Faculty Bibliography

Venous thromboembolism (VTE), comprised of deep vein thrombosis and pulmonary embolism, is a common health problem both in the United States and worldwide, with significant associated morbidity and mortality. Despite multiple known genetic and situational risk factors, an estimated 30% of all events remain classified as idiopathic, demonstrating a significant knowledge gap in the pathophysiology VTE. While platelets are well established as an essential contributor to thrombus formation and there has been recent interest in the role of neutrophil extracellular traps, specific cell types and pathways involved in the pathogenesis of VTE remain uncertain. In this study, our primary aims were to define a unique transcriptional signature for VTE and to identify the types of cells and specific pathways involved in development of VTE. Whole blood was collected in PAX gene tubes and RNA sequencing for coding mRNA was performed in an unbiased manner in 201 patients with prevalent VTE as well as 43 healthy controls. We used a bioinformatics approach to develop a unique signature for VTE by identifying differentially expressed genes, developing cell-type modules, and ascertaining pathways driving differentially expressed transcripts. We performed additional analyses on subgroups of patients with idiopathic VTE, patients with incident VTE, and VTE patients matched to healthy controls by age and sex. We went on to use machine learning methods to learn models that best differentiate VTE patients from healthy controls and validated it on a left out test set within our VTE population. Genes specific to neutrophils, erythrocytes, and platelets, in that order, were most significantly upregulated in patients with VTE compared to healthy controls. Genes related to T-cells were downregulated. Pathway analysis revealed upregulated neutrophil activation and degranulation, erythrocyte differentiation and homeostasis, and platelet degranulation. A gene signature of 217 transcripts was outstanding at differentiating patients with VTE versus healthy controls (AUC 0.94). Following adjustment for age, sex, and race/ethnicity our genetic signature remained significantly robust at differentiating patients with VTE versus controls (AUC 0.83). Our expression signature remained stable across patients with idiopathic VTE (AUC 0.93), and in patients who went on to develop future VTE events (AUC 0.95). In summary, we have demonstrated a whole blood transcriptional signature for prevalent and incident VTE. Genes related to neutrophils, erythrocytes, and platelets are upregulated in patients with VTE and genes related to T-cells were downregulated. These findings suggest an active role of cell types once thought to be passively entrapped within thrombus and provide new areas of study to establish the pathophysiology of VTE

Unveiling the transcriptome of human blastocysts can provide a wealth of important information regarding early embryonic ontology. Comparing the mRNA production of embryos with normal and abnormal karyotypes allows for a deeper understanding of the protein pathways leading to viability and aberrant fetal development. In addition, identifying transcripts specific for normal or abnormal chromosome copy number could aid in the search for secreted substances that could be used to non-invasively identify embryos best suited for IVF embryo transfer. Using RNA-seq, we characterized the transcriptome of 71 normally developing human blastocysts that were karyotypically normal vs. trisomic or monosomic. Every monosomy and trisomy of the autosomal and sex chromosomes were evaluated, mostly in duplicate. We first mapped the transcriptome of three normal embryos and found that a common core of more than 3,000 genes is expressed in all embryos. These genes represent pathways related to actively dividing cells, such as ribosome biogenesis and function, spliceosome, oxidative phosphorylation, cell cycle and metabolic pathways. We then compared transcriptome profiles of aneuploid embryos to those of normal embryos. We observed that non-viable embryos had a large number of dysregulated genes, some showing a hundred-fold difference in expression. On the contrary, sex chromosome abnormalities, XO and XXX displayed transcriptomes more closely mimicking those embryos with 23 normal chromosome pairs. Intriguingly, we identified a set of commonly deregulated genes in the majority of both trisomies and monosomies. This is the first paper demonstrating a comprehensive transcriptome delineation of karyotypic abnormalities found in the human pre-implantation embryo. We believe that this information will contribute to the development of new pre-implantation genetic screening methods as well as a better understanding of the underlying developmental abnormalities of abnormal embryos, fetuses and children.

KRAS mutation is present in approximately 30% of human lung adenocarcinomas. Although recent advances in targeted therapy have shown great promise, effective targeting of KRAS remains elusive, and concurrent alterations in tumor suppressors render KRAS-mutant tumors even more resistant to existing therapies. Contributing to the refractoriness of KRAS-mutant tumors are immunosuppressive mechanisms, such as increased presence of suppressive regulatory T cells (Tregs) in tumors and elevated expression of the inhibitory receptor PD-1 on tumor-infiltrating T cells. Treatment with BET bromodomain inhibitors is beneficial for hematologic malignancies, and they have Treg-disruptive effects in a non-small cell lung cancer (NSCLC) model. Targeting PD-1 inhibitory signals through PD-1 antibody blockade also has substantial therapeutic impact in lung cancer, although these outcomes are limited to a minority of patients. We hypothesized that the BET bromodomain inhibitor JQ1 would synergize with PD-1 blockade to promote a robust antitumor response in lung cancer. In the present study, using Kras+/LSL-G12D; Trp53L/L (KP) mouse models of NSCLC, we identified cooperative effects between JQ1 and PD-1 antibody. The numbers of tumor-infiltrating Tregs were reduced and activation of tumor-infiltrating T cells, which had a T-helper type 1 (Th1) cytokine profile, was enhanced, underlying their improved effector function. Furthermore, lung tumor-bearing mice treated with this combination showed robust and long-lasting antitumor responses compared to either agent alone, culminating in substantial improvement in the overall survival of treated mice. Thus, combining BET bromodomain inhibition with immune checkpoint blockade offers a promising therapeutic approach for solid malignancies such as lung adenocarcinoma.

Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them-STK11, EGFR, FAT1, SETBP1, KRAS and TP53-can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH .

Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them-STK11, EGFR, FAT1, SETBP1, KRAS and TP53-can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH .

Cellular transformation is accompanied by extensive rewiring of many biological processes leading to augmented levels of distinct types of cellular stress, including proteotoxic stress. Cancer cells critically depend on stress-relief pathways for their survival. However, the mechanisms underlying the transcriptional initiation and maintenance of the oncogenic stress response remain elusive. Here, we show that the expression of heat shock transcription factor 1 (HSF1) and the downstream mediators of the heat shock response is transcriptionally upregulated in T cell acute lymphoblastic leukemia (T-ALL). Hsf1 ablation suppresses the growth of human T-ALL and eradicates leukemia in mouse models of T-ALL, while sparing normal hematopoiesis. HSF1 drives a compact transcriptional program and among the direct HSF1 targets, specific chaperones and co-chaperones mediate its critical role in T-ALL. Notably, we demonstrate that the central T-ALL oncogene NOTCH1 hijacks the cellular stress response machinery by inducing the expression of HSF1 and its downstream effectors. The NOTCH1 signaling status controls the levels of chaperone/co-chaperone complexes and predicts the response of T-ALL patient samples to HSP90 inhibition. Our data demonstrate an integral crosstalk between mediators of oncogene and non-oncogene addiction and reveal critical nodes of the heat shock response pathway that can be targeted therapeutically.

Rapid impulse propagation is a defining attribute of the pectinated atrial myocardium and His-Purkinje system (HPS) that safeguards against atrial and ventricular arrhythmias, conduction block, and myocardial dyssynchrony. The complex transcriptional circuitry that dictates rapid conduction remains incompletely understood. Here, we demonstrate that ETV1 (ER81)-dependent gene networks dictate the unique electrophysiological characteristics of atrial and His-Purkinje myocytes. Cardiomyocyte-specific deletion of ETV1 results in cardiac conduction abnormalities, decreased expression of rapid conduction genes (Nkx2-5, Gja5, and Scn5a), HPS hypoplasia, and ventricularization of the unique sodium channel properties that define Purkinje and atrial myocytes in the adult heart. Forced expression of ETV1 in postnatal ventricular myocytes (VMs) reveals that ETV1 promotes a HPS gene signature while diminishing ventricular and nodal gene networks. Remarkably, ETV1 induction in human induced pluripotent stem cell-derived cardiomyocytes increases rapid conduction gene expression and inward sodium currents, converting them towards a HPS phenotype. Our data identify a cardiomyocyte-autonomous, ETV1-dependent pathway that is responsible for specification of rapid conduction zones in the heart and demonstrate that ETV1 is sufficient to promote a HPS transcriptional and functional program upon VMs.