Small molecule branched-chain ketoacid dehydrogenase kinase (BDK) inhibitors with opposing effects on BDK protein levels.

Branched chain amino acid (BCAA) catabolic impairments have been implicated in several diseases. Branched chain ketoacid dehydrogenase (BCKDH) controls the rate limiting step in BCAA degradation, the activity of which is inhibited by BCKDH kinase (BDK)-mediated phosphorylation. Screening efforts to discover BDK inhibitors led to identification of thiophene PF-07208254, which improved cardiometabolic endpoints in mice. Structure-activity relationship studies led to identification of a thiazole series of BDK inhibitors; however, these inhibitors did not improve metabolism in mice upon chronic administration. While the thiophenes demonstrated sustained branched chain ketoacid (BCKA) lowering and reduced BDK protein levels, the thiazoles increased BCKAs and BDK protein levels. Thiazoles increased BDK proximity to BCKDH-E2, whereas thiophenes reduced BDK proximity to BCKDH-E2, which may promote BDK degradation. Thus, we describe two BDK inhibitor series that possess differing attributes regarding BDK degradation or stabilization and provide a mechanistic understanding of the desirable features of an effective BDK inhibitor.

Chronic UCN2 treatment desensitizes CRHR2 and improves insulin sensitivity.

Urocortin 2 (UCN2) acts as a ligand for the G protein-coupled receptor corticotropin-releasing hormone receptor 2 (CRHR2). UCN2 has been reported to improve or worsen insulin sensitivity and glucose tolerance in vivo. Here we show that acute dosing of UCN2 induces systemic insulin resistance in male mice and skeletal muscle. Inversely, chronic elevation of UCN2 by injection with adenovirus encoding UCN2 resolves metabolic complications, improving glucose tolerance. CRHR2 recruits Gs in response to low concentrations of UCN2, as well as Gi and ß-Arrestin at high concentrations of UCN2. Pre-treating cells and skeletal muscle ex vivo with UCN2 leads to internalization of CRHR2, dampened ligand-dependent increases in cAMP, and blunted reductions in insulin signaling. These results provide mechanistic insights into how UCN2 regulates insulin sensitivity and glucose metabolism in skeletal muscle and in vivo. Importantly, a working model was derived from these results that unifies the contradictory metabolic effects of UCN2.

CHAC1 inactivation is effective to preserve muscle glutathione but is insufficient to protect against muscle wasting in cachexia.

Muscle wasting is one of the main characteristics of cachexia associated with cancer and other chronic diseases and is often exacerbated by antineoplastic agents. Increased oxidative stress is associated with muscle wasting, along with depletion of glutathione, the most abundant endogenous antioxidant. Therefore, boosting endogenous glutathione has been proposed as a therapeutic strategy to prevent muscle wasting. Here, we tested this hypothesis by inactivating CHAC1, an intracellular glutathione degradation enzyme. We found CHAC1 expression is increased under multiple muscle wasting conditions in animal models, including fasting, cancer cachexia, and chemotherapy. The elevation of muscle Chac1 expression is associated with reduced glutathione level. CHAC1 inhibition via CRSPR/Cas9 mediated knock-in of an enzyme inactivating mutation demonstrates a novel strategy to preserve muscle glutathione levels under wasting conditions but fails to prevent muscle wasting in mice. These results suggest that preserving intracellular glutathione level alone may not be sufficient to prevent cancer or chemotherapy induced muscle wasting.

GDF15 neutralization restores muscle function and physical performance in a mouse model of cancer cachexia.

Cancer cachexia is a disorder characterized by involuntary weight loss and impaired physical performance. Decline in physical performance of patients with cachexia is associated with poor quality of life, and currently there are no effective pharmacological interventions that restore physical performance. Here we examine the effect of GDF15 neutralization in a mouse model of cancer-induced cachexia (TOV21G) that manifests weight loss and muscle function impairments. With comprehensive assessments, our results demonstrate that cachectic mice treated with the anti-GDF15 antibody mAB2 exhibit body weight gain with near-complete restoration of muscle mass and markedly improved muscle function and physical performance. Mechanistically, the improvements induced by GDF15 neutralization are primarily attributed to increased caloric intake, while altered gene expression in cachectic muscles is restored in caloric-intake-dependent and -independent manners. The findings indicate potential of GDF15 neutralization as an effective therapy to enhance physical performance of patients with cachexia.

BDK inhibition acts as a catabolic switch to mimic fasting and improve metabolism in mice.

OBJECTIVE: Branched chain amino acid (BCAA) catabolic defects are implicated to be causal determinates of multiple diseases. This work aimed to better understand how enhancing BCAA catabolism affected metabolic homeostasis as well as the mechanisms underlying these improvements. METHODS: The rate limiting step of BCAA catabolism is the irreversible decarboxylation by the branched chain ketoacid dehydrogenase (BCKDH) enzyme complex, which is post-translationally controlled through phosphorylation by BCKDH kinase (BDK). This study utilized BT2, a small molecule allosteric inhibitor of BDK, in multiple mouse models of metabolic dysfunction and NAFLD including the high fat diet (HFD) model with acute and chronic treatment paradigms, the choline deficient and methionine minimal high fat diet (CDAHFD) model, and the low-density lipoprotein receptor null mouse model (Ldlr-/-). shRNA was additionally used to knock down BDK in liver to elucidate liver-specific effects of BDK inhibition in HFD-fed mice. RESULTS: A rapid improvement in insulin sensitivity was observed in HFD-fed and lean mice after BT2 treatment. Resistance to steatosis was assessed in HFD-fed mice, CDAHFD-fed mice, and Ldlr-/- mice. In all cases, BT2 treatment reduced steatosis and/or inflammation. Fasting and refeeding demonstrated a lack of response to feeding-induced changes in plasma metabolites including insulin and beta-hydroxybutyrate and hepatic gene changes in BT2-treated mice. Mechanistically, BT2 treatment acutely altered the expression of genes involved in fatty acid oxidation and lipogenesis in liver, and upstream regulator analysis suggested that BT2 treatment activated PPARα. However, BT2 did not directly activate PPARα in vitro. Conversely, shRNA-AAV-mediated knockdown of BDK specifically in liver in vivo did not demonstrate any effects on glycemia, steatosis, or PPARα-mediated gene expression in mice. CONCLUSIONS: These data suggest that BT2 treatment acutely improves metabolism and liver steatosis in multiple mouse models. While many molecular changes occur in liver in BT2-treated mice, these changes were not observed in mice with AAV-mediated shRNA knockdown of BDK. All together, these data suggest that systemic BDK inhibition is required to improve metabolism and steatosis by prolonging a fasting signature in a paracrine manner. Therefore, BCAA may act as a "fed signal" to promote nutrient storage and reduced systemic BCAA levels as shown in this study via BDK inhibition may act as a "fasting signal" to prolong the catabolic state.

Fully automated mouse echocardiography analysis using deep convolutional neural networks.

Echocardiography (echo) is a translationally relevant ultrasound imaging modality widely used to assess cardiac structure and function in preclinical models of heart failure (HF) during research and drug development. Although echo is a very valuable tool, the image analysis is a time-consuming, resource-demanding process, and is susceptible to interreader variability. Recent advancements in deep learning have enabled researchers to automate image processing and reduce analysis time and interreader variability in the field of medical imaging. In the present study, we developed a fully automated tool, mouse-echocardiography neural net (MENN), for the analysis of both long-axis brightness (B)-mode and short-axis motion (M)-mode images of left ventricle. MENN is a series of fully convolutional neural networks that were trained and validated using manually segmented B-mode and M-mode echo images of the left ventricle. The segmented images were then used to compute cardiac structural and functional metrics. The performance of MENN was further validated in two preclinical models of HF. MENN achieved excellent correlations (Pearson's r = 0.85-0.99) and good-to-excellent agreement between automated and manual analyses. Further interreader variability analysis showed that MENN has better agreements with an expert analyst than both a trained analyst and a novice. Notably, the use of MENN reduced manual analysis time by >92%. In conclusion, we developed an automated echocardiography analysis tool that allows for fast and accurate analysis of B-mode and M-mode mouse echo data and mitigates the issue of interreader variability in manual analysis.NEW & NOTEWORTHY Echocardiography is commonly used in preclinical research to evaluate cardiac structure and function. Despite the broad applications across therapeutic areas, the analysis of echo data is laborious and susceptible to interreader variability. In this study, we developed a fully automated mouse-echocardiography neural net (MENN). Cardiac measurements from MENN showed excellent correlations with manual analysis. Furthermore, the use of MENN leads to >92% reduction in analysis time and potentially eliminates the interobserver variability issue.

Neutralization of GDF15 Prevents Anorexia and Weight Loss in the Monocrotaline-Induced Cardiac Cachexia Rat Model.

Growth and differentiation factor 15 (GDF15) is a cytokine reported to cause anorexia and weight loss in animal models. Neutralization of GDF15 was efficacious in mitigating cachexia and improving survival in cachectic tumor models. Interestingly, elevated circulating GDF15 was reported in patients with pulmonary arterial hypertension and heart failure, but it is unclear whether GDF15 contributes to cachexia in these disease conditions. In this study, rats treated with monocrotaline (MCT) manifested a progressive decrease in body weight, food intake, and lean and fat mass concomitant with elevated circulating GDF15, as well as development of right-ventricular dysfunction. Cotreatment of GDF15 antibody mAb2 with MCT prevented MCT-induced anorexia and weight loss, as well as preserved lean and fat mass. These results indicate that elevated GDF15 by MCT is causal to anorexia and weight loss. GDF15 mAb2 is efficacious in mitigating MCT-induced cachexia in vivo. Furthermore, the results suggest GDF15 inhibition is a potential therapeutic approach to alleviate cardiac cachexia in patients.

Discovery of a Series of Pyrimidine Carboxamides as Inhibitors of Vanin-1.

A diaryl ketone series was identified as vanin-1 inhibitors from a high-throughput screening campaign. While this novel scaffold provided valuable probe 2 that was used to build target confidence, concerns over the ketone moiety led to the replacement of this group. The successful replacement of this moiety was achieved with pyrimidine carboxamides derived from cyclic secondary amines that were extensively characterized using biophysical and crystallographic methods as competitive inhibitors of vanin-1. Through optimization of potency and physicochemical and ADME properties, and guided by co-crystal structures with vanin-1, 3 was identified with a suitable profile for advancement into preclinical development.

AAV-mediated expression of galactose-1-phosphate uridyltransferase corrects defects of galactose metabolism in classic galactosemia patient fibroblasts.

Classic galactosemia (CG) is a rare disorder of autosomal recessive inheritance. It is caused predominantly by point mutations as well as deletions in the gene encoding the enzyme galactose-1-phosphate uridyltransferase (GALT). The majority of the more than 350 mutations identified in the GALT gene cause a significant reduction in GALT enzyme activity resulting in the toxic buildup of galactose metabolites that in turn is associated with cellular stress and injury. Consequently, developing a therapeutic strategy that reverses both the oxidative and ER stress in CG cells may be helpful in combating this disease. Recombinant adeno-associated virus (AAV)-mediated gene therapy to restore GALT activity offers the potential to address the unmet medical needs of galactosemia patients. Here, utilizing fibroblasts derived from CG patients we demonstrated that AAV-mediated augmentation of GALT protein and activity resulted in the prevention of ER and oxidative stress. We also demonstrate that these CG patient fibroblasts exhibit reduced CD109 and TGFßRII protein levels and that these effectors of cellular homeostasis could be restored following AAV-mediated expression of GALT. Finally, we show initial in vivo proof-of-concept restoration of galactose metabolism in a GALT knockout mouse model following treatment with AAV-GALT.

An assessment of thermoneutral housing conditions on murine cardiometabolic function.

Mouse models are used to model human diseases and perform pharmacological efficacy testing to advance therapies to humans; most of these studies are conducted in room temperature conditions. At room temperature (22°C), mice are cold-stressed and must use brown adipose tissue (BAT) to maintain body temperature. This cold stress increases catecholamine tone to maintain adipocyte lipid release via lipolysis, which will fuel adaptive thermogenesis. Maintaining rodents at thermoneutral temperatures (28°C) ameliorates the need for adaptive thermogenesis, thus reducing catecholamine tone and BAT activity. Cardiovascular tone is also determined by catecholamine levels in rodents, as ß-adrenergic stimuli are primary drivers of not only lipolytic but also ionotropic and chronotropic responses. As mice have increased catecholamine tone at room temperature, we investigated how thermoneutral housing conditions would impact cardiometabolic function. Here, we show a rapid and reversible effect of thermoneutrality on both heart rate and blood pressure in chow-fed animals, which was blunted in animals fed a high-fat diet. Animals subjected to transverse aortic constriction displayed compensated hypertrophy at room temperature, whereas animals displayed less hypertrophy and a trend toward worse systolic function at thermoneutrality. Despite these dramatic changes in blood pressure and heart rate at thermoneutral housing conditions, enalapril effectively improved cardiac hypertrophy and gene expression alterations. There were surprisingly few differences in cardiac parameters in high-fat-fed animals at thermoneutrality. Overall, these data suggest that thermoneutral housing may alter some aspects of cardiac remodeling in preclinical mouse models of heart failure.NEW & NOTEWORTHY Thermoneutral housing conditions cause rapid and reversible changes in mouse heart rate and blood pressure. Despite dramatic reductions in heart rate and blood pressure, thermoneutrality reduced the compensatory hypertrophic response in a pressure overload heart failure model compared with room temperature housing, and ACE inhibitors were still efficacious to prevent pressure overload-induced cardiac remodeling. The effects of thermoneutrality on heart rate and blood pressure are abrogated in the context of diet-induced obesity.

Adolescent stress sensitizes the adult neuroimmune transcriptome and leads to sex-specific microglial and behavioral phenotypes.

Adolescent exposure to chronic stress, a risk factor for mood disorders in adulthood, sensitizes the neuroinflammatory response to a subsequent immune challenge. We previously showed that chronic adolescent stress (CAS) in rats led to distinct patterns of neuroimmune priming in adult male and female rats. However, sex differences in the neuroimmune consequences of CAS and their underlying mechanisms are not fully understood. Here we hypothesized that biological sex would dictate differential induction of inflammation-related transcriptomic pathways and immune cell involvement (microglia activation and leukocyte presence) in the hippocampus of male and female rats with a history of CAS. Adolescent rats underwent CAS (six restraint and six social defeat episodes during postnatal days 38-49), and behavioral assessments were conducted in adolescence and adulthood. Neuroimmune measures were obtained following vehicle or a systemic lipopolysaccharide (LPS) challenge in adulthood. CAS led to increased time in the corners of the open field in adolescence. In males, CAS also increased social avoidance. As adults, CAS rats displayed an exaggerated enrichment of the nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) pathway and chemokine induction following LPS challenge, and increased number of perivascular CD45+ cells in the hippocampus. However, CAS females, but not males, showed exaggerated glucocorticoid receptor (GR) pathway enrichment and increased microglial complexity. These results provide further insight to the mechanisms by which peripheral immune events may influence neuroimmune responses differentially among males and females and further demonstrate the importance of adolescent stress in shaping adult responses.

Correction to: SpectralTAD: an R package for defining a hierarchy of topologically associated domains using spectral clustering.

An amendment to this paper has been published and can be accessed via the original article.

SpectralTAD: an R package for defining a hierarchy of topologically associated domains using spectral clustering.

BACKGROUND: The three-dimensional (3D) structure of the genome plays a crucial role in gene expression regulation. Chromatin conformation capture technologies (Hi-C) have revealed that the genome is organized in a hierarchy of topologically associated domains (TADs), sub-TADs, and chromatin loops. Identifying such hierarchical structures is a critical step in understanding genome regulation. Existing tools for TAD calling are frequently sensitive to biases in Hi-C data, depend on tunable parameters, and are computationally inefficient. METHODS: To address these challenges, we developed a novel sliding window-based spectral clustering framework that uses gaps between consecutive eigenvectors for TAD boundary identification. RESULTS: Our method, implemented in an R package, SpectralTAD, detects hierarchical, biologically relevant TADs, has automatic parameter selection, is robust to sequencing depth, resolution, and sparsity of Hi-C data. SpectralTAD outperforms four state-of-the-art TAD callers in simulated and experimental settings. We demonstrate that TAD boundaries shared among multiple levels of the TAD hierarchy were more enriched in classical boundary marks and more conserved across cell lines and tissues. In contrast, boundaries of TADs that cannot be split into sub-TADs showed less enrichment and conservation, suggesting their more dynamic role in genome regulation. CONCLUSION: SpectralTAD is available on Bioconductor, http://bioconductor.org/packages/SpectralTAD/ .

Marginal Improvement in Survival Post-Heart Transplantation in Patients With Prior Left Ventricular Assist Device: A Temporal Analysis of United Network of Organ Sharing Registry.

OBJECTIVE: An increasing number of patients undergoing heart transplantation are being bridged with left ventricular assist devices (LVADs). Bridge-to-transplantation (BTT) LVAD has improved wait list survival remarkably. Historically, post-heart transplantation survival in BTT-LVAD patients, however, has remained inferior to that of primary heart transplantation. The authors hypothesized that in the modern era, the difference between post-heart transplantation survival in BTT-LVAD versus primary heart transplantation should be reduced. The objective of the present study was to determine whether there has been a change in survival after heart transplantation in patients with prior LVAD. The present study's cohort was compared with a historical cohort using the United Network of Organ Sharing (UNOS) database from 1995 to 2004.5 DESIGN: Retrospective observational analysis of data from the United Network of Organ Sharing database. SETTINGS: Registry-based, observational, retrospective. PARTICIPANTS: Patients undergoing adult orthotopic heart transplantation, excluding redo transplantation and multiorgan transplantations. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: From the UNOS database, 22,065 patients who underwent heart transplantation between January 1, 2006, and December 31, 2016, were analyzed. Of these, 7,008 (31.76%) patients had prior LVAD (BTT-LVAD). Data analysis was performed with R software (Version 3.5.1) for Kaplan-Meier survival analysis and Cox proportional hazard ratio (HR) modeling to identify variables influencing survival. For patients with prior LVAD, the overall HR was 1.15 (95% confidence interval [CI] 1.07-1.24) for survival. An HR of 3.22 (95% CI 2.23-4.68) for death in patients who received extracorporeal membrane oxygenation post-transplantation and an HR of 0.72 (95% CI 0.58-0.90) for survival in patients whose procedures were performed in high-volume centers performing more than 35 transplantations per year were identified. CONCLUSION: Reduced survival in patients who received an LVAD before heart transplantation persists. However, there may have been a slight improvement in the HR for survival in the study cohort in the recent decade compared with the historical cohort from previous decades. It is intriguing that despite the paramount advances in both technology and clinical practice of LVAD, relatively minor survival benefit, if any, has occurred in post-heart transplantation for patients bridged with prior LVAD.

CtBP-a targetable dependency for tumor-initiating cell activity and metastasis in pancreatic adenocarcinoma.

Ctbp2 is a uniquely targetable oncogenic transcriptional coregulator, exhibiting overexpression in most common solid tumors, and critical to the tumor-initiating cell (TIC) transcriptional program. In the "CKP" mouse pancreatic ductal adenocarcinoma (PDAC) model driven by mutant K-Ras, Ctbp2 haploinsufficiency prolonged survival, abrogated peritoneal metastasis, and caused dramatic downregulation of c-Myc, a known critical dependency for TIC activity and tumor progression in PDAC. A small-molecule inhibitor of CtBP2, 4-chloro-hydroxyimino phenylpyruvate (4-Cl-HIPP) phenocopied Ctbp2 deletion, decreasing tumor burden similarly to gemcitabine, and the combination of 4-Cl-HIPP and gemcitabine further synergistically suppressed tumor growth. Pharmacodynamic monitoring revealed that the 4-Cl-HIPP/gemcitabine combination induced robust and synergistic tumor apoptosis and marked downregulation of the TIC marker CD133 in CKP PDAC tumors. Collectively, our data demonstrate that targeting CtBP represents a fruitful avenue for development of highly active agents in PDAC that cooperate with standard therapy to limit both primary and metastatic tumor burden.

R Tutorial: Detection of Differentially Interacting Chromatin Regions From Multiple Hi-C Datasets.

The three-dimensional (3D) interactions of chromatin regulate cell-type-specific gene expression, recombination, X-chromosome inactivation, and many other genomic processes. High-throughput chromatin conformation capture (Hi-C) technologies capture the structure of the chromatin on a global scale by measuring all-vs.-all interactions and can provide new insights into genomic regulation. The workflow presented here describes how to analyze and interpret a comparative Hi-C experiment. We describe the process of obtaining Hi-C data from public repositories and give suggestions for pre-processing pipelines for users who intend to analyze their own raw data. We then describe the data normalization and comparative analysis process. We present three protocols describing the use of the multiHiCcompare, diffHic, and FIND R packages, respectively, to perform a comparative analysis of Hi-C experiments. Finally, visualization of the results and downstream interpretation of the differentially interacting regions are discussed. The bulk of this tutorial uses the R programming environment, and the processes described can be performed with most operating systems and a single computer. © 2019 by John Wiley & Sons, Inc.

multiHiCcompare: joint normalization and comparative analysis of complex Hi-C experiments.

MOTIVATION: With the development of chromatin conformation capture technology and its high-throughput derivative Hi-C sequencing, studies of the three-dimensional interactome of the genome that involve multiple Hi-C datasets are becoming available. To account for the technology-driven biases unique to each dataset, there is a distinct need for methods to jointly normalize multiple Hi-C datasets. Previous attempts at removing biases from Hi-C data have made use of techniques which normalize individual Hi-C datasets, or, at best, jointly normalize two datasets. RESULTS: Here, we present multiHiCcompare, a cyclic loess regression-based joint normalization technique for removing biases across multiple Hi-C datasets. In contrast to other normalization techniques, it properly handles the Hi-C-specific decay of chromatin interaction frequencies with the increasing distance between interacting regions. multiHiCcompare uses the general linear model framework for comparative analysis of multiple Hi-C datasets, adapted for the Hi-C-specific decay of chromatin interaction frequencies. multiHiCcompare outperforms other methods when detecting a priori known chromatin interaction differences from jointly normalized datasets. Applied to the analysis of auxin-treated versus untreated experiments, and CTCF depletion experiments, multiHiCcompare was able to recover the expected epigenetic and gene expression signatures of loss of chromatin interactions and reveal novel insights. AVAILABILITY AND IMPLEMENTATION: multiHiCcompare is freely available on GitHub and as a Bioconductor R package https://bioconductor.org/packages/multiHiCcompare. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

HiCcompare: an R-package for joint normalization and comparison of HI-C datasets.

BACKGROUND: Changes in spatial chromatin interactions are now emerging as a unifying mechanism orchestrating the regulation of gene expression. Hi-C sequencing technology allows insight into chromatin interactions on a genome-wide scale. However, Hi-C data contains many DNA sequence- and technology-driven biases. These biases prevent effective comparison of chromatin interactions aimed at identifying genomic regions differentially interacting between, e.g., disease-normal states or different cell types. Several methods have been developed for normalizing individual Hi-C datasets. However, they fail to account for biases between two or more Hi-C datasets, hindering comparative analysis of chromatin interactions. RESULTS: We developed a simple and effective method, HiCcompare, for the joint normalization and differential analysis of multiple Hi-C datasets. The method introduces a distance-centric analysis and visualization of the differences between two Hi-C datasets on a single plot that allows for a data-driven normalization of biases using locally weighted linear regression (loess). HiCcompare outperforms methods for normalizing individual Hi-C datasets and methods for differential analysis (diffHiC, FIND) in detecting a priori known chromatin interaction differences while preserving the detection of genomic structures, such as A/B compartments. CONCLUSIONS: HiCcompare is able to remove between-dataset bias present in Hi-C matrices. It also provides a user-friendly tool to allow the scientific community to perform direct comparisons between the growing number of pre-processed Hi-C datasets available at online repositories. HiCcompare is freely available as a Bioconductor R package https://bioconductor.org/packages/HiCcompare/ .

Toward Signaling-Driven Biomarkers Immune to Normal Tissue Contamination.

The goal of this study was to discover a minimally invasive pathway-specific biomarker that is immune to normal cell mRNA contamination for diagnosing head and neck squamous cell carcinoma (HNSCC). Using Elsevier's MedScan natural language processing component of the Pathway Studio software and the TRANSFAC database, we produced a curated set of genes regulated by the signaling networks driving the development of HNSCC. The network and its gene targets provided prior probabilities for gene expression, which guided our CoGAPS matrix factorization algorithm to isolate patterns related to HNSCC signaling activity from a microarray-based study. Using patterns that distinguished normal from tumor samples, we identified a reduced set of genes to analyze with Top Scoring Pair in order to produce a potential biomarker for HNSCC. Our proposed biomarker comprises targets of the transcription factor (TF) HIF1A and the FOXO family of TFs coupled with genes that show remarkable stability across all normal tissues. Based on validation with novel data from The Cancer Genome Atlas (TCGA), measured by RNAseq, and bootstrap sampling, the biomarker for normal vs. tumor has an accuracy of 0.77, a Matthews correlation coefficient of 0.54, and an area under the curve (AUC) of 0.82.