Head and Neck Squamous Cell Carcinoma (HNSCC) is the fifth most common cancer, annually affecting over half a million people worldwide. Presently, there are no accepted biomarkers for clinical detection and surveillance of HNSCC. In this work, a comprehensive genome-wide analysis of epigenetic alterations in primary HNSCC tumors was employed in conjunction with cancer-specific outlier statistics to define novel biomarker genes which are differentially methylated in HNSCC. The 37 identified biomarker candidates were top-scoring outlier genes with prominent differential methylation in tumors, but with no signal in normal tissues. These putative candidates were validated in independent HNSCC cohorts from our institution and TCGA (The Cancer Genome Atlas). Using the top candidates, ZNF14, ZNF160, and ZNF420, an assay was developed for detection of HNSCC cancer in primary tissue and saliva samples with 100% specificity when compared to normal control samples. Given the high detection specificity, the analysis of ZNF DNA methylation in combination with other DNA methylation biomarkers may be useful in the clinical setting for HNSCC detection and surveillance, particularly in high-risk patients. Several additional candidates identified through this work can be further investigated toward future development of a multi-gene panel of biomarkers for the surveillance and detection of HNSCC.

Head and neck squamous cell carcinoma (HNSCC) is largely divided into two groups based on their etiology, human papillomavirus (HPV)-positive and -negative. Global DNA methylation changes are known to drive oncogene and tumor suppressor expression in primary HNSCC of both types. However, significant heterogeneity in DNA methylation within the groups results in different transcriptional profiles and clinical outcomes. We applied a meta-pathway analysis to link gene expression changes to DNA methylation in distinguishing HNSCC subtypes. This approach isolated specific epigenetic changes controlling expression in HPV- HNSCC that distinguish it from HPV+ HNSCC. Analysis of genes identified Hedgehog pathway activation specific to HPV- HNSCC. We confirmed that GLI1, the primary Hedgehog target, showed higher expression in tumors compared to normal samples with HPV- tumors having the highest GLI1 expression, suggesting that increased expression of GLI1 is a potential driver in HPV- HNSCC. Our algorithm for integration of DNA methylation and gene expression can infer biologically significant molecular pathways that may be exploited as therapeutics targets. Our results suggest that therapeutics targeting the Hedgehog pathway may be of benefit in HPV- HNSCC. Similar integrative analysis of high-throughput coupled DNA methylation and expression datasets may yield novel insights into deregulated pathways in other cancers.

Development of head and neck squamous cell carcinoma (HNSCC) is characterized by accumulation of mutations in several oncogenes and tumor suppressor genes. We have formerly described the mutation pattern of HNSCC and described NOTCH signaling pathway alterations. Given the complexity of the HNSCC, here we extend the previous study to understand the overall HNSCC mutation context and to discover additional genetic alterations. We performed high depth targeted exon sequencing of 51 highly actionable cancer-related genes with a high frequency of mutation across many cancer types, including head and neck. DNA from primary tumor tissues and matched normal tissues was analyzed for 37 HNSCC patients. We identified 26 non-synonymous or stop-gained mutations targeting 11 of 51 selected genes. These genes were mutated in 17 out of 37 (46%) studied HNSCC patients. Smokers harbored 3.2-fold more mutations than non-smokers. Importantly, TP53 was mutated in 30%, NOTCH1 in 8% and FGFR3 in 5% of HNSCC. HPV negative patients harbored 4-fold more TP53 mutations than HPV positive patients. These data confirm prior reports of the HNSCC mutational profile. Additionally, we detected mutations in two new genes, CEBPA and FES, which have not been previously reported in HNSCC. These data extend the spectrum of HNSCC mutations and define novel mutation targets in HNSCC carcinogenesis, especially for smokers and HNSCC without HPV infection.

Prior studies have demonstrated tumor-specific alternative splicing events in various solid tumor types. The role of alternative splicing in the development and progression of head and neck squamous cell carcinoma (HNSCC) is unclear. Our study queried exon-level expression to implicate splice variants in HNSCC tumors.

A subset of patients with oral squamous cell carcinoma (OSCC), the most common subtype of head and neck squamous cell carcinoma (HNSCC), harbor dysplastic lesions (often visually identified as leukoplakia) prior to cancer diagnosis. Although evidence suggest that leukoplakia represents an initial step in the progression to cancer, signaling networks driving this progression are poorly understood. Here, we applied in silico Pathway Activation Network Decomposition Analysis (iPANDA), a new bioinformatics software suite for qualitative analysis of intracellular signaling pathway activation using transcriptomic data, to assess a network of molecular signaling in OSCC and pre-neoplastic oral lesions. In tumor samples, our analysis detected major conserved mitogenic and survival signaling pathways strongly associated with HNSCC, suggesting that some of the pathways identified by our algorithm, but not yet validated as HNSCC related, may be attractive targets for future research. While pathways activation landscape in the majority of leukoplakias was different from that seen in OSCC, a subset of pre-neoplastic lesions has demonstrated some degree of similarity to the signaling profile seen in tumors, including dysregulation of the cancer-driving pathways related to survival and apoptosis. These results suggest that dysregulation of these signaling networks may be the driving force behind the early stages of OSCC tumorigenesis. While future studies with larger leukoplakia data sets are warranted to further estimate the values of this approach for capturing signaling features that characterize relevant lesions that actually progress to cancers, our platform proposes a promising new approach for detecting cancer-promoting pathways and tailoring the right therapy to prevent tumorigenesis.

Identifying potential resistance mechanisms while tumour cells still respond to therapy is critical to delay acquired resistance.

The glutaminyl-tRNA synthetase (GlnRS) enzyme, which pairs glutamine with tRNA(Gln) for protein synthesis, evolved by gene duplication in early eukaryotes from a nondiscriminating glutamyl-tRNA synthetase (GluRS) that aminoacylates both tRNA(Gln) and tRNA(Glu) with glutamate. This ancient GluRS also separately differentiated to exclude tRNA(Gln) as a substrate, and the resulting discriminating GluRS and GlnRS further acquired additional protein domains assisting function in cis (the GlnRS N-terminal Yqey domain) or in trans (the Arc1p protein associating with GluRS). These added domains are absent in contemporary bacterial GlnRS and GluRS. Here, using Saccharomyces cerevisiae enzymes as models, we find that the eukaryote-specific protein domains substantially influence amino acid binding, tRNA binding and aminoacylation efficiency, but they play no role in either specific nucleotide readout or discrimination against noncognate tRNA. Eukaryotic tRNA(Gln) and tRNA(Glu) recognition determinants are found in equivalent positions and are mutually exclusive to a significant degree, with key nucleotides located adjacent to portions of the protein structure that differentiated during the evolution of archaeal nondiscriminating GluRS to GlnRS. These findings provide important corroboration for the evolutionary model and suggest that the added eukaryotic domains arose in response to distinctive selective pressures associated with the greater complexity of the eukaryotic translational apparatus. We also find that the affinity of GluRS for glutamate is significantly increased when Arc1p is not associated with the enzyme. This is consistent with the lower concentration of intracellular glutamate and the dissociation of the Arc1p:GluRS complex upon the diauxic shift to respiratory conditions.

In eukaryotic genomes, nucleosomes function to compact DNA and to regulate access to it both by simple physical occlusion and by providing the substrate for numerous covalent epigenetic tags. While competition with other DNA-binding factors and action of chromatin remodeling enzymes significantly affect nucleosome formation in vivo, nucleosome positions in vitro are determined by steric exclusion and sequence alone. We have developed a biophysical model, DNABEND, for the sequence dependence of DNA bending energies, and validated it against a collection of in vitro free energies of nucleosome formation and a set of in vitro nucleosome positions mapped at high resolution. We have also made a first ab initio prediction of nucleosomal DNA geometries, and checked its accuracy against the nucleosome crystal structure. We have used DNABEND to design both strong and weak histone- binding sequences, and measured the corresponding free energies of nucleosome formation. We find that DNABEND can successfully predict in vitro nucleosome positions and free energies, providing a physical explanation for the intrinsic sequence dependence of histone-DNA interactions.

Patients with oncogene driven tumors are treated with targeted therapeutics including EGFR inhibitors. Genomic data from The Cancer Genome Atlas (TCGA) demonstrates molecular alterations to EGFR, MAPK, and PI3K pathways in previously untreated tumors. Therefore, this study uses bioinformatics algorithms to delineate interactions resulting from EGFR inhibitor use in cancer cells with these genetic alterations. We modify the HaCaT keratinocyte cell line model to simulate cancer cells with constitutive activation of EGFR, HRAS, and PI3K in a controlled genetic background. We then measure gene expression after treating modified HaCaT cells with gefitinib, afatinib, and cetuximab. The CoGAPS algorithm distinguishes a gene expression signature associated with the anticipated silencing of the EGFR network. It also infers a feedback signature with EGFR gene expression itself increasing in cells that are responsive to EGFR inhibitors. This feedback signature has increased expression of several growth factor receptors regulated by the AP-2 family of transcription factors. The gene expression signatures for AP-2alpha are further correlated with sensitivity to cetuximab treatment in HNSCC cell lines and changes in EGFR expression in HNSCC tumors with low CDKN2A gene expression. In addition, the AP-2alpha gene expression signatures are also associated with inhibition of MEK, PI3K, and mTOR pathways in the Library of Integrated Network-Based Cellular Signatures (LINCS) data. These results suggest that AP-2 transcription factors are activated as feedback from EGFR network inhibition and may mediate EGFR inhibitor resistance.

Over a half million new cases of Head and Neck Squamous Cell Carcinoma (HNSCC) are diagnosed annually worldwide, however, 5 year overall survival is only 50% for HNSCC patients. Recently, high throughput technologies have accelerated the genome-wide characterization of HNSCC. However, comprehensive pipelines with statistical algorithms that account for HNSCC biology and perform independent confirmatory and functional validation of candidates are needed to identify the most biologically relevant genes. We applied outlier statistics to high throughput gene expression data, and identified 76 top-scoring candidates with significant differential expression in tumors compared to normal tissues. We identified 15 epigenetically regulated candidates by focusing on a subset of the genes with a negative correlation between gene expression and promoter methylation. Differential expression and methylation of 3 selected candidates (BANK1, BIN2, and DTX1) were confirmed in an independent HNSCC cohorts from Johns Hopkins and TCGA (The Cancer Genome Atlas). We further performed functional evaluation of NOTCH regulator, DTX1, which was downregulated by promoter hypermethylation in tumors, and demonstrated that decreased expression of DTX1 in HNSCC tumors maybe associated with NOTCH pathway activation and increased migration potential.

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.

Many eukaryotic genes are regulated at the level of transcript elongation. Nucleosomes are likely targets for this regulation. Previously, we have shown that nucleosomes formed on very strong positioning sequences (601 and 603), present a high, orientation-dependent barrier to transcription by RNA polymerase II in vitro. The existence of this polar barrier correlates with the interaction of a 16-bp polar barrier signal (PBS) with the promoter-distal histone H3-H4 dimer. Here, we show that the polar barrier is relieved by ISW2, an ATP-dependent chromatin remodeler, which translocates the nucleosome over a short distance, such that the PBS no longer interacts with the distal H3-H4 dimer, although it remains within the nucleosome. In vivo, insertion of the 603 positioning sequence into the yeast CUP1 gene results in a modest reduction in transcription, but this reduction is orientation-independent, indicating that the polar barrier can be circumvented. However, the 603-nucleosome is present at the expected position in only a small fraction of cells. Thus, the polar barrier is probably non-functional in vivo because the nucleosome is not positioned appropriately, presumably due to nucleosome sliding activities. We suggest that interactions between PBSs and chromatin remodelers might have significant regulatory potential.

ANO1 is a calcium-activated chloride channel that is frequently overexpressed in head and neck squamous cell carcinoma (HNSCC) and other cancers. While ANO1 expression negatively correlates with survival in several cancers, its epigenetic regulation is poorly understood. We analyzed HNSCC samples from TCGA and a separate dataset of HPV+ oropharyngeal squamous cell carcinoma (OPSCC) samples to identify differentially methylated regions. E6 and E7 transfected normal oral keratinocytes (NOK) were used to induce hypermethylation of the ANO1 promoter. We found three CpG islands that correlated with ANO1 expression, including two positively correlated with expression. Using two HNSCC datasets with differential expression of ANO1, we showed hypermethylation of positively correlated CpG islands potentiates ANO1 expression. E7 but not E6 transfection of NOK cells led to hypermethylation of a positively correlated CpG island without a change in ANO1 expression. ANO1 promoter methylation was also correlated with patient survival. Our results are the first to show the contribution of positively correlated CpG's for regulating gene expression in HNSCC. Hypermethylation of the ANO1 promoter was strongly correlated with but not sufficient to increase ANO1 expression, suggesting methylation of positively correlated CpG's likely serves as an adjunct to other mechanisms of ANO1 activation.

Although promoter-associated CpG islands have been established as targets of DNA methylation changes in cancer, previous studies suggest that epigenetic dysregulation outside the promoter region may be more closely associated with transcriptional changes. Here we examine DNA methylation, chromatin marks, and transcriptional alterations to define the relationship between transcriptional modulation and spatial changes in chromatin structure. Using human papillomavirus-related oropharyngeal carcinoma as a model, we show aberrant enrichment of repressive H3K9me3 at the transcriptional start site (TSS) with methylation-associated, tumor-specific gene silencing. Further analysis identifies a hypermethylated subtype which shows a functional convergence on MYC targets and association with CREBBP/EP300 mutation. The tumor-specific shift to transcriptional repression associated with DNA methylation at TSSs was confirmed in multiple tumor types. Our data may show a common underlying epigenetic dysregulation in cancer associated with broad enrichment of repressive chromatin marks and aberrant DNA hypermethylation at TSSs in combination with MYC network activation.

The dominant paradigm for HPV carcinogenesis includes integration into the host genome followed by expression of E6 and E7 (E6/E7). We explored an alternative carcinogenic pathway characterized by episomal E2, E4, and E5 (E2/E4/E5) expression. Half of HPV positive cervical and pharyngeal cancers comprised a subtype with increase in expression of E2/E4/E5, as well as association with lack of integration into the host genome. Models of the E2/E4/E5 carcinogenesis show p53 dependent enhanced proliferation in vitro, as well as increased susceptibility to induction of cancer in vivo. Whole genomic expression analysis of the E2/E4/E5 pharyngeal cancer subtype is defined by activation of the fibroblast growth factor receptor (FGFR) pathway and this subtype is susceptible to combination FGFR and mTOR inhibition, with implications for targeted therapy.

Targeted therapies specifically act by blocking the activity of proteins that are encoded by genes critical for tumorigenesis. However, most cancers acquire resistance and long-term disease remission is rarely observed. Understanding the time course of molecular changes responsible for the development of acquired resistance could enable optimization of patients' treatment options. Clinically, acquired therapeutic resistance can only be studied at a single time point in resistant tumors.

We previously have shown that platelet-derived growth factor (PDGF) modulates the biological activity of extracellular vesicles released by adipose-derived mesenchymal stem cells (ASC-EVs). ASC-EVs may interact with blood and vessel cells by transferring proteins and nucleic acids and regulate their functions. In this study, we investigated immunomodulatory activity and protection from acute hindlimb ischemia of EVs released by PDGF-stimulated ASC (PDGF-EVs). PDGF treatment of ASC changed protein and RNA composition of released EVs by enhancing the expression of anti-inflammatory and immunomodulatory factors. In vitro, control EVs (cEVs) derived from non-stimulated ASC increased the secretion of both the IL-1b, IL-17, IFNγ, TNFα pro-inflammatory factors and the IL-10 anti-inflammatory factor, and enhanced the in vitro peripheral blood mononuclear cell (PBMC) adhesion on endothelium. In contrast, PDGF-EVs enhanced IL-10 secretion and induced TGF-β1 secretion by PBMC. Moreover, PDGF-EVs stimulated the formation of T regulatory cells. In vivo, PDGF-EVs protected muscle tissue from acute ischemia, reduced infiltration of inflammatory cells and increased T regulatory cell infiltration in respect to cEVs. Our results suggest that PDGF-EVs are enriched in anti-inflammatory and immunomodulatory factors and induced in PBMC an enhanced production of IL-10 and TGF-β1 resulting in protection of muscle from acute ischemia in vivo.

In all organisms, aminoacyl tRNA synthetases covalently attach amino acids to their cognate tRNAs. Many eukaryotic tRNA synthetases have acquired appended domains, whose origin, structure and function are poorly understood. The N-terminal appended domain (NTD) of glutaminyl-tRNA synthetase (GlnRS) is intriguing since GlnRS is primarily a eukaryotic enzyme, whereas in other kingdoms Gln-tRNA(Gln) is primarily synthesized by first forming Glu-tRNA(Gln), followed by conversion to Gln-tRNA(Gln) by a tRNA-dependent amidotransferase. We report a functional and structural analysis of the NTD of Saccharomyces cerevisiae GlnRS, Gln4. Yeast mutants lacking the NTD exhibit growth defects, and Gln4 lacking the NTD has reduced complementarity for tRNA(Gln) and glutamine. The 187-amino acid Gln4 NTD, crystallized and solved at 2.3 Å resolution, consists of two subdomains, each exhibiting an extraordinary structural resemblance to adjacent tRNA specificity-determining domains in the GatB subunit of the GatCAB amidotransferase, which forms Gln-tRNA(Gln). These subdomains are connected by an apparent hinge comprised of conserved residues. Mutation of these amino acids produces Gln4 variants with reduced affinity for tRNA(Gln), consistent with a hinge-closing mechanism proposed for GatB recognition of tRNA. Our results suggest a possible origin and function of the NTD that would link the phylogenetically diverse mechanisms of Gln-tRNA(Gln) synthesis.

Current literature suggests that epigenetically regulated super-enhancers (SEs) are drivers of aberrant gene expression in cancers. Many tumor types are still missing chromatin data to define cancer-specific SEs and their role in carcinogenesis. In this work, we develop a simple pipeline, which can utilize chromatin data from etiologically similar tumors to discover tissue-specific SEs and their target genes using gene expression and DNA methylation data. As an example, we applied our pipeline to human papillomavirus-related oropharyngeal squamous cell carcinoma (HPV + OPSCC). This tumor type is characterized by abundant gene expression changes, which cannot be explained by genetic alterations alone. Chromatin data are still limited for this disease, so we used 3627 SE elements from public domain data for closely related tissues, including normal and tumor lung, and cervical cancer cell lines. We integrated the available DNA methylation and gene expression data for HPV + OPSCC samples to filter the candidate SEs to identify functional SEs and their affected targets, which are essential for cancer development. Overall, we found 159 differentially methylated SEs, including 87 SEs that actively regulate expression of 150 nearby genes (211 SE-gene pairs) in HPV + OPSCC. Of these, 132 SE-gene pairs were validated in a related TCGA cohort. Pathway analysis revealed that the SE-regulated genes were associated with pathways known to regulate nasopharyngeal, breast, melanoma, and bladder carcinogenesis and are regulated by the epigenetic landscape in those cancers. Thus, we propose that gene expression in HPV + OPSCC may be controlled by epigenetic alterations in SE elements, which are common between related tissues. Our pipeline can utilize a diversity of data inputs and can be further adapted to SE analysis of diseased and non-diseased tissues from different organisms.

While the methods available for single-cell ATAC-seq analysis are well optimized for clustering cell types, the question of how to integrate multiple scATAC-seq data sets and/or sequencing modalities is still open. We present an analysis framework that enables such integration across scATAC-seq data sets by applying the CoGAPS Matrix Factorization algorithm and the projectR transfer learning program to identify common regulatory patterns across scATAC-seq data sets. We additionally integrate our analysis with scRNA-seq data to identify orthogonal evidence for transcriptional regulators predicted by scATAC-seq analysis. Using publicly available scATAC-seq data, we find patterns that accurately characterize cell types both within and across data sets. Furthermore, we demonstrate that these patterns are both consistent with current biological understanding and reflective of novel regulatory biology.