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Abstract Disclosure: Z. Quandt: None. S. Yellamilli: None. E. Flynn: None. V. Johri: None. B. Davidson: None. J. Tsui: None. A. Combes: None. G. Fragiadakis: None. A. Young: None. M. Anderson: None. Introduction: Immune checkpoint inhibitor (ICI) type 1 diabetes (T1DM) is a rare but morbid immune related adverse event (irAE) that can occur in patients with cancer following immunotherapy. ICI-T1DM almost exclusively results from immune checkpoint inhibitors targeting the PD-1/PD-L1 pathway rather than CTLA-4. While some shared features of spontaneous T1DM, such as HLA type and presence of islet cell autoantibodies, are apparent in some, but not all, ICI-T1DM; however, little is known about the immunophenotypic characteristics that predispose patients with cancer to risk of ICI-T1DM as compared to healthy individuals and spontaneous T1DM. Methods: We collected peripheral blood mononuclear cells from 69 patients, 10 with recent onset ICI-T1DM, 17 with recent onset T1DM and 42 healthy controls and performed CITEseq. Individual libraries were processed using a standard single-cell analysis pipeline for RNA and TCR-sequencing alongside protein integration for antibody-derived tags (CellRanger for alignment, followed by Seurat for quality control and initial processing). Multiplexed samples were demultiplexed using freemuxlet/demuxlet, and intrasample doublets were removed using doubletFinder. Individual libraries were integrated using Harmony for RNA data and dsbNormalize with reciprocal principal components (RPCA) for protein (ADT) data. A combined embedding was generated using Weighted Nearest Neighbors, followed by UMAP visualization and clustering. Differential expression analysis was performed using EdgeR with subsequent pathway analysis using Gene Ontology (GO) terms and Reactome pathways. Results: Differential gene expression analysis revealed enhanced MHC-II pathway activity in ICI-T1DM patients compared to healthy individuals. Sub-clustering of T cells identified five distinct clusters with differential abundance between ICI-T1DM, T1DM, and healthy controls. One cluster showed significant enrichment for a T follicular helper (Tfh) cell signature previously implicated in ICI-T1DM in the NOD mouse model (Huang et al. 2024). The proportion of these cells was significantly higher in ICI-T1DM patients compared to both individuals with recent onset spontaneous T1DM and healthy individuals (FDR adjusted p=0.02). Conclusions: These findings suggest a potential activation state in the T cell compartment by upregulation of HLA genes and the expansion of Tfh cells that correlate with the development of ICI-T1DM in patients with cancer. We will next validate these findings in a secondary cohort of ICI-treated patients with cancer that do not have ICI-T1DM. Presentation: Sunday, July 13, 2025

The anti-tumor function of CD8 T cells is limited through well-established pathways of T cell exhaustion (T ). Strategies to capture emergent functional states amongst this dominant trajectory of dysfunction are necessary to find pathways to durable anti-tumor immunity. By leveraging transcriptional reporting (by the fluorescent protein TFP) of the T cell activation marker related to upstream AP-1 transcription factors, we define a classifier for potent versus suboptimal CD69+ activation states arising from T cell stimulation. In tumors, this delineation acts an additional functional readout along the T differentiation trajectory, within and across T subsets, marked by enhanced effector cytokine and granzyme B production. The more potent state remains differentially prominent in a T cell-mediated tumor clearance model, where they also show increased engagement in the microenvironment and are superior in tumor cell killing. Employing multimodal CITE-Seq in human head and neck tumors enables a similar strategy to identify Cd69RNA CD69+ cells that also have enhanced functional features in comparison to Cd69RNA CD69+ cells, again within and across intratumoral CD8 T cell subsets. Refining the contours of the T cell functional landscape in tumors in this way paves the way for the identification of rare exceptional effectors, with imminent relevance to cancer treatment.

Obesity potently alters immune responses across various inflammatory contexts . However, it is unclear whether a transient high-fat diet (HFD) can affect immune function despite minimal effects on body weight. Here, we demonstrate that a short-term HFD regimen significantly exacerbates disease severity in a model of experimental psoriasis, comparable to what is observed in obese mice on long-term HFD. We find that a critical 4-day window of HFD coinciding with disease onset is sufficient to overactivate the immune response, leading to worsened disease outcomes. Mechanistically, we identify the CD4 T cell compartment as an essential mediator of HFD-induced disease severity. Within the compartment, we functionally validate that disease exacerbation is driven by increased differentiation of a pathogenic population of T helper 17 (T 17) cells expressing IL1R1 (interleukin-1 receptor, type I) , which is triggered by localized activation of the NLRP3 (NOD-, LRR-, and pyrin domain-containing protein 3) inflammasome . This brief window of HFD at disease onset leads to immune-dependent sensitization, as disease severity is increased upon a subsequent flare, despite complete recovery and under a low-fat diet (LFD) regimen. Our data indicate that transient dietary changes during the initial stages of an inflammatory event can rewire the immune milieu, profoundly influencing disease progression and inflammatory memory . This phenomenon may have broad implications for conditions where obesity, and not diet itself, is considered the primary risk factor.

Imaging-based, single-cell spatial transcriptomics (iSCST) using formalin-fixed, paraffin-embedded (FFPE) tissue could transform translational research by retaining all tissue cell subsets and spatial locations while enabling the analysis of archived specimens. We aimed to develop a robust framework for applying iSCST to archived clinical FFPE mucosal biopsies from patients with inflammatory bowel disease (IBD). We performed a comprehensive benchmarking comparison of three iSCST platforms capable of analyzing FFPE specimens. We analyzed FFPE mucosal biopsies (n=57) up to 5 years old from non-IBD controls (HC; n=9) and patients with ulcerative colitis (UC;n=11). After platform-specific cell segmentation, we applied a uniform data processing pipeline to all datasets, including transcript detection, cell annotation, differential gene expression, and neighborhood enrichment. Transcriptomic signatures identified with iSCST were validated using external, publicly available bulk transcriptomic datasets. A custom 290-plex Xenium gene panel exhibited the highest sensitivity and specificity for transcript detection, enabling precise identification and quantification of diverse cell subsets and differentially expressed genes across cell types and disease states. We mapped transcriptionally distinct fibroblast subsets to discrete spatial locations and identified inflammation-associated fibroblasts (IAFs) and monocytes as a colitis-associated cellular neighborhood. We also identified signatures associated with Vedolizumab (VDZ) responsiveness. VDZ non-responders were characterized by an IAF-monocyte transcriptional signature, while responders exhibited enrichment of epithelial gene sets. Our optimized iSCST framework for archived FFPE biopsies provides unique advantages for assessing the role of colitis-associated cellular networks in routinely collected clinical samples. FFPE-based biomarkers could integrate with existing clinical workflows and potentially aid in risk-stratifying patients.

Human immune systems are highly variable, with most variation attributable to non-genetic sources. The gut microbiome crucially shapes the immune system; however, its relationship with the baseline immune states of healthy humans remains incompletely understood. Therefore, we performed multi-omic profiling of 110 healthy participants through the ImmunoMicrobiome study. A factor-based integrative approach identified coordinated variation, revealing that the tonic interferon response was amongst the most variable immune features in healthy participants. Microbiome composition, pathways, and stool metabolites varied concomitantly with interferon response pathways. Distinct transcriptional programs involving inflammation and TGF-β in SIGLEC-1 monocytes and CD69 activated MAIT and NK cells were representative of these programs. Our study provides extensive data to examine the relationship between the immune states and microbiomes of healthy individuals at steady state, which paves the way for delineating inter-individual differences relevant for disease susceptibility and responses to therapy.

CD8+ T cell responses are critical for anti-tumor immunity. While extensively profiled in the tumor microenvironment (TME), recent studies in mice identified responses in lymph nodes (LN) as essential; however, the role of LN in human cancer patients remains unknown. We examined CD8+ T cells in human head and neck squamous cell carcinomas, regional LN, and blood using mass cytometry, single-cell genomics, and multiplexed ion beam imaging. We identified progenitor exhausted CD8+ T cells (Tpex) that were abundant in uninvolved LN and clonally related to terminally exhausted cells in the TME. After anti-PD-L1 immunotherapy, Tpex in uninvolved LN reduced in frequency but localized near dendritic cells and proliferating intermediate-exhausted CD8+ T cells (Tex-int), consistent with activation and differentiation. LN responses coincided with increased circulating Tex-int. In metastatic LN, these response hallmarks were impaired by immunosuppressive cellular niches. Our results identify important roles for LN in anti-tumor immune responses in humans.Competing Interest StatementW.E.G. is an employee of Genentech/Roche. M.F.K. is senior advisor and founder of Foundery Immune Studios. M.A. is an inventor on patents related to MIBI technology. M.A. is a consultant, board member, and shareholder in Ionpath Inc. M.H.S. is founder and a board member of Teiko Bio. M.F.K., L.F., A.P.A., P.H., and M.H.S. received research funding from Roche/Genentech.