Faculty Bibliography

The development of dendritic cells (DCs), including antigen-presenting conventional DCs (cDCs) and cytokine-producing plasmacytoid DCs (pDCs), is controlled by the growth factor Flt3 ligand (Flt3L) and its receptor Flt3. We genetically dissected Flt3L-driven DC differentiation using CRISPR-Cas9-based screening. Genome-wide screening identified multiple regulators of DC differentiation including subunits of TSC and GATOR1 complexes, which restricted progenitor growth but enabled DC differentiation by inhibiting mTOR signaling. An orthogonal screen identified the transcriptional repressor Trim33 (TIF-1γ) as a regulator of DC differentiation. Conditional targeting in vivo revealed an essential role of Trim33 in the development of all DCs, but not of monocytes or granulocytes. In particular, deletion of Trim33 caused rapid loss of DC progenitors, pDCs, and the cross-presenting cDC1 subset. Trim33-deficient Flt3⁺ progenitors up-regulated pro-inflammatory and macrophage-specific genes but failed to induce the DC differentiation program. Collectively, these data elucidate mechanisms that control Flt3L-driven differentiation of the entire DC lineage and identify Trim33 as its essential regulator.

RATIONALE & OBJECTIVE/UNASSIGNED:While urine excretion of nitrogen estimates the total protein intake, biomarkers of specific dietary protein sources have been sparsely studied. Using untargeted metabolomics, this study aimed to identify serum metabolomic markers of 6 protein-rich foods and to examine whether dietary protein-related metabolites are associated with incident chronic kidney disease (CKD). STUDY DESIGN/UNASSIGNED:Prospective cohort study. SETTING & PARTICIPANTS/UNASSIGNED:A total of 3,726 participants from the Atherosclerosis Risk in Communities study without CKD at baseline. EXPOSURES/UNASSIGNED:Dietary intake of 6 protein-rich foods (fish, nuts, legumes, red and processed meat, eggs, and poultry), serum metabolites. OUTCOMES/UNASSIGNED:with ≥25% estimated glomerular filtration rate decline relative to visit 1, hospitalization or death related to CKD, or end-stage kidney disease). ANALYTICAL APPROACH/UNASSIGNED:Multivariable linear regression models estimated cross-sectional associations between protein-rich foods and serum metabolites. C statistics assessed the ability of the metabolites to improve the discrimination of highest versus lower 3 quartiles of intake of protein-rich foods beyond covariates (demographics, clinical factors, health behaviors, and the intake of nonprotein food groups). Cox regression models identified prospective associations between protein-related metabolites and incident CKD. RESULTS/UNASSIGNED:). LIMITATIONS/UNASSIGNED:Residual confounding and sample-storage duration. CONCLUSIONS/UNASSIGNED:We identified candidate biomarkers of fish, nuts, red and processed meat, eggs, and poultry. A fish-related metabolite, 1-docosahexaenoylglycerophosphocholine (22:6n3), was associated with a lower risk of CKD.

Loss-of-function mutations in KEAP1 frequently occur in lung cancer and are associated with poor prognosis and resistance to standard of care treatment, highlighting the need for the development of targeted therapies. We previously showed that KEAP1 mutant tumors consume glutamine to support the metabolic rewiring associated with NRF2-dependent antioxidant production. Here, using preclinical patient-derived xenograft models and antigenic orthotopic lung cancer models, we show that the glutamine antagonist prodrug DRP-104 impairs the growth of KEAP1 mutant tumors. We find that DRP-104 suppresses KEAP1 mutant tumors by inhibiting glutamine-dependent nucleotide synthesis and promoting antitumor T cell responses. Using multimodal single-cell sequencing and ex vivo functional assays, we demonstrate that DRP-104 reverses T cell exhaustion, decreases T_regs, and enhances the function of CD4 and CD8 T cells, culminating in an improved response to anti-PD1 therapy. Our preclinical findings provide compelling evidence that DRP-104, currently in clinical trials, offers a promising therapeutic approach for treating patients with KEAP1 mutant lung cancer.

Self-supervised learning (SSL) automates the extraction and interpretation of histopathology features on unannotated hematoxylin-and-eosin-stained whole-slide images (WSIs). We trained an SSL Barlow Twins-encoder on 435 TCGA colon adenocarcinoma WSIs to extract features from small image patches. Leiden community detection then grouped tiles into histomorphological phenotype clusters (HPCs). HPC reproducibility and predictive ability for overall survival was confirmed in an independent clinical trial cohort (N=1213 WSIs). This unbiased atlas resulted in 47 HPCs displaying unique and sharing clinically significant histomorphological traits, highlighting tissue type, quantity, and architecture, especially in the context of tumor stroma. Through in-depth analysis of these HPCs, including immune landscape and gene set enrichment analysis, and association to clinical outcomes, we shed light on the factors influencing survival and responses to treatments like standard adjuvant chemotherapy and experimental therapies. Further exploration of HPCs may unveil new insights and aid decision-making and personalized treatments for colon cancer patients.

BACKGROUND:Chronic kidney disease (CKD) has been implicated as a risk factor for venous thromboembolism, but the evidence is limited to relatively healthy populations. The objective of the current study was to discern whether parameters of kidney function and damage are associated with the occurrence of venous thromboembolism after hospitalization. METHODS:We conducted a retrospective study including 23,899 and 11,552 adult individuals hospitalized within Geisinger Health System and NYU Langone Health from 2004 to 2019 and 2012 to 2022, respectively. A Poisson model was used to evaluate adjusted incidence rates of venous thromboembolism according to estimated glomerular filtration rate (eGFR) and albuminuria categories in each cohort. Cox proportional hazards models were used to analyze associations of eGFR and urinary albumin to creatinine ratio (UACR) with venous thromboembolism and hazard ratios were meta-analyzed across cohorts. RESULTS:Both lower eGFR and higher UACR were associated with higher risks of venous thromboembolism. In the Geisinger cohort, the incidence of venous thromboembolism after hospital discharge ranged from 10.7 (95% CI 9.2 - 12.6) events per 1000 person-years in individuals in G1A1 (eGFR >90 mL/min/1.73 m2 and UACR <30 mg/g) to 27.7 (95% CI 20.6 - 37.2) events per 1000 person-years in individuals with G4-5A3 (eGFR <30 mL/min/1.73 m2 and UACR >300 mg/g). A similar pattern was observed in the NYU cohort. Meta-analyses of the two cohorts showed that every 10 mL/min/1.73m2 reduction in eGFR below 60 mL/min/1.73m2 was associated with a 6% higher risk of venous thromboembolism (HR 1.06 [1.02 - 1.11], P = 0.01), and each two-fold higher UACR was associated with a 5% higher risk of venous thromboembolism (HR 1.05 [1.03 - 1.07], P <0.001). CONCLUSIONS:Both eGFR and UACR were independently associated with higher risk of venous thromboembolism after hospitalization. The incidence rate was higher with greater severity of CKD.

BACKGROUND/UNASSIGNED:), which may be less accurate in older adults. OBJECTIVE/UNASSIGNED:) and 8 outcomes. DESIGN/UNASSIGNED:Population-based cohort study. SETTING/UNASSIGNED:Stockholm, Sweden, 2010 to 2019. PARTICIPANTS/UNASSIGNED:82 154 participants aged 65 years or older with outpatient creatinine and cystatin C testing. MEASUREMENTS/UNASSIGNED:Hazard ratios for all-cause mortality, cardiovascular mortality, and kidney failure with replacement therapy (KFRT); incidence rate ratios for recurrent hospitalizations, infection, myocardial infarction or stroke, heart failure, and acute kidney injury. RESULTS/UNASSIGNED:, and for KFRT they were 2.6 (CI, 1.2 to 5.8) and 1.4 (CI, 0.7 to 2.8), respectively. Similar findings were observed in subgroups, including those with a urinary albumin-creatinine ratio below 30 mg/g. LIMITATION/UNASSIGNED:No GFR measurements. CONCLUSION/UNASSIGNED:was more strongly associated with adverse outcomes and the associations were more uniform. PRIMARY FUNDING SOURCE/UNASSIGNED:Swedish Research Council, National Institutes of Health, and Dutch Kidney Foundation.

In type 2 diabetes (T2D), the dawn phenomenon is an overnight glucose rise recognized to contribute to overall glycemia and is a potential target for therapeutic intervention. Existing CGM-based approaches do not account for sensor error, which can mask the true extent of the dawn phenomenon. To address this challenge, we developed a probabilistic framework that incorporates sensor error to assign a probability to the occurrence of dawn phenomenon. In contrast, the current approaches label glucose fluctuations as dawn phenomena as a binary yes/no. We compared the proposed probabilistic model with a standard binary model on CGM data from 173 participants (71% female, 87% Hispanic/Latino, 54 ± 12 years, with either a diagnosis of T2D for six months or with an elevated risk of T2D) stratified by HbA_1c levels into normal but at risk for T2D, with pre-T2D, or with non-insulin-treated T2D. The probabilistic model revealed a higher dawn phenomenon frequency in T2D [49% (95% CI 37-63%)] compared to pre-T2D [36% (95% CI 31-48%), p = 0.01] and at-risk participants [34% (95% CI 27-39%), p < 0.0001]. While these trends were also found using the binary approach, the probabilistic model identified significantly greater dawn phenomenon frequency than the traditional binary model across all three HbA_1c sub-groups (p < 0.0001), indicating its potential to detect the dawn phenomenon earlier across diabetes risk categories.

BACKGROUND/UNASSIGNED:Identifying patients with the optimal risk:benefit for ticagrelor is challenging. The aim was to identify ticagrelor-responsive platelet transcripts as biomarkers of platelet function and cardiovascular risk. METHODS/UNASSIGNED:Healthy volunteers (n=58, discovery; n=49, validation) were exposed to 4 weeks of ticagrelor with platelet RNA data, platelet function, and self-reported bleeding measured pre-/post-ticagrelor. RNA sequencing was used to discover platelet genes affected by ticagrelor, and a subset of the most informative was summarized into a composite score and tested for validation. This score was further analyzed (1) in CD34+ megakaryocytes exposed to an P2Y12 inhibitor in vitro, (2) with baseline platelet function in healthy controls, (3) in peripheral artery disease patients (n=139) versus patient controls (n=30) without atherosclerosis, and (4) in patients with peripheral artery disease for correlation with atherosclerosis severity and risk of incident major adverse cardiovascular and limb events. RESULTS/UNASSIGNED:Ticagrelor exposure differentially expressed 3409 platelet transcripts. Of these, 111 were prioritized to calculate a Ticagrelor Exposure Signature score, which ticagrelor reproducibly increased in discovery and validation cohorts. Ticagrelor's effects on platelets transcripts positively correlated with effects of P2Y12 inhibition in primary megakaryocytes. In healthy controls, higher baseline scores correlated with lower baseline platelet function and with minor bleeding while receiving ticagrelor. In patients, lower scores independently associated with both the presence and extent of atherosclerosis and incident ischemic events. CONCLUSIONS/UNASSIGNED:Ticagrelor-responsive platelet transcripts are a biomarker for platelet function and cardiovascular risk and may have clinical utility for selecting patients with optimal risk:benefit for ticagrelor use.