Billadeau, Daniel D.

TRAIL is a TNF family ligand that trimerizes TRAIL-R1 (DR4) or TRAIL-R2 (DR5) to induce apoptosis, necroptosis, and/or NF-κB activation in receptor-bearing cells. We previously identified TRAILshort as a splice variant of TRAIL that lacks cysteine 230, cannot trimerize, and acts as a dominant-negative ligand that blocks TRAIL-mediated apoptosis. TRAILshort is expressed on cell surfaces and within extracellular vesicles, enabling it to confer TRAIL resistance to both producing and bystander cells. In this study, we showed that elevated TRAILshort levels were associated with chronic viral infections, cancer, and autoimmune diseases, suggesting a link to impaired immune regulation. Using unbiased phosphoproteomics and mechanistic studies, we demonstrated that TRAILshort binding to DR5 recruited and activated the phosphatase Src homology region 2 domain–containing phosphatase 1 (SHP-1), leading to zeta-chain-associated protein kinase 70 (ZAP-70) dephosphorylation, disruption of ZAP-70–CD3ζ interactions, and impaired T cell receptor signaling, thereby reducing T cell activation, proliferation, and cytokine production in response to antigen or CD3/CD28 ligation. Genetic or pharmacologic SHP-1 inhibition reverses these effects. In humanized mouse models, TRAILshort promoted the persistence of transformed mouse embryonic fibroblasts (MEFs) and L428 and antagonized CD19-directed CAR T cell activity, revealing TRAILshort as an immunomodulator of T cell function with therapeutic implications, including blocking TRAILshort to restore T cell immunity or delivering TRAILshort to enforce tolerance. TRAILshort, a variant of TRAIL, suppresses T cell function and immune responses in cancer and infectious diseases, highlighting its potential as a therapeutic target.

TAF7, a core subunit of the general transcription factor TFIID, regulates transcription and additionally functions as an RNA chaperone that directs nascent nuclear RNAs to cytoplasmic polysomes, thereby influencing protein synthesis. Here, we identify a set of novel cytoplasmic interactors and a previously unappreciated cytoplasmic role for TAF7 in oncogenesis. BioID-mediated proximity labeling identified STAT3 and the CCT and WASH complexes as prominent cytoplasmic interactors of TAF7. These interactions were validated by co-immunoprecipitation and proximity ligation assays. We further showed that cytoplasmic TAF7 levels increased during oncogenesis in proportion to cancer cell pathogenicity. Notably, TAF7 engagement with STAT3, CCT and WASH complexes is markedly enhanced during cellular transformation, consistent with their functions in cancer progression. Together, these findings reveal a cytoplasmic TAF7 interactome and implicate elevated cytoplasmic TAF7 as associated with oncogenesis.

Human diseases are complex and arise from the coordinated action of multiple genes and their protein products. Genes’ behaviors extend beyond genetic variants, mutations, and differential expressions. Their coordinated activity across biological scales (molecules, cells, tissues, organs) produces emergent behaviors that shape health and disease. These emergent behaviors span time and space and are often hard to measure directly from observation when using standard experimental measurements. Yet these “hidden” or latent gene characteristics can be powerful drivers of disease. We propose a Mini-Galaxy Model (MGM), a systems-level AI-driven network framework that models cells as “mini-galaxies” composed of multilayered biological information, with each layer encoding a different dimension of genes’ behavior. Here, we delineate a strategy on how to construct and compare MGMs across health and disease and map their etiological relatedness. We also operationalize the MGM as a discovery platform for translational medicine, offering modules to allow target prioritization and editing. By reframing human diseases as the result of emergent behavior of multilayered multimode biological networks and their perturbations, the MGM yields actionable rules to streamline biomarker discovery, guide target selection and enable rational design of combinatorial interventions, and accelerate drug repurposing.

ABSTRACT Cytotoxic T lymphocytes (CTLs) are known to eliminate target cells through perforin-mediated, contact-dependent killing - a process limited by the number of effector T cells despite its serial nature. CTLs likely also possess a mass killing mechanism that can eliminate target cells more efficiently. Using CAR-T cells against B7H3 present on B16 tumor targets, we demonstrate that activated T cells can also kill targets in a perforin-independent manner by releasing diffusible TNF and IFNγ capable of killing nearby targets in a paracrine fashion even if they bear no antigen. Against an unperturbed target, paracrine killing is inefficient but is enhanced by the deletion of TNFR1 signaling molecules such as TAK1, HOIP, or TBK1/IKKε. Notably, these molecules are inhibited naturally by pathogen-encoded antagonists. Expression of a microbial-encoded antagonist, such as the Yersinia -encoded YopJ that antagonizes TAK1 or Ebola-encoded VP35 that antagonizes TBK1/IKKε, alters the target cell response to these cytokines from non-lethal to lethal. We propose that target cells are inherently resistant to killing by TNF and IFNγ, but the presence of a microbial factor alters this sensitivity, providing for the selective elimination of the infected cell while minimizing harm to uninfected bystander cells. We propose the term ‘pathogen-restriction’ to describe this discriminatory mechanism. Potentially, any microbial-derived factor that crosstalks with the TNF and IFNγ signaling pathways can function as a pathogen-restriction element. GRAPHICAL ABSTRACT Short Summary T cells use TNF and IFNγ to kill target cells in a paracrine manner where target elimination is restricted by the presence of pathogen-derived factors.

Abstract Description B7-H3 is a member of the B7 superfamily, which includes co-inhibitory receptors such as B7-H1/PD-L1 and co-stimulatory receptors such as B7-1/CD80 and B7-2/CD86. B7-H3 is upregulated by almost all types of tumors and is associated with worse prognosis. However, the exact mechanism by which B7-H3 suppresses anti-tumor immune response remains to be discovered as its ligand has yet to be identified. Sialic acid modifications are also increased in many cancers and are similarly associated with poor outcome. Here, we demonstrate for the first time that sialylated B7-H3 binds to the immune inhibitory receptor Siglec-9. Siglec-9 is expressed on many immune cells, including NK cells and T cells. We have shown that B7-H3 expression on target cells reduces killing by Siglec-9 expressing NK cells in vitro. We then hypothesized that antibodies that block B7-H3 binding to Siglec-9 will be an effective intervention to boost anti-tumor immunity. We have generated a high affinity anti-B7-H3 monoclonal antibody, F7, which blocks B7-H3 binding to Siglec-9. F7 functions to enhance NK cell killing of B7-H3 expressing target cells in vitro. F7 also dramatically enhances CART19 mediated killing of B7-H3 expressing Nalm6 cells in a relapse model in NSG mice in vivo. In summary, our work has demonstrated that B7-H3 binds Siglec-9, and blockade of such interaction can enhance anti-tumor immunity. Funding Sources • Mayo Clinic Center for Biomedical Discovery • NIH Glycobiology Common Fund supplement to R01CA243545-01A1 to VSS Topic Categories Tumor Immunology: Checkpoints, Prevention, and Treatment (TIPT)

Clinical trial enrichment is the targeted recruitment of prospective individual patients with defined clinical characteristics who are likely to benefit from newly developed or repurposed drugs. This process is central to the success of clinical trials together with patient management and regulatory compliance. A main challenge in clinical trial enrichment lies in the recognition of a priori clinical parameters and information that informs drug efficacy or toxicity, particularly when intended for a broader unseen population. Although Artificial Intelligence (AI) approaches, especially large language models (LLMs), have been employed in many aspects of clinical trials, to our knowledge, there is no AI method that has been developed which offers a prospective prediction and assesses the extent to which a given therapeutic intervention benefits an unseen population. Here, we offer an outlook on how to build Artificial Clinic Intelligence (ACI), a generative AI (GAI)-powered modeling platform for modeling clinical trial enrichment. ACI generates synthetic patient data and models clinical trial enrichment to inform clinicians on key clinical parameters that are enriched in prospective patients prior to accrual.

Abstract BACKGROUND Intraductal papillary mucinous neoplasm (IPMN) is one of the two most common precursor lesions leading to the development of pancreatic ductal adenocarcinoma (PDA). IPMNs comprise a heterogeneous group of tumors with a wide range of grades and histotypes, and the emergence of single-cell RNA sequencing (RNA-seq) and multiplex digital spatial profiling have characterized unique cell populations, including dysplastic epithelial and immune cells, within the heterogeneous tumor microenvironment that carry signature gene expressions, which could be used as markers for disease progression. However, it is not clear on the heterogeneity of the epithelial and immune response of the evolution during progression of IPMN to PDA. OBJECTIVE Combining nuclear GSK-3β with oncogenic KRas mice (referred to as KNGC – KRas, nuclear GSK-3β, Cre) resulted in the development of IPMN. We have found that 4-week-old KNGC mice show progressive desmoplasia and ductal lesion development with increased M2-like macrophage infiltration. Interestingly, CX3CL1 (fractalkine), a chemokine involved in the recruitment of CX3CR1-expressing monocytes and M2-like macrophage conversion in various disease models is expressed by IPMN progenitor ductal cells. We aim to investigate expression and contribution of CX3CL1-CX3CL1 axis in the development and progression of IPMN. METHODS We utilized a newly generated CX3CL1-mCherry and well-established CX3CR1-GFP knockin/knockout mouse for crossbreeding with KNGC and KGC (KRas, GNas, Cre) for lineage tracing and function analysis by immunofluorescent staining, flow cytometry and CyTOF. RESULTS Both KNGC- and KGC-3LmCherry/+ mice harbor a large population of CX3CL1-mCherry/EPCAM+ epithelial cells as compared to 3LmCherry/+ and wildtype (WT) control mice. In KNGC and KGC mice, we show that there was a unique population of macrophages (CD45+ CD11b+ Ly6G- F4/80+ Ly6c- ) with significantly higher expression of CX3CR1 (CX3CR1Hi) that was not seen in WT mice. Significantly, Knockout of CX3CR1 in KNGC-3RGFP/GFP animals had a paucity of M2-like macrophages, reduced T regulatory cells (Tregs), substantially reduced desmoplasia and impaired development of IPMN. CONCLUSIONS The study provides important knowledge regarding the role of CX3CL1-CX3CR1 axis in recruitment and generation of M2-like macrophages, and their impact on the initiation of the immune/stroma microenvironment facilitating IPMN development. Further investigations using these models have the potential to identify new biomarkers for risk stratification and therapeutic intervention. Citation Format: Li Ding, Kaely Roeck, Easton Maeder, Cheng Zhang, Taylor Weiskittel, Esther Rodman, Mark Maynes, Bibo Zhu, Aaron Johnson, Jie Sun, Li Hu, Daniel Billadeau. Uncoupling CX3CL1-CX3CR1 Axis in IPMN Development Through Transgenic Mouse Models [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr A064.

Abstract Purpose: Germline pathogenic variants (PV) in ATM increase the risk of pancreatic ductal adenocarcinoma (PDAC), but the underlying tumor biology of PDAC associated with germline PV in ATM has not been adequately explored. Experimental Design: Whole-genome, whole-exome, and RNA sequencing were performed on PDAC tumors from 25 germline ATM PV carriers diagnosed at Mayo Clinic between 2007 and 2017. Somatic and copy-number alterations, mutational signatures, transcriptomic subtypes, and the immune landscape were evaluated. Results: High-quality whole-exome and whole-genome sequencing were obtained from 21 and 15 tumors, respectively. Biallelic inactivation of ATM was observed in 87%, KRAS PV in 90%, CDKN2A homozygous loss in 60%, and TP53 alterations in <10% of these tumors. A predominant clock-like mutational signature was present in all samples. Whole-transcriptome analysis identified that the aberrantly differentiated endocrine exocrine subtype accounted for 18% of PDAC and was consistently associated with >5-year overall survival. In addition, a 28-gene expression–based signature associated with overall survival was identified and further validated in The Cancer Genome Atlas cohort. Immune landscape analysis through CODEX identified enriched CD4 T-helper cell/tumor interactions and reduced B7H3-high cell/tumor interactions in ATM PV carriers compared with noncarriers. Conclusions: The observed absence of TP53 PV and enrichment for CDKN2A alterations in ATM tumors, along with differences in the mutational signatures, transcriptomic subtypes and immune landscape, improve our understanding of the mechanistic pathways involved in PDAC development in germline ATM PV carriers and help identify potential targeted therapeutic strategies.