Comprehensive Analysis of Tumor-Infiltrating Immune Cells and Relevant Therapeutic Strategy in Esophageal Cancer
A growing body of evidence has indicated that behaviors of cancers are defined by not only intrinsic activities of tumor cells but also tumor-infiltrating immune cells (TIICs) in the tumor microenvironment. However, it still lacks a well-structured and comprehensive analysis of TIICs and its therape...
Gespeichert in:
| Veröffentlicht in: | Disease markers 2020, Vol.2020 (2020), p.1-12 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 12 |
|---|---|
| container_issue | 2020 |
| container_start_page | 1 |
| container_title | Disease markers |
| container_volume | 2020 |
| creator | Feng, Yuao Wu, Shengjie Chen, Liping Lu, Guangrong Lin, Tiesu |
| description | A growing body of evidence has indicated that behaviors of cancers are defined by not only intrinsic activities of tumor cells but also tumor-infiltrating immune cells (TIICs) in the tumor microenvironment. However, it still lacks a well-structured and comprehensive analysis of TIICs and its therapeutic value in esophageal cancer (EC). The proportions of 22 TIICs were evaluated between 150 normal tissues and 141 tumor tissues of EC by the CIBERSORT algorithm. Besides, correlation analyses between proportions of TIICs and clinicopathological characters, including age, gender, histologic grade, tumor location, histologic type, LRP1B mutation, TP53 mutation, tumor stage, lymph node stage, and TNM stage, were conducted. We constructed a risk score model to improve prognostic capacity with 5 TIICs by least absolute shrinkage and selection operator (lasso) regression analysis. The risk score=−1.86∗plasma+2.56∗T cell follicular helper−1.37∗monocytes−3.64∗activated dendritic cells−2.24∗resting mast cells (immune cells in the risk model mean the proportions of immune cell infiltration in EC). Patients in the high-risk group had significantly worse overall survival than these in the low-risk group (HR: 2.146, 95% CI: 1.243-3.705, p=0.0061). Finally, we identified Semustine and Sirolimus as two candidate compounds for the treatment of EC based on CMap analysis. In conclusion, the proportions of TIICs may be important to the progression, prognosis, and treatment of EC. |
| doi_str_mv | 10.1155/2020/8974793 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7238334</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A627689536</galeid><sourcerecordid>A627689536</sourcerecordid><originalsourceid>FETCH-LOGICAL-c499t-584b8f742d08a70cf96837f34d0a66566eca685213b234b349527027639ee5143</originalsourceid><addsrcrecordid>eNqN0c-L1DAUB_Agijuu3jxLwKPWTfM7F2Eoqw4sCDqeQ6Z97WRp05q0I_Pfm2HGXb15yuF9-PLyvgi9LsmHshTihhJKbrRRXBn2BK1KrUShJSNP0YpQpQtCOblCL1K6J6Skhpvn6IpRLrgheoWmahymCHsIyR8Ar4Prj8knPLZ4uwxjLDah9f0c3exDhzfDsATAFfR9wi40-Bv0cHBhxts9RDfBMvsafz9x6I7YB3ybxmnvOnA9rlyoIb5Ez1rXJ3h1ea_Rj0-32-pLcff186Za3xU1N2YuhOY73SpOG6KdInVrpGaqZbwhTkohJdROakFLtqOM7xg3gqr8X8kMgCg5u0Yfz7nTshugqSHkrXo7RT-4eLSj8_bfSfB7240HqyjTjJ0C3l4C4vhzgTTb-3GJ-T7J5otKqqgw6lF1rgfrQzvmsHrwqbbrbKQ2gsms3p9VHceUIrQPe5TEnlq0pxbtpcXM3_y9-wP-U1sG785g70Pjfvn_jINsoHWPuhScEs5-AwWerf8</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2406272597</pqid></control><display><type>article</type><title>Comprehensive Analysis of Tumor-Infiltrating Immune Cells and Relevant Therapeutic Strategy in Esophageal Cancer</title><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Wiley Online Library Open Access</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Feng, Yuao ; Wu, Shengjie ; Chen, Liping ; Lu, Guangrong ; Lin, Tiesu</creator><contributor>Knaś, Małgorzata ; Małgorzata Knaś</contributor><creatorcontrib>Feng, Yuao ; Wu, Shengjie ; Chen, Liping ; Lu, Guangrong ; Lin, Tiesu ; Knaś, Małgorzata ; Małgorzata Knaś</creatorcontrib><description>A growing body of evidence has indicated that behaviors of cancers are defined by not only intrinsic activities of tumor cells but also tumor-infiltrating immune cells (TIICs) in the tumor microenvironment. However, it still lacks a well-structured and comprehensive analysis of TIICs and its therapeutic value in esophageal cancer (EC). The proportions of 22 TIICs were evaluated between 150 normal tissues and 141 tumor tissues of EC by the CIBERSORT algorithm. Besides, correlation analyses between proportions of TIICs and clinicopathological characters, including age, gender, histologic grade, tumor location, histologic type, LRP1B mutation, TP53 mutation, tumor stage, lymph node stage, and TNM stage, were conducted. We constructed a risk score model to improve prognostic capacity with 5 TIICs by least absolute shrinkage and selection operator (lasso) regression analysis. The risk score=−1.86∗plasma+2.56∗T cell follicular helper−1.37∗monocytes−3.64∗activated dendritic cells−2.24∗resting mast cells (immune cells in the risk model mean the proportions of immune cell infiltration in EC). Patients in the high-risk group had significantly worse overall survival than these in the low-risk group (HR: 2.146, 95% CI: 1.243-3.705, p=0.0061). Finally, we identified Semustine and Sirolimus as two candidate compounds for the treatment of EC based on CMap analysis. In conclusion, the proportions of TIICs may be important to the progression, prognosis, and treatment of EC.</description><identifier>ISSN: 0278-0240</identifier><identifier>EISSN: 1875-8630</identifier><identifier>DOI: 10.1155/2020/8974793</identifier><identifier>PMID: 32454908</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Adult ; Algorithms ; Analysis ; Antineoplastic Agents - therapeutic use ; Atrophy ; B cells ; Cancer ; Cancer therapies ; Cell Count ; Connectivity ; Correlation analysis ; Databases, Factual ; Dendritic cells ; Dendritic Cells - drug effects ; Dendritic Cells - immunology ; Dendritic Cells - pathology ; Esophageal cancer ; Esophageal Neoplasms - diagnosis ; Esophageal Neoplasms - drug therapy ; Esophageal Neoplasms - immunology ; Esophageal Neoplasms - mortality ; Esophagus ; Female ; Gender ; Gene Expression ; Genes ; Health aspects ; Humans ; Immune system ; Lymph nodes ; Lymph Nodes - drug effects ; Lymph Nodes - immunology ; Lymph Nodes - pathology ; Lymphocytes ; Lymphocytes T ; Lymphocytes, Tumor-Infiltrating - drug effects ; Lymphocytes, Tumor-Infiltrating - immunology ; Lymphocytes, Tumor-Infiltrating - pathology ; Male ; Mast cells ; Mast Cells - drug effects ; Mast Cells - immunology ; Mast Cells - pathology ; Medical prognosis ; Metastases ; Middle Aged ; Monocytes ; Monocytes - drug effects ; Monocytes - immunology ; Monocytes - pathology ; Mutation ; Neoplasm Staging ; p53 Protein ; Plasma Cells - drug effects ; Plasma Cells - immunology ; Plasma Cells - pathology ; Prognosis ; Rapamycin ; Receptors, LDL - genetics ; Receptors, LDL - immunology ; Regression Analysis ; Risk analysis ; Risk groups ; Semustine - therapeutic use ; Sirolimus - therapeutic use ; Survival Analysis ; T cells ; T Follicular Helper Cells - drug effects ; T Follicular Helper Cells - immunology ; T Follicular Helper Cells - pathology ; Tumor cells ; Tumor Microenvironment - drug effects ; Tumor Microenvironment - genetics ; Tumor Microenvironment - immunology ; Tumor proteins ; Tumor Suppressor Protein p53 - genetics ; Tumor Suppressor Protein p53 - immunology ; Tumor-infiltrating lymphocytes ; Tumors</subject><ispartof>Disease markers, 2020, Vol.2020 (2020), p.1-12</ispartof><rights>Copyright © 2020 Guangrong Lu et al.</rights><rights>COPYRIGHT 2020 John Wiley & Sons, Inc.</rights><rights>Copyright © 2020 Guangrong Lu 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. http://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2020 Guangrong Lu et al. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c499t-584b8f742d08a70cf96837f34d0a66566eca685213b234b349527027639ee5143</citedby><cites>FETCH-LOGICAL-c499t-584b8f742d08a70cf96837f34d0a66566eca685213b234b349527027639ee5143</cites><orcidid>0000-0001-6087-7355</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/PMC7238334/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7238334/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,4009,27902,27903,27904,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32454908$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Knaś, Małgorzata</contributor><contributor>Małgorzata Knaś</contributor><creatorcontrib>Feng, Yuao</creatorcontrib><creatorcontrib>Wu, Shengjie</creatorcontrib><creatorcontrib>Chen, Liping</creatorcontrib><creatorcontrib>Lu, Guangrong</creatorcontrib><creatorcontrib>Lin, Tiesu</creatorcontrib><title>Comprehensive Analysis of Tumor-Infiltrating Immune Cells and Relevant Therapeutic Strategy in Esophageal Cancer</title><title>Disease markers</title><addtitle>Dis Markers</addtitle><description>A growing body of evidence has indicated that behaviors of cancers are defined by not only intrinsic activities of tumor cells but also tumor-infiltrating immune cells (TIICs) in the tumor microenvironment. However, it still lacks a well-structured and comprehensive analysis of TIICs and its therapeutic value in esophageal cancer (EC). The proportions of 22 TIICs were evaluated between 150 normal tissues and 141 tumor tissues of EC by the CIBERSORT algorithm. Besides, correlation analyses between proportions of TIICs and clinicopathological characters, including age, gender, histologic grade, tumor location, histologic type, LRP1B mutation, TP53 mutation, tumor stage, lymph node stage, and TNM stage, were conducted. We constructed a risk score model to improve prognostic capacity with 5 TIICs by least absolute shrinkage and selection operator (lasso) regression analysis. The risk score=−1.86∗plasma+2.56∗T cell follicular helper−1.37∗monocytes−3.64∗activated dendritic cells−2.24∗resting mast cells (immune cells in the risk model mean the proportions of immune cell infiltration in EC). Patients in the high-risk group had significantly worse overall survival than these in the low-risk group (HR: 2.146, 95% CI: 1.243-3.705, p=0.0061). Finally, we identified Semustine and Sirolimus as two candidate compounds for the treatment of EC based on CMap analysis. In conclusion, the proportions of TIICs may be important to the progression, prognosis, and treatment of EC.</description><subject>Adult</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Antineoplastic Agents - therapeutic use</subject><subject>Atrophy</subject><subject>B cells</subject><subject>Cancer</subject><subject>Cancer therapies</subject><subject>Cell Count</subject><subject>Connectivity</subject><subject>Correlation analysis</subject><subject>Databases, Factual</subject><subject>Dendritic cells</subject><subject>Dendritic Cells - drug effects</subject><subject>Dendritic Cells - immunology</subject><subject>Dendritic Cells - pathology</subject><subject>Esophageal cancer</subject><subject>Esophageal Neoplasms - diagnosis</subject><subject>Esophageal Neoplasms - drug therapy</subject><subject>Esophageal Neoplasms - immunology</subject><subject>Esophageal Neoplasms - mortality</subject><subject>Esophagus</subject><subject>Female</subject><subject>Gender</subject><subject>Gene Expression</subject><subject>Genes</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Immune system</subject><subject>Lymph nodes</subject><subject>Lymph Nodes - drug effects</subject><subject>Lymph Nodes - immunology</subject><subject>Lymph Nodes - pathology</subject><subject>Lymphocytes</subject><subject>Lymphocytes T</subject><subject>Lymphocytes, Tumor-Infiltrating - drug effects</subject><subject>Lymphocytes, Tumor-Infiltrating - immunology</subject><subject>Lymphocytes, Tumor-Infiltrating - pathology</subject><subject>Male</subject><subject>Mast cells</subject><subject>Mast Cells - drug effects</subject><subject>Mast Cells - immunology</subject><subject>Mast Cells - pathology</subject><subject>Medical prognosis</subject><subject>Metastases</subject><subject>Middle Aged</subject><subject>Monocytes</subject><subject>Monocytes - drug effects</subject><subject>Monocytes - immunology</subject><subject>Monocytes - pathology</subject><subject>Mutation</subject><subject>Neoplasm Staging</subject><subject>p53 Protein</subject><subject>Plasma Cells - drug effects</subject><subject>Plasma Cells - immunology</subject><subject>Plasma Cells - pathology</subject><subject>Prognosis</subject><subject>Rapamycin</subject><subject>Receptors, LDL - genetics</subject><subject>Receptors, LDL - immunology</subject><subject>Regression Analysis</subject><subject>Risk analysis</subject><subject>Risk groups</subject><subject>Semustine - therapeutic use</subject><subject>Sirolimus - therapeutic use</subject><subject>Survival Analysis</subject><subject>T cells</subject><subject>T Follicular Helper Cells - drug effects</subject><subject>T Follicular Helper Cells - immunology</subject><subject>T Follicular Helper Cells - pathology</subject><subject>Tumor cells</subject><subject>Tumor Microenvironment - drug effects</subject><subject>Tumor Microenvironment - genetics</subject><subject>Tumor Microenvironment - immunology</subject><subject>Tumor proteins</subject><subject>Tumor Suppressor Protein p53 - genetics</subject><subject>Tumor Suppressor Protein p53 - immunology</subject><subject>Tumor-infiltrating lymphocytes</subject><subject>Tumors</subject><issn>0278-0240</issn><issn>1875-8630</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><recordid>eNqN0c-L1DAUB_Agijuu3jxLwKPWTfM7F2Eoqw4sCDqeQ6Z97WRp05q0I_Pfm2HGXb15yuF9-PLyvgi9LsmHshTihhJKbrRRXBn2BK1KrUShJSNP0YpQpQtCOblCL1K6J6Skhpvn6IpRLrgheoWmahymCHsIyR8Ar4Prj8knPLZ4uwxjLDah9f0c3exDhzfDsATAFfR9wi40-Bv0cHBhxts9RDfBMvsafz9x6I7YB3ybxmnvOnA9rlyoIb5Ez1rXJ3h1ea_Rj0-32-pLcff186Za3xU1N2YuhOY73SpOG6KdInVrpGaqZbwhTkohJdROakFLtqOM7xg3gqr8X8kMgCg5u0Yfz7nTshugqSHkrXo7RT-4eLSj8_bfSfB7240HqyjTjJ0C3l4C4vhzgTTb-3GJ-T7J5otKqqgw6lF1rgfrQzvmsHrwqbbrbKQ2gsms3p9VHceUIrQPe5TEnlq0pxbtpcXM3_y9-wP-U1sG785g70Pjfvn_jINsoHWPuhScEs5-AwWerf8</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Feng, Yuao</creator><creator>Wu, Shengjie</creator><creator>Chen, Liping</creator><creator>Lu, Guangrong</creator><creator>Lin, Tiesu</creator><general>Hindawi Publishing Corporation</general><general>Hindawi</general><general>John Wiley & Sons, Inc</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><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>7QL</scope><scope>7QO</scope><scope>7TK</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-6087-7355</orcidid></search><sort><creationdate>2020</creationdate><title>Comprehensive Analysis of Tumor-Infiltrating Immune Cells and Relevant Therapeutic Strategy in Esophageal Cancer</title><author>Feng, Yuao ; Wu, Shengjie ; Chen, Liping ; Lu, Guangrong ; Lin, Tiesu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c499t-584b8f742d08a70cf96837f34d0a66566eca685213b234b349527027639ee5143</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adult</topic><topic>Algorithms</topic><topic>Analysis</topic><topic>Antineoplastic Agents - therapeutic use</topic><topic>Atrophy</topic><topic>B cells</topic><topic>Cancer</topic><topic>Cancer therapies</topic><topic>Cell Count</topic><topic>Connectivity</topic><topic>Correlation analysis</topic><topic>Databases, Factual</topic><topic>Dendritic cells</topic><topic>Dendritic Cells - drug effects</topic><topic>Dendritic Cells - immunology</topic><topic>Dendritic Cells - pathology</topic><topic>Esophageal cancer</topic><topic>Esophageal Neoplasms - diagnosis</topic><topic>Esophageal Neoplasms - drug therapy</topic><topic>Esophageal Neoplasms - immunology</topic><topic>Esophageal Neoplasms - mortality</topic><topic>Esophagus</topic><topic>Female</topic><topic>Gender</topic><topic>Gene Expression</topic><topic>Genes</topic><topic>Health aspects</topic><topic>Humans</topic><topic>Immune system</topic><topic>Lymph nodes</topic><topic>Lymph Nodes - drug effects</topic><topic>Lymph Nodes - immunology</topic><topic>Lymph Nodes - pathology</topic><topic>Lymphocytes</topic><topic>Lymphocytes T</topic><topic>Lymphocytes, Tumor-Infiltrating - drug effects</topic><topic>Lymphocytes, Tumor-Infiltrating - immunology</topic><topic>Lymphocytes, Tumor-Infiltrating - pathology</topic><topic>Male</topic><topic>Mast cells</topic><topic>Mast Cells - drug effects</topic><topic>Mast Cells - immunology</topic><topic>Mast Cells - pathology</topic><topic>Medical prognosis</topic><topic>Metastases</topic><topic>Middle Aged</topic><topic>Monocytes</topic><topic>Monocytes - drug effects</topic><topic>Monocytes - immunology</topic><topic>Monocytes - pathology</topic><topic>Mutation</topic><topic>Neoplasm Staging</topic><topic>p53 Protein</topic><topic>Plasma Cells - drug effects</topic><topic>Plasma Cells - immunology</topic><topic>Plasma Cells - pathology</topic><topic>Prognosis</topic><topic>Rapamycin</topic><topic>Receptors, LDL - genetics</topic><topic>Receptors, LDL - immunology</topic><topic>Regression Analysis</topic><topic>Risk analysis</topic><topic>Risk groups</topic><topic>Semustine - therapeutic use</topic><topic>Sirolimus - therapeutic use</topic><topic>Survival Analysis</topic><topic>T cells</topic><topic>T Follicular Helper Cells - drug effects</topic><topic>T Follicular Helper Cells - immunology</topic><topic>T Follicular Helper Cells - pathology</topic><topic>Tumor cells</topic><topic>Tumor Microenvironment - drug effects</topic><topic>Tumor Microenvironment - genetics</topic><topic>Tumor Microenvironment - immunology</topic><topic>Tumor proteins</topic><topic>Tumor Suppressor Protein p53 - genetics</topic><topic>Tumor Suppressor Protein p53 - immunology</topic><topic>Tumor-infiltrating lymphocytes</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Feng, Yuao</creatorcontrib><creatorcontrib>Wu, Shengjie</creatorcontrib><creatorcontrib>Chen, Liping</creatorcontrib><creatorcontrib>Lu, Guangrong</creatorcontrib><creatorcontrib>Lin, Tiesu</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><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>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Disease markers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Feng, Yuao</au><au>Wu, Shengjie</au><au>Chen, Liping</au><au>Lu, Guangrong</au><au>Lin, Tiesu</au><au>Knaś, Małgorzata</au><au>Małgorzata Knaś</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comprehensive Analysis of Tumor-Infiltrating Immune Cells and Relevant Therapeutic Strategy in Esophageal Cancer</atitle><jtitle>Disease markers</jtitle><addtitle>Dis Markers</addtitle><date>2020</date><risdate>2020</risdate><volume>2020</volume><issue>2020</issue><spage>1</spage><epage>12</epage><pages>1-12</pages><issn>0278-0240</issn><eissn>1875-8630</eissn><abstract>A growing body of evidence has indicated that behaviors of cancers are defined by not only intrinsic activities of tumor cells but also tumor-infiltrating immune cells (TIICs) in the tumor microenvironment. However, it still lacks a well-structured and comprehensive analysis of TIICs and its therapeutic value in esophageal cancer (EC). The proportions of 22 TIICs were evaluated between 150 normal tissues and 141 tumor tissues of EC by the CIBERSORT algorithm. Besides, correlation analyses between proportions of TIICs and clinicopathological characters, including age, gender, histologic grade, tumor location, histologic type, LRP1B mutation, TP53 mutation, tumor stage, lymph node stage, and TNM stage, were conducted. We constructed a risk score model to improve prognostic capacity with 5 TIICs by least absolute shrinkage and selection operator (lasso) regression analysis. The risk score=−1.86∗plasma+2.56∗T cell follicular helper−1.37∗monocytes−3.64∗activated dendritic cells−2.24∗resting mast cells (immune cells in the risk model mean the proportions of immune cell infiltration in EC). Patients in the high-risk group had significantly worse overall survival than these in the low-risk group (HR: 2.146, 95% CI: 1.243-3.705, p=0.0061). Finally, we identified Semustine and Sirolimus as two candidate compounds for the treatment of EC based on CMap analysis. In conclusion, the proportions of TIICs may be important to the progression, prognosis, and treatment of EC.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>32454908</pmid><doi>10.1155/2020/8974793</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-6087-7355</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0278-0240 |
| ispartof | Disease markers, 2020, Vol.2020 (2020), p.1-12 |
| issn | 0278-0240 1875-8630 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7238334 |
| source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Wiley Online Library Open Access; PubMed Central; Alma/SFX Local Collection |
| subjects | Adult Algorithms Analysis Antineoplastic Agents - therapeutic use Atrophy B cells Cancer Cancer therapies Cell Count Connectivity Correlation analysis Databases, Factual Dendritic cells Dendritic Cells - drug effects Dendritic Cells - immunology Dendritic Cells - pathology Esophageal cancer Esophageal Neoplasms - diagnosis Esophageal Neoplasms - drug therapy Esophageal Neoplasms - immunology Esophageal Neoplasms - mortality Esophagus Female Gender Gene Expression Genes Health aspects Humans Immune system Lymph nodes Lymph Nodes - drug effects Lymph Nodes - immunology Lymph Nodes - pathology Lymphocytes Lymphocytes T Lymphocytes, Tumor-Infiltrating - drug effects Lymphocytes, Tumor-Infiltrating - immunology Lymphocytes, Tumor-Infiltrating - pathology Male Mast cells Mast Cells - drug effects Mast Cells - immunology Mast Cells - pathology Medical prognosis Metastases Middle Aged Monocytes Monocytes - drug effects Monocytes - immunology Monocytes - pathology Mutation Neoplasm Staging p53 Protein Plasma Cells - drug effects Plasma Cells - immunology Plasma Cells - pathology Prognosis Rapamycin Receptors, LDL - genetics Receptors, LDL - immunology Regression Analysis Risk analysis Risk groups Semustine - therapeutic use Sirolimus - therapeutic use Survival Analysis T cells T Follicular Helper Cells - drug effects T Follicular Helper Cells - immunology T Follicular Helper Cells - pathology Tumor cells Tumor Microenvironment - drug effects Tumor Microenvironment - genetics Tumor Microenvironment - immunology Tumor proteins Tumor Suppressor Protein p53 - genetics Tumor Suppressor Protein p53 - immunology Tumor-infiltrating lymphocytes Tumors |
| title | Comprehensive Analysis of Tumor-Infiltrating Immune Cells and Relevant Therapeutic Strategy in Esophageal Cancer |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T02%3A26%3A22IST&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=Comprehensive%20Analysis%20of%20Tumor-Infiltrating%20Immune%20Cells%20and%20Relevant%20Therapeutic%20Strategy%20in%20Esophageal%20Cancer&rft.jtitle=Disease%20markers&rft.au=Feng,%20Yuao&rft.date=2020&rft.volume=2020&rft.issue=2020&rft.spage=1&rft.epage=12&rft.pages=1-12&rft.issn=0278-0240&rft.eissn=1875-8630&rft_id=info:doi/10.1155/2020/8974793&rft_dat=%3Cgale_pubme%3EA627689536%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=2406272597&rft_id=info:pmid/32454908&rft_galeid=A627689536&rfr_iscdi=true |