Electrospun Scaffold Micro-Architecture Induces an Activated Transcriptional Phenotype within Tendon Fibroblasts

Biomaterial augmentation of surgically repaired rotator cuff tendon tears aims to improve the high failure rates (∼40%) of traditional repairs. Biomaterials that can alter cellular phenotypes through the provision of microscale topographical cues are now under development. We aimed to systematically evaluate the effect of topographic architecture on the cellular phenotype of fibroblasts from healthy and diseased tendons. Electrospun polydioxanone scaffolds with fiber diameters ranging from 300 to 4000 nm, in either a highly aligned or random configuration, were produced. Healthy tendon fibroblasts cultured for 7 days on scaffolds with highly aligned fibers demonstrated a distinctive elongated morphology, whilst those cultured on randomly configured fibers demonstrated a flattened and spread morphology. The effect of scaffold micro-architecture on the transcriptome of both healthy and diseased tendon fibroblasts was assessed with bulk RNA-seq. Both healthy (n = 3) and diseased tendon cells (n = 3) demonstrated a similar transcriptional response to architectural variants. Gene set enrichment analysis revealed that large diameter (≥2000 nm) aligned scaffolds induced an upregulation of genes involved in cellular replication and a downregulation of genes defining inflammatory responses and cell adhesion. Similarly, PDPN and CD248, markers of inflammatory or “activated” fibroblasts, were downregulated during culture of both healthy and diseased fibroblasts on aligned scaffolds with large (≥2000 nm) fiber diameters. In conclusion scaffold architectures resembling that of disordered type III collagen, typically present during the earlier phases of wound healing, resulted in tendon fibroblast activation. Conversely, scaffolds mimicking aligned diameter collagen I fibrils, present during tissue remodelling, did not activate tendon derived fibroblasts. This has implications for the design of scaffolds used during rotator cuff repair augmentation.

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Identification of long noncoding RNAs reveals the effects of dinotefuran on the brain in Apis mellifera (Hymenopptera: Apidae)

BMC Genomics ◽

10.1186/s12864-021-07811-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Minjie Huang ◽

Jie Dong ◽

Haikun Guo ◽

Minghui Xiao ◽

Deqian Wang

Keyword(s):

Immune Response ◽

Honey Bee ◽

Honey Bees ◽

Transforming Growth Factor ◽

Sublethal Effects ◽

Inflammatory Responses ◽

Noncoding Rnas ◽

Enrichment Analysis ◽

Long Noncoding Rnas ◽

Gene Set Enrichment Analysis

Abstract Background Dinotefuran (CAS No. 165252–70-0), a neonicotinoid insecticide, has been used to protect various crops against invertebrate pests and has been associated with numerous negative sublethal effects on honey bees. Long noncoding RNAs (lncRNAs) play important roles in mediating various biological and pathological processes, involving transcriptional and gene regulation. The effects of dinotefuran on lncRNA expression and lncRNA function in the honey bee brain are still obscure. Results Through RNA sequencing, a comprehensive analysis of lncRNAs and mRNAs was performed following exposure to 0.01 mg/L dinotefuran for 1, 5, and 10 d. In total, 312 lncRNAs and 1341 mRNAs, 347 lncRNAs and 1458 mRNAs, and 345 lncRNAs and 1155 mRNAs were found to be differentially expressed (DE) on days 1, 5 and 10, respectively. Gene set enrichment analysis (GSEA) indicated that the dinotefuran-treated group showed enrichment in carbohydrate and protein metabolism and immune-inflammatory responses such as glycine, serine and threonine metabolism, pentose and glucuronate interconversion, and Hippo and transforming growth factor-β (TGF-β) signaling pathways. Moreover, the DE lncRNA TCONS_00086519 was shown by fluorescence in situ hybridization (FISH) to be distributed mainly in the cytoplasm, suggesting that it may serve as a competing endogenous RNA and a regulatory factor in the immune response to dinotefuran. Conclusion This study characterized the expression profile of lncRNAs upon exposure to neonicotinoid insecticides in young adult honey bees and provided a framework for further study of the role of lncRNAs in honey bee growth and the immune response.

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Fold-Change-Specific Enrichment Analysis (FSEA): Quantification of Transcriptional Response Magnitude for Functional Gene Groups

Genes ◽

10.3390/genes11040434 ◽

2020 ◽

Vol 11 (4) ◽

pp. 434 ◽

Cited By ~ 1

Author(s):

Daniil S. Wiebe ◽

Nadezhda A. Omelyanchuk ◽

Aleksei M. Mukhin ◽

Ivo Grosse ◽

Sergey A. Lashin ◽

...

Keyword(s):

Abiotic Factors ◽

Transcriptional Response ◽

Enrichment Analysis ◽

R Package ◽

Fold Change ◽

Functional Gene ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Go Terms ◽

Singular Enrichment Analysis

Gene expression profiling data contains more information than is routinely extracted with standard approaches. Here we present Fold-Change-Specific Enrichment Analysis (FSEA), a new method for functional annotation of differentially expressed genes from transcriptome data with respect to their fold changes. FSEA identifies Gene Ontology (GO) terms, which are shared by the group of genes with a similar magnitude of response, and assesses these changes. GO terms found by FSEA are fold-change-specifically (e.g., weakly, moderately, or strongly) affected by a stimulus under investigation. We demonstrate that many responses to abiotic factors, mutations, treatments, and diseases occur in a fold-change-specific manner. FSEA analyses suggest that there are two prevailing responses of functionally-related gene groups, either weak or strong. Notably, some of the fold-change-specific GO terms are invisible by classical algorithms for functional gene enrichment, Singular Enrichment Analysis (SEA), and Gene Set Enrichment Analysis (GSEA). These are GO terms not enriched compared to the genome background but strictly regulated by a factor within specific fold-change intervals. FSEA analysis of a cancer-related transcriptome suggested that the gene groups with a tightly coordinated response can be the valuable source to search for possible regulators, markers, and therapeutic targets in oncogenic processes. Availability and Implementation: FSEA is implemented as the FoldGO Bioconductor R package and a web-server.

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Defining hierarchical protein interaction networks from spectral analysis of bacterial proteomes

10.1101/2021.09.28.462107 ◽

2021 ◽

Author(s):

Mark A. Zaydman ◽

Alexander Little ◽

Fidel Haro ◽

Valeryia Aksianiuk ◽

William J. Buchser ◽

...

Keyword(s):

Protein Interaction ◽

Protein Interactions ◽

Enrichment Analysis ◽

Protein Interaction Networks ◽

Gene Set Enrichment Analysis ◽

Interaction Networks ◽

Spectral Correlation ◽

Hierarchical Networks ◽

Statistical Pattern ◽

Cellular Phenotypes

AbstractCellular phenotypes emerge from a hierarchy of molecular interactions: proteins interact to form complexes, pathways, and phenotypes. We show that hierarchical networks of protein interactions can be extracted from the statistical pattern of proteome variation as measured across thousands of bacteria and that these hierarchies reflect the emergence of complex bacterial phenotypes. We describe the mathematics underlying our statistical approach and validate our results through gene-set enrichment analysis and comparison to existing experimentally-derived hierarchical databases. We demonstrate the biological utility of our unbiased hierarchical models by creating a model of motility in Pseudomonas aeruginosa and using it to discover a previously unappreciated genetic effector of twitch-based motility. Overall, our approach, SCALES (Spectral Correlation Analysis of Layered Evolutionary Signals), predicts hierarchies of protein interaction networks describing emergent biological function using only the statistical pattern of bacterial proteome variation.

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Monocyte transcriptomes from patients with axial spondyloarthritis reveal dysregulated monocytopoiesis and a distinct inflammatory imprint

Arthritis Research & Therapy ◽

10.1186/s13075-021-02623-7 ◽

2021 ◽

Vol 23 (1) ◽

Author(s):

Fabian Karow ◽

Biljana Smiljanovic ◽

Joachim R. Grün ◽

Denis Poddubnyy ◽

Fabian Proft ◽

...

Keyword(s):

Disease Activity ◽

Blood Cells ◽

Axial Spondyloarthritis ◽

Inflammatory Responses ◽

Binding Protein ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Fatty Acid Binding ◽

Gut Inflammation ◽

Activated Monocytes

Abstract Background In patients with axial spondyloarthritis (axSpA), monocytes show a pre-activated phenotype. Gut inflammation is a trigger of monocyte activation and may also affect their development in the bone marrow (BM). As gut inflammation is commonly observed in axSpA patients, we performed a detailed analysis of monocyte transcriptomes of axSpA patients in two cohorts and searched for signs of activation and developmental adaptations as putative imprints of gut inflammation. Methods Transcriptomes of blood CD14+ monocytes of HLA-B27+ axSpA patients and healthy controls (HC) were generated by microarrays from cohort 1 and by RNA-sequencing from cohort 2. Differentially expressed genes from both analyses were subjected to gene set enrichment analysis (GSEA) and to co-expression analysis in reference transcriptomes from BM cells, blood cells and activated monocytes. As serological markers of translocation, 1,3 beta-glycan, intestinal fatty acid binding protein, and lipopolysaccharide binding protein (LBP) were determined by LAL and ELISA. Results Transcriptome analysis identified axSpA-specific monocyte signatures showing an imprint of LPS/cytokine-activated monocytes, late granulopoietic BM cells, blood neutrophils, and G-CSF-mobilized blood cells, which suggests LPS/TNF activation and more prominent BM adaptation promoting a neutrophil-like phenotype. GSEA mapped axSpA upregulated genes to inflammatory responses and TNFα signaling and downregulated probe-sets to metabolic pathways. Among translocation markers, LBP levels were significantly increased in axSpA patients vs. HC (p < 0.001). Stratified analysis by disease activity and stage identified an “active disease signature” (BASDAI ≥ 4) with an imprint of LPS/cytokine-activated monocytes and CD16+ monocyte subsets. The “AS signature” (vs. non-radiographic axSpA) showed a reinforced neutrophil-like phenotype due to deprivation of dendritic cell transcripts. Conclusions The neutrophil-like phenotype of axSpA monocytes points towards a biased monocytopoiesis from granulocyte-monocyte progenitors. This shift in monocytopoiesis and the LPS/cytokine imprint as well as the elevated LBP levels are indicators of systemic inflammation, which may result from bacterial translocation. The BM adaptation is most prominent in AS patients while disease activity appears to be linked to activation and trafficking of monocytes.

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Expression Profile and Prognostic Value of CXCR Family Members in Head and Neck Squamous Cell Carcinoma

10.21203/rs.3.rs-1078583/v1 ◽

2021 ◽

Author(s):

Yiming Shen ◽

Chongchang Zhou ◽

Yujie Cao ◽

Qun Li ◽

Hongxia Deng ◽

...

Keyword(s):

Head And Neck ◽

Expression Profile ◽

Prognostic Value ◽

Inflammatory Responses ◽

Receptor Gene ◽

Family Members ◽

Enrichment Analysis ◽

Progression Free Survival ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas

Abstract Background: CXC chemokine receptor gene family consists of seven well-established members which are broadly involved in biological functions of various cancers. Currently, limited studies have shed light on the expression profile of CXCR family members (CXCRs), as well as their prognostic value, in head and neck squamous cells carcinoma (HNSCC). Methods: The data for this study were retrieved from the Cancer Genome Atlas database and other publicly available databases, including gene expression, methylation profiles, clinical information, immunological features and prognoses. The expression pattern and prognostic values of CXCRs were identified, and the potential mechanism underlying CXCRs function in HNSCC was investigated by gene set enrichment analysis (GSEA). Results: CXCRs were differentially expressed in HNSCC. As shown by Kaplan Meier analysis, high CXCR3-6 expression was significantly associated with better prognostic outcomes of HNSCC patients, including overall survival and progression-free survival. According to the results of univariate and multivariate Cox proportional risk regression analysis, it was demonstrated that upregulation of CXCR3-6 was an independent factor for better prognosis, while the two other clinical features, age and stage, were factors for worse prognosis. A significant positive correlation between CXCR3-6 and tumor-infiltrated immune cells was revealed by results from Tumor Immune Estimation Resource and CIBERSORT analysis database. The main involvement of CXCRs in immune and inflammatory responses was further confirmed by GSEA. Conclusions: Overall, this study provided a rationale for targeting CXCRs as a promising therapeutic strategy of HNSCC.

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Gene Expression Profiling of Age-Related Epstein-Barr Virus (EBV)-Associated B-Cell Lymphoproliferative Disorder Uncovers Alterations in Immune and Inflammatory Genes: Possible Implications for Pathogenesis,

Blood ◽

10.1182/blood.v118.21.3448.3448 ◽

2011 ◽

Vol 118 (21) ◽

pp. 3448-3448

Author(s):

Harumi Kato ◽

Kazuhito Yamamoto ◽

Kennosuke Karube ◽

Miyuki Katayama ◽

Shinobu Tsuzuki ◽

...

Keyword(s):

Inflammatory Responses ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Enrichment Score ◽

P Value ◽

Toll Like Receptor ◽

Gene Set Enrichment ◽

Gene Set ◽

Age Related ◽

Gene Sets

Abstract Abstract 3448 Age-related EBV-associated B-cell lymphoproliferative disorder (AR-EBLPD) is classified as a subtype of diffuse large cell lymphoma (DLBCL) according to the WHO classification. However, molecular genetic characterization of AR-EBLPD remains largely unknown. We studied expression profiles of 5 AR-EBLPD and 8 EB-negative DLBCL samples using the Agilent 44K human oligonucleotide microarray. Total RNA was extracted from fresh-frozen tumor samples. Each microarray slide was converted into datasets using the Agilent Micro Array Scanner and Feature extractions. Data was standardized with Z-scores. Differences in mRNA expression levels between two sample groups were calculated using a two-sided t-test. A total of 1973 probes showed a p-value less than 0.05 with less than a 25% false discovery rate (FDR). These probes included 1688 genes. The number of probes showing high expression in AR-EBLPD and EB-negative DLBCL was 804 (693 genes) and 1169 (995 genes), respectively. First, we selected the top 300 differentially expressed genes. Genes highly expressed in AR-EBLPD included IL6, TNFAIP3, HOPX, and SLAMF1. IL6 is known as a gene encoding a cytokine which functions in inflammation and the maturation of B lymphocytes, and TNFAIP3 is known as a negative regulatory gene of the NF-kB pathway. HOPX and SLAMF1 are reported as genes related to lymphocyte function or the immune system (Schwartzberg et al. Nature immunology 2009, Hawiger et al. Nature immunology 2011). For better characterization, we next performed Gene Ontology Analysis using the WEB-based GEne SeT AnaLysis Toolkit and found that categories of external stimulus and inflammatory responses were enriched in AR-EBLPD. The Kyoto Encyclopedia of Genes and Genomes (KEGG)-signaling analyses showed that pathways of the NOD-like receptor (p-value =1.30e-06), JAK-STAT (p-value =9.01e-06), and Toll-like receptor (p-value =0.0002) were characteristic of AR-EBLPD. These results implied that inflammation would be prominent in AR-EBLPD cases. For validation, we next performed Gene Set Enrichment Analysis (GSEA) using all the database of KEGG pathways (186 gene sets). Dominant gene sets in AR-EBLPD included the cytokine-cytokine receptor interaction [Normalized Enrichment Score (NES) =2.66, p-value<0.001], NOD-like receptor pathway (NES =2.26, p-value<0.001), TOLL-like receptor pathway (NES =2.14, p-value<0.001), and JAK-STAT pathway (NES =1.79, p-value<0.001). Since all the pathways were related to the NF-kB pathway, inflammatory responses were suggested to activate the NF-kB pathway or vice versa. For confirmation, we finally performed GSEA using gene sets of the NF-kB pathway, which were obtained from a gene set reported by an NIH group (Puente et al. Nature 2011) and 30 gene sets in the GSEA database, and found that the gene sets of the NF-kB pathway were enriched in AR-EBLPD (Figure 1). Our results suggested that the inflammatory and immune-related genes were enriched in AR-EBLPD and that activation of the genes may be associated with NF-kB activation. Aberrant immune and inflammatory responses could define the clinical presentations of AR-EBLPD cases. (Figure 1) Gene Set Enrichment Analysis of 5 AR-EBLPD and 8 EB-negative DLBCL samples. The NF-kB signature reported from an NIH group (Puente et al. Nature 2011) was enriched in AR-EBLPD [Normalized Enrichment Score (NES) =2.20, p-value<0.001]. Disclosures: No relevant conflicts of interest to declare.

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A method for downstream analysis of gene set enrichment results facilitates the biological interpretation of vaccine efficacy studies

10.1101/043158 ◽

2016 ◽

Author(s):

Yan Tan ◽

Jernej Godec ◽

Felix Wu ◽

Pablo Tamayo ◽

Jill P. Mesirov ◽

...

Keyword(s):

Transcriptional Response ◽

Leading Edge ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Biological Processes ◽

Gene Set Enrichment ◽

Gene Set ◽

Gene Sets ◽

Biological Interpretation ◽

Downstream Analysis

AbstractGene set enrichment analysis (GSEA) is a widely employed method for analyzing gene expression profiles. The approach uses annotated sets of genes, identifies those that are coordinately up‐ or down-regulated in a biological comparison of interest, and thereby elucidates underlying biological processes relevant to the comparison. As the number of gene sets available in various collections for enrichment analysis has grown, the resulting lists of significant differentially regulated gene sets may also become larger, leading to the need for additional downstream analysis of GSEA results. Here we present a method that allows the rapid identification of a small number of co-regulated groups of genes – “leading edge metagenes” (LEMs) - from high scoring sets in GSEA results. LEM are sub-signatures which are common to multiple gene sets and that “explain” their enrichment specific to the experimental dataset of interest. We show that LEMs contain more refined lists of context-dependent and biologically meaningful genes than the parental gene sets. LEM analysis of the human vaccine response using a large database of immune signatures identified core biological processes induced by five different vaccines in datasets from human peripheral blood mononuclear cells (PBMC). Further study of these biological processes over time following vaccination showed that at day 3 post-vaccination, vaccines derived from viruses or viral subunits exhibit patterns of biological processes that are distinct from protein conjugate vaccines; however, by day 7 these differences were less pronounced. This suggests that the immune response to diverse vaccines eventually converge to a common transcriptional response. LEM analysis can significantly reduce the dimensionality of enriched gene sets, improve the identification of core biological processes active in a comparison of interest, and simplify the biological interpretation of GSEA results.Author SummaryGenome-wide expression profiling is a widely used tool to identify biological mechanisms in a comparison of interest. One analytic method, Gene set enrichment analysis (GSEA) uses annotated sets of genes and identifies those that are coordinately up‐ or down-regulated in a biological comparison of interest. This approach capitalizes on the fact that alternations in biological processes often cause the coordinated change of a large number of genes. However, as the number of gene sets available in various collections for enrichment analysis has grown, the resulting lists of significant differentially regulated gene sets may also become larger, leading to the need for additional downstream analysis of GSEA results. Here we present a method that allows the identification of a small number of co-regulated groups of genes – “leading edge metagenes” (LEMs) – from high scoring sets in GSEA results. We show that LEMs contain more refined lists of context-dependent biologically meaningful genes than the parental gene sets and demonstrate the utility of this approach in analyzing the transcriptional response to vaccination. LEM analysis can significantly reduce the dimensionality of enriched gene sets, improve the identification of core biological processes active in a comparison of interest, and facilitate the biological interpretation of GSEA results.

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Genome-wide methylation profiles in coronary artery ectasia

Clinical Science ◽

10.1042/cs20160821 ◽

2017 ◽

Vol 131 (7) ◽

pp. 583-594 ◽

Cited By ~ 4

Author(s):

Tzu-Pin Lu ◽

Nai-Chen Chuang ◽

Chin-Yu Cheng ◽

Cheng-An Hsu ◽

Yi-Chih Wang ◽

...

Keyword(s):

Coronary Artery ◽

Coronary Arteries ◽

Inflammatory Responses ◽

Functional Characterization ◽

Enrichment Analysis ◽

Systematic Investigation ◽

Gene Set Enrichment Analysis ◽

Coronary Artery Ectasia ◽

Protein Levels ◽

Genome Wide

Coronary artery ectasia (CAE) is a disease characterized by abnormally dilated coronary arteries. The mechanism of CAE remains unclear, and its treatment is limited. Previous studies have shown that risk factors for CAE were related to changes in DNA methylation. However, no systematic investigation of methylation profiles has been performed. Therefore, we compared methylation profiles between 12 CAE patients and 12 propensity-matched individuals with normal coronary arteries using microarrays. Wilcoxon's rank sum tests revealed 89 genes with significantly different methylation levels (P<0.05 and Δβ > |0.1|). Functional characterization using the DAVID database and gene set enrichment analysis indicated that these genes were involved in immune and inflammatory responses. Of these genes 6 were validated in 29 CAE patients and 87 matched individuals with CAE, using pyro-sequencing. TLR6 and NOTCH4 showed significant differences in methylation between the two groups, and lower protein levels of toll-like receptor 6 (TLR6) were detected in CAE patients. In conclusion, this genome-wide analysis of methylation profiles in CAE patients showed that significant changes in both methylation and expression of TLR6 deserve further study to elucidate their roles in CAE.

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Comprehensive Analysis to Identify Key Genes Involved in Advanced Atherosclerosis

Disease Markers ◽

10.1155/2021/4026604 ◽

2021 ◽

Vol 2021 ◽

pp. 1-25

Author(s):

Tian-ming Huo ◽

Zhi-wei Wang

Keyword(s):

Gene Expression ◽

Network Analysis ◽

Lupus Erythematosus ◽

Inflammatory Responses ◽

Therapeutic Targets ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Hub Genes ◽

Key Genes

Background. The study was aimed at finding accurate and effective therapeutic targets and deepening our understanding of the mechanisms of advanced atherosclerosis (AA). Methods. We downloaded the gene expression datasets GSE28829, GSE120521, and GSE43292 from Gene Expression Omnibus. Weighted gene coexpression network analysis (WGCNA) was performed for GSE28829, and functional enrichment analysis and protein–protein interaction network analysis were conducted on the key module. Significant genes in the key module were analyzed by molecular complex detection, and genes in the most important subnetwork were defined as hub genes. Multiple dataset analyses for hub genes were conducted. Genes that overlapped between hub genes and differentially expressed genes (DEGs) of GSE28829 and GSE120521 were defined as key genes. Further validation for key genes was performed using GSE28829 and GSE43292. Gene set enrichment analysis (GSEA) was applied to key genes. Results. A total of 77 significant genes in the key module of GSE28829 were screened out that were mainly associated with inflammation and immunity. The subnetwork was obtained from significant genes, and 18 genes in this module were defined as hub genes, which were related to immunity and expressed in multiple diseases, particularly systemic lupus erythematosus. Some hub genes were regulated by SPI1 and associated with the blood, spleen, and lung. After overlapping with DEGs of GSE28829 and GSE120521, a total of 10 genes (HCK, ITGAM, CTSS, TYROBP, LAPTM5, FCER1G, ITGB2, NCF2, AIF1, and CD86) were identified as key genes. All key genes were validated and evaluated successfully and were related to immune response pathways. Conclusion. Our study suggests that the key genes related to immune and inflammatory responses are involved in the development of AA. This may deepen our understanding of the mechanisms of and provide valuable therapeutic targets for AA.

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Prognostic Relevance of Expression of EMP1, CASP1, and NLRP3 Genes in Pediatric B-Lineage Acute Lymphoblastic Leukemia

Frontiers in Oncology ◽

10.3389/fonc.2021.606370 ◽

2021 ◽

Vol 11 ◽

Author(s):

Jay Singh ◽

Sarita Kumari ◽

Mohit Arora ◽

Deepak Verma ◽

Jayanth Kumar Palanichamy ◽

...

Keyword(s):

Gene Expression ◽

Acute Lymphoblastic Leukemia ◽

Molecular Mechanisms ◽

Inflammatory Responses ◽

Remission Rate ◽

Lymphoblastic Leukemia ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Poor Responders ◽

B Lineage

Glucocorticoid (GC), such as prednisolone, is an essential component of multidrug chemotherapy regimen for pediatric acute lymphoblastic leukemia (ALL). Resistance to GC in leukemia cells is associated with disease progression and poor prognosis. Despite the extensive use of GC for many years, molecular mechanisms underlying its resistance in ALL have not been fully uncovered. Recent studies have shown a potential role of EMP1, CASP1, and NLRP3 genes in prednisolone response. In this study on 148 pediatric B-ALL patients, we studied these three genes to assess their association with prednisolone response measured by day 8 blast count after 7 days of induction therapy with prednisolone. Intriguingly, ALL samples exhibited higher expression of EMP1 along with a low expression of CASP1 and NLRP3 compared to disease free normal bone marrow collected from patients with solid tumors. Among the three analyzed genes, only EMP1 was found to be overexpressed in prednisolone poor responders (p=0.015). Further, a comparison of gene expression between cytogenetic subtypes revealed higher expression of EMP1 in BCR-ABL subtype. Expression of EMP1 in multiple gene expression datasets was used for gene set enrichment analysis, which revealed TNF-α, IL-2-STAT5 signaling, inflammatory responses and hypoxia as the major positively associated pathways and E2F targets as negatively associated pathways. Interestingly, the clinical remission rate was higher in CASP1 high patients (p=0.048). In univariate survival analysis, higher EMP1 expression was associated with poor prognostic measures while higher expression of NLRP3 and CASP1 was associated with better prognostic measures in our data. Further, multivariate analysis revealed an independent association of high CASP1 and NLRP3 with a better prognosis. This study strengthens the available evidence that mRNA expression of EMP1, CASP1, and NLRP3 may serve as potential biomarkers for risk stratification of pediatric B-ALL patients.

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