Citations

Abstract In this study, we harnessed immunomodulatory Siglec-sialic acid interactions to mitigate autoimmune rejection of beta cells in Type 1 Diabetes (T1D). Mice engineered to express the sialyltransferase ST8Sia6 in beta cells (βST mice) were backcrossed to the non-obese diabetic mouse model of T1D and followed for disease; 60% of female littermates spontaneously developed diabetes by 300 days, compared to minimal occurrence (5%) in female βST mice. Histologic analysis of pancreas sections from non-diabetic βST and littermate mice suggested a similar degree of immune infiltration at 4 and 8 weeks of age, but the severity of insulitis was drastically reduced in βST mice beyond 20 weeks of age as compared to littermates. IHC for various immune populations suggested no difference in composition of insulitis at 8 weeks between βST and littermate mice. ELISA for serum anti-insulin antibodies demonstrated no difference in concentration between female βST and littermate mice. After female euglycemic βST and littermate mice at 16 weeks of age were challenged with anti-PD-L1 monoclonal antibodies, both groups resulted in similarly rapid induction of disease, suggesting that ST8Sia6 dependent protection occurs peripherally. Shut-off of ST8Sia6 expression in euglycemic βST mice at 20 weeks of age did not abrogate protection from disease, supporting persistent immune tolerance beyond this time. Flow analysis of islet infiltrating immune cells at 300 days confirmed reduced number of infiltrating immune cells in βST mice. Thus, induced expression of ST8Sia6 has been shown to mitigate autoimmune attack in the NOD mouse and presents a novel path forward for improving the success of curative islet transplant into T1D patients. Supported by funding from the Mayo Clinic (Mayo Clinic Center for Biomedical Discovery, Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic MSTP) and the NIH (5R21AI135858-02, 1F30DK127564). Supported by funding from the Mayo Clinic (Mayo Clinic Center for Biomedical Discovery, Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic MSTP) and the NIH (5R21AI135858-02, 1F30DK127564).

Abstract Inhibitory receptors have a critical role in the regulation of immunity. Siglecs are a family of primarily inhibitory receptors expressed by immune cells, which recognize specific sialic acid modifications on cell surface glycans. Sialyltransferases are the enzymes that catalyzing the addition of sialic acids onto glycoproteins and glycolipids. Siglec-E binds to α2,8-linked disialic acids, generated by the enzyme ST8Sia6 on O-linked glycoproteins and functions to inhibit activation of innate immune cells. Many tumors have increased sialic acid incorporation. Overexpression of the sialyltransferase ST8Sia6 on tumors led to altered macrophage polarization and increased tumor growth through engagement of ligands generated by ST8Sia6 with Siglec-E. Here, we examine the role of ST8Sia6 on immune cells in regulating anti-tumor immunity. The loss of ST8Sia6 in tumor bearing mice reduced tumor growth, increased survival, and altered the immune response as compared to ST8Sia6 sufficient tumor bearing mice. Using MC38, B16, and B16-OVA flank tumor mouse models, tumor growth was decreased in ST8Sia6 KO mice as compared to C57Bl/6 mice. Within the tumor microenvironment of tumors present in ST8Sia6 KO mice compared to tumors present in C57Bl/6 mice, macrophages and dendritic cells altered their phenotype towards enhanced immune activation. Tregs from tumors in ST8Sia6 KO mice also displayed an increase in RORγt and a reduction in TNFRII, suggesting a possible shift to a less suppressive Treg. These alterations in the immune response to tumors were due to the loss of ST8Sia6 in macrophages and dendritic cells and not T-cells. Thus, ST8Sia6 generates ligands for Siglecs that dampen anti-tumor immunity. Supported by grants from NIH (R01CA243545, 2T32AI007425) and Mayo Clinic Center of Biomedical Discovery

Abstract Tumor antigen-specific T-cell tolerance is a critical element of tumor escape. It is known that MDSC can induce antigen-specific CD8+ T cell tolerance in an experimental system with adoptive transfer of transgenic T cells. In this study we addressed the critical question whether a similar phenomenon can be observed in a "natural" non-transgenic experimental model. Balb/C mice were subcutaneously inoculated with two different tumor cell lines, a derivative A2L2 cell line, which expresses high levels of HER2/neu and the parental cell line 66.3. HER2/neu specific CD8+T cells were generated by immunization of mice with peptide. MDSC were able to tolerize antigen-specific T cells in vivo if they were collected from A2L2 but not from 66.3 tumor-bearing mice indicating the tumor-specific nature of T cell tolerance induced by MDSC. Next we investigated the type of signaling caused by MDSC in CD8+T cells that could lead to tolerance. MDSC dramatically reduced the ability of CD8+ T cells to respond to the specific peptide. However, study of various signaling molecules using different experimental systems and tests found that MDSC did not induce negative signaling in T cells. This conclusion was confirmed in adoptive transfer experiments with CD8+T cells expressing dual TCR: LCMV glycoprotein peptide gp33-41 and OVA-derived H-2Kb-restricted peptide ova257-264. We found that MDSC loaded with peptide specific for one TCR induced tolerance only against that specific epitope but CD8+ T cells retained the ability to respond to the peptide specific for the other TCR expressed on the same cell.

Abstract Purpose: We sought to identify biomarkers that predict overall survival (OS) and response to immune checkpoint inhibitors (ICI) for patients with gastric cancer. Experimental Design: This was a retrospective study of multiple independent cohorts of patients with gastric cancer. The association between tumor ACTA2 expression and OS and ICI response were determined in patients whose tumors were analyzed with bulk mRNA sequencing. Single-cell RNA sequencing (scRNA-seq) and digital spatial profiling data were used to compare tumors from patients with gastric cancer who did and did not respond to ICI. Results: Increasing tumor ACTA2 expression was independently associated with worse OS in a 567-patient discovery cohort [HR, 1.28 per unit increase; 95% confidence interval (CI), 1.02–1.62]. This finding was validated in three independent cohorts (n = 974; HR, 1.52 per unit increase; 95% CI, 1.34–1.73). Of the 108 patients treated with ICI, 56% of patients with low ACTA2 expression responded to ICI versus 25% of patients with high ACTA2 expression (P = 0.004). In an analysis of a publicly available scRNA-seq dataset of 5 microsatellite instability-high patients treated with ICI, the patient who responded to ICI had lower tumor stromal ACTA2 expression than the 4 nonresponders. Digital spatial profiling of tumor samples from 4 ICI responders and 5 ICI nonresponders revealed that responders may have lower ACTA2 expression in α-SMA–positive cancer-associated fibroblasts (CAF) than nonresponders (median: 5.00 vs. 5.50). Conclusions: ACTA2 expression is associated with survival and ICI response in patients with gastric cancer. ACTA2 expression in CAFs, but not in other cellular compartments, appears to be associated with ICI response.

Background and Objectives: The number of patients who undergo multiple operations on a knee is increasing. The objective of this study was to develop a deep learning algorithm that could detect 17 different surgical implants on plain knee radiographs. Materials and Methods: An internal dataset consisted of 5206 plain knee antero-posterior X-rays from a single, tertiary institute for model development. An external set contained 238 X-rays from another tertiary institute. A total of 17 different types of implants including total knee arthroplasty, unicompartmental knee arthroplasty, plate, and screw were labeled. The internal dataset was approximately split into a train set, a validation set, and an internal test set at a ratio of 7:1:2. You Only look Once (YOLO) was selected as the detection network. Model performances with the validation set, internal test set, and external test set were compared. Results: Total accuracy, total sensitivity, total specificity value of the validation set, internal test set, and external test set were (0.978, 0.768, 0.999), (0.953, 0.810, 0.990), and (0.956, 0.493, 0.975), respectively. Means ± standard deviations (SDs) of diagonal components of confusion matrix for these three subsets were 0.858 ± 0.242, 0.852 ± 0.182, and 0.576 ± 0.312, respectively. True positive rate of total knee arthroplasty, the most dominant class of the dataset, was higher than 0.99 with internal subsets and 0.96 with an external test set. Conclusion: Implant identification on plain knee radiographs could be automated using a deep learning technique. The detection algorithm dealt with overlapping cases while maintaining high accuracy on total knee arthroplasty. This could be applied in future research that analyzes X-ray images with deep learning, which would help prompt decision-making in clinics.

AbstractAimsAn artificial intelligence algorithm detecting age from 12-lead electrocardiogram (ECG) has been suggested to reflect ‘physiological age’. An increased physiological age has been associated with a higher risk of cardiac mortality in the non-transplant population. We aimed to investigate the utility of this algorithm in patients who underwent heart transplantation (HTx).Methods and resultsA total of 540 patients were studied. The average ECG ages within 1 year before and after HTx were used to represent pre- and post-HTx ECG ages. Major adverse cardiovascular event (MACE) was defined as any coronary revascularization, heart failure hospitalization, re-transplantation, and mortality. Recipient pre-transplant ECG age (mean 63 ± 11 years) correlated significantly with recipient chronological age (mean 49 ± 14 years, R = 0.63, P < 0.0001), while post-transplant ECG age (mean 54 ± 10 years) correlated with both the donor (mean 32 ± 13 years, R = 0.45, P < 0.0001) and the recipient ages (R = 0.38, P < 0.0001). During a median follow-up of 8.8 years, 307 patients experienced MACE. Patients with an increase in ECG age post-transplant showed an increased risk of MACE [hazard ratio (HR): 1.58, 95% confidence interval (CI): (1.24, 2.01), P = 0.0002], even after adjusting for potential confounders [HR: 1.58, 95% CI: (1.19, 2.10), P = 0.002].ConclusionElectrocardiogram age-derived cardiac ageing after transplantation is associated with a higher risk of MACE. This study suggests that physiological age change of the heart might be an important determinant of MACE risk post-HTx.

INTRODUCTION: We recently developed a fluorescence in situ hybridization probe set for evaluating suspicious biliary and pancreatic duct strictures (PB-FISH). We aimed to determine whether PB-FISH results in biliary brush cytology specimens are associated with outcomes of patients with cholangiocarcinoma (CCA). METHODS: We performed a retrospective study of patients with CCA tested by PB-FISH from January 2015 to August 2018. CCA was stratified by primary sclerosing cholangitis (PSC) into those with (PSC CCA) or without PSC ( de novo CCA). PB-FISH results were categorized as polysomy (gain of multiple loci), nonpolysomy (single locus gain, single locus gain with 9p21 loss, homozygous 9p21 loss, tetrasomy), and disomy (no abnormalities). Overall survival (OS) was estimated using Kaplan-Meier methods and compared between the PB-FISH results using log-rank tests. Cox models were adjusted for age, sex, CA 19-9, cytology results, source of brushing sample, and treatments. RESULTS: Characteristics of 264 eligible patients (median age 60.4; range 18–92) were comparable for patients with PB-FISH polysomy vs nonpolysomy vs disomy. The median OS was similar between disomy, nonpolysomy, and polysomy in the overall population (22.7 vs 22.7 vs 20.3 months, respectively). For de novo CCA, both polysomy and nonpolysomy were associated with worse OS compared with disomy (polysomy: hazard ratio [HR] = 2.09, 95% confidence interval [CI] = 1.14–3.83; nonpolysomy: HR = 2.4, 95% CI = 0.54–2.46; P = 0.027). For PSC CCA, neither polysomy nor nonpolysomy were significantly associated with worse OS (polysomy: 0.90, 95% CI = 0.47–1.75; nonpolysomy: HR = 1.78, CI = 0.71–4.49; P = 0.27). DISCUSSION: PB-FISH alterations are associated with worse survival in de novo CCA, though statistical significance was lost when adjusting for confounding variables.