The effectiveness of immunotherapy in estrogen receptor–positive (ER+) breast cancer remains limited. ER+ tumors typically exhibit low tumor-infiltrating lymphocytes and an immunosuppressive tumor microenvironment, both of which contribute to poor responsiveness to immune checkpoint blockade. Prior work in the PEARL trial (NCT03366844) showed that triple-negative breast cancer responders to anti–programmed cell death 1 (anti-PD-1) combined with radiation therapy showed an increase in intratumoral CD8+ T cells, highlighting the importance of effective T cell activation in mediating treatment response. The current study investigates whether ER+ breast tumors demonstrate similar T cell-driven mechanisms following anti-PD-1 therapy alone and in combination with radiation. Single-cell RNA sequencing (scRNA-seq) and T cell receptor sequencing (scTCR-seq) were performed on matched tumor biopsies and peripheral blood mononuclear cells collected from ER+ breast cancer patients (n= 12) at three treatment timepoints: baseline, after first cycle of anti-PD-1, and after second cycle of anti-PD-1 plus radiation. We identified diverse T cell subsets in tumor and blood, including cytotoxic, exhausted, regulatory, and memory phenotypes. TCR analyses demonstrated expansion of intratumoral T cell clones following anti-PD-1 treatment, and these expanded clones persisted after anti-PD-1 plus radiation, with responders maintaining clonal expansion compared to non-responders. Notably, responders had more shared T cell clonotypes between tumor and peripheral blood after anti-PD-1 plus radiation than non-responders, suggesting an enhanced systemic immune response mediated by tumor-reactive clones in responders. Overall, this study identifies intratumoral T cell signatures associated with anti-PD-1 and radiation response in ER+ breast cancer. By characterizing how T cell dynamics change across treatment timepoints and between tumor and blood, these findings provide insight into mechanisms that may contribute to resistance to checkpoint blockade, informing the development of improved therapeutic strategies for ER+ breast cancer. Disclosure: Portions of this abstract were revised using generative AI under full author supervision. Na Jeong Kim, Vaishnavi Devarakonda, Kamal Asadipour, Isaiah Vazquez, Elvin Canseco, Julie Jang, Anthony Nguyen, Yuan Yuan, Jin Sun Bitar, Scott Karlan, Simon Knott, Stephen Shiao. Single-cell immune profiling reveals T cell dynamics in estrogen receptor–positive breast cancer treated with anti-PD-1 and radiation therapy [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr B034.

Abstract Background: Peritoneal carcinomatosis and malignant ascites are frequently caused by solid tumors, and the presence of ascites is associated with a poor prognosis and resistance to immune checkpoint inhibitors. While some immunosuppressive features of ascites have been described, the role of dendritic cell (DC) subsets in this microenvironment is unknown. Recently, a subset of DCs that express RORC have been found in normal mouse and human tissues, and they have been linked to tolerance of gut antigens. However, this DC population has not previously been associated with cancer or well characterized in humans. Methods: We performed single-cell RNA sequencing (scRNA-seq) with paired surface proteomics (CITE-seq), and secreted proteomics (n = 109 analytes) on ascites (n = 23) and matched peripheral blood (n = 15) from patients with gastric and gastroesophageal adenocarcinoma (GEA; n = 523,322 total cells). Allogeneic mixed lymphocyte reactions (MLRs) were performed using DCs from GEA and pancreas cancer patients with ascites. In vitro differentiation experiments leveraged cDCs from healthy donors and cultured them in media supplemented with ascites supernatant or paired plasma from GEA patients. Results: We identified a DC subset expressing PIGR and RORC (PRDCs) that were transcriptionally distinct from canonical DC subsets and similar to tolerogenic cell subsets. Analysis of >1x107 cells from public datasets suggest that PRDCs are found in other human tissues but enriched in malignant ascites from both GEA and ovarian cancers. Sorted PRDCs stimulated T-cell proliferation in MLRs. However, scRNAseq of T cells stimulated by PRDCs showed that those T cells were less effectively polarized due to reduced expression of effector cytokine genes (e.g., IFNG, IL5, IL13) compared to T cells stimulated by cDC2s. Spatial transcriptomics confirmed the presence of PRDC-like cells in human lymphoid tissues, and neighboring, proliferating CD4 T cells similarly showed reduced polarization signatures. Features of the PRDC transcriptional program could be induced by culturing blood-derived cDC1s from healthy donors in supernatant from patients with malignant ascites, suggesting that PRDCs are induced in the ascites microenvironment. Conclusions: PRDCs represent a conserved, immunomodulatory DC subset enriched in malignant ascites. PRDCs are capable of modulating T-cell responses and may represent a tolerogenic state induced by the ascites microenvironment. Targeting PRDCs or their differentiation pathways may offer new strategies to enhance anti-tumor immunity in patients with peritoneal metastases. Citation Format: Steven M. Blum, Thomas L. Chan, Neal P. Smith, Courtney Ambrose, Katherine H. Xu, Alice Tirard, Nandini Samanta, Sidney Martin, Roya Best, Elizabeth Tuttle, Christopher T. Stueber, Vaishnavi R. Yalala, Haley Barnes, Sean T. Bannon, Yuhui Song, Benjamin Y. Arnold, Mushriq Al-Jazrawe, Joseph J. Zhao, Kamil Slowikowski, Jessica Tantivit, Kasidet Manakongtreecheep, Lukas M. Altenburger, Simon Knott, Matthew R. Strickland, Michael G. Drage, Linda T. Nieman, Jesse S. Boehm, Raghav Sundar, Gary Reynolds, Samuel J. Klempner, Alexandra-Chloé Villani. Immunomodulatory PIGR + RORC + dendritic cells (PRDCs) are enriched in malignant ascites [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 6134.

Abstract Background: High-plex spatial proteomics platforms (e.g., PhenoCycler) have transformed our ability to map the tumor microenvironment (TME) at single-cell resolution, but their cost constrains cohort sizes for biomarker discovery and validation. Recently, ROSIE (Wu et al., Nat Commun 2025) aimed to tackle this problem by predicting protein markers directly from H&E stained slides. However, the number of robustly predicted markers obtained by it has been fairly limited, with only 5 markers reaching a Pearson r correlation of above 0.4 between measured and predicted marker intensity. Here, we present Path2Marker, a cell-level deep learning framework that substantially expands the panel of robustly predicted protein markers in multiple tumor types. Methods: We analyzed three new cancer-specific PhenoCycler (CODEX) cohorts with paired H&E and multiplex immunofluorescence, including lung cancer (88 samples, 660791 cells), colorectal cancer (106 samples, 624919 cells) and breast cancer (115 samples, 901684 cells), each stained with a 55 proteomic marker panel. For each disease, we trained a cancer-specific model to predict per-cell marker intensities from the H&E slides, and additionally evaluated an ensemble model that averages predictions from all three cancer-specific models. Model performance was evaluated on 60 held-out samples (all three diseases; 396,995 cells), using Pearson correlation between the measured and predicted marker intensities. Results: We robustly predict (Pearson r > 0.4 for measured vs. predicted intensity) 23, 26, and 44 markers in the breast, lung and colorectal cohorts, respectively, markedly outperforming the published state of the art. When benchmarked on the same samples, ROSIE achieved fewer robustly predicted markers, with only 3 markers in colon, 2 in lung and 0 in breast. The ensemble model significantly improved mean marker-level correlation in lung and was comparable to the indication-specific models in breast and colorectal cancer. Top-performing markers included EpCAM in colon (r=0.79), PanCK in lung (r=0.73), and PanCK in breast (r=0.64). Notably, they include not only lineage markers (e.g., PanCK, CD3e) but also functional markers (e.g., PD-L1, Ki-67), enabling downstream cell-state and cell-type annotation, laying the basis for robust annotation of 25, 16, and 17 different cell-types in colon, lung, and breast, respectively. Conclusion: Path2Marker enables robust prediction of more than 20 multiplex protein markers at single-cell, spatial resolution directly from standard H&E slides across three major solid tumors. It markedly improves upon the predictive accuracy of extant tools, opening up the possibility of fast and low-cost annotation of large cancer patients cohorts directly from the histopathology slides. Citation Format: Amos Stemmer, Tiangen Chang, Thomas Cantore, Saugato Rahman Dhruba, Sumona Biswas, Sumeet Patiyal, Eldad David Shulman, Emma M. Campagnolo, Aagam Shah, Simon Knott, Chi-Ping Day, Danh-Tai Hoang, Eytan Ruppin. Path2Marker: Cell-level prediction of multiplex protein expression from routine H&E slides [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 85.

Abstract Background: The KEYNOTE-522 trial established pembrolizumab plus neoadjuvant chemotherapy as a standard for early-stage triple-negative breast cancer (TNBC) by significantly improving pathologic complete response (pCR) and event-free survival. Yet biomarkers predicting response and the biology underlying residual disease—particularly the divergent outcomes observed among patients with residual cancer burden class 2 (RCB2) from chemotherapy only and chemotherapy plus immunotherapy—remain poorly defined. We hypothesized that spatial cellular architectures at diagnosis, and their longitudinal remodeling with therapy, govern TNBC treatment response and resistance. Methods: We performed single-cell resolution spatial transcriptomic profiling on 131 diagnostic biopsies, 161 resection specimens, and 38 metastatic lesions from patients treated with neoadjuvant chemotherapy with or without pembrolizumab, including 50 paired pre/post-treatment samples for longitudinal analysis. A 60-marker spatial proteomic panel provided cross-modality validation. Spatial features, including cell-type abundance, co-localization, tumor-immune interface structure, and niche organization, were evaluated across pCR versus non-pCR groups, RCB classes (0-3), and longitudinal transitions within each therapeutic arm. Results: Across 6 pathologist-annotated histologic regions, we resolved 17 major cell types, 72 gene-defined subtypes, and 96 spatial communities. Early analyses highlight contrasting CD8+ T-cell spatial states: intra-tumoral CD8+ infiltration characterizes responders, whereas stromal-restricted CD8+ localization, together with CD33+ myeloid programs, marks non-response and T-cell exclusion. Additional cohort-specific variation was observed in fibroblast density, stromal architecture, and myeloid-lymphoid proximities. Integrating diagnostic and longitudinal spatial features, we are developing an interpretable spatial risk score to distinguish treatment response and RCB class. Conclusions: This study represents one of the largest integrated spatial transcriptomic and proteomic analyses of TNBC neoadjuvant therapy to date. Emerging patterns suggest that cytotoxic T-cell access to tumor nests marks effective anti-PD-1 response, whereas fibroblast-driven stroma and myeloid-mediated exclusion underlie resistance. These insights provide a roadmap for designing combination therapies to overcome stromal and myeloid barriers to neoadjuvant immunotherapy. Citation Format: Shiqing Liao, Teia Noel, Joseph Lownik, Pavithra Nedumaran, Yoona Yang, Richard Mebane, Aagam Shah, Andrew Martinez, Akil A. Merchant, Simon Knott. Spatial transcriptomic features associated with response to neoadjuvant therapy in triple-negative 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 3968.

Defining mechanisms used by gut microbiota to control anti-tumor immunity may offer novel therapeutic modalities. Here, we demonstrate that Bacteroides rodentium and closely related Bacteroides uniformis species induce anti-tumor immunity and limit melanoma development when colonized in either germ-free (GF) mice, mice with a complex microbiome, or WT mice. Enhanced CD8 + T cell infiltration seen in tumors of mice harboring B. rodentium coincided with increased expression of immune-stimulating pathways and activation of bone marrow-derived dendritic cells that were co-cultured with the B. rodentium secretome. Metabolomic analyses of cecal samples from GF mice colonized with Altered Shedlar Flora (ASF) plus B. rodentium revealed lower tryptophan levels than in ASF-colonized controls, and WT mice fed a tryptophan-deficient diet exhibited inhibition of melanoma development. In silico genomic reconstruction of metabolic pathways revealed that both B. rodentium and B. uniformis harbor tryptophanase A ( TnaA ) and aromatic amino transferase ( ArAT ) genes, both of which function in tryptophan degradation. Administration of a B. uniformis harboring TnaA mutant failed to inhibit melanoma growth in gnotobiotic mice. Notably, administration of indoles, but not kynurenines, also effectively inhibited melanoma development, increasing immune cell infiltration into the tumors. Correspondingly, levels of bacterially encoded tryptophan-degrading enzymes were higher in cohorts of melanoma patients responding to immune checkpoint blockade. These findings highlight a novel mechanism of anti-tumor immunity and tumor growth inhibition dependent on the tryptophan degradation products, indoles, produced by intestinal Bacteroides species.

Study of gut microbiota control of anti-tumor immunity (ATI) identifies Bacteroides rodentium and the human-related Bacteroides uniformis species to be capable of inducing ATI and limiting melanoma development in germ-free (GF), complex microbiome, or wild-type (WT) mice. Enhanced CD8+ T cell infiltration within tumors of mice harboring B. rodentium coincides with increased expression of immune-stimulating pathways. Metabolomic analyses identify lower tryptophan levels in the cecal samples of GF mice harboring B. rodentium. In silico genomic reconstruction reveals that B. rodentium and B. uniformis harbor tryptophanase A (TnaA) and aromatic aminotransferase genes, which degrade tryptophan to indoles. Administration of B. uniformis harboring TnaA mutant fails to inhibit melanoma growth. Notably, administration of indoles effectively induces ATI and inhibits melanoma development. Correspondingly, the levels of bacterially encoded tryptophan-degrading enzymes are higher in cohorts of patients with melanoma responding to immunotherapy. These findings identify indoles as tryptophan breakdown products capable of inducing ATI resulting in melanoma inhibition.

Abstract Background: High-grade non-muscle invasive bladder cancer (NMIBC) is an aggressive malignancy characterized by a high rate of progression to muscle-invasive bladder cancer (MIBC). Once muscle-invasive, the disease is associated with significantly worse overall survival. Thus, novel strategies for identifying therapeutic targets and biomarkers of progression are urgently needed. We utilized spatial transcriptomics to elucidate the tumor microenvironment states and cellular interactions that underlie progressive NMIBC. We hypothesized that progressive NMIBC is defined by distinct molecular and architectural compositions that converge on an MIBC-like phenotype. Methods: We constructed tissue microarrays using transurethral resection specimens from 18 high-grade NMIBC patients who progressed to MIBC within 5 years and 27 risk-matched non-progressors, along with 52 MIBC cystectomy specimens. We then performed Xenium in situ expression analysis using a 5,000-gene panel with an additional 100 genes focused on stromal and immune signaling. Data were analyzed using single-cell variational inference with Leiden clustering-based cell typing, custom neighborhood (“niche”) evaluation, and computational workflows to characterize cellular interactions, transcriptional programs, and ligand-receptor signaling across progressor status and disease states. Results: We generated a single-cell-resolution spatial transcriptomic atlas of over 4 million cells spanning NMIBC and MIBC tissues. Preliminary analysis revealed substantial intra- and inter-patient heterogeneity in both tumor-intrinsic transcriptional programs and microenvironment composition. Non-progressor tumors demonstrated increased immune activation signatures and enrichment of cytotoxic CD8+ T cells, while progressors showed enrichment of tumoral mTOR signaling and other oncogenic pathways. Ongoing work aims to define spatial niches and cellular interaction networks that differentiate progressive versus non-progressive disease and evaluate their alignment with MIBC-like architecture. Conclusions: This study establishes the first single-cell spatial transcriptomic analysis directly comparing NMIBC progressors and non-progressors, providing a framework to define microenvironmental trajectories underlying progression to invasion. By leveraging high-resolution spatial transcriptomics to identify candidate biomarkers and potential drivers of invasion, this work may inform early risk stratification and microenvironment-targeted therapeutics aimed at preventing transition to MIBC. Citation Format: Jacob Alltucker, Yiling Shen, Suhyeon Choi, Pavithra Nedumaran, Andrew Martinez, Joseph Lownik, Huihui Ye, Hideki Furuya, Dan Theodorescu, Simon Knott. Spatial transcriptomic dissection of microenvironmental drivers of NMIBC progression [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 3950.

Spatial transcriptomics (ST) is transforming our understanding of tumor heterogeneity by enabling high-resolution, location-specific mapping of gene expression across tumors and their microenvironment. However, the translational potential of spatial transcriptomics is still limited by its high cost, hindering the assembly of large patient cohorts needed for robust biomarker discovery. Here we present Path2Space, a deep learning approach that predicts spatial gene expression directly from histopathology slides. Trained on substantial breast cancer ST data, it robustly predicts the spatial expression of over 4,300 genes in independent validations, markedly outperforming existing ST predictors. Path2Space additionally accurately infers cell-type abundances in the tumor microenvironment (TME) based on the inferred ST data. Applied to more than a thousand breast tumor histopathology slides from the TCGA, Path2Space characterizes their TME on an unprecedented scale and identifies three new spatially-grounded breast cancer subgroups with distinct survival rates. Path2Space-inferred TME landscapes enable more accurate predictions of patients’ response to chemotherapy and trastuzumab directly from H&E slides than those obtained by existing established sequencing-based biomarkers. Path2Space thus offers a transformative, fast and cost-effective approach to robustly delineate the TME directly from their histopathology slides, facilitating the development of spatially-grounded biomarkers to advance precision oncology. Emma M. Campagnolo, Eldad D. Shulman, Roshan Lodha, Amos Stemmer, Peng Jiang, Carlos Caldas, Simon Knott, Danh-Tai Hoang, Kenneth Aldape, Eytan Ruppin. Path2Space: An AI approach for cancer biomarker discovery via histopathology inferred spatial transcriptomics [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning; 2025 Jul 10-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(13_Suppl):Abstract nr B047.

Tumor infiltrating lymphocytes (TILs) that mediate tumor regression through recognition of cancer-specific antigens by their T-cell receptors (TCRs) are of great clinical value in the treatment of cancer. However, it is unclear what these antigens are and whether they contribute to anti-tumor immunity. Based on our previous antigen discovery platform, TCR-MAP, we have developed a rapid screening method to isolate cells carrying the cognate antigen from a library of hundreds of thousands of antigen-presenting cells. Our screening strategy is highly effective in identifying antigenic targets recognized by TCRs of known specificity and can allow us to identify the cognate antigens of therapeutically relevant TCRs from cancer patient TILs. Using a cohort of triple negative breast cancer patients who have undergone radiation and anti-PD-1 combination therapy, we conducted single-cell sequencing analyses of tumor biopsies to obtain TCR sequences from the top expanded CD8 T cell clones. These TCRs are being screened against a human peptidome library for self and aberrantly expressed antigens to map the antigen landscape of breast cancer and characterize the contribution of the identified antigens to anti-tumor immunity. Initial screens reveal a few unique self-antigens but show that most patient TCRs do not recognize non-mutated antigens. With additional TCR antigens being screened, our eventual antigen landscape will help guide the development of future TCR-based therapies. Ge Zhu is a Damon Runyon Fellow supported by the Damon Runyon Cancer Research Foundation (DRG-2473-22). Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)

Chimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment of hematological malignancies. However, its application in solid tumors remains limited because single targets are unlikely to suffice due to tumor antigen heterogeneity and off-tumor toxicities. To overcome these obstacles, we developed LogiCAR designer, a computational approach that utilizes single-cell transcriptomics data from patient tumors to systematically identify the cancer-specific antigen circuits with logic gates ("AND," "OR," and "NOT") that target the majority of cancer cells in a tumor while sparing normal cells and tissues as much as possible. LogiCAR designer efficiently scales to higher-order antigen combinations involving up to five genes. Applied to a large-scale dataset encompassing approximately 2 million cells (including > 620k tumor cells) from 342 clinical patient samples across all major breast cancer subtypes, LogiCAR designer identified antigen circuits with enhanced tumor-targeting efficacy and improved safety profiles compared to both previously reported circuits and single-target therapies in clinical trials. However, even these optimized shared circuits still proved insufficient for some patients. We hence systematically studied LogiCAR designer's ability to identify highly effective CAR circuits that are individualized to each patient. Remarkably, such personalized CAR circuits provide estimated tumor-targeting efficacy tantamount to complete response in 76% of patients and partial response for all patients. Taken together, this analysis is the first systematic quantification of the efficacy and safety of all possible CAR circuits, showing that: (a) the quality of existing solutions leaves much to be desired; (b) the ability of shared circuits optimized across many patients is moderate, and finally, (c) individually tailored circuits offer significantly higher tumor-targeting efficacies for patients. LogiCAR designer offers a rigorous, data-driven way to facilitate the rational design of safe and effective CAR-based immunotherapies for cancer.

Phenotypic plasticity is a recognized mechanism of therapeutic resistance in prostate cancer (PCa), however current knowledge of driver mechanisms and therapeutic interventions are limited. Using genetically engineered mouse models (GEMMs) devoid of Pten and Rb1, we previously demonstrated the chromatin reprogramming factor enhancer of zeste homolog 2 (EZH2) as an important regulator of alternative transcription programs promoting phenotypic plasticity. Here, using a multi-omics approach we demonstrate that EZH2 regulates multilineage cell states dependent on the RNA binding protein Tristetraprolin (TTP) that mediates RNA stability and activation of translation. Combined chemical inhibition of EZH2 and PI3K/mTORC1 resulted in superior anti-tumor activity in murine and human phenotypic plastic models and was most significant when this combination was used with castration or enzalutamide. Together, these data indicate phenotypic plasticity dependence on coordination between EZH2, TTP and mTORC1 signaling that represent novel therapeutic dependencies for this lethal PCa phenotype.

Loss of the Y chromosome (LOY) in peripheral blood mononuclear cells (PBMCs) is the most common somatic alteration in men and is associated with higher mortality from epithelial cancers1-3. In tumours, epithelial LOY is also associated with poor survival4-7. This raises several fundamental questions, such as why LOY in PBMCs drives cancer mortality and whether there is a relationship between LOY in PBMCs, PBMC-derived immune cells and cancer cells (and, if so, what its consequences are). We sought to answer these questions through a comprehensive pan-cancer analysis of bulk and single-cell RNA sequencing data from 29 human tumour types, along with autochthonous and syngeneic mouse models. In human and mouse tumours, malignant epithelial cells had the highest LOY prevalence, yet LOY was also present in tumour stromal and immune cells, with LOY in malignant epithelial cells predicting LOY in benign cells. LOY also correlated between paired tumour and PBMC samples from patients. Among benign cells, LOY induced the strongest shift in CD4+ and CD8+ T cells, with both showing transcriptomic signatures of immunosuppression. Furthermore, the magnitude of LOY in epithelial cells, CD4+ T cells and CD8+ T cells independently predicts survival, with tumours exhibiting concurrent epithelial and T cell LOY having the worst outcomes. Here we establish a model that links LOY in immune cells to LOY in malignant cells, which may explain in part why LOY in PBMCs is associated with increased cancer mortality.

CDK4/6 inhibitors are central to the clinical management of HR+HER2- breast cancer. We have recently demonstrated that immunosuppressive, IL17-secreting γδ T cells recruited to the tumor microenvironment by a CCL2-dependent mechanism upon CDK4/6 inhibition can repolarize tumor-associated macrophages toward a CX3CR1+ phenotype associated with resistance to therapy.

Resistance to cyclin-dependent kinase 4/6 (CDK4/CDK6) inhibitors leads to treatment failure and disease progression in women with hormone receptor+HER2− (HR+HER2−) breast cancer (BC). We delineated a hypoxia-sensitive, CCL2-dependent pathway recruiting interleukin-17A (IL-17A)-secreting γδ T cells to mouse HR+HER2− BCs following CDK4/CDK6 inhibition, resulting in repolarization of tumor-associated macrophages (TAMs) toward an immunosuppressive CX3CR1+ phenotype associated with resistance. Increased IL-17A signaling and intratumoral γδ T cell abundance positively correlated with advanced grade and/or reduced survival in two cohorts of individuals with HR+HER2− BC. Circulating γδ T cells and plasma CCL2 levels negatively correlated with progression in an independent series of individuals with HR+HER2− BC receiving CDK4/CDK6 inhibitors. Intratumoral γδ T cells were increased in post- versus pretreatment biopsies from individuals with HR+HER2− BC relapsing on CDK4/CDK6 inhibitors. CX3CR1+ TAMs had negative prognostic impact in women with HR+HER2− BC receiving neoadjuvant PD-1 blockage and radiotherapy. Thus, γδ T cells and CX3XR1+ TAMs may favor resistance to CDK4/CDK6 inhibitors in individuals with HR+HER2− BC. Petroni et al. report that the infiltration of IL-17A-secreting γδ T cells in the tumor microenvironment coupled with the accumulation of immunosuppressive macrophages is associated with resistance to CDK4/CDK6 inhibition in HR+HER2− breast cancer.

The molecular and cellular pathways through which breast cancer evades immunosurveillance remain poorly understood. Recent data from Camargo et al. demonstrate that - on recruitment to the tumor microenvironment by ductal macrophages - a heterogeneous population of neutrophils can establish physical contacts with malignant cells within spatial niches that sustain mammary oncogenesis.

Current CAR-T therapies for solid tumors are limited by suboptimal target selection, with single antigens failing to address tumor heterogeneity and causing on-target, off-tumor toxicities. Systematic identification of multi-target combinations using logic gates (AND, OR, NOT) represents an untapped approach for discovering safer, more effective CAR immunotherapy targets. We developed LogiCAR designer, a genetic algorithm-based framework that systematically screens 2,758 cell surface proteins to identify optimal 1-5 gene logic-gated target combinations (i.e., ‘circuits’) from single-cell transcriptomics data. Applied to the largest breast cancer single-cell dataset (∼2 million cells, >620k tumor cells from 342 patients across 17 cohorts), we optimized tumor-targeting efficacy while maintaining safety across 689,601 normal cells from 31 Human Protein Atlas tissues. Comprehensive target validation included RNA and protein expression profiling across major human tissues and tumor microenvironment specificity analysis. Our systematic approach identified novel cell surface targets with superior profiles compared to current clinical candidates. The top 3-gene circuit ('GABRP | PRLR | VTCN1') achieved 60% tumor-targeting efficacy—234% higher than the best clinical trial targets. Newly discovered single targets (ELAPOR1, PRLR, BAMBI, LDLRAD3) demonstrated consistent tumor-specific expression (>2-fold tumor vs. non-tumor cells, p<0.05) across all datasets, unlike current clinical targets. Safety profiling revealed that many existing targets (BSG, EPCAM, TACSTD2) showed concerning expression in critical normal tissues, while our identified circuits maintained superior safety profiles. Finally, shared circuits were still ineffective for some patients, prompting development of personalized approaches. Individualized target combinations addressed intratumor heterogeneity: in our new 82-patient multi-ethnicity cohort, personalized circuits reached 98% mean efficacy with 76% of patients achieving complete response-equivalent targeting. This work establishes the first systematic molecular target discovery pipeline for multi-antigen therapeutic design, identifying previously unrecognized targets with superior efficacy-safety profiles. Our approach transforms target selection from empirical to data-driven, providing a foundation for next-generation precision therapeutics across cancer types. Sanna Madan, Tian-Gen Chang, Andrew Martinez, Alexandra R. Harris, Huaitian Liu, Saugato R. Dhruba, Binbin Wang, Padma S. Rajagopal, Sanju Sinha, Aravind Srinivasan, Simon R. V. Knott, Shahin Sayed, Francis Makokha, Chi-Ping Day, Gretchen L. Gierach, Stefan Ambs, Alejandro A. Schäffer, Eytan Ruppin. Systematic discovery of logic-gated cell surface targets for enhanced solid tumor CAR therapy through single-cell transcriptomics [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr C042.

Tertiary lymphoid structures (TLSs) are associated with improved cancer immunotherapy responses. However, TLSs vary in their ability to elicit anticancer immune activity, so it is important to develop databases that allow study of variables that regulate their function. We applied single RNA molecule resolution imaging to longitudinal biopsies taken from women with TLS-enriched triple negative breast cancers prior to therapy, after pembrolizumab and after pembrolizumab plus radiation therapy. We developed a computational framework to align and analyze spatial trajectories between TLSs and tumor beds. Tumors with higher T cell infiltration rates were eradicated after pembrolizumab. In contrast, those with lower malignant cell and T cell interaction rates at baseline showed CXCL9+ macrophage infiltration after pembrolizumab, and infiltration of T cells expressing CXCL9-associated programs prior to cancer cell removal after radiation therapy. This manuscript describes single RNA molecule resolution profiling of breast tumors bearing tertiary lymphoid structures throughout an immunotherapy response.