Non-Invasive Diagnosis of Sun Damaged Skin: Actinic Keratosis Vs Squamous Cell Carcinoma.

IMPORTANCE: Actinic keratosis (AK) is a premalignant lesion that has a1% to 10% potential of progression to squamous cell carcinoma (SCC), but it is not possible to determine which lesions are at higher risk. OBJECTIVE: This study examined the epidermal genetic profiles of actinic keratosis and SCC through non-invasive techniques seeking to develop a biopsy-free method for AK monitoring and aid in the early diagnosis of developing SCC. DESIGN: Ribonucleic acid (RNA) was collected from adhesive tape strips and gene expression levels were measured. A threshold fold change >2 and adjusted P-value <0.05 were used to determine differentially expressed genes. SETTING: Single center dermatology clinic. PARTICIPANTS: Patients who presented to the clinic with lesions suspicious of non-melanoma skin cancer that had never been previously biopsied. MAIN OUTCOME AND MEASURE: RNA was extracted via non-invasive biopsy and sequenced. Low quality samples were filtered out and the remaining samples underwent differential gene expression analysis by DESeq2 in R package. A threshold of fold change >2 and adjusted P-value <0.05 was used for determination of differentially expressed genes. The differentially expressed genes that overlapped between the corrected and uncorrected groups were the most significant for analysis. RESULTS: From 47 lesions, 6 significant differentially expressed genes were found between AK and SCC, and 25 significant differentially expressed genes between in-situ SCC and invasive SCC. Individual samples showed similarities based on diagnosis, suggesting mutations were specific to the disease and not the individual. CONCLUSIONS AND RELEVANCE: These findings highlight which genes may play a role in AK progression to SCC. The genomic differences between in-situ and invasive squamous cell carcinoma open an opportunity for early diagnosis of squamous cell carcinoma and risk prediction of actinic keratosis. J Drugs Dermatol. 2023;22(5): doi:10.36849/JDD.7097.

Identification of DNA motifs that regulate DNA methylation.

DNA methylation is an important epigenetic mark but how its locus-specificity is decided in relation to DNA sequence is not fully understood. Here, we have analyzed 34 diverse whole-genome bisulfite sequencing datasets in human and identified 313 motifs, including 92 and 221 associated with methylation (methylation motifs, MMs) and unmethylation (unmethylation motifs, UMs), respectively. The functionality of these motifs is supported by multiple lines of evidence. First, the methylation levels at the MM and UM motifs are respectively higher and lower than the genomic background. Second, these motifs are enriched at the binding sites of methylation modifying enzymes including DNMT3A and TET1, indicating their possible roles of recruiting these enzymes. Third, these motifs significantly overlap with "somatic QTLs" (quantitative trait loci) of methylation and expression. Fourth, disruption of these motifs by mutation is associated with significantly altered methylation level of the CpGs in the neighbor regions. Furthermore, these motifs together with somatic mutations are predictive of cancer subtypes and patient survival. We revealed some of these motifs were also associated with histone modifications, suggesting a possible interplay between the two types of epigenetic modifications. We also found some motifs form feed forward loops to contribute to DNA methylation dynamics.

PTPN14 phosphatase and YAP promote TGFß signalling in rheumatoid synoviocytes.

OBJECTIVE: We aimed to understand the role of the tyrosine phosphatase PTPN14-which in cancer cells modulates the Hippo pathway by retaining YAP in the cytosol-in fibroblast-like synoviocytes (FLS) from patients with rheumatoid arthritis (RA). METHODS: Gene/protein expression levels were measured by quantitative PCR and/or Western blotting. Gene knockdown in RA FLS was achieved using antisense oligonucleotides. The interaction between PTPN14 and YAP was assessed by immunoprecipitation. The cellular localisation of YAP and SMAD3 was examined via immunofluorescence. SMAD reporter studies were carried out in HEK293T cells. The RA FLS/cartilage coimplantation and passive K/BxN models were used to examine the role of YAP in arthritis. RESULTS: RA FLS displayed overexpression of PTPN14 when compared with FLS from patients with osteoarthritis (OA). PTPN14 knockdown in RA FLS impaired TGFß-dependent expression of MMP13 and potentiation of TNF signalling. In RA FLS, PTPN14 formed a complex with YAP. Expression of PTPN14 or nuclear YAP-but not of a non-YAP-interacting PTPN14 mutant-enhanced SMAD reporter activity. YAP promoted TGFß-dependent SMAD3 nuclear localisation in RA FLS. Differences in epigenetic marks within Hippo pathway genes, including YAP, were found between RA FLS and OA FLS. Inhibition of YAP reduced RA FLS pathogenic behaviour and ameliorated arthritis severity. CONCLUSION: In RA FLS, PTPN14 and YAP promote nuclear localisation of SMAD3. YAP enhances a range of RA FLS pathogenic behaviours which, together with epigenetic evidence, points to the Hippo pathway as an important regulator of RA FLS behaviour.

Computationally expanding infinium HumanMethylation450 BeadChip array data to reveal distinct DNA methylation patterns of rheumatoid arthritis.

MOTIVATION: DNA methylation signatures in rheumatoid arthritis (RA) have been identified in fibroblast-like synoviocytes (FLS) with Illumina HumanMethylation450 array. Since <2% of CpG sites are covered by the Illumina 450K array and whole genome bisulfite sequencing is still too expensive for many samples, computationally predicting DNA methylation levels based on 450K data would be valuable to discover more RA-related genes. RESULTS: We developed a computational model that is trained on 14 tissues with both whole genome bisulfite sequencing and 450K array data. This model integrates information derived from the similarity of local methylation pattern between tissues, the methylation information of flanking CpG sites and the methylation tendency of flanking DNA sequences. The predicted and measured methylation values were highly correlated with a Pearson correlation coefficient of 0.9 in leave-one-tissue-out cross-validations. Importantly, the majority (76%) of the top 10% differentially methylated loci among the 14 tissues was correctly detected using the predicted methylation values. Applying this model to 450K data of RA, osteoarthritis and normal FLS, we successfully expanded the coverage of CpG sites 18.5-fold and accounts for about 30% of all the CpGs in the human genome. By integrative omics study, we identified genes and pathways tightly related to RA pathogenesis, among which 12 genes were supported by triple evidences, including 6 genes already known to perform specific roles in RA and 6 genes as new potential therapeutic targets. AVAILABILITY AND IMPLEMENTATION: The source code, required data for prediction, and demo data for test are freely available at: http://wanglab.ucsd.edu/star/LR450K/ CONTACT: wei-wang@ucsd.edu or gfirestein@ucsd.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Predicting CpG methylation levels by integrating Infinium HumanMethylation450 BeadChip array data.

The Infinium HumanMethylation450 BeadChip array, referred as 450K array hereinafter, has been widely adopted as an affordable technique to determine DNA methylation. Tens of thousands of data have been generated on diverse cell types and patient tissues, which have provided great insight into understanding the crucial roles of epigenetic modifications in many biological processes and diseases. The limitation of this technique is its coverage, which measures methylation levels of about 450,000 CpGs, accounting for about 1.6% of all CpGs in the human genome. In the present study we developed and compared computational models to significantly expand the coverage of Illumina 450K (~11 folds). Using the whole genome bisulfite sequencing and Illumina 450K data in the human H1 embryonic stem cell, we showed that the predicted and measured methylation levels were well correlated. Our proposed model showed superior prediction accuracies compared to the existing methods on the same dataset. When applied to predict the DNA methylome on other cells, our proposed model achieved comparable performance in cross-validations, which indicates the generalizibility of the method. Our method would thus be invaluable to maximize the usage of the existing data.

Assessing characteristics of RNA amplification methods for single cell RNA sequencing.

BACKGROUND: Recently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known. RESULTS: Here, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate measurements to be quantitative at an expression level greater than ~5-10 molecules. CONCLUSIONS: Based on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information.

Normalization and noise reduction for single cell RNA-seq experiments.

UNLABELLED: A major roadblock towards accurate interpretation of single cell RNA-seq data is large technical noise resulted from small amount of input materials. The existing methods mainly aim to find differentially expressed genes rather than directly de-noise the single cell data. We present here a powerful but simple method to remove technical noise and explicitly compute the true gene expression levels based on spike-in ERCC molecules. AVAILABILITY AND IMPLEMENTATION: The software is implemented by R and the download version is available at http://wanglab.ucsd.edu/star/GRM. CONTACT: wei-wang@ucsd.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Skin Cancer Risk Is Increased by Somatic Mutations Detected Noninvasively in Healthy-Appearing Sun-Exposed Skin.

Skin cancer risk is increased by exposure to ultraviolet radiation (UVR). Because UVR exposure accumulates over time and lighter skin is more susceptible to UVR, age and skin tone are risk factors for skin cancer. However, measurements of somatic mutations in healthy-appearing skin have not been used to calculate skin cancer risk. In this study, we developed a noninvasive test that quantifies somatic mutations in healthy-appearing sun-exposed skin and applied it to a 1038-subject cohort. Somatic mutations were combined with other known skin cancer risk factors to train a model to calculate risk. The final model (DNA-Skin Cancer Assessment of Risk) was trained to predict personal history of skin cancer from age, family history, skin tone, and mutation count. The addition of mutation count significantly improved model performance (OR = 1.3, 95% confidence interval = 1.14-1.48; P = 5.3 × 10-6) and made a more significant contribution than skin tone. Calculations of skin cancer risk matched the known United States population prevalence, indicating that DNA-Skin Cancer Assessment of Risk was well-calibrated. In conclusion, somatic mutations in healthy-appearing sun-exposed skin increase skin cancer risk, and mutations capture risk information that is not accounted for by other risk factors. Clinical utility is supported by the noninvasive nature of skin sample collection through adhesive patches.

Multifaceted immune dysregulation characterizes individuals at-risk for rheumatoid arthritis.

Molecular markers of autoimmunity, such as antibodies to citrullinated protein antigens (ACPA), are detectable prior to inflammatory arthritis (IA) in rheumatoid arthritis (RA) and may define a state that is 'at-risk' for future RA. Here we present a cross-sectional comparative analysis among three groups that include ACPA positive individuals without IA (At-Risk), ACPA negative individuals and individuals with early, ACPA positive clinical RA (Early RA). Differential methylation analysis among the groups identifies non-specific dysregulation in peripheral B, memory and naïve T cells in At-Risk participants, with more specific immunological pathway abnormalities in Early RA. Tetramer studies show increased abundance of T cells recognizing citrullinated (cit) epitopes in At-Risk participants, including expansion of T cells reactive to citrullinated cartilage intermediate layer protein I (cit-CILP); these T cells have Th1, Th17, and T stem cell memory-like phenotypes. Antibody-antigen array analyses show that antibodies targeting cit-clusterin, cit-fibrinogen and cit-histone H4 are elevated in At-Risk and Early RA participants, with the highest levels of antibodies detected in those with Early RA. These findings indicate that an ACPA positive at-risk state is associated with multifaceted immune dysregulation that may represent a potential opportunity for targeted intervention.

Epigenetic Regulation of Nutrient Transporters in Rheumatoid Arthritis Fibroblast-like Synoviocytes.

OBJECTIVE: Since previous studies indicate that metabolism is altered in rheumatoid arthritis (RA) fibroblast-like synoviocytes (FLS), we undertook this study to determine if changes in the genome-wide chromatin and DNA states in genes associated with nutrient transporters could help to identify activated metabolic pathways in RA FLS. METHODS: Data from a previous comprehensive epigenomic study in FLS were analyzed to identify differences in genome-wide states and gene transcription between RA and osteoarthritis. We utilized the single nearest genes to regions of interest for pathway analyses. Homer promoter analysis was used to identify enriched motifs for transcription factors. The role of solute carrier transporters and glutamine metabolism dependence in RA FLS was determined by small interfacing RNA knockdown, functional assays, and incubation with CB-839, a glutaminase inhibitor. We performed 1 H nuclear magnetic resonance to quantify metabolites. RESULTS: The unbiased pathway analysis demonstrated that solute carrier-mediated transmembrane transport was one pathway associated with differences in at least 4 genome-wide states or gene transcription. Thirty-four transporters of amino acids and other nutrients were associated with a change in at least 4 epigenetic marks. Functional assays revealed that solute carrier family 4 member 4 (SLC4A4) was critical for invasion, and glutamine was sufficient as an alternate source of energy to glucose. Experiments with CB-839 demonstrated decreased RA FLS invasion and proliferation. Finally, we found enrichment of motifs for c-Myc in several nutrient transporters. CONCLUSION: Our findings demonstrate that changes in the epigenetic landscape of genes are related to nutrient transporters, and metabolic pathways can be used to identify RA-specific targets, including critical solute carrier transporters, enzymes, and transcription factors, to develop novel therapeutic agents.

Discovery of antimicrobial agent targeting tryptophan synthase.

Antibiotic resistance is a continually growing challenge in the treatment of various bacterial infections worldwide. New drugs and new drug targets are necessary to curb the threat of infectious diseases caused by multidrug-resistant pathogens. The tryptophan biosynthesis pathway is essential for bacterial growth but is absent in higher animals and humans. Drugs that can inhibit the bacterial biosynthesis of tryptophan offer a new class of antibiotics. In this work, we combined a structure-based strategy using in silico docking screening and molecular dynamics (MD) simulations to identify compounds targeting the α subunit of tryptophan synthase with experimental methods involving the whole-cell minimum inhibitory concentration (MIC) test, solution state NMR, and crystallography to confirm the inhibition of L-tryptophan biosynthesis. Screening 1,800 compounds from the National Cancer Institute Diversity Set I against α subunit revealed 28 compounds for experimental validation; four of the 28 hit compounds showed promising activity in MIC testing. We performed solution state NMR experiments to demonstrate that a one successful inhibitor, 3-amino-3-imino-2-phenyldiazenylpropanamide (Compound 1) binds to the α subunit. We also report a crystal structure of Salmonella enterica serotype Typhimurium tryptophan synthase in complex with Compound 1 which revealed a binding site at the αß interface of the dimeric enzyme. MD simulations were carried out to examine two binding sites for the compound. Our results show that this small molecule inhibitor could be a promising lead for future drug development.

Caspase-8 Variant G Regulates Rheumatoid Arthritis Fibroblast-Like Synoviocyte Aggressive Behavior.

OBJECTIVE: Fibroblast-like synoviocytes (FLS) play a pivotal role in rheumatoid arthritis (RA) by contributing to synovial inflammation and progressive joint damage. An imprinted epigenetic state is associated with the FLS aggressive phenotype. We identified CASP8 (encoding for caspase-8) as a differentially marked gene and evaluated its pathogenic role in RA FLSs. METHODS: RA FLS lines were obtained from synovial tissues at arthroplasty and used at passage 5-8. Caspase-8 was silenced using small interfering RNA, and its effect was determined in cell adhesion, migration and invasion assays. Quantitative reverse transcription PCR and western blot were used to assess gene and protein expression, respectively. A caspase-8 selective inhibitor was used determine the role of enzymatic activity on FLS migration and invasion. Caspase-8 isoform transcripts and epigenetic marks in FLSs were analyzed in FLS public databases. Crystal structures of caspase-8B and G were determined. RESULTS: Caspase-8 deficiency in RA FLSs reduced cell adhesion, migration, and invasion independent of its catalytic activity. Epigenetic and transcriptomic analyses of RA FLSs revealed that a specific caspase-8 isoform, variant G, is the dominant isoform expressed (~80% of total caspase-8) and induced by PDGF. The crystal structures of caspase-8 variant G and B were identical except for a unique unstructured 59 amino acid N-terminal domain in variant G. Selective knockdown of caspase-8G was solely responsible for the effects of caspase-8 on calpain activity and cell invasion in FLS. CONCLUSION: Blocking caspase-8 variant G could decrease cell invasion in diseases like RA without the potential deleterious effects of nonspecific caspase-8 inhibition.

Distinct DNA Methylation Patterns of Rheumatoid Arthritis Peripheral Blood and Synovial Tissue T Cells.

OBJECTIVE: To study epigenetic patterns in T lymphocytes that accumulate in the rheumatoid arthritis (RA) synovium, we characterized DNA methylation of CD3+ T cells in peripheral blood and synovial tissue in patients with RA and osteoarthritis (OA). METHODS: Genomic DNA of CD3+ T cells was isolated from patients with RA (n = 8) and OA (n = 5) from blood or the synovium at the time of an arthroplasty using antibodies and magnetic beads. Methylation was measured by using the Illumina Infinium MethylationEPIC Kit. Differentially methylated loci (DML) and differentially methylated genes (DMGs) were identified by using Welch's t-test. Principal component analysis, hierarchical clustering, and pathway analysis were used to determine relationships among groups. RESULTS: When we compared DNA methylation of CD3+ T cells between peripheral blood and synovial tissue within each disease, 4615 and 164 DML were identified in RA and OA samples, respectively, resulting in 832 and 36 DMGs. A principal component analysis showed that methylation differences in T cells were greater on the basis of on location (blood vs synovium) rather than disease (RA vs OA). Differentially modified pathways were significantly enriched between RA blood and synovial T cells, especially in genes related to complement, integrin cell surface interactions, and the P53 pathway. The limited number of DMGs identified between OA blood and synovial T cells did not conform to biologic pathways. CONCLUSION: The patterns of DNA methylation in RA show location-specific differences related to immune pathways, whereas methylation differences in OA are limited. The RA joint-specific signatures could be due to selective accumulation of T-cell populations or expansion of differentially marked adaptive immune cells. Understanding epigenetic patterns could provide clues to the types of T cells that accumulate in the RA joint and identify potential therapeutic targets.

Lasp1 regulates adherens junction dynamics and fibroblast transformation in destructive arthritis.

The LIM and SH3 domain protein 1 (Lasp1) was originally cloned from metastatic breast cancer and characterised as an adaptor molecule associated with tumourigenesis and cancer cell invasion. However, the regulation of Lasp1 and its function in the aggressive transformation of cells is unclear. Here we use integrative epigenomic profiling of invasive fibroblast-like synoviocytes (FLS) from patients with rheumatoid arthritis (RA) and from mouse models of the disease, to identify Lasp1 as an epigenomically co-modified region in chronic inflammatory arthritis and a functionally important binding partner of the Cadherin-11/ß-Catenin complex in zipper-like cell-to-cell contacts. In vitro, loss or blocking of Lasp1 alters pathological tissue formation, migratory behaviour and platelet-derived growth factor response of arthritic FLS. In arthritic human TNF transgenic mice, deletion of Lasp1 reduces arthritic joint destruction. Therefore, we show a function of Lasp1 in cellular junction formation and inflammatory tissue remodelling and identify Lasp1 as a potential target for treating inflammatory joint disorders associated with aggressive cellular transformation.

T-Analyst: a program for efficient analysis of protein conformational changes by torsion angles.

T-Analyst is a user-friendly computer program for analyzing trajectories from molecular modeling. Instead of using Cartesian coordinates for protein conformational analysis, T-Analyst is based on internal bond-angle-torsion coordinates in which internal torsion angle movements, such as side-chain rotations, can be easily detected. The program computes entropy and automatically detects and corrects angle periodicity to produce accurate rotameric states of dihedrals. It also clusters multiple conformations and detects dihedral rotations that contribute hinge-like motions. Correlated motions between selected dihedrals can also be observed from the correlation map. T-Analyst focuses on showing changes in protein flexibility between different states and selecting representative protein conformations for molecular docking studies. The program is provided with instructions and full source code in Perl.

Enhancing KDM5A and TLR activity improves the response to immune checkpoint blockade.

Immune checkpoint blockade (ICB) therapies are now established as first-line treatments for multiple cancers, but many patients do not derive long-term benefit from ICB. Here, we report that increased amounts of histone 3 lysine 4 demethylase KDM5A in tumors markedly improved response to the treatment with the programmed cell death protein 1 (PD-1) antibody in mouse cancer models. In a screen for molecules that increased KDM5A abundance, we identified one (D18) that increased the efficacy of various ICB agents in three murine cancer models when used as a combination therapy. D18 potentiated ICB efficacy through two orthogonal mechanisms: (i) increasing KDM5A abundance, which suppressed expression of the gene PTEN (encoding phosphatase and tensin homolog) and increased programmed cell death ligand 1 abundance through a pathway involving PI3K-AKT-S6K1, and (ii) activating Toll-like receptors 7 and 8 (TLR7/8) signaling pathways. Combination treatment increased T cell activation and expansion, CD103+ tumor-infiltrating dendritic cells, and tumor-associated M1 macrophages, ultimately enhancing the overall recruitment of activated CD8+ T cells to tumors. In patients with melanoma, a high KDM5A gene signature correlated with KDM5A expression and could potentially serve as a marker of response to anti-PD-1 immunotherapy. Furthermore, our results indicated that bifunctional agents that enhance both KDM5A and TLR activity warrant investigation as combination therapies with ICB agents.

Synoviocyte-targeted therapy synergizes with TNF inhibition in arthritis reversal.

Fibroblast-like synoviocytes (FLS) are joint-lining cells that promote rheumatoid arthritis (RA) pathology. Current disease-modifying antirheumatic agents (DMARDs) operate through systemic immunosuppression. FLS-targeted approaches could potentially be combined with DMARDs to improve control of RA without increasing immunosuppression. Here, we assessed the potential of immunoglobulin-like domains 1 and 2 (Ig1&2), a decoy protein that activates the receptor tyrosine phosphatase sigma (PTPRS) on FLS, for RA therapy. We report that PTPRS expression is enriched in synovial lining RA FLS and that Ig1&2 reduces migration of RA but not osteoarthritis FLS. Administration of an Fc-fusion Ig1&2 attenuated arthritis in mice without affecting innate or adaptive immunity. Furthermore, PTPRS was down-regulated in FLS by tumor necrosis factor (TNF) via a phosphatidylinositol 3-kinase-mediated pathway, and TNF inhibition enhanced PTPRS expression in arthritic joints. Combination of ineffective doses of TNF inhibitor and Fc-Ig1&2 reversed arthritis in mice, providing an example of synergy between FLS-targeted and immunosuppressive DMARD therapies.

Synergistic regulation and ligand-induced conformational changes of tryptophan synthase.

Conformational changes of enzyme complexes are often related to regulating and creating an optimal environment for efficient chemistry. We investigated the synergistic regulation of the tryptophan synthase (TRPS) complex, studied for decades as a model of allosteric regulation and substrate channeling within protein complexes. TRPS is a bifunctional tetrameric alphabetabetaalpha enzyme complex that exhibits cooperative motions of the alpha- and beta-subunits by tightly controlled allosteric interactions. We have delineated the atomically detailed dynamics and conformational changes of TRPS in the absence and presence of substrates using molecular dynamics simulations. The computed energy and entropy associated with the protein motions also offer mechanistic insights into the conformational fluctuations and the ligand binding mechanism. The flexible alpha-L6 loop samples both open and partially closed conformations in the ligand-free state but shifts to fully closed conformations when its substrates are present. The fully closed conformations are induced by favorable protein-ligand interactions but are partly compensated by configurational entropy loss. Considerable local rearrangements exist during ligand binding processes when the system is searching for energy minima. The motion of the region that closes the beta-subunit during catalysis, the COMM domain, couples with the motion of the alpha-subunit, although the fluctuations are smaller than in the flexible loop regions. Because of multiple conformations of ligand-free TRPS in the open and partially closed states, the alpha-L6 loop fluctuations have preferential directionality, which may facilitate the fully closed conformations induced by alpha- and beta-substrates binding to both subunits. Such cooperative and directional motion may be a general feature that contributes to catalysis in many enzyme complexes.

Integrative analysis with expanded DNA methylation data reveals common key regulators and pathways in cancers.

The integration of genomic and DNA methylation data has been demonstrated as a powerful strategy in understanding cancer mechanisms and identifying therapeutic targets. The TCGA consortium has mapped DNA methylation in thousands of cancer samples using Illumina Infinium Human Methylation 450 K BeadChip (Illumina 450 K array) that only covers about 1.5% of CpGs in the human genome. Therefore, increasing the coverage of the DNA methylome would significantly leverage the usage of the TCGA data. Here, we present a new model called EAGLING that can expand the Illumina 450 K array data 18 times to cover about 30% of the CpGs in the human genome. We applied it to analyze 13 cancers in TCGA. By integrating the expanded methylation, gene expression, and somatic mutation data, we identified the genes showing differential patterns in each of the 13 cancers. Many of the triple-evidenced genes identified in majority of the cancers are biomarkers or potential biomarkers. Pan-cancer analysis also revealed the pathways in which the triple-evidenced genes are enriched, which include well known ones as well as new ones, such as axonal guidance signaling pathway and pathways related to inflammatory processing or inflammation response. Triple-evidenced genes, particularly TNXB, RRM2, CELSR3, SLC16A3, FANCI, MMP9, MMP11, SIK1, and TRIM59 showed superior predictive power in both tumor diagnosis and prognosis. These results have demonstrated that the integrative analysis using the expanded methylation data is powerful in identifying critical genes/pathways that may serve as new therapeutic targets.

Joint Location-Specific JAK-STAT Signaling in Rheumatoid Arthritis Fibroblast-like Synoviocytes.

OBJECTIVE: Rheumatoid arthritis (RA) fibroblast-like synoviocytes (FLS) derived from hip and knee have distinctive DNA methylation and transcriptome patterns in interleukin (IL)-6 signaling and Janus kinase (JAK)-signal transducers and activators of transcription (STAT) pathways. To determine the functional effects of these joint-specific signatures, we evaluated how RA hip and knee FLS differ in their response to IL-6. METHODS: Hip or knee RA FLS were obtained after arthroplasty. Previously published datasets on epigenetic landscape of FLS were mined to identify joint-specific IL-6-related epigenomic differences. RNA sequencing was performed on five RA hip and five knee FLS treated with or without IL-6. Differential gene expression was determined using edgeR software. STAT3 phosphorylation was measured using bead assays. Sensitivity to tofacitinib was evaluated by measuring CCL2 inhibition using quantitative polymerase chain reaction. RESULTS: Assay for Transposase-Accessible Chromatin sequencing and histone chromatin immunoprecipitation sequencing datasets from RA FLS were analyzed to identify epigenomic differences between hip and knee. Differential chromatin accessibility was associated with IL-6,IL-6R, and JAK1 genes. H3K27ac was also differentially marked at other JAK-STAT-related genes, including STAT3-STAT5A region. Principal component analysis of RNA sequencing data confirmed segregation between RA hip and knee FLS under basal conditions, that persisted following IL-6 treatment. STAT3 phosphorylation after IL-6 was significantly higher in knee than hip FLS and was highly correlated with JAK1 protein levels. Knee FLS were less sensitive to the JAK inhibitor tofacitinib than hip FLS. CONCLUSION: RA hip and knee FLS have distinct transcriptomes, epigenetic marks, and STAT3 activation patterns in the IL-6 pathway. These joint-specific differences might contribute to a differential clinical response in individual joints to targeted therapies such as JAK inhibitors.