scholarly journals Metabolic Pathways Enhancement Confers Poor Prognosis in p53 Exon Mutant Hepatocellular Carcinoma

2020 ◽  
Vol 19 ◽  
pp. 117693511989991
Author(s):  
Po-Ming Chen ◽  
Jian-Rong Li ◽  
Chun-Chi Liu ◽  
Feng-Yao Tang ◽  
En-Pei Isabel Chiang
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Expression Profiles ◽  
Therapeutic Targets ◽  
P53 Mutation ◽  
Gene Set Enrichment Analysis ◽  
Enrichment Score ◽  
Rna Seq ◽  
P53 Expression

RNA-Sequencing (RNA-Seq), the most commonly used sequencing application tool, is not only a method for measuring gene expression but also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels), or fusion transcripts. The Cancer Genome Atlas (TCGA) contains genomic data from a variety of cancer types and also provides the raw data generated by TCGA consortium. p53 is among the top 10 somatic mutations associated with hepatocellular carcinoma (HCC). The aim of the present study was to analyze concordant different gene profiles and the priori defined set of genes based on p53 mutation status in HCC using RNA-Seq data. In the study, expression profile of 11 799 genes on 42 paired tumor and adjacent normal tissues was collected, processed, and further stratified by the mutated versus normal p53 expression. Furthermore, we used a knowledge-based approach Gene Set Enrichment Analysis (GSEA) to compare between normal and p53 mutation gene expression profiles. The statistical significance (nominal P value) of the enrichment score (ES) genes was calculated. The ranked gene list that reflects differential expression between p53 wild-type and mutant genotypes was then mapped to metabolic process by KEGG, an encyclopedia of genes and genomes to assign functional meanings. These approaches enable us to identify pathways and potential target gene/pathways that are highly expressed in p53 mutated HCC. Our analysis revealed 2 genes, the hexokinase 2 ( HK2) and Enolase 1 ( ENO1), were conspicuous of red pixel in the heatmap. To further explore the role of these genes in HCC, the overall survival plots by Kaplan-Meier method were performed for HK2 and ENO1 that revealed high HK2 and ENO1 expression in patients with HCC have poor prognosis. These results suggested that these glycolysis genes are associated with mutated-p53 in HCC that may contribute to poor prognosis. In this proof-of-concept study, we proposed an approach for identifying novel potential therapeutic targets in human HCC with mutated p53. These approaches can take advantage of the massive next-generation sequencing (NGS) data generated worldwide and make more out of it by exploring new potential therapeutic targets.

scholarly journals Transcriptomic Evaluation of CD34+ Marrow Cells from Myelodysplastic Syndrome (MDS) Patients

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1894-1894
Author(s):  
Hogune Im ◽  
Varsha Rao ◽  
Kunju Joshi Sridhar ◽  
Rui Chen ◽  
George Mias ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differential Expression ◽  
High Throughput ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Reference Sequence ◽  
Rna Seq ◽  
Cd34 Cells ◽  
Marrow Cells

Abstract Background: Prior studies using microarray platforms have shown alterations of gene expression profiles (GEPs) in MDS CD34+ marrow cells related to clinical outcomes (Sridhar et al, Blood 2009, Pellagatti et al, JCO 2013). Given the increased sensitivity and accuracy of high-throughput RNA sequencing (RNA-Seq) (Mortazavi et al, Nat Meth 2008, Soon et al, Mol Syst Bio 2012) for detecting and quantifying mRNA transcripts, we applied this methodology for evaluating differential gene expression between MDS and normal CD34+ marrow cells. Methods:RNA was isolated from magnetic bead affinity-enriched CD34+ (>90%) marrow aspirate cells (Miltenyi Biotec, Auburn, CA) and amplified using the Smarter Kit (Clontech, Mt View, CA). The amplified product (ds DNA) was fragmented to a size distribution of ~200-300bp using the E220 Focused Ultrasonicator (Covaris Inc, Woburn, MA). End repair, adapter ligation and PCR amplification were performed using the NEBNext Ultra RNA library prep kit for Illumina (New England Biolabs, Ipswich, MA). The indexed cDNA libraries were sequenced (paired end, 100bp) on an Illumina HiSeq2000 platform with median read counts of 69 million. The sequences were aligned to Human Reference sequence hg19 using DNAnexus mapper with gene detection focused on known annotated genes. The differential expression was analyzed using edgeR. DAVID and Ingenuity IPA programs were used for pathway analyses. Gene Set Enrichment Analysis (GSEA) was used to identify biologic processes in our dataset present across phenotypes. Results: Correlations of RNA-Seq data from unamplified to amplified transcripts demonstrated high fidelity of transcripts obtained (Pearson and Spearman R2 = 0.80). After filtering samples for adequate read counts, 12,323 genes were evaluated. Differential expression analysis yielded 719 differentially expressed genes (DEGs) in MDS (n=30) vs normal (n=21) with FDR <.05. Among the DEGs, 548 and 171 were over- and under-expressed ≥2 fold in MDS vs Normal, respectively: 20% of the overexpressed genes were present in >50% of the patients. Hierarchical cluster analysis using these DEGs confirmed clear separation of MDS patients from normals, with 2 differential expression clusters—one region overexpressed and one underexpressed. A distinctive trend toward clustering of the patients was seen which related to their IPSS categories and marrow blast %. In functional pathway analysis of the 2 distinctive gene clusters which distinguished MDS from normal, the underexpressed MDS DEGs demonstrated enrichment of inflammatory cytokines, oxidative stress and interleukin signaling pathways, plus mitochondrial calcium transport; whereas the MDS overexpressed DEG cluster showed enrichment of adherens junction/cytokeletal remodeling, cell cycle control of chromosome replication and DNA damage response pathways. Using GSEA analysis, significantly increased numbers of genes in MDS vs normal, common to those in gene sets present within curated public databases, were involved with TP53 targets and mTOR signaling pathways. Conclusions: Our study demonstrated that RNA-Seq methodology, a high-throughput and more comprehensive technique than most gene expression microarrays, was capable of showing significant and distinctive differences in gene expression between MDS and normal marrow CD34+ cells. Specific clustering of the DEGs was demonstrated to distinguish patient subsets associated with their major clinical features. Further, the stringently identified DEGs shown to be engaged in functional pathways and biologic processes highly relevant for MDS were extant within the patients’ CD34+ cells. These transcriptomic data provide information complementary to exomic mutational findings contributing to improved understanding of biologic mechanisms underlying MDS. Disclosures No relevant conflicts of interest to declare.

scholarly journals A Nomogram Based on Glycolysis-related Gene Expression Profilings Serve as a Novel Prognosis Risk Classifiers for Human Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Lingyu Zhang ◽  
Yu Li ◽  
Yibei Dai ◽  
Danhua Wang ◽  
Xuchu Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Expression Profiles ◽  
Area Under The Curve ◽  
Prognostic Index ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Metabolic Pattern

Abstract Metabolic pattern reconstruction is an important element in tumor progression. The metabolism of tumor cells is characterized by the abnormal increase of anaerobic glycolysis, regardless of the higher oxygen concentration, resulting in a large accumulation of energy from glucose sources, and contributes to rapid cell proliferation and tumor growth which is further referenced as the Warburg effect. We tried to reconstruct the metabolic pattern in the progression of cancer to screen which genetic changes are specific in cancer cells. A total of 12 common types of solid tumors were enrolled in the prospective study. Gene set enrichment analysis (GSEA) was implemented to analyze 9 glycolysis-related gene sets, which are closely related to the glycolysis process. Univariate and multivariate analyses were used to identify independent prognostic variables for the construction of a nomogram based on clinicopathological characteristics and a glycolysis-related gene prognostic index (GRGPI). The prognostic model based on glycolysis genes has the highest area under the curve (AUC) in LIHC (Liver hepatocellular carcinoma). 8-gene signatures (AURKA, CDK1, CENPA, DEPDC1, HMMR, KIF20A, PFKFB4, STMN1) were related to overall survival (OS) and recurrence-free survival (RFS). Further analysis demonstrates that the prediction model can accurately distinguish between high- and low-risk cancer patients among patients in different clusters in LIHC. A nomogram with a well-fitted calibration curve based on gene expression profiles and clinical characteristics improves discrimination in internal and external cohorts. Furthermore, the altering expression of metabolic genes related to glycolysis may contribute to the reconstruction of the tumor-related microenvironment.

RNA-seq analysis of non-muscular invasive bladder cancer to reveal different gene expression profiles between smoking and non-smoking patients.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 478-478
Author(s):  
Zhichao Fu ◽  
Shenghua Liu ◽  
Jianfei Wang ◽  
Ning He ◽  
Yadong Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Tumor Progression ◽  
Urothelial Carcinoma ◽  
Differentially Expressed Genes ◽  
Poor Prognosis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Rna Seq

478 Background: Bladder cancer is the ninth most common malignancy in the world, approximately 75% of patients are diagnosed with non-muscle invasive bladder cancer (NMIBC). Smoking has been established to be a carcinogenic risk factor of bladder cancer. Nevertheless, the detailed relationship between smoking and progression of NMIBC are poorly understood. In this study, we revealed high expressed genes in smoking patients were significantly related to tumor progression in NMIBC patients. Methods: A total of 54 NMIBC patients including 19 never smokers and 35 smokers (current smokers and previous smokers) were enrolled in this study.The gene expression profiles were obtained by RNA-seq and the differentially expressed genes between smoking and non-smoking patients were identified using DESeq2 .The further analysis of the association between genes expression and patient survival in NMIBC cohorts(Jakob et al., 2016)and IMvigor 210 cohorts(Jonathan et al., 2016)by Kaplan-Meier survival estimate. Results: We identified 46 differentially expressed genes (p<0.05) in smoking and non-somking NMIBC patients. IDO1 and KRT14 gene, which related to bladder cancer progression and poor prognosis, was identified significantly higher expressed in somking group compared with non-smoking and they have a logFC of 2.6,3.9 with FDR 1.83E-5,3.40E-5 respectively. The expression of other genes, including KRT6A, CASP14, SERPINA1, MYO3A and IL20RB, were significantly higher in smoking patients compared to non-somking. Notably, survival data analysis from 476 NMIBC cohorts showed that IL20RB had a significant relationship with poor PFS(p = 0.021) and in the Mvigor 210 Cohort including 310 advanced or metastatic urothelial carcinoma patients treated with atezolizumab, we found that the high expression of IL20RB was significantly related to poor OS(p = 0.002). Conclusions: We identified 14 genes related to tumor progression were significantly higher in smoking NMIBC patients than in non-smoking. Among these genes, the expression of IL20RB was related to the poor prognosis of NMIBC, and it may correlates with reduced clinical benefit of immunotherapeutic in patients with urothelial carcinoma.

scholarly journals Construction and Validation of an Immune Cell Signature Score to Evaluate Prognosis and Therapeutic Efficacy in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Linfeng Xu ◽  
Xingxing Jian ◽  
Zhenhao Liu ◽  
Jingjing Zhao ◽  
Siwen Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Expression Profiles ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Marker Genes ◽  
High Morbidity ◽  
Therapeutic Benefits

Background: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with high morbidity and mortality worldwide. Tumor immune microenvironment (TIME) plays a pivotal role in the outcome and treatment of HCC. However, the effect of immune cell signatures (ICSs) representing the characteristics of TIME on the prognosis and therapeutic benefit of HCC patients remains to be further studied.Materials and methods: In total, the gene expression profiles of 1,447 HCC patients from several databases, i.e., The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium, and Gene Expression Omnibus, were obtained and applied. Based on a comprehensive collection of marker genes, 182 ICSs were evaluated by single sample gene set enrichment analysis. Then, by performing univariate and multivariate Cox analysis and random forest modeling, four significant signatures were selected to fit an immune cell signature score (ICSscore).Results: In this study, an ICSscore-based prognostic model was constructed to stratify HCC patients into high-risk and low-risk groups in the TCGA-LIHC cohort, which was successfully validated in two independent cohorts. Moreover, the ICSscore values were found to positively correlate with the current American Joint Committee on Cancer staging system, indicating that ICSscore could act as a comparable biomarker for HCC risk stratification. In addition, when setting the four ICSs and ICSscores as features, the classifiers can significantly distinguish treatment-responding and non-responding samples in HCC. Also, in melanoma and breast cancer, the unified ICSscore could verify samples with therapeutic benefits.Conclusion: Overall, we simplified the tedious ICS to develop the ICSscore, which can be applied successfully for prognostic stratification and therapeutic evaluation in HCC. This study provides an insight into the therapeutic predictive efficacy of prognostic ICS, and a novel ICSscore was constructed to allow future expanded application.

scholarly journals Glycolysis-related gene expression profiling serves as a novel prognosis risk predictor for human hepatocellular carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lingyu Zhang ◽  
Yu Li ◽  
Yibei Dai ◽  
Danhua Wang ◽  
Xuchu Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Expression Profiles ◽  
Area Under The Curve ◽  
Prognostic Index ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Metabolic Pattern

AbstractMetabolic pattern reconstruction is an important factor in tumor progression. Metabolism of tumor cells is characterized by abnormal increase in anaerobic glycolysis, regardless of high oxygen concentration, resulting in a significant accumulation of energy from glucose sources. These changes promotes rapid cell proliferation and tumor growth, which is further referenced a process known as the Warburg effect. The current study reconstructed the metabolic pattern in progression of cancer to identify genetic changes specific in cancer cells. A total of 12 common types of solid tumors were included in the current study. Gene set enrichment analysis (GSEA) was performed to analyze 9 glycolysis-related gene sets, which are implicated in the glycolysis process. Univariate and multivariate analyses were used to identify independent prognostic variables for construction of a nomogram based on clinicopathological characteristics and a glycolysis-related gene prognostic index (GRGPI). The prognostic model based on glycolysis genes showed high area under the curve (AUC) in LIHC (Liver hepatocellular carcinoma). The findings of the current study showed that 8 genes (AURKA, CDK1, CENPA, DEPDC1, HMMR, KIF20A, PFKFB4, STMN1) were correlated with overall survival (OS) and recurrence-free survival (RFS). Further analysis showed that the prediction model accurately distinguished between high- and low-risk cancer patients among patients in different clusters in LIHC. A nomogram with a well-fitted calibration curve based on gene expression profiles and clinical characteristics showed good discrimination based on internal and external cohorts. These findings indicate that changes in expression level of metabolic genes implicated in glycolysis can contribute to reconstruction of tumor-related microenvironment.

Utilizing Cancer - Functional Gene Set - Compound Networks to Identify Putative Drugs for Breast Cancer

2018 ◽  
Vol 21 (2) ◽  
pp. 74-83
Author(s):  
Tzu-Hung Hsiao ◽  
Yu-Chiao Chiu ◽  
Yu-Heng Chen ◽  
Yu-Ching Hsu ◽  
Hung-I Harry Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Therapy ◽  
Cancer Treatment ◽  
Cancer Survival ◽  
Expression Profiles ◽  
Functional Gene ◽  
Gene Set Enrichment Analysis ◽  
Gene Set ◽  
Gene Sets

Aim and Objective: The number of anticancer drugs available currently is limited, and some of them have low treatment response rates. Moreover, developing a new drug for cancer therapy is labor intensive and sometimes cost prohibitive. Therefore, “repositioning” of known cancer treatment compounds can speed up the development time and potentially increase the response rate of cancer therapy. This study proposes a systems biology method for identifying new compound candidates for cancer treatment in two separate procedures. Materials and Methods: First, a “gene set–compound” network was constructed by conducting gene set enrichment analysis on the expression profile of responses to a compound. Second, survival analyses were applied to gene expression profiles derived from four breast cancer patient cohorts to identify gene sets that are associated with cancer survival. A “cancer–functional gene set– compound” network was constructed, and candidate anticancer compounds were identified. Through the use of breast cancer as an example, 162 breast cancer survival-associated gene sets and 172 putative compounds were obtained. Results: We demonstrated how to utilize the clinical relevance of previous studies through gene sets and then connect it to candidate compounds by using gene expression data from the Connectivity Map. Specifically, we chose a gene set derived from a stem cell study to demonstrate its association with breast cancer prognosis and discussed six new compounds that can increase the expression of the gene set after the treatment. Conclusion: Our method can effectively identify compounds with a potential to be “repositioned” for cancer treatment according to their active mechanisms and their association with patients’ survival time.

scholarly journals Transcriptomal dissection of soybean circadian rhythmicity in two geographically, phenotypically and genetically distinct cultivars

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanlei Yue ◽  
Ze Jiang ◽  
Enoch Sapey ◽  
Tingting Wu ◽  
Shi Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Circadian Clock ◽  
Chromosome Structure ◽  
Clock Genes ◽  
Expression Profiles ◽  
Circadian Rhythmicity ◽  
Rna Seq ◽  
Night Time ◽  
Time Points ◽  
Circadian Clock Genes

Abstract Background In soybean, some circadian clock genes have been identified as loci for maturity traits. However, the effects of these genes on soybean circadian rhythmicity and their impacts on maturity are unclear. Results We used two geographically, phenotypically and genetically distinct cultivars, conventional juvenile Zhonghuang 24 (with functional J/GmELF3a, a homolog of the circadian clock indispensable component EARLY FLOWERING 3) and long juvenile Huaxia 3 (with dysfunctional j/Gmelf3a) to dissect the soybean circadian clock with time-series transcriptomal RNA-Seq analysis of unifoliate leaves on a day scale. The results showed that several known circadian clock components, including RVE1, GI, LUX and TOC1, phase differently in soybean than in Arabidopsis, demonstrating that the soybean circadian clock is obviously different from the canonical model in Arabidopsis. In contrast to the observation that ELF3 dysfunction results in clock arrhythmia in Arabidopsis, the circadian clock is conserved in soybean regardless of the functional status of J/GmELF3a. Soybean exhibits a circadian rhythmicity in both gene expression and alternative splicing. Genes can be grouped into six clusters, C1-C6, with different expression profiles. Many more genes are grouped into the night clusters (C4-C6) than in the day cluster (C2), showing that night is essential for gene expression and regulation. Moreover, soybean chromosomes are activated with a circadian rhythmicity, indicating that high-order chromosome structure might impact circadian rhythmicity. Interestingly, night time points were clustered in one group, while day time points were separated into two groups, morning and afternoon, demonstrating that morning and afternoon are representative of different environments for soybean growth and development. However, no genes were consistently differentially expressed over different time-points, indicating that it is necessary to perform a circadian rhythmicity analysis to more thoroughly dissect the function of a gene. Moreover, the analysis of the circadian rhythmicity of the GmFT family showed that GmELF3a might phase- and amplitude-modulate the GmFT family to regulate the juvenility and maturity traits of soybean. Conclusions These results and the resultant RNA-seq data should be helpful in understanding the soybean circadian clock and elucidating the connection between the circadian clock and soybean maturity.

scholarly journals HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Cd4 T Cells ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Infected Cells ◽  
Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

Abstract 16564: Analysis of the Mechanisms of Intravenous Immunoglobulin-Resistant Kawasaki Disease Using iPS Cell Technology

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Kazuyuki Ikeda ◽  
Tomonaga Ameku ◽  
Yui Nomiya ◽  
Masahiro Nakamura ◽  
Satoshi Matsui ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kawasaki Disease ◽  
Intravenous Immunoglobulin ◽  
Expression Profiles ◽  
Systemic Vasculitis ◽  
Dermal Fibroblasts ◽  
Gene Set Enrichment Analysis ◽  
Recurrent Fever ◽  
Ips Cell ◽  
Ivig Resistance

Introduction: Kawasaki disease (KD) is a systemic vasculitis of unknown origin. Although the treatment of intravenous immunoglobulin (IVIG) significantly resolves inflammation, 10-20% of KD patients have persistent or recurrent fever after the administration of IVIG, and IVIG-resistant patients have a particularly high risk of developing coronary artery abnormalities. Hypothesis: The mechanisms of IVIG-resistant KD have been analyzed using the patients’ leukocyte samples. However, vascular endothelial cells (ECs), closely related to the vasculitis of KD, have not been examined in the previous reports. We propose a hypothesis that ECs are mainly involved in the etiology of IVIG-resistance. Methods: The purpose of this study is to establish new in vitro disease models of vasculitis using induced pluripotent stem cell (iPSC) technology, and clarify the mechanisms of IVIG-resistance in KD. Dermal fibroblasts or T cells from 2 IVIG-resistant and 2 IVIG-responsive KD patients were reprogrammed by episomal vectors encoding Oct3/4, Sox2, Klf4, L-Myc, LIN28, and p53 shRNA. The iPSC lines were then differentiated into ECs by using a previously-reported differentiation method, and the EC samples were subjected to the microarray analyses. Results: The KD patient-derived iPSCs could be differentiated into ECs. The gene expression profiles were compared between iPS-derived ECs (iPS-ECs) generated from IVIG-resistant and IVIG-responsive KD patients. We found that 107 genes were at least two fold up-regulated and 101 genes were at least two fold down-regulated in iPS-ECs from IVIG-resistant KD patients compared with those from IVIG-responsive patients. The Principle Component Analysis (PCA) was performed, but the gene expression levels showed no significant differences between the groups. The Gene Set Enrichment Analysis (GSEA) revealed that the gene sets related to IL-6, NRAS (a member of the RAS oncogene family) and breast cancer were up-regulated in iPS-ECs from IVIG-resistant KD patients. Conclusions: Taking into account that the concentration of IL-6 has been reported to be elevated in acute phase of IVIG-resistant KD, our results suggest that the up-regulation of IL-6 related genes in ECs might be involved in the pathogenesis of IVIG-resistant KD.

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