The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment
Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tiss...
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| Veröffentlicht in: | BMC pulmonary medicine 2021-12, Vol.21 (1), p.400-400, Article 400 |
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| creator | Wang, Gongjun Qi, Weiwei Shen, Liwei Wang, Shasha Xiao, Ruoxi Li, Wenqian Zhang, Yuqi Bian, Xiaoqian Sun, Libin Qiu, Wensheng |
| description | Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets. |
| doi_str_mv | 10.1186/s12890-021-01776-0 |
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Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.</description><identifier>ISSN: 1471-2466</identifier><identifier>EISSN: 1471-2466</identifier><identifier>DOI: 10.1186/s12890-021-01776-0</identifier><identifier>PMID: 34872548</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Adenocarcinoma ; Adenocarcinoma of Lung - genetics ; Adenocarcinoma of Lung - immunology ; Adenocarcinoma of Lung - mortality ; Adenocarcinoma of Lung - pathology ; Algorithms ; Alternative splicing ; Alternative Splicing - genetics ; Alternative Splicing - immunology ; Bioinformatics ; Biomarkers, Tumor - analysis ; Biomarkers, Tumor - genetics ; Biomarkers, Tumor - immunology ; Cancer ; Carcinogenesis ; China ; Databases, Genetic ; Development and progression ; Disease-Free Survival ; Drug development ; Gene expression ; Genetic aspects ; Genomes ; Humans ; Immune ; Immunology ; Immunosuppressive agents ; LUAD ; Lung cancer ; Lung Neoplasms - genetics ; Lung Neoplasms - immunology ; Lung Neoplasms - mortality ; Lung Neoplasms - pathology ; Medical prognosis ; Metastases ; Oncology, Experimental ; Prognosis ; Pulmonology ; Risk Assessment - methods ; Risk groups ; RNA splicing ; Survival Rate ; Therapeutic targets ; Tumor microenvironment ; Tumor Microenvironment - genetics ; Tumor Microenvironment - immunology ; Tumorigenesis</subject><ispartof>BMC pulmonary medicine, 2021-12, Vol.21 (1), p.400-400, Article 400</ispartof><rights>2021. The Author(s).</rights><rights>COPYRIGHT 2021 BioMed Central Ltd.</rights><rights>2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c514t-c37c17186f8095bf0a4bd29fcf0c95f44258a2aa5c35a24972984adc70687b133</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8647402/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8647402/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,2096,27905,27906,53772,53774</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34872548$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Gongjun</creatorcontrib><creatorcontrib>Qi, Weiwei</creatorcontrib><creatorcontrib>Shen, Liwei</creatorcontrib><creatorcontrib>Wang, Shasha</creatorcontrib><creatorcontrib>Xiao, Ruoxi</creatorcontrib><creatorcontrib>Li, Wenqian</creatorcontrib><creatorcontrib>Zhang, Yuqi</creatorcontrib><creatorcontrib>Bian, Xiaoqian</creatorcontrib><creatorcontrib>Sun, Libin</creatorcontrib><creatorcontrib>Qiu, Wensheng</creatorcontrib><title>The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment</title><title>BMC pulmonary medicine</title><addtitle>BMC Pulm Med</addtitle><description>Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.</description><subject>Adenocarcinoma</subject><subject>Adenocarcinoma of Lung - genetics</subject><subject>Adenocarcinoma of Lung - immunology</subject><subject>Adenocarcinoma of Lung - mortality</subject><subject>Adenocarcinoma of Lung - pathology</subject><subject>Algorithms</subject><subject>Alternative splicing</subject><subject>Alternative Splicing - genetics</subject><subject>Alternative Splicing - immunology</subject><subject>Bioinformatics</subject><subject>Biomarkers, Tumor - analysis</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biomarkers, Tumor - immunology</subject><subject>Cancer</subject><subject>Carcinogenesis</subject><subject>China</subject><subject>Databases, Genetic</subject><subject>Development and progression</subject><subject>Disease-Free Survival</subject><subject>Drug development</subject><subject>Gene expression</subject><subject>Genetic aspects</subject><subject>Genomes</subject><subject>Humans</subject><subject>Immune</subject><subject>Immunology</subject><subject>Immunosuppressive agents</subject><subject>LUAD</subject><subject>Lung cancer</subject><subject>Lung Neoplasms - genetics</subject><subject>Lung Neoplasms - immunology</subject><subject>Lung Neoplasms - mortality</subject><subject>Lung Neoplasms - pathology</subject><subject>Medical prognosis</subject><subject>Metastases</subject><subject>Oncology, Experimental</subject><subject>Prognosis</subject><subject>Pulmonology</subject><subject>Risk Assessment - methods</subject><subject>Risk groups</subject><subject>RNA splicing</subject><subject>Survival Rate</subject><subject>Therapeutic targets</subject><subject>Tumor microenvironment</subject><subject>Tumor Microenvironment - genetics</subject><subject>Tumor Microenvironment - immunology</subject><subject>Tumorigenesis</subject><issn>1471-2466</issn><issn>1471-2466</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>DOA</sourceid><recordid>eNptUk1v1DAQjRCIlsIf4IAsceGS4s84uSBVFR-VKnEpZ2vijHe9SuzFTrbqL-Bv4-2W0kXIh7HG773xzLyqesvoOWNt8zEz3na0ppzVlGnd1PRZdcqkZjWXTfP8yf2kepXzhhZUq8TL6kTIVnMl29Pq180ayRbmGVMg0REY9zeY_Q5J3o7e-rAiPpBxKREGDNFCKsk4AcnreJtJiDscCe4wzJnYmBKOMONAbv28JvMyxeRXGDD7TCAMxE_TEpBM3qaIYedTDFOhvq5eOBgzvnmIZ9WPL59vLr_V19-_Xl1eXNdWMTnXVmjLdGnetbRTvaMg-4F3zjpqO-Wk5KoFDqCsUMBlp3nXShispk2reybEWXV10B0ibMw2-QnSnYngzX0ippWBNHs7onHYCdGLAcG2UjWi78u4Je873gjhuqFofTpobZd-wsGWNhKMR6LHL8GvzSruTNtILSkvAh8eBFL8uWCezeSzxXGEgHHJhjdUq65A9_9-_w90E5eyqHGPYkwo1Un9F7WC0oAPLpa6di9qLppSlWnRyII6_w-qnAHLWmJA50v-iMAPhLKznBO6xx4ZNXsrmoMVTbGiubeioYX07ul0Hil_vCd-A68Y28I</recordid><startdate>20211206</startdate><enddate>20211206</enddate><creator>Wang, Gongjun</creator><creator>Qi, Weiwei</creator><creator>Shen, Liwei</creator><creator>Wang, Shasha</creator><creator>Xiao, Ruoxi</creator><creator>Li, Wenqian</creator><creator>Zhang, Yuqi</creator><creator>Bian, Xiaoqian</creator><creator>Sun, Libin</creator><creator>Qiu, Wensheng</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><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>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20211206</creationdate><title>The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment</title><author>Wang, Gongjun ; Qi, Weiwei ; Shen, Liwei ; Wang, Shasha ; Xiao, Ruoxi ; Li, Wenqian ; Zhang, Yuqi ; Bian, Xiaoqian ; Sun, Libin ; Qiu, Wensheng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c514t-c37c17186f8095bf0a4bd29fcf0c95f44258a2aa5c35a24972984adc70687b133</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adenocarcinoma</topic><topic>Adenocarcinoma of Lung - genetics</topic><topic>Adenocarcinoma of Lung - immunology</topic><topic>Adenocarcinoma of Lung - mortality</topic><topic>Adenocarcinoma of Lung - pathology</topic><topic>Algorithms</topic><topic>Alternative splicing</topic><topic>Alternative Splicing - genetics</topic><topic>Alternative Splicing - immunology</topic><topic>Bioinformatics</topic><topic>Biomarkers, Tumor - analysis</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Biomarkers, Tumor - immunology</topic><topic>Cancer</topic><topic>Carcinogenesis</topic><topic>China</topic><topic>Databases, Genetic</topic><topic>Development and progression</topic><topic>Disease-Free Survival</topic><topic>Drug development</topic><topic>Gene expression</topic><topic>Genetic aspects</topic><topic>Genomes</topic><topic>Humans</topic><topic>Immune</topic><topic>Immunology</topic><topic>Immunosuppressive agents</topic><topic>LUAD</topic><topic>Lung cancer</topic><topic>Lung Neoplasms - genetics</topic><topic>Lung Neoplasms - immunology</topic><topic>Lung Neoplasms - mortality</topic><topic>Lung Neoplasms - pathology</topic><topic>Medical prognosis</topic><topic>Metastases</topic><topic>Oncology, Experimental</topic><topic>Prognosis</topic><topic>Pulmonology</topic><topic>Risk Assessment - methods</topic><topic>Risk groups</topic><topic>RNA splicing</topic><topic>Survival Rate</topic><topic>Therapeutic targets</topic><topic>Tumor microenvironment</topic><topic>Tumor Microenvironment - genetics</topic><topic>Tumor Microenvironment - immunology</topic><topic>Tumorigenesis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Gongjun</creatorcontrib><creatorcontrib>Qi, Weiwei</creatorcontrib><creatorcontrib>Shen, Liwei</creatorcontrib><creatorcontrib>Wang, Shasha</creatorcontrib><creatorcontrib>Xiao, Ruoxi</creatorcontrib><creatorcontrib>Li, Wenqian</creatorcontrib><creatorcontrib>Zhang, Yuqi</creatorcontrib><creatorcontrib>Bian, Xiaoqian</creatorcontrib><creatorcontrib>Sun, Libin</creatorcontrib><creatorcontrib>Qiu, Wensheng</creatorcontrib><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>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</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>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</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><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC pulmonary medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Gongjun</au><au>Qi, Weiwei</au><au>Shen, Liwei</au><au>Wang, Shasha</au><au>Xiao, Ruoxi</au><au>Li, Wenqian</au><au>Zhang, Yuqi</au><au>Bian, Xiaoqian</au><au>Sun, Libin</au><au>Qiu, Wensheng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment</atitle><jtitle>BMC pulmonary medicine</jtitle><addtitle>BMC Pulm Med</addtitle><date>2021-12-06</date><risdate>2021</risdate><volume>21</volume><issue>1</issue><spage>400</spage><epage>400</epage><pages>400-400</pages><artnum>400</artnum><issn>1471-2466</issn><eissn>1471-2466</eissn><abstract>Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>34872548</pmid><doi>10.1186/s12890-021-01776-0</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Adenocarcinoma Adenocarcinoma of Lung - genetics Adenocarcinoma of Lung - immunology Adenocarcinoma of Lung - mortality Adenocarcinoma of Lung - pathology Algorithms Alternative splicing Alternative Splicing - genetics Alternative Splicing - immunology Bioinformatics Biomarkers, Tumor - analysis Biomarkers, Tumor - genetics Biomarkers, Tumor - immunology Cancer Carcinogenesis China Databases, Genetic Development and progression Disease-Free Survival Drug development Gene expression Genetic aspects Genomes Humans Immune Immunology Immunosuppressive agents LUAD Lung cancer Lung Neoplasms - genetics Lung Neoplasms - immunology Lung Neoplasms - mortality Lung Neoplasms - pathology Medical prognosis Metastases Oncology, Experimental Prognosis Pulmonology Risk Assessment - methods Risk groups RNA splicing Survival Rate Therapeutic targets Tumor microenvironment Tumor Microenvironment - genetics Tumor Microenvironment - immunology Tumorigenesis |
| title | The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment |
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