Integrated Analysis Of Gene Expression Research Articles

MARVEL: an integrated alternative splicing analysis platform for single-cell RNA sequencing data.

Alternative splicing is an important source of heterogeneity underlying gene expression between individual cells but remains an understudied area due to the paucity of computational tools to analyze splicing dynamics at single-cell resolution. Here, we present MARVEL, a comprehensive R package for single-cell splicing analysis applicable to RNA sequencing generated from the plate- and droplet-based methods. We performed extensive benchmarking of MARVEL against available tools and demonstrated its utility by analyzing multiple publicly available datasets in diverse cell types, including in disease. MARVEL enables systematic and integrated splicing and gene expression analysis of single cells to characterize the splicing landscape and reveal biological insights.

Identification of potential biomarkers for systemic lupus erythematosus by integrated analysis of gene expression and methylation data.

Systemic lupus erythematosus (SLE) is a heterogeneous and chronic autoimmune disease. Aberrant DNA methylation occurs during various processes of SLE development regulating the mRNA expression of interrelated genes. This study aims to screen potential DNA methylation markers for SLE. Gene expression and methylation datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between SLE patients and healthy controls were screened using the limma R package, and differentially methylated positions (DMPs) and regions (DMRs) were identified using dmpfinder and bumphunter (minfi). Additionally, the DNA methylation markers to distinguish SLE patients from healthy controls were explored through receiver operating characteristic (ROC) curves and logistic regression analyses. Finally, we validated the results of the bioinformatic analysis by pyrosequencing. In total, 91 DEGs, 90,092 DMPs, 15 DMRs, and 13 DMR-associated genes were identified. Through the integrative analysis of DEG- and DMR-associated genes, we identified five type I interferon (IFN)-related genes as key epigenetic-driven genes in SLE. GO enrichment analysis showed that the five SLE-associated epigenetic-driven genes were mainly enriched in the type I IFN signaling pathway involved in immune response and defense response to virus. Moreover, we identified two SLE-specific DNA methylation markers, three SLE without lupus nephritis (SLE-LN-)-specific DNA methylation markers, and two SLE with lupus nephritis (SLE-LN+)-specific DNA methylation markers by stepwise logistic regression. Overall, our study demonstrates potential DNA methylation markers of SLE, SLE-LN-, and SLE-LN+, which may help the diagnosis, boost the development of new epigenetic therapy, and contribute to individualized treatment. Key Points • This study identified five type I IFN-related genes as key epigenetic-driven genes in SLE, which support the importance of the type I IFN pathway in the pathogenesis of SLE • We identified novel DNA methylation biomarkers in SLE, SLE-LN-, and SLE-LN+ by a comprehensive analysis of bioinformatics methods and executed experimental validation, and binary logistic regression analysis showed that they have excellent potential • These results may provide new insights into the biological mechanisms of SLE, and identify reliable biomarkers for SLE, SLE-LN-, and SLE-LN+, which may contribute to diagnosis and individualized treatment.

Integrated transcriptomics and metabolomics analyses provide insights into salt-stress response in germination and seedling stage of wheat (Triticum aestivum L.)

One of the key elements impacting the productivity of wheat production is soil salinity. Here, we characterize the metabolomic and transcriptome responses to salt stress in two distinct wheat cultivars with varying levels of salt tolerance. Cangmai 6005 (CM6005) is a new wheat variety bred in the Cangzhou Academy of Agriculture and Forestry Sciences. After salt treatment, the germination and seedling stage of CM6005 maintains green leaves and produces a longer bud length than the cultivar Kenong9204 (KN9204). In this study, we investigated genes/metabolite activity changes in both types subjected to salt and control treatments using integrated transcriptomics and metabolomics analyses. By comparing data from the salt-treated plants with the control, 5161 (3235 upregulated and 1926 downregulated) and 211 (29 up and 182 downregulated) DEGs(Differentially Expressed Genes) were identified in the germination and seedling stage of CM6005. A total of 2061 (898 upregulated and 1163 downregulated) and 99 (84 upregulated and 15 downregulated) DEGs were identified in the germination and seedling stage of KN9204. CM6005's germination and seedling stage saw the identification of 792 (492 upregulated and 300 downregulated) and 2217 (1195 upregulated and 1032 downregulated) DAMs(Differentially Accumulated Metabolites), while KN9204's germination and seedling stage saw the identification of 1999 (997 upregulated and 1002 downregulated) and 1702 (860 upregulated and 842 downregulated) DAMs. The effects of salt stress on glycerolipid metabolism, phenylalanine metabolism, and glycerophospholipid metabolism were significantly modulated under salt treatments in the germination and seedling stages of CM6005 and KN9204, respectively, according to an integrated analysis of gene expression and metabolite profiles, assessment of metabolic pathways, and KEGG enrichment. Our findings showed that salt treatments caused stress-induced significant alterations in both transcriptomes and metabolomes. Wheat salt tolerance was regulated by key pathways linked to glycerolipid and phenylalanine metabolism, and these pathways serve as a crucial guide for growing wheat in saline soil. GRAS and MYB transcription factors might also regulate Glycerolipid metabolism and Phenylalanine metabolism.

LINE-1 hypomethylation is associated with poor outcomes in locoregionally advanced oropharyngeal cancer

Background and purposeCurrently, human papillomavirus (HPV) positivity represents a strong prognostic factor for both reduced risk of relapse and improved survival in patients with oropharyngeal squamous cell carcinoma (OPSCC). However, a subset of HPV-positive OPSCC patients still experience poor outcomes. Furthermore, HPV-negative OPSCC patients, who have an even higher risk of relapse, are still lacking suitable prognostic biomarkers for clinical outcome. Here, we evaluated the prognostic value of LINE-1 methylation level in OPSCC patients and further addressed the relationship between LINE-1 methylation status and p53 protein expression as well as genome-wide/gene-specific DNA methylation.ResultsIn this study, DNA was extracted from 163 formalin-fixed paraffin-embedded tissue samples retrospectively collected from stage III-IVB OPSCC patients managed with curative intent with up-front treatment. Quantitative methylation-specific PCR revealed that LINE-1 hypomethylation was directly associated with poor prognosis (5-year overall survival—OS: 28.1% for LINE-1 methylation < 35% vs. 69.1% for ≥ 55%; p < 0.0001). When LINE-1 methylation was dichotomized as < 55% versus ≥ 55%, interaction with HPV16 emerged: compared with hypermethylated HPV16-positive patients, subjects with hypomethylated HPV16-negative OPSCC reported an adjusted higher risk of death (HR 4.83, 95% CI 2.24–10.38) and progression (HR 4.54, 95% CI 2.18–9.48). Tumor protein p53 (TP53) gene is often mutated and overexpressed in HPV-negative OPSCC. Since p53 has been reported to repress LINE-1 promoter, we then analyzed the association between p53 protein expression and LINE-1 methylation levels. Following p53 immunohistochemistry, results indicated that among HPV16-negative patients with p53 ≥ 50%, LINE-1 methylation levels declined and remained stable at approximately 43%; any HPV16-positive patient reported p53 ≥ 50%. Finally, DNA methylation analysis demonstrated that genome-wide average methylation level at cytosine–phosphate–guanine sites was significantly lower in HPV16-negative OPSCC patients who relapsed within two years. The subsequent integrative analysis of gene expression and DNA methylation identified 20 up-regulated/hypomethylated genes in relapsed patients, and most of them contained LINE-1 elements in their promoter sequences.ConclusionsEvaluation of the methylation level of LINE-1 may help in identifying the subset of OPSCC patients with bad prognosis regardless of their HPV status. Aberrant LINE-1 hypomethylation might occur along with TP53 mutations and lead to altered gene expression in OPSCC.

Immuno-AML, a Novel Immunogenomic Classifier Predicting Chemotherapy Response in Pediatric Patients with AML

Introduction Acute myeloid leukemia (AML) represents 20% of pediatric leukemias. Despite therapeutic improvements, ∼30% of children die due to therapy-related toxicity and relapse. In solid tumors, the density and functional orientation of the tumor microenvironment (TME) influence prognosis and response to chemotherapy and immunotherapy. Defining immunologic features associated with unfavorable response to standard treatment in pediatric AML might improve stratification systems that can be used for experimental interventions and personalized approaches. In this study, we investigated the potential mechanisms and effect of immune response and evasion in bone marrow (BM) of AML pediatric patients through an integrative gene expression analysis. Methods Thirty-two BM aspirates were collected from pediatric patients with non-promyelocytic AML at diagnosis in 3 different hospitals in Qatar, Pakistan, and Italy. Patients were assigned to 2 prognosis-related groups: patients who maintained a complete remission (CR) after first line of chemotherapy (sustained CR) vs patients who progressed/relapsed and/or obtained CR after hematopoietic stem cells transplantation (HSCT) (non-sustained CR). BM mRNA samples were analyzed with RNA sequencing (RNA-Seq) and/or NanoString's PanCancer IO 360 Gene Expression research panel. In particular, mRNA of 25 samples (Cohort 1, discovery set) were analyzed by NanoString's PanCancer IO 360. Subsequently, a subset of samples from Cohort 1 (n=19), was analyzed by RNA-Seq for technical validation. Cohort 1 results were then used to build a predictive classifier that was tested on Cohort 2 samples (n=7, validation set), analyzed with RNA-Seq. Results Gene expression analysis of 25 samples (Cohort 1, sustained CR, n=6; non-sustained CR, n=19) using NanoStringassay revealed 67 significant differentially expressed genes (DEGs; p < 0.05, LIMMA) among sustained CR vs non-sustained CR groups. Patients with sustained CR displayed coherent overexpression of immune genes related to IFN activation (IFIT3, IFITM1, IFI27, STAT1, GBP1), cytotoxic function (PRF1, GNLY), antigen presentation and B cell functions (TAP1, CD19), and T cell infiltration (CD3D, CD8A), consistent with a favorable T helper 1 (Th1)-cytotoxic polarization of the TME. This pattern was not observed in non-sustained CR patients, which overexpressed genes consistent with macrophage-myeloid suppression (CD68, TREM1) and intrinsic oncogene signaling linked with T cell exclusion and immune suppression (WNT5A, WNT-β- catenin pathway, and EFGR) (Fig1 A,B). This 67-gene signature (67GenSig) was technically validated using an orthogonal platform (RNA-Seq) on a subset of 19 patients (sustained CR, n=5; non-sustained CR, n=14) for which sufficient RNA-Seq data was available (65 out of 67 transcripts were available for analysis, 2 transcripts were filtered out after QC). Unsupervised PCA (Fig1 C) based on 67GenSig clearly segregated samples according to outcome, confirming the previous NanoString results. Next, we sought to identify a predictive classifier to precisely discriminate sustained CR from non-sustained CR AML pediatric patients using a minimal number of genes. By applying a Random Forest-based feature selection on 67GenSig transcripts of RNA-Seq data from Cohort 1 samples, we developed a 13-gene classifier (Immuno-AML) that was tested in a new independent dataset (Fig1 D; Cohort 2, n=7: sustained CR, n=4; non-sustained CR, n=3). Overall, genes included in the Immuno-AML predictor substantiated a positive Th1/cytotoxic vs myeloid polarization. The Immuno-AML predictor was able to classify patients in the validation cohort (Cohort 2) in "sustained CR" and "non-sustained CR" prognostic groups with a very good performance achieving 85.71% accuracy, 100% specificity, and 75% sensitivity. Conclusion Our data suggest that response to conventional therapy in AML pediatric patients is conditional to the presence of a Th1 polarization of the TME while is prevented by myeloid-mediated immune suppression and intrinsic oncogenic signaling. The optimized predictive signature (Immuno-AML) might be tested and/or refined in larger cohort to develop a clinical-grade predictive biomarker. It might help to provide a rational guidance for risk stratification criteria and personalized treatment decision paths, implying the possibility of combining immunotherapy drugs. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Whole-Genome Analysis of Histone Modifications Reveals New Insights into the Biology and Clinical Behavior of Mantle Cell Lymphoma Subtypes

Introduction: Mantle cell lymphoma (MCL) is a mature B-cell neoplasm characterized by the t(11;14)(q13;q32) leading to cyclin D1 overexpression. Two major clinico-biological subtypes of MCL have been recognized, conventional (cMCL) and leukemic non-nodal MCL (nnMCL), being the former clinically more aggressive than the latter. Although these subtypes have been well characterized at the genomic level, the genome-wide landscape of histone modifications is widely unknown. Aim: To explore whether an integrative multiomic analysis of chromatin marks and gene expression may help us to better understand the biology and clinical behavior of cMCL and nnMCL. Methods: We carried out 2 profiling strategies. On the one hand, we performed ChIP-seq for H3K27ac, which marks active regulatory elements, in a series of 52 MCL cases, and we also profiled chromatin accessibility by ATAC-seq in 28 of these cases. On the other hand, we performed ChIP-seq for 6 histone modifications with complementary functions (H3K4me1, H3K4me3, H3K27ac, H3K36me3, H3K27me3 and H3K9me3) in purified neoplastic cells of 3 cMCL and 3 nnMCL, and we mined ChIP-seq data from normal B cell subpopulations. Additionally, we analyzed previously published expression data from 44 MCL profiled by Affymetrix U219 microarrays. Clinical data were available for most cases. Data were analyzed using a battery of computational and statistical approaches. Results: An initial unsupervised principal component analyses of the H3K27ac and ATAC-seq data revealed 2 main clusters corresponding to cMCL and nnMCL, indicating that the chromatin landscape is markedly different between the 2 MCL subtypes. A supervised differential analysis of H3K27ac data between cMCL and nnMCL showed extensive differences, mostly associated with increased H3K27ac in cMCL. Putting the data in the context of normal B cell subpopulations, we identified 746 de novo active regions in cMCL and 126 in nnMCL (LFC>1, FDR ≤0.05). Interestingly, more than 60% of these regions were enhancers according to the chromatin states analysis (derived from the integration of 6 histone modifications), and the majority of them presented an open chromatin configuration. This chromatin activation patterns correlated with transcriptional differences between cMCL and nnMCL. Analyzing the target genes of these regions, we identified 167 and 20 upregulated genes in cMCL and nnMCL, respectively. Upregulated genes in cMCL were linked to cellular processes related to cell cycle and cell proliferation according to gene ontology analysis. Analyzing the transcription factor binding motifs present in the ATAC-seq peaks among the de novo active H3K27ac regions in cMCL, we observed an enrichment in specific transcription factor families such as Krüppel-like family (KLF) and E2F. However, there was no significant enrichment in any transcription factor family among nnMCL de novo active regions. Moreover, although the cMCL-associated de novo H3K27ac signature was common to all cMCL cases, we did observe varying H3K27ac levels among cases. We then explored whether H3K27ac levels could be associated with clinical features in cMCL. In fact, we identified 100 specific regions whose increased H3K27ac levels were significantly associated with shorter overall survival, leading to the identification of two subgroups of cMCL with markedly different clinical behavior. Conclusions: The results obtained with this multilayer chromatin analysis confirm that MCL is a heterogeneous disease showing widespread differences between the 2 subtypes. cMCL present a clear de novo chromatin activation associated with upregulation of key genes involved in cMCL pathogenesis, while nnMCL cases seem to be characterized by the absence of this signature and an overall chromatin profile more similar to normal B cells. Moreover, the level of activation in regulatory regions in cMCL seems to be related with the clinical outcome of the patients, with more activation associated with shorter overall survival.

Integrated Gene Expression Analysis Identifies ETS2 Involved in Oncogene Induced Senescence to be Associated with Poor Outcome in Paediatric AML

Pathogenicity of AML is characterized by many chromosomal and gene alterations, which summarize substantial differences in response to therapy and survival of patients following chemotherapy. More in-depth understanding of the molecular and genomic landscape of AML is paramount to improving the therapeutic outcome and prospecting new targets to help combat the battle against AML. Genome-wide transcriptomics-based approaches have shown promising results in identifying signatures associated with poor outcomes. Our group has previously developed and applied an innovative PROMISE (PRojection Onto the Most Interesting Statistical Evidence) statistical method to enable simultaneous and directional evaluation of multiple clinical endpoints against an omic variable (1). In our previous investigations, we used a cohort of 42 patients from the multi-site AML97 clinical trial and a cohort of 46 patients from multi-site AML02 (NCT00136084). to identify genes associated with the biologically meaningful and therapeutically relevant pattern of association with multiple clinical and pharmacologic endpoints (2). Given the small sample size investigated in previous report, we now extended PROMISE analysis, we extended PROMISE analysis (unadjusted and risk-adjusted analysis) using three clinical endpoints (Minimal Residual Disease at day 22 (MRD22), Event Free Survival (EFS), and overall survival (OS)) in 163 patients treated on multi-site AML02 clinical trial (NCT00136084). At the PROMISE p-value threshold of <0.001, 177 probes mapping to 153 unique genes were identified, of these, 59 were associated with detrimental pattern (MRD positivity and inferior EFS and OS) of outcome association, and 94 were associated with beneficial pattern (MRD negativity and better EFS and OS) of association with clinical outcome. Fig 1 shows the bar-plot and heat-map for the top 100 genes identified in the integrated PROMISE analysis. As expected, DNMT3B, GPR56, SPINK2, and FAM30A, part of our recently reported leukemic stem cell scores, were among the top detrimental hits (MRD1, EFS, OS, and PROMISE, all p values <0.0002). Pathway analysis of 59 genes associated with detrimental outcomes using Reactome, Ingenuity pathway analysis, and other pathway analysis tools identified pathways enriched with the genes significantly associated with outcome. We want to highlight a few detrimental genes worth pursuing as prognostic biomarkers or for novel drug development. ETS2 plays a role in 'Oncogene Induced Senescence,' which is triggered by high levels of RAS/RAF/MAPK signalling. ETS2 is also involved in HER2 signalling in breast cancer and HGF signaling (Fig 1). In our dataset, ETS2 was significantly associated with higher MRD22 positivity and inferior EFS and OS (all p<0.002), Fig 2. ETS2 was further expressed at a higher level in AML cells than normal (p<0.05). Though the role of ETS2 in adult AML has been recently reported, our results in paediatric AML further support it as a potential therapeutic target for pursuing drug development. Among the significant detrimental genes with potential actionable drugs included drug transporter ABCC1, a glycoprotein 2A, a transmembrane receptor ITGA2B and YES1, a protooncogene belonging to SRC tyrosine kinase superfamily. Overall, our integrated analysis to identify genes that are predictive of a therapeutically meaningful patterns of association with multiple clinical outcome endpoints identified markers of significant prognostic and therapeutic relevance; ongoing studies are focused on PROMISE validation analysis in an independent cohort of patients from AML08 clinical trial.

Integrated analysis of lncRNA and gene expression in longissimus dorsi muscle at two developmental stages of Hainan black goats.

It is deemed that meat quality of kids' is better than that of adults' for Hainan black goat. Generally, meat quality is affected by many indicators, such as intramuscular fat (IMF) content, muscle fiber diameter and shear force. It is indicated that long non-coding RNAs (lncRNAs) play essential roles in meat quality of goats. However, it is unclear whether and how lncRNAs and genes play their roles in meat quality of Hainan Black goats. Here, we firstly compared the meat quality between two-month-old kids (kids) and adult goats (adults). Then, the lncRNA-seq and RNA-seq data were integrated and analyzed to explore the potential functions of lncRNAs and genes. The results showed that adults' IMF content and muscle fiber diameter were extremely significantly higher than that of kids (P<0.01). For the sequenced data, average 84,970,398, and 83,691,250 clean reads were obtained respectively for Kids and adults, among which ~96% were mapped to the reference genome of goats. Through analyzing, 18,242 goat annotated genes, 1,429 goat annotated lncRNAs and 2,967 novel lncRNAs were obtained. Analysis of differential expression genes (DEGs) and lncRNAs (DELs) showed that 328 DEGs and 98 DELs existed between kids and adults. Furthermore, functional enrichment analysis revealed that a number of DEGs and DELs were mainly associated with IMF. Primarily, DGAT2 expressed higher in adults than that in kids and CPT1A expressed higher in kids than that in adults. Both of them were overlapped by DEGs and targets of DELs, suggesting the two DEGs and the DELs targeted by the two DEGs might be the potential regulators of goat IMF deposition. Taken together, our results provide basic support for further understanding the function and mechanism of lncRNAs and genes in meat quality of Hainan black goats.

AIscEA: unsupervised integration of single-cell gene expression and chromatin accessibility via their biological consistency.

The integrative analysis of single-cell gene expression and chromatin accessibility measurements is essential for revealing gene regulation, but it is one of the key challenges in computational biology. Gene expression and chromatin accessibility are measurements from different modalities, and no common features can be directly used to guide integration. Current state-of-the-art methods lack practical solutions for finding heterogeneous clusters. However, previous methods might not generate reliable results when cluster heterogeneity exists. More importantly, current methods lack an effective way to select hyper-parameters under an unsupervised setting. Therefore, applying computational methods to integrate single-cell gene expression and chromatin accessibility measurements remains difficult. We introduce AIscEA-Alignment-based Integration of single-cell gene Expression and chromatin Accessibility-a computational method that integrates single-cell gene expression and chromatin accessibility measurements using their biological consistency. AIscEA first defines a ranked similarity score to quantify the biological consistency between cell clusters across measurements. AIscEA then uses the ranked similarity score and a novel permutation test to identify cluster alignment across measurements. AIscEA further utilizes graph alignment for the aligned cell clusters to align the cells across measurements. We compared AIscEA with the competing methods on several benchmark datasets and demonstrated that AIscEA is highly robust to the choice of hyper-parameters and can better handle the cluster heterogeneity problem. Furthermore, AIscEA significantly outperforms the state-of-the-art methods when integrating real-world SNARE-seq and scMultiome-seq datasets in terms of integration accuracy. AIscEA is available at https://figshare.com/articles/software/AIscEA_zip/21291135 on FigShare as well as {https://github.com/elhaam/AIscEA} onGitHub. Supplementary data are available at Bioinformatics online.

Bioinformatics Identification of Aberrantly Methylated Differentially Expressed Genes Associated with Arteriosclerosis by Integrative Analysis of Gene Expression and DNA Methylation Datasets.

The prognosis of patients with advanced arteriosclerosis is bleak due to the lack of understanding of arteriosclerosis. Epigenetics-based DNA methylation plays an important role in the pathogenesis of arteriosclerosis. Hence, we aimed to identify the epigenetics-related aberrantly methylated differentially expressed genes (AMDEGs) in arteriosclerosis. A gene expression dataset and DNA methylation dataset were downloaded from the Gene Expression Omnibus database, and AMDEGs were identified on the basis of the relationship between methylation and expression. Subsequently, the expression levels of candidate hub genes were detected in human peripheral blood mononuclear cells (PBMCs) from atherosclerotic patients and control subjects by RT-qPCR and Western blot. Lastly, the methylation level of the target gene was detected using the MassARRAY method. In the present study, the hypermethylated and downregulated genes were mainly involved in vascular smooth muscle contraction. The hypomethylated and upregulated genes were markedly associated with immune-inflammatory processes. Following validation, LMOD1 was identified as the target gene, which was hypermethylated and downregulated in arteriosclerosis. The methylation levels of CpG sites in LMOD1 promoter were detected to be elevated in the PBMCs of atherosclerotic patients. In conclusion, AMDEGs identified in the present study may assist in understanding the pathogenesis of arteriosclerosis. LMOD1 exhibits potential as a promising diagnostic and therapeutic biomarker for arteriosclerosis.

Integrated analysis of intestinal microbiota and host gene expression in colorectal cancer patients.

Introduction. Colorectal cancer (CRC) is one of the most common cancers and poses heavy burden on global health. The relationship between mucosal microbiome composition and colorectal gene expression are rarely studied. In this study, we integrated transcriptome data with microbiome data to investigate the relationship between them in colorectal cancer patients.Gap statement. Previous studies have identified the contribution of gut microbiota and DEGs to the pathogenesis of CRC, but the relationship between mucosal microbiome composition and colorectal gene expression are rarely studied.Aim. In this study, we integrated transcriptome data with microbiome data to investigate the relationship between mucosal microbiome composition and colorectal gene expression.Methodology. First, three independent CRC gene expression profiles (GSE184093, GSE156355 and GSE146587) from Gene Expression Omnibus (GEO) were used to identify differentially expressed genes (DEGs). Second, another dataset (GSE163366) was used to analyse gut mucosal microbiome differential abundance. GO (Gene Ontology) function and KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway enrichment analyses of the DEGs were performed. Protein-protein interactions (PPIs) of the DEGs were constructed. The Spearman correlation analysis was computed between host DEGs and gut microbiome abundance data.Results. A total of 1036 upregulated DEGs and 1194 downregulated DEGs between noncancerous tissues and cancerous tissues were identified based on the analysis. One significant module with a score 37.65 was selected out via MCODE including 41 upregulated DEGs, which are were mostly enriched in two pathways, including microtubule binding and tubulin binding. In particular, significant negative correlations are prevalent between Fusobacterium and the 41 DEGs with the correlation ranging between -0.54 and -0.35, and there commonly exist significant positive correlations between Blautia and the 41 DEGs with the correlation ranging between 0.42 and 0.54, indicating that Fusobacterium and Blautia are two of the most important microbes interacting with the gene regulation.Conclusion. Our results demonstrate significant correlation between some gut microbes and DEGs, providing a comprehensive bioinformatics analysis of them for future investigation into the molecular mechanisms and biomarkers.

An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis

Background: Abnormal DNA methylation of gene promoters is an important feature in lung adenocarcinoma (LUAD). However, the prognostic value of DNA methylation remains to be further explored. Objectives. We sought to explore DNA methylation characteristics and develop a quantifiable criterion related to DNA methylation to improve survival prediction for LUAD patients. Methods: Illumina Human Methylation450K array data, level 3 RNA-seq data and corresponding clinical information were obtained from TCGA. Cox regression analysis and the Akaike information criterion were used to construct the best-prognosis methylation signature. Receiver operating characteristic curve analysis was used to validate the prognostic ability of the DNA methylation-related feature score. qPCR was used to measure the transcription levels of the identified genes upon methylation. Results: We identified a set of DNA methylation features composed of 11 genes (MYEOV, KCNU1, SLC27A6, NEUROD4, HMGB4, TACR3, GABRA5, TRPM8, NLRP13, EDN3 and SLC34A1). The feature score, calculated based on DNA methylation features, was independent of tumor recurrence and TNM stage in predicting overall survival. Of note, the combination of this feature score and TNM stage provided a better overall survival prediction than either of them individually. The transcription levels of all the hypermethylated genes were significantly increased after demethylation, and the expression levels of 3 hypomethylated proteins were significantly higher in tumor tissues than in normal tissues, as indicated by immunohistochemistry data from the Human Protein Atlas. Our results suggested that these identified genes with prognostic features were regulated by DNA methylation of their promoters. Conclusion: Our studies demonstrated the potential application of DNA methylation markers in the prognosis of LUAD.

Multiomic Signatures of Chronic Beryllium Disease Bronchoalveolar Lavage Cells Relate to T-Cell Function and Innate Immunity.

Chronic beryllium disease (CBD) is a Th1 granulomatous lung disease preceded by sensitization to beryllium (BeS). We profiled the methylome, transcriptome, and selected proteins in the lung to identify molecular signatures and networks associated with BeS and CBD. BAL cell DNA and RNA were profiled using microarrays from CBD (n = 30), BeS (n = 30), and control subjects (n = 12). BAL fluid proteins were measured using Olink Immune Response Panel proteins from CBD (n = 22) and BeS (n = 22) subjects. Linear models identified features associated with CBD, adjusting for covariation and batch effects. Multiomic integration methods identified correlated features between datasets. We identified 1,546 differentially expressed genes in CBD versus control subjects and 204 in CBD versus BeS. Of the 101 shared transcripts, 24 have significant cis relationships between gene expression and DNA methylation, assessed using expression quantitative trait methylation analysis, including genes not previously identified in CBD. A multiomic model of top DNA methylation and gene expression features demonstrated that the first component separated CBD from other samples and the second component separated control subjects from remaining samples. The top features on component one were enriched for T-lymphocyte function, and the top features on component two were enriched for innate immune signaling. We identified six differentially abundant proteins in CBD versus BeS, with two (SIT1 and SH2D1A) selected as important RNA features in the multiomic model. Our integrated analysis of DNA methylation, gene expression, and proteins in the lung identified multiomic signatures of CBD that differentiated it from BeS and control subjects.

Integrated analysis of Wnt signalling system component gene expression.

ABSTRACTWnt signalling controls patterning and differentiation across many tissues and organs of the developing embryo through temporally and spatially restricted expression of multi-gene families encoding ligands, receptors, pathway modulators and intracellular components. Here, we report an integrated analysis of key genes in the 3D space of the mouse embryo across multiple stages of development. We applied a method for 3D/3D image transformation to map all gene expression patterns to a single reference embryo for each stage, providing both visual analysis and volumetric mapping allowing computational methods to interrogate the combined expression patterns. We identify territories where multiple Wnt and Fzd genes are co-expressed and cross-compare all patterns, including all seven Wnt paralogous gene pairs. The comprehensive analysis revealed regions in the embryo where no Wnt or Fzd gene expression is detected, and where single Wnt genes are uniquely expressed. This work provides insight into a previously unappreciated level of organisation of expression patterns, as well as presenting a resource that can be utilised further by the research community for whole-system analysis.

Integrative coexpression network detects the epicardial adipose tissue specific exosome vesicles as key predictor biomarker of cardiovascular disease

Cardiovascular disease (CVD), one of the leading causes of morbidity and mortality in many countries. Also, in past few decades the cardiovascular disease is prevalent among young adults. The core pathogenic gene and its molecular mechanism in cardiovascular disease remains unidentified. Therefore, the purpose of exploring the genetic basis of the cardiovascular disease became to be a primary research concept. Integrative gene expression analysis is a powerful approach to understand the gene regulation involved in cardiovascular disease. In this study mRNA expression of ~11,315 genes across 600 samples were investigated by applying Weighted gene coexpression network analysis (WGCNA) method. The highly coexpressed genes were grouped into modules. The CD3 module genes coexpression are conserved in many independent profile data and overexpressed in special tissue type of cardiac muscle the Epicardial adipose tissue (EAT). Fortunately, the gene ontology enrichment analysis reveals the enrichment of Exosome vesicles and immune response genes. Hence CD3 module gene characterize the epicardial adipose tissue secreted exosomes. Among the enriched urine exosome genes, the key genes CRK, GLTP, ITGAM, PPT1 genes had AUC value of 0.86 upon screening with and without cardiovascular disease presume it as a competent candidate biomarker in urine sample of cardiac patient. The results obtained projects these four key genes as prominent biomarker of cardiovascular disease.

Single-cell multiomics analysis reveals regulatory programs in clear cell renal cell carcinoma

The clear cell renal cell carcinoma (ccRCC) microenvironment consists of many different cell types and structural components that play critical roles in cancer progression and drug resistance, but the cellular architecture and underlying gene regulatory features of ccRCC have not been fully characterized. Here, we applied single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to generate transcriptional and epigenomic landscapes of ccRCC. We identified tumor cell-specific regulatory programs mediated by four key transcription factors (TFs) (HOXC5, VENTX, ISL1, and OTP), and these TFs have prognostic significance in The Cancer Genome Atlas (TCGA) database. Targeting these TFs via short hairpin RNAs (shRNAs) or small molecule inhibitors decreased tumor cell proliferation. We next performed an integrative analysis of chromatin accessibility and gene expression for CD8+ T cells and macrophages to reveal the different regulatory elements in their subgroups. Furthermore, we delineated the intercellular communications mediated by ligand–receptor interactions within the tumor microenvironment. Taken together, our multiomics approach further clarifies the cellular heterogeneity of ccRCC and identifies potential therapeutic targets.

DNA methylation subtypes guiding prognostic assessment and linking to responses the DNA methyltransferase inhibitor SGI-110 in urothelial carcinoma

BackgroundAt present, the extent and clinical relevance of epigenetic differences between upper tract urothelial carcinoma (UTUC) and urothelial carcinoma of the bladder (UCB) remain largely unknown. Here, we conducted a study to describe the global DNA methylation landscape of UTUC and UCB and to address the prognostic value of DNA methylation subtype and responses to the DNA methyltransferase inhibitor SGI-110 in urothelial carcinoma (UC).MethodsUsing whole-genome bisulfite sequencing (n = 49 samples), we analyzed epigenomic features and profiles of UTUC (n = 36) and UCB (n = 9). Next, we characterized potential links between DNA methylation, gene expression (n = 9 samples), and clinical outcomes. Then, we integrated an independent UTUC cohort (Fujii et al., n = 86) and UCB cohort (TCGA, n = 411) to validate the prognostic significance. Furthermore, we performed an integrative analysis of genome-wide DNA methylation and gene expression in two UC cell lines following transient DNA methyltransferase inhibitor SGI-110 treatment to identify potential epigenetic driver events that contribute to drug efficacy.ResultsWe showed that UTUC and UCB have very similar DNA methylation profiles. Unsupervised DNA methylation classification identified two epi-clusters, Methy-High and Methy-Low, associated with distinct muscle-invasive statuses and patient outcomes. Methy-High samples were hypermethylated, immune-infiltrated, and enriched for exhausted T cells, with poor clinical outcome. SGI-110 inhibited the migration and invasion of Methy-High UC cell lines (UMUC-3 and T24) by upregulating multiple antitumor immune pathways.ConclusionsDNA methylation subtypes pave the way for predicting patient prognosis in UC. Our results provide mechanistic rationale for evaluating SGI-110 in treating UC patients in the clinic.

Integrated analysis of dermal blister fluid proteomics and genome-wide skin gene expression in systemic sclerosis: an observational study.

Skin fibrosis is a hallmark feature of systemic sclerosis. Skin biopsy transcriptomics and blister fluid proteomics give insight into the local environment of the skin. We have integrated these modalities with the aim of developing a surrogate for the modified Rodnan skin score (mRSS), using candidate genes and proteins from the skin and blister fluid as anchors to identify key analytes in the plasma. In this single-centre, prospective observational study at the Royal Free Campus, University College London, London, UK, transcriptional and proteomic analyses of blood and skin were performed in a cohort of patients with systemic sclerosis (n=52) and healthy controls (n=16). Weighted gene co-expression network analysis was used to explore the association of skin transcriptomics data, clinical traits, and blister fluid proteomic results. Candidate hub analytes were identified as those present in both blister and skin gene sets (modules), and which correlated with plasma (module membership >0·7 and gene significance >0·6). Hub analytes were confirmed using RNA transcript data obtained from skin biopsy samples from patients with early diffuse cutaneous systemic sclerosis at 12 months. We identified three modules in the skin, and two in blister fluid, which correlated with a diagnosis of early diffuse cutaneous systemic sclerosis. From these modules, 11 key hub analytes were identified, present in both skin and blister fluid modules, whose transcript and protein levels correlated with plasma protein concentrations, mRSS, and showed statistically significant correlation on repeat transcriptomic samples taken at 12 months. Multivariate analysis identified four plasma analytes as correlates of mRSS (COL4A1, COMP, SPON1, and TNC), which can be used to differentiate disease subtype. This unbiased approach has identified potential biological candidates that might be drivers of local skin pathogenesis in systemic sclerosis. By focusing on measurable analytes in the plasma, we generated a promising composite plasma protein biomarker that could be used for assessment of skin severity, case stratification, and as a potential outcome measure for clinical trials and practice. Once fully validated, the biomarker score could replace a clinical score such as the mRSS, which carries substantial variability. GlaxoSmithKline and UK Medical Research Council.

Abstract 5013: Integrated analysis of intragastric microbiome and human gene expression uncovers genetic, microbial, and immunological associations in gastritis and gastric cancer

Abstract Background: Gastric carcinogenesis has been found to be associated with intragastric microbiome, gastric mucosal gene expression, and immune cells comprising the tumor microenvironment separately in independent studies. However, to date, there has been no multi-omic investigations analyzing these biological traits simultaneously. Thus, there is a paucity in our understanding of the intricate relationship between intragastric microbes and the host in gastric disease. To address this gap, we aimed to comprehensively investigate the microbiome, host gene expression, and immune cells in the stomach across a range of different states along the gastric carcinogenesis pathway. Methods: Gastric biopsy samples were obtained from healthy individuals or patients with gastritis or gastric cancer (biopsy cohort, n=30). Surgical samples (of cancer and adjacent severe gastritis tissues) were obtained from gastric cancer patients (surgery cohort, n=40). Using 16S rRNA gene sequencing, RNA-seq, and cell-type enrichment analysis of each participant’s biospecimens, we identified associations between the microbiome and host transcriptome or inferred immune cell types. Results: Microbiome composition and gene expression patterns showed significant differences between disease states (healthy, gastritis, or cancer). Expression of ‘Cell cycle’ pathway genes was enriched in gastric cancer in both biopsy and surgery cohorts. In the biopsy cohort, Helicobacteraceae, which was abundant in gastritis, was highly correlated with FAM3D, which was previously found to be involved in gastrointestinal inflammation. In the surgery cohort, Lachnospiraceae, which was abundant in gastric cancer, was highly correlated with UBD, which is known to regulate mitosis and reduce cell cycle time. Cell-type enrichment analysis revealed lower B cell infiltration in gastric cancer than in gastritis (both cohorts). Tissue-infiltrating B cells were associated with Helicobacteraceae. Conclusions: Associations between the intragastric microbiome, human gene expression, and tissue-infiltrating immune cells are unique to gastric disease state. The findings herein may aid the discovery of novel biomarkers or therapeutic targets of gastric cancer. Citation Format: Chan Hyuk Park, Changjin Hong, A-reum Lee, Jaeyun Sung, Tae Hyun Hwang. Integrated analysis of intragastric microbiome and human gene expression uncovers genetic, microbial, and immunological associations in gastritis and gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5013.

Integrative Analysis of DNA Methylation and Gene Expression in the Pathogenesis of Endobronchial Tuberculosis

AbstractThe aim of this study is to identify novel DNA methylation sites significant for endobronchial tuberculosis (EBTB) and comprehensively understand their underlying pathological mechanisms. The following two steps are performed 1) genome‐wide DNA methylation and mRNA expression profiling in endobronchial internal membrane tissue from EBTB patients and healthy controls and 2) a correlation analysis and causal inference tests (CITs) for DNA methylation and mRNA expression data. A total of 1258 DNA methylation regions (DMRs) are found associated with EBTB. The identified DMRs have regulatory effects on mRNA expression. CITs identified four DNA methylation–mRNA–EBTB regulatory chains (ATP6V1B1, KCNAB2, LRP5, and FCER1G). In conclusion, integrated DNA methylation and transcriptome analyses could provide valuable resources for epigenetics studies in EBTB. In addition, the correlation analysis highlighted the importance of a series of regulatory chains in EBTB pathogenesis. The results enhanced our understanding of the important role of DNA methylation in the pathology of EBTB.