Cystic Fibrosis: Systems Biology Analysis from Homozygous p.Phe508del Variant Patients’ Samples Reveals Perturbations in Tissue-Specific Pathways
Cystic fibrosis (CF) is an autosomal recessive disorder, caused by diverse genetic variants for the CF transmembrane conductance regulator (CFTR) protein. Among these, p.Phe508del is the most prevalent variant. The effects of this variant on the physiology of each tissue remains unknown. This study...
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description | Cystic fibrosis (CF) is an autosomal recessive disorder, caused by diverse genetic variants for the CF transmembrane conductance regulator (CFTR) protein. Among these, p.Phe508del is the most prevalent variant. The effects of this variant on the physiology of each tissue remains unknown. This study is aimed at predicting cell signaling pathways present in different tissues of fibrocystic patients, homozygous for p.Phe508del. The study involved analysis of two microarray datasets, E-GEOD-15568 and E-MTAB-360 corresponding to the rectal and bronchial epithelium, respectively, obtained from the ArrayExpress repository. Particularly, differentially expressed genes (DEGs) were predicted, protein-protein interaction (PPI) networks were designed, and centrality and functional interaction networks were analyzed. The study reported that p.Phe508del-mutated CFTR-allele in homozygous state influenced the whole gene expression in each tissue differently. Interestingly, gene ontology (GO) term enrichment analysis revealed that only “neutrophil activation” was shared between both tissues; however, nonshared DEGs were grouped into the same GO term. For further verification, functional interaction networks were generated, wherein no shared nodes were reported between these tissues. These results suggested that the p.Phe508del-mutated CFTR-allele in homozygous state promoted tissue-specific pathways in fibrocystic patients. The generated data might further assist in prediction diagnosis to define biomarkers or devising therapeutic strategies. |
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Among these, p.Phe508del is the most prevalent variant. The effects of this variant on the physiology of each tissue remains unknown. This study is aimed at predicting cell signaling pathways present in different tissues of fibrocystic patients, homozygous for p.Phe508del. The study involved analysis of two microarray datasets, E-GEOD-15568 and E-MTAB-360 corresponding to the rectal and bronchial epithelium, respectively, obtained from the ArrayExpress repository. Particularly, differentially expressed genes (DEGs) were predicted, protein-protein interaction (PPI) networks were designed, and centrality and functional interaction networks were analyzed. The study reported that p.Phe508del-mutated CFTR-allele in homozygous state influenced the whole gene expression in each tissue differently. Interestingly, gene ontology (GO) term enrichment analysis revealed that only “neutrophil activation” was shared between both tissues; however, nonshared DEGs were grouped into the same GO term. For further verification, functional interaction networks were generated, wherein no shared nodes were reported between these tissues. These results suggested that the p.Phe508del-mutated CFTR-allele in homozygous state promoted tissue-specific pathways in fibrocystic patients. The generated data might further assist in prediction diagnosis to define biomarkers or devising therapeutic strategies.</description><identifier>ISSN: 2314-6133</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2021/5262000</identifier><identifier>PMID: 34901273</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Alleles ; Analysis ; Biomarkers ; Biomarkers - metabolism ; Care and treatment ; Cell activation ; Cell signaling ; Cellular signal transduction ; Cystic fibrosis ; Cystic Fibrosis - genetics ; Datasets ; Diagnosis ; DNA microarrays ; Epithelium ; Epithelium - physiology ; Gene expression ; Gene Expression - genetics ; Genetic diversity ; Genetic variance ; Hereditary diseases ; Homozygote ; Humans ; Leukocytes (neutrophilic) ; Lungs ; Mutation - genetics ; Networks ; Ontology ; Pathogenesis ; Perturbation ; Protein interaction ; Protein Interaction Maps - genetics ; Protein-protein interactions ; Proteins ; Risk factors ; Signal Transduction - genetics ; Systems Biology - methods ; Tissues</subject><ispartof>BioMed research international, 2021, Vol.2021, p.5262000-16</ispartof><rights>Copyright © 2021 Joice de Faria Poloni et al.</rights><rights>COPYRIGHT 2021 John Wiley & Sons, Inc.</rights><rights>Copyright © 2021 Joice de Faria Poloni et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2021 Joice de Faria Poloni et al. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3910-f8b39b2c25518c65d99c913b8dca31b1cd18b1a8ef7a9d708990d7e2b8fbecc43</citedby><cites>FETCH-LOGICAL-c3910-f8b39b2c25518c65d99c913b8dca31b1cd18b1a8ef7a9d708990d7e2b8fbecc43</cites><orcidid>0000-0002-6128-5025 ; 0000-0003-4421-8995 ; 0000-0002-7729-5738 ; 0000-0002-3896-6404 ; 0000-0002-9672-9394</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8660202/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8660202/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,728,781,785,886,4025,27928,27929,27930,53796,53798</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34901273$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Gu, Chang</contributor><contributor>Chang Gu</contributor><creatorcontrib>de Faria Poloni, Joice</creatorcontrib><creatorcontrib>Rispoli, Thaiane</creatorcontrib><creatorcontrib>Rossetti, Maria Lucia</creatorcontrib><creatorcontrib>Trindade, Cristiano</creatorcontrib><creatorcontrib>Vargas, José Eduardo</creatorcontrib><title>Cystic Fibrosis: Systems Biology Analysis from Homozygous p.Phe508del Variant Patients’ Samples Reveals Perturbations in Tissue-Specific Pathways</title><title>BioMed research international</title><addtitle>Biomed Res Int</addtitle><description>Cystic fibrosis (CF) is an autosomal recessive disorder, caused by diverse genetic variants for the CF transmembrane conductance regulator (CFTR) protein. Among these, p.Phe508del is the most prevalent variant. The effects of this variant on the physiology of each tissue remains unknown. This study is aimed at predicting cell signaling pathways present in different tissues of fibrocystic patients, homozygous for p.Phe508del. The study involved analysis of two microarray datasets, E-GEOD-15568 and E-MTAB-360 corresponding to the rectal and bronchial epithelium, respectively, obtained from the ArrayExpress repository. Particularly, differentially expressed genes (DEGs) were predicted, protein-protein interaction (PPI) networks were designed, and centrality and functional interaction networks were analyzed. The study reported that p.Phe508del-mutated CFTR-allele in homozygous state influenced the whole gene expression in each tissue differently. Interestingly, gene ontology (GO) term enrichment analysis revealed that only “neutrophil activation” was shared between both tissues; however, nonshared DEGs were grouped into the same GO term. For further verification, functional interaction networks were generated, wherein no shared nodes were reported between these tissues. These results suggested that the p.Phe508del-mutated CFTR-allele in homozygous state promoted tissue-specific pathways in fibrocystic patients. The generated data might further assist in prediction diagnosis to define biomarkers or devising therapeutic strategies.</description><subject>Alleles</subject><subject>Analysis</subject><subject>Biomarkers</subject><subject>Biomarkers - metabolism</subject><subject>Care and treatment</subject><subject>Cell activation</subject><subject>Cell signaling</subject><subject>Cellular signal transduction</subject><subject>Cystic fibrosis</subject><subject>Cystic Fibrosis - genetics</subject><subject>Datasets</subject><subject>Diagnosis</subject><subject>DNA microarrays</subject><subject>Epithelium</subject><subject>Epithelium - physiology</subject><subject>Gene expression</subject><subject>Gene Expression - genetics</subject><subject>Genetic diversity</subject><subject>Genetic variance</subject><subject>Hereditary diseases</subject><subject>Homozygote</subject><subject>Humans</subject><subject>Leukocytes (neutrophilic)</subject><subject>Lungs</subject><subject>Mutation - genetics</subject><subject>Networks</subject><subject>Ontology</subject><subject>Pathogenesis</subject><subject>Perturbation</subject><subject>Protein interaction</subject><subject>Protein Interaction Maps - genetics</subject><subject>Protein-protein interactions</subject><subject>Proteins</subject><subject>Risk factors</subject><subject>Signal Transduction - genetics</subject><subject>Systems Biology - methods</subject><subject>Tissues</subject><issn>2314-6133</issn><issn>2314-6141</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kk1v1DAQhiMEolXpjTOyxAUJ0s7Ymw9zQFpWlCJVYsUWrpbtOLuukjjYSatw4j9w4u_xS_Bql-XjgHyw5XnmnfH4TZLHCGeIWXZOgeJ5RnMKAPeSY8pwluY4w_uHM2NHyWkINxGAEnPg-cPkiM04IC3YcfJtMYXBanJhlXfBhpdkFS9MG8hr6xq3nsi8k80UI6T2riWXrnVfprUbA-nPlhuTQVmZhnyS3spuIEs5WNMN4cfX72Ql274xgXwwt0Y2gSyNH0avIuG6QGxHrm0Io0lXvdG2jj3E5M2dnMKj5EEdE8zpfj9JPl68uV5cplfv375bzK9SzThCWpeKcUU1zTIsdZ5VnGuOTJWVlgwV6gpLhbI0dSF5VUDJOVSFoaqsldF6xk6SVzvdflStqXRs3MtG9N620k_CSSv-jnR2I9buVpR5DnHyUeDZXsC7z6MJg2ht0KZpZGfihATNEaDgWEBEn_6D3rjRx9FuKeCY0Rnw39RaNkbYrnaxrt6KinnO4yoAMFIvdpSOXxa8qQ8tI4itLcTWFmJvi4g_-fOZB_iXCSLwfAdsbFfJO_t_uZ_P0cGU</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>de Faria Poloni, Joice</creator><creator>Rispoli, Thaiane</creator><creator>Rossetti, Maria Lucia</creator><creator>Trindade, Cristiano</creator><creator>Vargas, José Eduardo</creator><general>Hindawi</general><general>John Wiley & Sons, Inc</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7QO</scope><scope>7T7</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-6128-5025</orcidid><orcidid>https://orcid.org/0000-0003-4421-8995</orcidid><orcidid>https://orcid.org/0000-0002-7729-5738</orcidid><orcidid>https://orcid.org/0000-0002-3896-6404</orcidid><orcidid>https://orcid.org/0000-0002-9672-9394</orcidid></search><sort><creationdate>2021</creationdate><title>Cystic Fibrosis: Systems Biology Analysis from Homozygous p.Phe508del Variant Patients’ Samples Reveals Perturbations in Tissue-Specific Pathways</title><author>de Faria Poloni, Joice ; Rispoli, Thaiane ; Rossetti, Maria Lucia ; Trindade, Cristiano ; Vargas, José Eduardo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3910-f8b39b2c25518c65d99c913b8dca31b1cd18b1a8ef7a9d708990d7e2b8fbecc43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Alleles</topic><topic>Analysis</topic><topic>Biomarkers</topic><topic>Biomarkers - metabolism</topic><topic>Care and treatment</topic><topic>Cell activation</topic><topic>Cell signaling</topic><topic>Cellular signal transduction</topic><topic>Cystic fibrosis</topic><topic>Cystic Fibrosis - genetics</topic><topic>Datasets</topic><topic>Diagnosis</topic><topic>DNA microarrays</topic><topic>Epithelium</topic><topic>Epithelium - physiology</topic><topic>Gene expression</topic><topic>Gene Expression - genetics</topic><topic>Genetic diversity</topic><topic>Genetic variance</topic><topic>Hereditary diseases</topic><topic>Homozygote</topic><topic>Humans</topic><topic>Leukocytes (neutrophilic)</topic><topic>Lungs</topic><topic>Mutation - genetics</topic><topic>Networks</topic><topic>Ontology</topic><topic>Pathogenesis</topic><topic>Perturbation</topic><topic>Protein interaction</topic><topic>Protein Interaction Maps - genetics</topic><topic>Protein-protein interactions</topic><topic>Proteins</topic><topic>Risk factors</topic><topic>Signal Transduction - genetics</topic><topic>Systems Biology - methods</topic><topic>Tissues</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Faria Poloni, Joice</creatorcontrib><creatorcontrib>Rispoli, Thaiane</creatorcontrib><creatorcontrib>Rossetti, Maria Lucia</creatorcontrib><creatorcontrib>Trindade, Cristiano</creatorcontrib><creatorcontrib>Vargas, José Eduardo</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BioMed research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>de Faria Poloni, Joice</au><au>Rispoli, Thaiane</au><au>Rossetti, Maria Lucia</au><au>Trindade, Cristiano</au><au>Vargas, José Eduardo</au><au>Gu, Chang</au><au>Chang Gu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cystic Fibrosis: Systems Biology Analysis from Homozygous p.Phe508del Variant Patients’ Samples Reveals Perturbations in Tissue-Specific Pathways</atitle><jtitle>BioMed research international</jtitle><addtitle>Biomed Res Int</addtitle><date>2021</date><risdate>2021</risdate><volume>2021</volume><spage>5262000</spage><epage>16</epage><pages>5262000-16</pages><issn>2314-6133</issn><eissn>2314-6141</eissn><abstract>Cystic fibrosis (CF) is an autosomal recessive disorder, caused by diverse genetic variants for the CF transmembrane conductance regulator (CFTR) protein. Among these, p.Phe508del is the most prevalent variant. The effects of this variant on the physiology of each tissue remains unknown. This study is aimed at predicting cell signaling pathways present in different tissues of fibrocystic patients, homozygous for p.Phe508del. The study involved analysis of two microarray datasets, E-GEOD-15568 and E-MTAB-360 corresponding to the rectal and bronchial epithelium, respectively, obtained from the ArrayExpress repository. Particularly, differentially expressed genes (DEGs) were predicted, protein-protein interaction (PPI) networks were designed, and centrality and functional interaction networks were analyzed. The study reported that p.Phe508del-mutated CFTR-allele in homozygous state influenced the whole gene expression in each tissue differently. Interestingly, gene ontology (GO) term enrichment analysis revealed that only “neutrophil activation” was shared between both tissues; however, nonshared DEGs were grouped into the same GO term. For further verification, functional interaction networks were generated, wherein no shared nodes were reported between these tissues. These results suggested that the p.Phe508del-mutated CFTR-allele in homozygous state promoted tissue-specific pathways in fibrocystic patients. The generated data might further assist in prediction diagnosis to define biomarkers or devising therapeutic strategies.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>34901273</pmid><doi>10.1155/2021/5262000</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0002-6128-5025</orcidid><orcidid>https://orcid.org/0000-0003-4421-8995</orcidid><orcidid>https://orcid.org/0000-0002-7729-5738</orcidid><orcidid>https://orcid.org/0000-0002-3896-6404</orcidid><orcidid>https://orcid.org/0000-0002-9672-9394</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Alleles Analysis Biomarkers Biomarkers - metabolism Care and treatment Cell activation Cell signaling Cellular signal transduction Cystic fibrosis Cystic Fibrosis - genetics Datasets Diagnosis DNA microarrays Epithelium Epithelium - physiology Gene expression Gene Expression - genetics Genetic diversity Genetic variance Hereditary diseases Homozygote Humans Leukocytes (neutrophilic) Lungs Mutation - genetics Networks Ontology Pathogenesis Perturbation Protein interaction Protein Interaction Maps - genetics Protein-protein interactions Proteins Risk factors Signal Transduction - genetics Systems Biology - methods Tissues |
title | Cystic Fibrosis: Systems Biology Analysis from Homozygous p.Phe508del Variant Patients’ Samples Reveals Perturbations in Tissue-Specific Pathways |
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