Faculty Bibliography

SARS-CoV-2 infection and vaccination elicit potent immune responses. Our study presents a comprehensive multimodal single-cell analysis of blood from COVID-19 patients and healthy volunteers receiving the SARS-CoV-2 vaccine and booster. We profiled immune responses via transcriptional analysis and lymphocyte repertoire reconstruction. COVID-19 patients displayed an enhanced interferon signature and cytotoxic gene upregulation, absent in vaccine recipients. B and T cell repertoire analysis revealed clonal expansion among effector cells in COVID-19 patients and memory cells in vaccine recipients. Furthermore, while clonal αβ T cell responses were observed in both COVID-19 patients and vaccine recipients, expansion of clonal γδ T cells was found only in infected individuals. Our dataset enables side-by-side comparison of immune responses to infection versus vaccination, including clonal B and T cell responses. Our comparative analysis shows that vaccination induces a robust, durable clonal B and T cell responses, without the severe inflammation associated with infection.

IMPORTANCE:Biomarkers may improve prediction of cardiovascular events for patients with stable coronary artery disease (CAD), but their importance in addition to clinical tests of inducible ischemia and CAD severity is unknown. OBJECTIVES:To evaluate the prognostic value of multiple biomarkers in stable outpatients with obstructive CAD and moderate or severe inducible ischemia. DESIGN AND SETTING:The ISCHEMIA and ISCHEMIA CKD trials randomized 5,956 participants with CAD to invasive or conservative management from July 2012 to January 2018; 1,064 participated in the biorepository. MAIN OUTCOME MEASURES:Primary outcome was cardiovascular death, myocardial infarction (MI), or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest. Secondary outcome was cardiovascular death or MI. Improvements in prediction were assessed by cause-specific hazard ratios (HR) and area under the receiver operating characteristics curve (AUC) for an interquartile increase in each biomarker, controlling for other biomarkers, in a base clinical model of risk factors, left ventricular ejection fraction (LVEF) and ischemia severity. Secondary analyses were performed among patients in whom core-lab confirmed severity of CAD was ascertained by computed cardiac tomographic angiography (CCTA). EXPOSURES:Baseline levels of interleukin-6 (IL-6), high sensitivity troponin T (hsTnT), growth differentiation factor 15 (GDF-15), N-terminal pro-B-type natriuretic peptide (NT-proBNP), lipoprotein a (Lp[a]), high sensitivity C-reactive protein (hsCRP), Cystatin C, soluble CD 40 ligand (sCD40L), myeloperoxidase (MPO), and matrix metalloproteinase 3 (MMP3). RESULTS:Among 757 biorepository participants, median (IQR) follow-up was 3 (2-5) years, age was 67 (61-72) years, and 144 (19%) were female; 508 had severity of CAD by CCTA available. In an adjusted multimarker model with hsTnT, GDF-15, NT-proBNP and sCD40L, the adjusted HR for the primary outcome per interquartile increase in each biomarker was 1.58 (95% CI 1.22, 2.205), 1.60 (95% CI 1.16, 2.20), 1.61 (95% 1.22, 2.14), and 1.46 (95% 1.12, 1.90), respectively. The adjusted multimarker model also improved prediction compared with the clinical model, increasing the AUC from 0.710 to 0.792 (P < .01) and 0.714 to 0.783 (P < .01) for the primary and secondary outcomes, respectively. Similar findings were observed after adjusting for core-lab confirmed atherosclerosis severity. CONCLUSIONS AND RELEVANCE:Among ISCHEMIA biorepository participants, biomarkers of myocyte injury/distension, inflammation, and platelet activity improved cardiovascular event prediction in addition to risk factors, LVEF, and assessments of ischemia and atherosclerosis severity. These biomarkers may improve risk stratification for patients with stable CAD.

We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

Our previous studies identified a population of stem cell-like proliferating myeloid cells within inflamed tissues that could serve as a reservoir for tissue macrophages to adopt different activation states depending on the microenvironment. By lineage-tracing cells derived from CX3CR1+ precursors in mice during infection and profiling by single-cell RNA sequencing, in this study, we identify a cluster of BIRC5+ myeloid cells that expanded in the liver during chronic infection with either the parasite Schistosoma mansoni or the bacterial pathogen Staphylococcus aureus. In the absence of tissue-damaging toxins, S. aureus infection does not elicit these BIRC5+ cells. Moreover, deletion of BIRC5 from CX3CR1-expressing cells results in improved survival during S. aureus infection. Hence the combination of single-cell RNA sequencing and genetic fate-mapping CX3CR1+ cells revealed a toxin-dependent pathogenic role for BIRC5 in myeloid cells during S. aureus infection.

Both SARS-CoV-2 infection and vaccination elicit potent immune responses. A number of studies have described immune responses to SARS-CoV-2 infection. However, beyond antibody production, immune responses to COVID-19 vaccines remain largely uncharacterized. Here, we performed multimodal single-cell sequencing on peripheral blood of patients with acute COVID-19 and healthy volunteers before and after receiving the SARS-CoV-2 BNT162b2 mRNA vaccine to compare the immune responses elicited by the virus and by this vaccine. Phenotypic and transcriptional profiling of immune cells, coupled with reconstruction of the B and T cell antigen receptor rearrangement of individual lymphocytes, enabled us to characterize and compare the host responses to the virus and to defined viral antigens. While both infection and vaccination induced robust innate and adaptive immune responses, our analysis revealed significant qualitative differences between the two types of immune challenges. In COVID-19 patients, immune responses were characterized by a highly augmented interferon response which was largely absent in vaccine recipients. Increased interferon signaling likely contributed to the observed dramatic upregulation of cytotoxic genes in the peripheral T cells and innate-like lymphocytes in patients but not in immunized subjects. Analysis of B and T cell receptor repertoires revealed that while the majority of clonal B and T cells in COVID-19 patients were effector cells, in vaccine recipients clonally expanded cells were primarily circulating memory cells. Importantly, the divergence in immune subsets engaged, the transcriptional differences in key immune populations, and the differences in maturation of adaptive immune cells revealed by our analysis have far-ranging implications for immunity to this novel pathogen.

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

BACKGROUND:Psoriasis is an inflammatory skin disease associated with increased cardiovascular (CV) risk, whose pathogenesis is not fully known. OBJECTIVE:We identified a transcriptomic signature in psoriasis and investigated its association with prevalent and future risk of a CV event to understand the connection between psoriasis and CV disease (CVD). METHODS:Psoriasis patients (n = 37) with a history of moderate-severe skin disease without CVD and 11 matched controls underwent whole blood RNA sequencing. This transcriptomic signature in psoriasis versus controls was evaluated in two CVD cohorts: Women referred for cardiac catheterization with (n = 76) versus without (n = 97) myocardial infarction (MI), and patients with peripheral artery disease (n = 106) followed over 2.5 years for major adverse CV or limb events (MACLE). The association between genes differentially expressed in psoriasis and prevalent and incident CV events was assed. RESULTS:In psoriasis, median age was 44 (IQR; 34-51) years, 49% male and ACC/AHA ASCVD Risk Score of 1.0% (0.6-3.4) with no significant difference versus controls. The median psoriasis area and severity index score (PASI) was 4.0 (IQR 2.9-8.2) with 36% on biologic therapy. Overall, 247 whole blood genes were upregulated and 228 downregulated in psoriasis versus controls (p < 0.05), and 1302 genes positively and 1244 genes negatively correlated with PASI (p < 0.05). Seventy-three genes overlapped between psoriasis prevalence and PASI with key regulators identified as IL-6, IL-1β and interferon gamma. In the CVD cohorts, 50 of 73 genes (68%) identified in psoriasis associated with prevalent MI, and 29 (40%) with incident MACLE. Key regulator transcripts identified in psoriasis and CVD cohorts included SOCS3, BCL3, OSM, PIM2, PIM3 and STAT5A. CONCLUSIONS:A whole blood transcriptomic signature of psoriasis diagnosis and severity associated with prevalent MI and incident MACLE. These data have implications for better understanding the link between psoriasis, systemic inflammation and CVD.

Kinases are key players in cancer-relevant pathways and are the targets of many successful precision cancer therapies (1, 2). Phosphoproteomics is a powerful approach to study kinase activity and has been used increasingly for the characterization of tumor samples leading to the identification of novel chemotherapeutic targets and biomarkers (3-10). Finding co-regulated phosphorylation sites which represent potential kinase-substrate sets or members of the same signaling pathway allows us to harness this data to identify clinically relevant and targetable alterations in signaling cascades. Unfortunately, studies have found that databases of co-regulated phosphorylation sites (11, 12) are only experimentally supported in a small number of substrate sets (13, 14). To address the inherent challenge of defining co-regulated phosphorylation modules relevant to a given dataset, we developed PhosphoDisco, a toolkit for determining co-regulated phosphorylation modules. We applied this approach to tandem mass spectrometry based phosphoproteomic data for breast and non-small cell lung cancer and identified canonical as well as putative new phosphorylation site modules. Our analysis identified several interesting modules in each cohort. Among these was a new cell cycle checkpoint module enriched in basal breast cancer samples and a module of PRKC isozymes putatively co-regulated by CDK12 in lung cancer. We demonstrate that modules defined by PhosphoDisco can be used to further personalized cancer treatment strategies by establishing active signaling pathways in a given patient tumor or set of tumors, and in providing new ways to classify tumors based on signaling activity.

OBJECTIVE:Platelets are mediators of inflammation with immune effector cell properties, and have been implicated in the pathogenesis of systemic lupus erythematosus (SLE). This study investigated the role of platelet associated lectin galactoside-binding soluble 3 binding protein (LGALS3BP) as a mediator of inflammation in SLE, and a potential biomarker associated with clinical phenotypes. METHODS:We performed RNA sequencing on platelets of patients with SLE (n=54) and age, sex, and race-matched controls (n=18) and measured LGALS3BP in platelet releasate and in circulating serum. We investigated the association between levels of LGALS3BP with the prevalence, disease severity, and clinical phenotpyes of SLE, and studied platelet-mediated effects on myeloid inflammation. RESULTS:). Platelet-released LGALS3BP was highly correlated with circulating LGALS3BP (R = 0.69, p < 0.0001). Circulating LGALS3BP correlated with the SLE disease activity index (R = 0.32, p = 0.0006). Specifically, circulating LGALS3BP was higher in SLE patients with lupus nephritis than those with inactive disease (4.0 μg/mL vs 2.3 μg/mL, P < 0.001). IFN-α induced LGALS3BP transcription and translation in a megakaryoblastic cell line (MEG-01) cells in a dose-dependent manner. Recombinant LGALS3BP and platelet releasates from SLE patients enhanced pro-inflammatory cytokine production by macrophages. CONCLUSIONS:These data support that platelets act as potent effector cells contributing to the pathogenesis of SLE by secreting proinflammatory LGALS3BP, which also represents a novel biomarker of SLE clinical activity.