Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer
Background. Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in B...
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| description | Background. Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood. Methods. Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions. Results. We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages. Conclusion. RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response. |
| doi_str_mv | 10.1155/2021/8072796 |
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| fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8651385</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A696966936</galeid><sourcerecordid>A696966936</sourcerecordid><originalsourceid>FETCH-LOGICAL-c476t-554b4bbad44024a9ec13fe712948d5d8978b87c273f0b3d459b9a7ba04ce9a873</originalsourceid><addsrcrecordid>eNp9kc1LHDEYh0OpVFFvnmWgl0JdzffHpbAu2goWwbaHnkImk1kjM4kmMxX_ezPuutYemhwSkocned8fAAcIHiPE2AmGGJ1IKLBQ_B3YwQTRGUcUvd_sCdkG-znfwjIk4lDxD2CbUCklkWwHXJ366EMbU28Gb6t5MN1j9rmKbXXR92Nw1Q-_DL711gTrpuPr39e4-j4OhY-h8qE6Tc7koVpMQNoDW63psttfr7vg1_nZz8W32eXV14vF_HJmqeDDjDFa07o2DaUQU6OcRaR1AmFFZcMaqYSspbBYkBbWpKFM1cqI2kBqnTJSkF3wZeW9G-veNdaFIZlO3yXfm_Soo_H67U3wN3oZ_2jJGSqVF8GntSDF-9HlQfc-W9d1Jrg4Zo05LBSlBBf04z_obRxT6dQzpRDDnMpXamk6p6eelnftJNVzrsrkivBCHa0om2LOybWbLyOop0j1FKleR1rww7_L3MAvARbg8wq48aExD_7_uifcoaaF</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2609152648</pqid></control><display><type>article</type><title>Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer</title><source>MEDLINE</source><source>PubMed Central Open Access</source><source>Wiley Online Library (Open Access Collection)</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Xu, Zhiquan ; Xiang, Ling ; Wang, Rong ; Xiong, Yongfu ; Zhou, He ; Gu, Haitao ; Wang, Jijian ; Peng, Linglong</creator><contributor>Fang, Yujiang ; Yujiang Fang</contributor><creatorcontrib>Xu, Zhiquan ; Xiang, Ling ; Wang, Rong ; Xiong, Yongfu ; Zhou, He ; Gu, Haitao ; Wang, Jijian ; Peng, Linglong ; Fang, Yujiang ; Yujiang Fang</creatorcontrib><description>Background. Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood. Methods. Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions. Results. We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages. Conclusion. RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response.</description><identifier>ISSN: 2314-6133</identifier><identifier>ISSN: 2314-6141</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2021/8072796</identifier><identifier>PMID: 34888385</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Aged ; Algorithms ; Analysis ; Antitumor activity ; Biomarkers ; Biomarkers, Tumor - genetics ; Breast cancer ; Breast Neoplasms - genetics ; Cancer ; Cancer therapies ; Care and treatment ; CD4 antigen ; CD8 antigen ; Chemotherapy ; Computational Biology - methods ; Datasets ; Diagnosis ; E-cadherin ; Enrichment ; Female ; GATA-3 protein ; Gene Expression Regulation, Neoplastic - genetics ; Gene mutations ; Gene set enrichment analysis ; Genes ; Genetic aspects ; Genomes ; Health aspects ; Humans ; Immune response ; Immune system ; Immunological memory ; Immunotherapy ; Immunotherapy - methods ; Kaplan-Meier Estimate ; Lung cancer ; Lymphocytes ; Lymphocytes T ; Macrophages ; Medical prognosis ; Melanoma ; Memory cells ; Mutation ; Mutation - genetics ; p53 Protein ; Patient outcomes ; Prognosis ; PTEN protein ; Radiation therapy ; Regression analysis ; Regulatory mechanisms (biology) ; Risk factors ; Ryanodine Receptor Calcium Release Channel - genetics ; Ryanodine receptors ; Signal Transduction - genetics ; Software ; Survival analysis ; Tumor-infiltrating lymphocytes ; Tumors ; USH2A protein</subject><ispartof>BioMed research international, 2021-11, Vol.2021, p.8072796-12</ispartof><rights>Copyright © 2021 Zhiquan Xu et al.</rights><rights>COPYRIGHT 2021 John Wiley & Sons, Inc.</rights><rights>Copyright © 2021 Zhiquan Xu 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 Zhiquan Xu et al. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-554b4bbad44024a9ec13fe712948d5d8978b87c273f0b3d459b9a7ba04ce9a873</citedby><cites>FETCH-LOGICAL-c476t-554b4bbad44024a9ec13fe712948d5d8978b87c273f0b3d459b9a7ba04ce9a873</cites><orcidid>0000-0001-5774-3110 ; 0000-0003-1694-333X ; 0000-0001-8323-9903</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/PMC8651385/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8651385/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34888385$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Fang, Yujiang</contributor><contributor>Yujiang Fang</contributor><creatorcontrib>Xu, Zhiquan</creatorcontrib><creatorcontrib>Xiang, Ling</creatorcontrib><creatorcontrib>Wang, Rong</creatorcontrib><creatorcontrib>Xiong, Yongfu</creatorcontrib><creatorcontrib>Zhou, He</creatorcontrib><creatorcontrib>Gu, Haitao</creatorcontrib><creatorcontrib>Wang, Jijian</creatorcontrib><creatorcontrib>Peng, Linglong</creatorcontrib><title>Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer</title><title>BioMed research international</title><addtitle>Biomed Res Int</addtitle><description>Background. Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood. Methods. Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions. Results. We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages. Conclusion. RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response.</description><subject>Aged</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Antitumor activity</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - genetics</subject><subject>Cancer</subject><subject>Cancer therapies</subject><subject>Care and treatment</subject><subject>CD4 antigen</subject><subject>CD8 antigen</subject><subject>Chemotherapy</subject><subject>Computational Biology - methods</subject><subject>Datasets</subject><subject>Diagnosis</subject><subject>E-cadherin</subject><subject>Enrichment</subject><subject>Female</subject><subject>GATA-3 protein</subject><subject>Gene Expression Regulation, Neoplastic - genetics</subject><subject>Gene mutations</subject><subject>Gene set enrichment analysis</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genomes</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Immune response</subject><subject>Immune system</subject><subject>Immunological memory</subject><subject>Immunotherapy</subject><subject>Immunotherapy - methods</subject><subject>Kaplan-Meier Estimate</subject><subject>Lung cancer</subject><subject>Lymphocytes</subject><subject>Lymphocytes T</subject><subject>Macrophages</subject><subject>Medical prognosis</subject><subject>Melanoma</subject><subject>Memory cells</subject><subject>Mutation</subject><subject>Mutation - genetics</subject><subject>p53 Protein</subject><subject>Patient outcomes</subject><subject>Prognosis</subject><subject>PTEN protein</subject><subject>Radiation therapy</subject><subject>Regression analysis</subject><subject>Regulatory mechanisms (biology)</subject><subject>Risk factors</subject><subject>Ryanodine Receptor Calcium Release Channel - genetics</subject><subject>Ryanodine receptors</subject><subject>Signal Transduction - genetics</subject><subject>Software</subject><subject>Survival analysis</subject><subject>Tumor-infiltrating lymphocytes</subject><subject>Tumors</subject><subject>USH2A protein</subject><issn>2314-6133</issn><issn>2314-6141</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>eNp9kc1LHDEYh0OpVFFvnmWgl0JdzffHpbAu2goWwbaHnkImk1kjM4kmMxX_ezPuutYemhwSkocned8fAAcIHiPE2AmGGJ1IKLBQ_B3YwQTRGUcUvd_sCdkG-znfwjIk4lDxD2CbUCklkWwHXJ366EMbU28Gb6t5MN1j9rmKbXXR92Nw1Q-_DL711gTrpuPr39e4-j4OhY-h8qE6Tc7koVpMQNoDW63psttfr7vg1_nZz8W32eXV14vF_HJmqeDDjDFa07o2DaUQU6OcRaR1AmFFZcMaqYSspbBYkBbWpKFM1cqI2kBqnTJSkF3wZeW9G-veNdaFIZlO3yXfm_Soo_H67U3wN3oZ_2jJGSqVF8GntSDF-9HlQfc-W9d1Jrg4Zo05LBSlBBf04z_obRxT6dQzpRDDnMpXamk6p6eelnftJNVzrsrkivBCHa0om2LOybWbLyOop0j1FKleR1rww7_L3MAvARbg8wq48aExD_7_uifcoaaF</recordid><startdate>20211103</startdate><enddate>20211103</enddate><creator>Xu, Zhiquan</creator><creator>Xiang, Ling</creator><creator>Wang, Rong</creator><creator>Xiong, Yongfu</creator><creator>Zhou, He</creator><creator>Gu, Haitao</creator><creator>Wang, Jijian</creator><creator>Peng, Linglong</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/0000-0001-5774-3110</orcidid><orcidid>https://orcid.org/0000-0003-1694-333X</orcidid><orcidid>https://orcid.org/0000-0001-8323-9903</orcidid></search><sort><creationdate>20211103</creationdate><title>Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer</title><author>Xu, Zhiquan ; Xiang, Ling ; Wang, Rong ; Xiong, Yongfu ; Zhou, He ; Gu, Haitao ; Wang, Jijian ; Peng, Linglong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c476t-554b4bbad44024a9ec13fe712948d5d8978b87c273f0b3d459b9a7ba04ce9a873</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Aged</topic><topic>Algorithms</topic><topic>Analysis</topic><topic>Antitumor activity</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Breast cancer</topic><topic>Breast Neoplasms - genetics</topic><topic>Cancer</topic><topic>Cancer therapies</topic><topic>Care and treatment</topic><topic>CD4 antigen</topic><topic>CD8 antigen</topic><topic>Chemotherapy</topic><topic>Computational Biology - methods</topic><topic>Datasets</topic><topic>Diagnosis</topic><topic>E-cadherin</topic><topic>Enrichment</topic><topic>Female</topic><topic>GATA-3 protein</topic><topic>Gene Expression Regulation, Neoplastic - genetics</topic><topic>Gene mutations</topic><topic>Gene set enrichment analysis</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genomes</topic><topic>Health aspects</topic><topic>Humans</topic><topic>Immune response</topic><topic>Immune system</topic><topic>Immunological memory</topic><topic>Immunotherapy</topic><topic>Immunotherapy - methods</topic><topic>Kaplan-Meier Estimate</topic><topic>Lung cancer</topic><topic>Lymphocytes</topic><topic>Lymphocytes T</topic><topic>Macrophages</topic><topic>Medical prognosis</topic><topic>Melanoma</topic><topic>Memory cells</topic><topic>Mutation</topic><topic>Mutation - genetics</topic><topic>p53 Protein</topic><topic>Patient outcomes</topic><topic>Prognosis</topic><topic>PTEN protein</topic><topic>Radiation therapy</topic><topic>Regression analysis</topic><topic>Regulatory mechanisms (biology)</topic><topic>Risk factors</topic><topic>Ryanodine Receptor Calcium Release Channel - genetics</topic><topic>Ryanodine receptors</topic><topic>Signal Transduction - genetics</topic><topic>Software</topic><topic>Survival analysis</topic><topic>Tumor-infiltrating lymphocytes</topic><topic>Tumors</topic><topic>USH2A protein</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Zhiquan</creatorcontrib><creatorcontrib>Xiang, Ling</creatorcontrib><creatorcontrib>Wang, Rong</creatorcontrib><creatorcontrib>Xiong, Yongfu</creatorcontrib><creatorcontrib>Zhou, He</creatorcontrib><creatorcontrib>Gu, Haitao</creatorcontrib><creatorcontrib>Wang, Jijian</creatorcontrib><creatorcontrib>Peng, Linglong</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</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>Xu, Zhiquan</au><au>Xiang, Ling</au><au>Wang, Rong</au><au>Xiong, Yongfu</au><au>Zhou, He</au><au>Gu, Haitao</au><au>Wang, Jijian</au><au>Peng, Linglong</au><au>Fang, Yujiang</au><au>Yujiang Fang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer</atitle><jtitle>BioMed research international</jtitle><addtitle>Biomed Res Int</addtitle><date>2021-11-03</date><risdate>2021</risdate><volume>2021</volume><spage>8072796</spage><epage>12</epage><pages>8072796-12</pages><issn>2314-6133</issn><issn>2314-6141</issn><eissn>2314-6141</eissn><abstract>Background. Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood. Methods. Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions. Results. We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages. Conclusion. RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>34888385</pmid><doi>10.1155/2021/8072796</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-5774-3110</orcidid><orcidid>https://orcid.org/0000-0003-1694-333X</orcidid><orcidid>https://orcid.org/0000-0001-8323-9903</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Aged Algorithms Analysis Antitumor activity Biomarkers Biomarkers, Tumor - genetics Breast cancer Breast Neoplasms - genetics Cancer Cancer therapies Care and treatment CD4 antigen CD8 antigen Chemotherapy Computational Biology - methods Datasets Diagnosis E-cadherin Enrichment Female GATA-3 protein Gene Expression Regulation, Neoplastic - genetics Gene mutations Gene set enrichment analysis Genes Genetic aspects Genomes Health aspects Humans Immune response Immune system Immunological memory Immunotherapy Immunotherapy - methods Kaplan-Meier Estimate Lung cancer Lymphocytes Lymphocytes T Macrophages Medical prognosis Melanoma Memory cells Mutation Mutation - genetics p53 Protein Patient outcomes Prognosis PTEN protein Radiation therapy Regression analysis Regulatory mechanisms (biology) Risk factors Ryanodine Receptor Calcium Release Channel - genetics Ryanodine receptors Signal Transduction - genetics Software Survival analysis Tumor-infiltrating lymphocytes Tumors USH2A protein |
| title | Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T04%3A10%3A09IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Bioinformatic%20Analysis%20of%20Immune%20Significance%20of%20RYR2%20Mutation%20in%20Breast%20Cancer&rft.jtitle=BioMed%20research%20international&rft.au=Xu,%20Zhiquan&rft.date=2021-11-03&rft.volume=2021&rft.spage=8072796&rft.epage=12&rft.pages=8072796-12&rft.issn=2314-6133&rft.eissn=2314-6141&rft_id=info:doi/10.1155/2021/8072796&rft_dat=%3Cgale_pubme%3EA696966936%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2609152648&rft_id=info:pmid/34888385&rft_galeid=A696966936&rfr_iscdi=true |