Decoding the multicellular ecosystem of lung adenocarcinoma manifested as pulmonary subsolid nodules by single-cell RNA sequencing
Lung adenocarcinomas (LUAD) that radiologically display as subsolid nodules (SSNs) exhibit more indolent biological behavior than solid LUAD. The transcriptomic features and tumor microenvironment (TME) of SSN remain poorly understood. Here, we performed single-cell RNA sequencing analyses of 16 SSN...
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description | Lung adenocarcinomas (LUAD) that radiologically display as subsolid nodules (SSNs) exhibit more indolent biological behavior than solid LUAD. The transcriptomic features and tumor microenvironment (TME) of SSN remain poorly understood. Here, we performed single-cell RNA sequencing analyses of 16 SSN samples, 6 adjacent normal lung tissues (nLung), and 9 primary LUAD with lymph node metastasis (mLUAD). Approximately 0.6 billion unique transcripts were obtained from 118,293 cells. We found that cytotoxic natural killer/T cells were dominant in the TME of SSN, and malignant cells in SSN undergo a strong metabolic reprogram and immune stress. In SSN, the subtype composition of endothelial cells was similar to that in mLUAD, while the subtype distribution of fibroblasts was more like that in nLung. Our study provides single-cell transcriptomic profiling of SSN and their TME. This resource provides deeper insight into the indolent nature of SSN and will be helpful in advancing lung cancer immunotherapy. |
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The transcriptomic features and tumor microenvironment (TME) of SSN remain poorly understood. Here, we performed single-cell RNA sequencing analyses of 16 SSN samples, 6 adjacent normal lung tissues (nLung), and 9 primary LUAD with lymph node metastasis (mLUAD). Approximately 0.6 billion unique transcripts were obtained from 118,293 cells. We found that cytotoxic natural killer/T cells were dominant in the TME of SSN, and malignant cells in SSN undergo a strong metabolic reprogram and immune stress. In SSN, the subtype composition of endothelial cells was similar to that in mLUAD, while the subtype distribution of fibroblasts was more like that in nLung. Our study provides single-cell transcriptomic profiling of SSN and their TME. This resource provides deeper insight into the indolent nature of SSN and will be helpful in advancing lung cancer immunotherapy.</description><identifier>ISSN: 2375-2548</identifier><identifier>EISSN: 2375-2548</identifier><identifier>DOI: 10.1126/sciadv.abd9738</identifier><identifier>PMID: 33571124</identifier><language>eng</language><publisher>United States: American Association for the Advancement of Science</publisher><subject>Adenocarcinoma of Lung - genetics ; Adenocarcinoma of Lung - pathology ; Cancer ; Ecosystem ; Endothelial Cells - pathology ; Humans ; Lung Neoplasms - genetics ; Lung Neoplasms - pathology ; SciAdv r-articles ; Sequence Analysis, RNA ; Systems Biology ; Tomography, X-Ray Computed ; Tumor Microenvironment - genetics</subject><ispartof>Science advances, 2021-01, Vol.7 (5)</ispartof><rights>Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. 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Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). 2021 The Authors</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c456t-3aba1161fdd35f5a3d2bcc7abfd4d0f941efe623ff7d94514a873747a065688f3</citedby><cites>FETCH-LOGICAL-c456t-3aba1161fdd35f5a3d2bcc7abfd4d0f941efe623ff7d94514a873747a065688f3</cites><orcidid>0000-0002-0419-9139 ; 0000-0003-0681-9378 ; 0000-0002-1044-7821 ; 0000-0001-6119-8936 ; 0000-0001-8214-1605</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/PMC7840134/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840134/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33571124$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xing, Xudong</creatorcontrib><creatorcontrib>Yang, Fan</creatorcontrib><creatorcontrib>Huang, Qi</creatorcontrib><creatorcontrib>Guo, Haifa</creatorcontrib><creatorcontrib>Li, Jiawei</creatorcontrib><creatorcontrib>Qiu, Mantang</creatorcontrib><creatorcontrib>Bai, Fan</creatorcontrib><creatorcontrib>Wang, Jun</creatorcontrib><title>Decoding the multicellular ecosystem of lung adenocarcinoma manifested as pulmonary subsolid nodules by single-cell RNA sequencing</title><title>Science advances</title><addtitle>Sci Adv</addtitle><description>Lung adenocarcinomas (LUAD) that radiologically display as subsolid nodules (SSNs) exhibit more indolent biological behavior than solid LUAD. The transcriptomic features and tumor microenvironment (TME) of SSN remain poorly understood. Here, we performed single-cell RNA sequencing analyses of 16 SSN samples, 6 adjacent normal lung tissues (nLung), and 9 primary LUAD with lymph node metastasis (mLUAD). Approximately 0.6 billion unique transcripts were obtained from 118,293 cells. We found that cytotoxic natural killer/T cells were dominant in the TME of SSN, and malignant cells in SSN undergo a strong metabolic reprogram and immune stress. In SSN, the subtype composition of endothelial cells was similar to that in mLUAD, while the subtype distribution of fibroblasts was more like that in nLung. Our study provides single-cell transcriptomic profiling of SSN and their TME. This resource provides deeper insight into the indolent nature of SSN and will be helpful in advancing lung cancer immunotherapy.</description><subject>Adenocarcinoma of Lung - genetics</subject><subject>Adenocarcinoma of Lung - pathology</subject><subject>Cancer</subject><subject>Ecosystem</subject><subject>Endothelial Cells - pathology</subject><subject>Humans</subject><subject>Lung Neoplasms - genetics</subject><subject>Lung Neoplasms - pathology</subject><subject>SciAdv r-articles</subject><subject>Sequence Analysis, RNA</subject><subject>Systems Biology</subject><subject>Tomography, X-Ray Computed</subject><subject>Tumor Microenvironment - genetics</subject><issn>2375-2548</issn><issn>2375-2548</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVkc1v3CAQxVHVqImSXHusOPbirTFg7EulKE0_pKiVovSMxjBsqDBsjYmUa__ystptlJ5AzOM3b-YR8pa1G8a6_kM2HuzjBiY7Kj68ImcdV7LppBhev7ifksucf7Vty0TfSza-IaecS1UJ4oz8-YQmWR-3dH1AOpeweoMhlAALrZX8lFecaXI0lKoBizEZWIyPaQY6Q_QOq8JSyHRXwpwiLE80lymn4C2NyZaAmU71rfYI2Ozh9O77Fc34u2CsoO0FOXEQMl4ez3Py8_PN_fXX5vbHl2_XV7eNEbJfGw4TMNYzZy2XTgK33WSMgslZYVs3CoYO-447p-woJBMwKK6EgraX_TA4fk4-Hri7Ms1oDcZ1gaB3i5-raZ3A6_8r0T_obXrUahAt46IC3h8BS6rm86pnn_cDQcRUsu7EMHaiLnas0s1BapaU84LuuQ1r9T47fchOH7OrH969NPcs_5cU_wuwTJv7</recordid><startdate>20210101</startdate><enddate>20210101</enddate><creator>Xing, Xudong</creator><creator>Yang, Fan</creator><creator>Huang, Qi</creator><creator>Guo, Haifa</creator><creator>Li, Jiawei</creator><creator>Qiu, Mantang</creator><creator>Bai, Fan</creator><creator>Wang, Jun</creator><general>American Association for the Advancement of Science</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>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-0419-9139</orcidid><orcidid>https://orcid.org/0000-0003-0681-9378</orcidid><orcidid>https://orcid.org/0000-0002-1044-7821</orcidid><orcidid>https://orcid.org/0000-0001-6119-8936</orcidid><orcidid>https://orcid.org/0000-0001-8214-1605</orcidid></search><sort><creationdate>20210101</creationdate><title>Decoding the multicellular ecosystem of lung adenocarcinoma manifested as pulmonary subsolid nodules by single-cell RNA sequencing</title><author>Xing, Xudong ; Yang, Fan ; Huang, Qi ; Guo, Haifa ; Li, Jiawei ; Qiu, Mantang ; Bai, Fan ; Wang, Jun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c456t-3aba1161fdd35f5a3d2bcc7abfd4d0f941efe623ff7d94514a873747a065688f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adenocarcinoma of Lung - genetics</topic><topic>Adenocarcinoma of Lung - pathology</topic><topic>Cancer</topic><topic>Ecosystem</topic><topic>Endothelial Cells - pathology</topic><topic>Humans</topic><topic>Lung Neoplasms - genetics</topic><topic>Lung Neoplasms - pathology</topic><topic>SciAdv r-articles</topic><topic>Sequence Analysis, RNA</topic><topic>Systems Biology</topic><topic>Tomography, X-Ray Computed</topic><topic>Tumor Microenvironment - genetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xing, Xudong</creatorcontrib><creatorcontrib>Yang, Fan</creatorcontrib><creatorcontrib>Huang, Qi</creatorcontrib><creatorcontrib>Guo, Haifa</creatorcontrib><creatorcontrib>Li, Jiawei</creatorcontrib><creatorcontrib>Qiu, Mantang</creatorcontrib><creatorcontrib>Bai, Fan</creatorcontrib><creatorcontrib>Wang, Jun</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Science advances</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xing, Xudong</au><au>Yang, Fan</au><au>Huang, Qi</au><au>Guo, Haifa</au><au>Li, Jiawei</au><au>Qiu, Mantang</au><au>Bai, Fan</au><au>Wang, Jun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Decoding the multicellular ecosystem of lung adenocarcinoma manifested as pulmonary subsolid nodules by single-cell RNA sequencing</atitle><jtitle>Science advances</jtitle><addtitle>Sci Adv</addtitle><date>2021-01-01</date><risdate>2021</risdate><volume>7</volume><issue>5</issue><issn>2375-2548</issn><eissn>2375-2548</eissn><abstract>Lung adenocarcinomas (LUAD) that radiologically display as subsolid nodules (SSNs) exhibit more indolent biological behavior than solid LUAD. The transcriptomic features and tumor microenvironment (TME) of SSN remain poorly understood. Here, we performed single-cell RNA sequencing analyses of 16 SSN samples, 6 adjacent normal lung tissues (nLung), and 9 primary LUAD with lymph node metastasis (mLUAD). Approximately 0.6 billion unique transcripts were obtained from 118,293 cells. We found that cytotoxic natural killer/T cells were dominant in the TME of SSN, and malignant cells in SSN undergo a strong metabolic reprogram and immune stress. In SSN, the subtype composition of endothelial cells was similar to that in mLUAD, while the subtype distribution of fibroblasts was more like that in nLung. Our study provides single-cell transcriptomic profiling of SSN and their TME. 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subjects | Adenocarcinoma of Lung - genetics Adenocarcinoma of Lung - pathology Cancer Ecosystem Endothelial Cells - pathology Humans Lung Neoplasms - genetics Lung Neoplasms - pathology SciAdv r-articles Sequence Analysis, RNA Systems Biology Tomography, X-Ray Computed Tumor Microenvironment - genetics |
title | Decoding the multicellular ecosystem of lung adenocarcinoma manifested as pulmonary subsolid nodules by single-cell RNA sequencing |
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