2CT Network and NCI, the DECC’s achievements span four domains: (1) Administrative: built infrastructure, deployed centralized reporting platforms, coordinated key meetings, and strengthened community integration. (2) Data: standardized collection, secured network-wide data sharing through the DTA, enabled harmonized multi-site reporting, and advanced groundwork for interoperability and scientific value. (3) Program Evaluation: linked CP2CT activities to measurable outcomes through a Network-wide Logic Model, guided evaluation, established shared evaluation language, and launched a transferable Process Evaluation framework. (4) Learning Collaborative: developed a centralized resource hub, expanded the Speaker Series, and advanced authorship transparency with the CP2CT Publication Policy. < Conclusion: The CP2CT DECC has established a sustainable, scalable infrastructure that integrates administrative coordination, standardized data collection, robust program evaluation, and a collaborative learning environment. These efforts enhance clinical trial awareness, optimize referral pathways, and provide a transferable model for improving participant enrollment and scientific rigor across national research networks, ultimately addressing disparities in cancer outcomes. Citation Format: Laura E. Lectora, Cristina J. Orozco, Holly A. Thorson, Timethia Bonner, Robert R. Freimuth, Jennifer G. Le-Rademacher, Folakemi T. Odedina. Building a national network coordination center for clinical trials: Early implementation outcomes from the CP2CT DECC [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 899.

Abstract Introduction: The prostate cancer (PCa) tumor microenvironment (TME) is immunosuppressive and resistant to immune checkpoint blockade (ICB). Based on multi-omic single cell correlatives of response to neoadjuvant Fc-enhanced (FcE) αCTLA-4 in high-risk localized PCa (NCT04301414), we explored how modulating the balance between regulatory T cells (Tregs) and dendritic cells (DCs) in the PCa TME affects sensitivity to ICB. Methods: We leveraged three single cell transcriptomic atlases of PCa to assess how Tregs and DC frequencies are dynamically regulated during PCa progression. To investigate responses to Treg depletion (via FcE-αCTLA-4) alongside DC expansion (via Flt3L-Ig) and stimulation (via STING agonist ADU-S100) in PCa, we employed the castration-sensitive MycCaP PCa model and 45-parameter spectral flow cytometry. To investigate novel direct mechanisms of DC stimulation by FcE-αCTLA-4 via Fcγ receptor (FcγR) engagement, we optimized reductionist in vitro assays involving bone marrow-derived DCs (BMDCs) from wild-type (WT) mice or mice deficient in activating FcγRs (Fcer1g-/-) or inhibitory FcγRIIb (Fcgr2b-/-). To validate this effect in vivo we established a tumor antigen-specific T cell priming assay with both flow cytometry and ex vivo 2-photon live cell imaging readouts. Results: In three independent single cell transcriptomic PCa atlases, we find cDC2 frequencies are significantly decreased in advanced PCa while effector Tregs (TNFRSF9+) increase in proportion. Hypothesizing that excessive Treg function and DC insufficiency drive ICB resistance in PCa, we find in vivo DC expansion (Flt3L-Ig) prior to hormonal therapy, Treg depletion (FcE-αCTLA-4), and in situ DC stimulation (ADU-S100) drives robust control of established MycCaP tumors, with 87% of animals tumor-free 40-days post-treatment (27/31). Using 45-parameter spectral flow cytometry we find FcE-αCTLA-4 drives DC activation prior to Treg depletion in the TME, supporting a novel direct mechanism of DC modulation by FcE-αCTLA-4. In vitro, we find cell-associated FcE-αCTLA-4 is sufficient to drive BMDC maturation in an FcγR-dependent manner. In vivo, FcE-αCTLA-4 augments DC-mediated T cell priming in an FcγR-dependent manner. Ongoing experiments are investigating how FcE-αCTLA-4 shapes DC-T cell interactions via FcγR engagement and how DC/Treg axis modulation can be optimized to improve long-term curative response rates in the MycCaP model. Conclusions: DC insufficiency and effector Treg differentiation are hallmarks of advanced PCa. Enhancing DC number and function concomitant with Treg depletion can drive effective antitumor immunity in a pre-clinical PCa model. Direct DC modulation via FcγR engagement represents a novel mechanism of response to CTLA-4-targeted ICB. These findings will inform ongoing translation of FcE-αCTLA-4 agents and development of novel immunotherapy strategies for PCa. Citation Format: Jessica C. Hill, Kade R. Copple, Collin Jugler, Phuong Nguyen, Nilika Bhattacharya, Jessica N. Lancaster, Casey R. Ager. Rewiring the dendritic cell: Regulatory T cell axis sensitizes prostate cancer to immunotherapy [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 166.