Venous Thromboembolism Prevention in the Bariatric Surgical Patient: Are we doing enough?

Bariatric surgery has become an accepted, safe and durable method of weight loss for the obese patient. Despite this success, venous thromboembolism (VTE) continues to be one of the top two causes of mortality in bariatric surgery. Most bariatric surgeons today use a combination of non-invasive and pharmacologic techniques, including sequential compression devices, anti-embolic stockings, anticoagulation, and early ambulation, to prevent VTE. Despite these interventions, the incidence of VTE after bariatric surgery has been reported to be widely variable ranging from 0.3 to 3.8%. (1-11) The most recent study published to date reported an incidence of pulmonary emboli (PE) of 0.9%, deep venous thrombosis (DVT) without PE to be 1.3% and VTE (DVT + PE) to be 2.2% within the perioperative period. (12) Little data has been collected to evaluate the long term risk (greater than 30 days post-op) of VTE following bariatric surgery. Furthermore, the prevalence of asymptomatic deep venous thrombosis (DVT) in this population is unknown and is sure to be higher. Our main goal for this thesis was to study the effectiveness of current and future practices of venous thromboembolism prophylaxis in the bariatric surgical population. To do so, we first completed a narrative summary of the current agents and techniques used to prevent VTE in this population (Chapter one). We then analyzed a large administrative database to determine the long term risk and predictors for VTE in patients undergoing bariatric surgery using current VTE prophylaxis (Chapter two). We identified a history of previous VTE events as being the strongest predictor of development of a VTE post-surgery. This high rate of recurrence has led to the recommendation that patients with prior VTE or other high risk groups should be considered for prophylactic vena cava filter insertion before surgery. This finding motivated us to specifically assess the efficacy and risks of IVC filters in the bariatric surgery population. We completed a retrospective analysis of a large administrative database to determine these risks and benefits (Chapter three). The body habitus of a bariatric surgical patient presents technical challenges in the detection of VTE, especially asymptomatic DVT in the pelvis and lower limbs. Because of the limited sensitivity and specificity of ultrasound in the detection of DVT in the obese patient, we performed a systematic review and meta-analysis to determine the diagnostic accuracy of magnetic resonance venography in the detection of DVT in the obese (Chapter four). Based on these results above, we then designed a randomized double blinded controlled trial (RCT) to study the incidence of asymptomatic deep venous thrombosis in this special population. We compared two different anticoagulation regimens in the prevention of VTE in bariatric surgical patients:enoxaparin 40 mg subcutaneously twice daily (our standard regimen), and fondaparinux 5 mg subcutaneously once daily (a non-standard dose in the obese population, used under an IND obtained by Dr. Steele). We used MRV as a novel non-invasive diagnostic tool to detect asymptomatic DVT in our patient population (Chapter five). In the final chapter, Chapter six, we discuss public health-based approaches and future work in the prevention of VTE in this special population.

Sleep apnea predicts distinct alterations in glucose homeostasis and biomarkers in obese adults with normal and impaired glucose metabolism

<p>Abstract</p> <p>Background</p> <p>Notwithstanding previous studies supporting independent associations between obstructive sleep apnea (OSA) and prevalence of diabetes, the underlying pathogenesis of impaired glucose regulation in OSA remains unclear. We explored mechanisms linking OSA with prediabetes/diabetes and associated biomarker profiles. We hypothesized that OSA is associated with distinct alterations in glucose homeostasis and biomarker profiles in subjects with normal (NGM) and impaired glucose metabolism (IGM).</p> <p>Methods</p> <p>Forty-five severely obese adults (36 women) without certain comorbidities/medications underwent anthropometric measurements, polysomnography, and blood tests. We measured fasting serum glucose, insulin, selected cytokines, and calculated homeostasis model assessment estimates of insulin sensitivity (HOMA-IS) and pancreatic beta-cell function (HOMA-B).</p> <p>Results</p> <p>Both increases in apnea-hypopnea index (AHI) and the presence of prediabetes/diabetes were associated with reductions in HOMA-IS in the entire cohort even after adjustment for sex, race, age, and BMI (<it>P </it>= 0.003). In subjects with NGM (n = 30), OSA severity was associated with significantly increased HOMA-B (a trend towards decreased HOMA-IS) independent of sex and adiposity. OSA-related oxyhemoglobin desaturations correlated with TNF-α (r=-0.76; <it>P </it>= 0.001) in women with NGM and with IL-6 (rho=-0.55; <it>P </it>= 0.035) in women with IGM (n = 15) matched individually for age, adiposity, and AHI.</p> <p>Conclusions</p> <p>OSA is independently associated with altered glucose homeostasis and increased basal beta-cell function in severely obese adults with NGM. The findings suggest that moderate to severe OSA imposes an excessive functional demand on pancreatic beta-cells, which may lead to their exhaustion and impaired secretory capacity over time. The two distinct biomarker profiles linking sleep apnea with NGM and IGM via TNF-α and IL-6 have been discerned in our study to suggest that sleep apnea and particularly nocturnal oxyhemoglobin desaturations are associated with chronic metabolic fluxes and specific cytokine stressors that reflect links between sleep apnea and glucose metabolism. The study may help illuminate potential mechanisms for glucose dysregulation in OSA, and resolve some controversy over the associations of OSA with TNF-α and IL-6 in previous studies.</p

Impact of bariatric surgery on hypertensive disorders in pregnancy: retrospective analysis of insurance claims data

Objective To determine whether women who had a delivery after bariatric surgery have lower rates of hypertensive disorders in pregnancy compared with women who had a delivery before bariatric surgery

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation