基于囊性纤维化疾病分子特征及其作用机制的生物信息学分析

doi:10.13481/j.1671-587X.20220524

Abstract

Abstract:

Objective To screen the specific genes of cystic fibrosis （CF） and predict the target genes， and to study its mechanism. Methods The datasets（GSE71799，GSE24206，GSE98925 and GSE69764） including CF samples and normal samples were downloaded from the Gene Expression Omnibus（GEO）database and divided into CF group and control group. The R software limma package was used to screen the differentially expressed genes（DEGs） in CF group and control group. Gene Ontology（GO） and Kyoto Encyclopedia of Genes and Genomes（KEGG）were used to analyze the function and pathway enrichment of DEGs， Gene Set Enrichment Analysis（GSEA）was used to obtain the significantly enriched gene sets of DEGs， and STRING database was used to establish the protein-protein interaction（PPI）network. The PPI network was analyzed and visualized by Cytoscape software， and the hub genes were screened. Results A total of 429 DEGs were obtained and screened， including 105 DEGs that were overexpressed in CF group and 324 DEGs that were overexpressed in control group（|log2（FC）|>1，P<0.05）. The GO enrichment analysis results showed that DEGs were mainly enriched in the neutrophil mediated immunity， chemokine activity and cell adhesion molecule binding and so on（P<0.05）. The results of KEGG pathway analysis demonstrated that DEGs were mainly enriched in interleukin-17（IL-17） signaling pathway（P<0.05）. The results of GSEA demonstrated that DEGs were mainly enriched in signaling pathway translation， ribosomal RNA（rRNA） processing and mitochondrial translation and so on. Through STRING database and Cytoscape software， 35 hub genes in the PPI network were screened out， including matrix metallopeptidase 9（MMP9）， C-X-C motif chemokine ligand 2（CXCL2） and C-X-C motif chemokine ligand 3（CXCL3）. In addition， CXCL2 and CXCL3 were associated with DNA methylation. Conclusion The disorder of neutrophil-mediated immunity-related genes and IL-17 signaling pathway-related genes may play an important role in the occurrence and development of CF. CXCL2 and CXCL3 genes may become the biomarkers for DNA methylation therapy of CF.

Key words: Cystic fibrosis, Bioinformatics, Differentially expressed genes, Hub gene, Molecular mechanism

CLC Number:

Xiaoyan WANG,Qiuyue ZHANG,Yujie HU,Zhijing MO. Bioinformatics analysis based on molecular characteristics and mechanism of cystic fibrosis[J].Journal of Jilin University(Medicine Edition), 2022, 48(5): 1290-1297.

Figures/Tables 4

References 34

1	RIORDAN J R， ROMMENS J M， KEREM B S， et al. Identification of the cystic fibrosis gene： cloning and characterization of complementary DNA ［J］. Science， 1989， 245（4922）： 1066-1073.
2	BESSONOVA L， VOLKOVA N， HIGGINS M， et al. Data from the US and UK cystic fibrosis registries support disease modification by CFTR modulation with ivacaftor［J］. Thorax， 2018， 73（8）：731-740.
3	DRUMM M L， KONSTAN M W， SCHLUCHTER M D， et al. Genetic modifiers of lung disease in cystic fibrosis ［J］. N Engl J Med， 2005， 353（14）： 1443-1453.
4	CORVOL H， BLACKMAN S M， BOELLE P Y， et al. Genome-wide association meta-analysis identifies five modifier loci of lung disease severity in cystic fibrosis ［J］. Nat Commun， 2015， 6： 8382.
5	EMOND M J， LOUIE T， EMERSON J， et al. Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in cystic fibrosis［J］. Nat Genet， 2012， 44（8）： 886-889.
6	XU Y， LIU C， CLARK J C， et al. Functional genomic responses to cystic fibrosis transmembrane conductance regulator （CFTR） and CFTR（delta508） in the lung［J］. J Biol Chem， 2006， 281（16）：11279-11291.
7	DAVIS S， MELTZER P S. GEOquery： a bridge between the gene expression omnibus （GEO） and BioConductor ［J］. Bioinformatics， 2007， 23（14）： 1846-1847.
8	SMYTH G K. Limma： linear models for microarray data［M］//Bioinformatics and Computational Biology Solutions Using R and Bioconductor.New York：Spring Verlag，2005：397-420.
9	GU Z G， EILS R， SCHLESNER M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data ［J］. Bioinformatics， 2016， 32（18）： 2847-2849.
10	YU G C， WANG L G， HAN Y Y，et al. ClusterProfiler： an R package for comparing biological themes among gene clusters［J］. OMICS， 2012， 16（5）： 284-287.
11	SZKLARCZYK D， GABLE A L， LYON D， et al. STRING v11： protein-protein association networks with increased coverage， supporting functional discovery in genome-wide experimental datasets ［J］. Nucleic Acids Res， 2019， 47（D1）： D607-D613.
12	DEMCHAK B， HULL T， REICH M， et al. Cytoscape： the network visualization tool for GenomeSpace workflows［J］.F1000Research，2014，3：151.
13	BANDETTINI W P， KELLMAN P， MANCINI C，et al.MultiContrast Delayed Enhancement （MCODE）improves detection of subendocardial myocardial infarction by late gadolinium enhancement cardiovascular magnetic resonance： a clinical validation study ［J］. J Cardiovasc Magn Reson， 2012， 14（1）： 83.
14	ISIDRO-SÁNCHEZ J， AKDEMIR D， MONTILLA-BASCÓN G. Genome-wide association analysis using R［J］. Methods Mol Biol， 2017， 1536： 189-207.
15	LEY K， HOFFMAN H M， KUBES P， et al. Neutrophils： New insights and open questions［J］. Sci Immunol， 2018， 3（30）： eaat4579.
16	ADIB-CONQUY M， PEDRON T， PETIT-BERTRON A F， et al. Neutrophils in cystic fibrosis display a distinct gene expression pattern ［J］. Mol Med， 2008， 14（1/2）： 36-44.
17	DICKERHOF N， ISLES V， PATTEMORE P， et al. Exposure of Pseudomonas aeruginosa to bactericidal hypochlorous acid during neutrophil phagocytosis is compromised in cystic fibrosis ［J］. J Biol Chem， 2019， 294（36）： 13502-13514.
18	BRATCHER P E， ROWE S M， REEVES G， et al. Alterations in blood leukocytes of G551D-bearing cystic fibrosis patients undergoing treatment with ivacaftor ［J］. J Cyst Fibros， 2016， 15（1）： 67-73.
19	VAN KESSEL K P M， BESTEBROER J， VAN STRIJP J A G.Neutrophil-mediated phagocytosis of staphylococcus aureus ［J］. Front Immunol， 2014， 5： 467.
20	KHAN M A， FARAHVASH A， DOUDA D N， et al. JNK activation turns on LPS- and gram-negative bacteria-induced NADPH oxidase-dependent suicidal NETosis ［J］. Sci Rep， 2017， 7（1）： 3409.
21	TAMASSIA N， BIANCHETTO-AGUILERA F， ARRUDA-SILVA F，et al.Cytokine production by human neutrophils： Revisiting the “dark side of the moon”［J］. Eur J Clin Invest， 2018， 48（）： e12952.
22	CONTI H R， BRUNO V M， CHILDS E E， et al. IL-17 receptor signaling in oral epithelial cells is critical for protection against oropharyngeal candidiasis ［J］. Cell Host Microbe， 2016， 20（5）： 606-617.
23	MCGEACHY M J， CUA D J， GAFFEN S L.The IL-17 family of cytokines in health and disease ［J］. Immunity， 2019， 50（4）： 892-906.
24	SONG X Y， DAI D， HE X， et al. Growth factor FGF2 cooperates with interleukin-17 to repair intestinal epithelial damage［J］. Immunity， 2015，43（3）： 488-501.
25	MACLEOD A S， HEMMERS S， GARIJO O， et al. Dendritic epidermal T cells regulate skin antimicrobial barrier function［J］. J Clin Invest， 2013， 123（10）： 4364-4374.
26	CHEN X， CAI G， LIU C， et al. IL-17R-EGFR axis links wound healing to tumorigenesis in Lrig1+ stem cells ［J］. J Exp Med， 2019， 216（1）： 195-214.
27	O’NEILL L A J， ARTYOMOV M N. Itaconate： the poster child of metabolic reprogramming in macrophage function［J］. Nat Rev Immunol， 2019， 19（5）： 273-281.
28	BENYELLES M， O’DONOHUE M F， KERMASSON L， et al. NHP2 deficiency impairs rRNA biogenesis and causes pulmonary fibrosis and Høyeraal-Hreidarsson syndrome ［J］. Hum Mol Genet， 2020， 29（6）： 907-922.
29	YU H， GUO W K， LIU Y D，et al. Immune characteristics analysis and transcriptional regulation prediction based on gene signatures of chronic obstructive pulmonary disease［J］. Int J Chron Obstruct Pulmon Dis， 2021， 16： 3027-3039.
30	YIN Y， WU Y Y， ZHANG X， et al. PPA1 regulates systemic insulin sensitivity by maintaining adipocyte mitochondria function as a novel PPARγ target gene ［J］. Diabetes， 2021， 70（6）： 1278-1291.
31	ONENGUT-GUMUSCU S， PAILA U， CHEN W M， et al. Novel genetic risk factors influence progression of islet autoimmunity to type 1 diabetes ［J］. Sci Rep， 2020， 10： 19193.
32	AVERNA M， BAVESTRELLO M， CRESTA F，et al. Abnormal activation of calpain and protein kinase Cα promotes a constitutive release of matrix metalloproteinase 9 in peripheral blood mononuclear cells from cystic fibrosis patients ［J］. Arch Biochem Biophys， 2016， 604： 103-112.
33	TURNBULL A R， PYLE C J， PATEL D F， et al. Abnormal pro-gly-pro pathway and airway neutrophilia in pediatric cystic fibrosis［J］. J Cyst Fibros， 2020， 19（1）： 40-48.
34	HUAN C J， YANG T， LIANG J R， et al. Methylation-mediated BMPER expression in fibroblast activation in vitro and lung fibrosis in mice in vivo ［J］. Sci Rep， 2015， 5： 14910.

ID	Set size	Enrichment score	NES	P	FDR
REACTOME_TRANSLATION	248	0.665 1	2.354 4	0.025 2	0.017 5
REACTOME_RRNA_PROCESSING	168	0.690 3	2.352 7	0.025 2	0.017 5
REACTOME_MITOCHONDRIAL_TRANSLATION	91	0.726 3	2.269 2	0.025 2	0.017 5
REACTOME_EUKARYOTIC_TRANSLATION_ELONGATION	73	0.744 1	2.268 5	0.025 2	0.017 5
REACTOME_EUKARYOTIC_TRANSLATION_INITIATION	100	0.707 4	2.263 2	0.025 2	0.017 5

[1]	Liantao HU,Wenjun DENG,Shizhen LU,Luo SUN,Xuebing LI,Chuhao LI,Xinran WANG,chunbing ZHANG,Yue LI,Weiqun WANG. Bioinformatics analysis on CC chemokine ligand 20 expression in hepatocellular carcinoma tissue and its effect on prognostic assessment of liver hepatocellular carcinoma [J]. Journal of Jilin University(Medicine Edition), 2022, 48(4): 1010-1017.
[2]	Qian LIU,Guoping QI,Huayi YU,Yuyang DAI,Wenbin LU,Jianhua JIN. Bioinformatics analysis on screening of colon cancer core genes and independent prognostic factors [J]. Journal of Jilin University(Medicine Edition), 2022, 48(3): 755-765.
[3]	Xiaoyan LI,Wei ZHANG,Jie HE. Promotion effect of REG1A on proliferation and migration of lung adenocarcinoma cells by regulating Wnt/β-catenin signaling pathway [J]. Journal of Jilin University(Medicine Edition), 2022, 48(2): 444-453.
[4]	Ying ZHAO,Danyu ZHAO,Chao LIU. Bioinformatics analysis on prognostic evaluation value of TXNDC11 gene in pan-cancer and its immunity regulation [J]. Journal of Jilin University(Medicine Edition), 2022, 48(1): 142-153.
[5]	Zhijuan ZHAO,Lian MENG,Chunxia LIU. Bioinformatics analysis on miRNA-mRNA regulatory networks based on fusion genes acting in rhabdomyosarcoma [J]. Journal of Jilin University(Medicine Edition), 2022, 48(1): 154-162.
[6]	Nan LI,Lei CHEN,Tianmin XU,Kun ZHANG. Bioinformatics analysis on screening of extracellular matrix related genes in patients with endometriosis [J]. Journal of Jilin University(Medicine Edition), 2022, 48(1): 188-194.
[7]	Hao DONG,Haizhen JIANG,Chao LI,Dengke GAO,Yaping JIN,Huatao CHEN. Construction of mouse NR1D1 gene overexpression vector and its bioinformatics analysis [J]. Journal of Jilin University(Medicine Edition), 2022, 48(1): 94-103.
[8]	Weihang LI,Ziyi DING,Dong WANG,Yikai PAN,Yuhui LIU,Shilei ZHANG,Jing LI,Ming YAN. Bioinformatics analysis based on screening of core driving genes in osteosarcoma and construction of gene model for prediction of survival time of patients [J]. Journal of Jilin University(Medicine Edition), 2021, 47(6): 1570-1580.
[9]	Yang YU,Sainan LIU,Yunkai LIU,Yong LI,Yichun QIAO,Yi CHENG. Bioinformatic analysis on expression characteristics of PRPS2 and its relationship with prognosis of breast cancer [J]. Journal of Jilin University(Medicine Edition), 2021, 47(5): 1229-1236.
[10]	Yuqing PAN, Yunyan SUN, Yixun LI, Liying WANG, Zhuoma SINAN, Rui CHEN, Xi ZHANG, Yan DU. Construction and analysis of competitive endogenous RNA networks in acute myeloid leukemia based on high-throughput microarray [J]. Journal of Jilin University(Medicine Edition), 2021, 47(3): 669-676.
[11]	Yao LIN,Chunlin LIN,Qin WANG,Bin ZHANG,Shaoyu WANG,Guangwei ZHU. Expressions of minichromosome maintenance proteins and structural maintenance of chromosomes 4 genes in cervical squamous cell carcinoma tissue and bioinformation analysis [J]. Journal of Jilin University(Medicine Edition), 2021, 47(2): 430-437.
[12]	Lan ZHENG,Songzhe PIAO,Ran XU,Xinyue WANG,Yixuan WANG,Zhenhua LIN,Yang YANG. Bioinformatics analysis based on effect of expression levels of m⁶A regulators on immune infiltration and prognosis of uterine corpus endometrial carcinoma [J]. Journal of Jilin University(Medicine Edition), 2021, 47(2): 438-452.
[13]	ZHANG Xi, ZHAI Li, SUN Yunyan, YANG Wei, GAO Yanzhang, LEI Ming, PAN Yuqing. Bioinformatics analysis of pediatric acute myeloid leukemia based on high-throughput microarray [J]. Journal of Jilin University(Medicine Edition), 2020, 46(05): 1036-1042.
[14]	WANG Zhi, HONG Li, LI Suting, ZENG Wanling. Analysis on endometrial cancer-related genes and candidate pathways based on GEO database bioinformatics methods [J]. Journal of Jilin University(Medicine Edition), 2020, 46(04): 804-809.
[15]	TAN Qi, REN Liqun, ZHANG Yibing, WANG Yadi, GU Zehui, HUANG Peng, CHEN Suxian. Application of bioinformatics in screening of miRNA biomarkers in triple-negative breast cancer [J]. Journal of Jilin University(Medicine Edition), 2019, 45(05): 1098-1105.

Bioinformatics analysis based on molecular characteristics and mechanism of cystic fibrosis

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 4

References 34

Related Articles 15

Metrics

Comments

Recommended 0