Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma
Although recent clinical investigations emphasize the roles of myriad diversities of RNAs in stromal and immune components in the tumor microenvironment, especially in colon adenocarcinoma, however, analyses of “competing endogenous RNAs (ceRNA)” network in association with stromal and immune scores...
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description | Although recent clinical investigations emphasize the roles of myriad diversities of RNAs in stromal and immune components in the tumor microenvironment, especially in colon adenocarcinoma, however, analyses of “competing endogenous RNAs (ceRNA)” network in association with stromal and immune scores have yet to be determined. This study was conducted to explore the regulatory mechanisms of a stromal-immune score-based ceRNA network in colon adenocarcinoma. Stromal and immune scores of colon adenocarcinoma tumor samples were calculated by using the ESTIMATE algorithm. Differential expression analysis between samples with high/low stromal and immune scores was performed, followed by functional annotation for the overlapping DEmRNAs. The ceRNA network was constructed by differential expression analysis, prediction of RNA-RNA interaction, and correlation with clinicopathological parameters of the patients, which were further verified by external datasets and experiments. Colon adenocarcinoma patients having higher immune scores exhibited prolonged overall survival. RNA dataset analyses from TCGA revealed aberrant expressions of a total of 2052 mRNAs, 108 lncRNAs, and 70 miRNAs between high and low stromal/immune groups. Functional annotation mapped the differentially overexpressed mRNAs for immune-associated GO terms. To construct the ceRNA network, a total of 48 lncRNAs, 40 miRNAs, and 199 mRNAs were sorted out. A dysregulated ceRNA network consisting of 6 lncRNAs, 11 miRNAs, and 39 mRNAs was constructed by comparing RNA expressions between cancer as well as adjacent normal tissues. The ceRNA regulatory axis “MIAT/miR-532-3p/STC1” was regarded as a potential hit by the comprehensive analysis. The RT-qPCR assay showed upregulation of MIAT and STC1 while downregulation of hsa-miR-532-3p expression in cancer. Thus, our study highlights the potential role of a stromal-immune score-based ceRNA network in the colon adenocarcinoma microenvironment. The ceRNA axis MIAT/miR-532-3p/STC1 could serve as a promising therapeutic target for colon adenocarcinoma. |
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This study was conducted to explore the regulatory mechanisms of a stromal-immune score-based ceRNA network in colon adenocarcinoma. Stromal and immune scores of colon adenocarcinoma tumor samples were calculated by using the ESTIMATE algorithm. Differential expression analysis between samples with high/low stromal and immune scores was performed, followed by functional annotation for the overlapping DEmRNAs. The ceRNA network was constructed by differential expression analysis, prediction of RNA-RNA interaction, and correlation with clinicopathological parameters of the patients, which were further verified by external datasets and experiments. Colon adenocarcinoma patients having higher immune scores exhibited prolonged overall survival. RNA dataset analyses from TCGA revealed aberrant expressions of a total of 2052 mRNAs, 108 lncRNAs, and 70 miRNAs between high and low stromal/immune groups. Functional annotation mapped the differentially overexpressed mRNAs for immune-associated GO terms. To construct the ceRNA network, a total of 48 lncRNAs, 40 miRNAs, and 199 mRNAs were sorted out. A dysregulated ceRNA network consisting of 6 lncRNAs, 11 miRNAs, and 39 mRNAs was constructed by comparing RNA expressions between cancer as well as adjacent normal tissues. The ceRNA regulatory axis “MIAT/miR-532-3p/STC1” was regarded as a potential hit by the comprehensive analysis. The RT-qPCR assay showed upregulation of MIAT and STC1 while downregulation of hsa-miR-532-3p expression in cancer. Thus, our study highlights the potential role of a stromal-immune score-based ceRNA network in the colon adenocarcinoma microenvironment. The ceRNA axis MIAT/miR-532-3p/STC1 could serve as a promising therapeutic target for colon adenocarcinoma.</description><identifier>ISSN: 0278-0240</identifier><identifier>EISSN: 1875-8630</identifier><identifier>DOI: 10.1155/2022/4235305</identifier><identifier>PMID: 35607443</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Adenocarcinoma ; Algorithms ; Annotations ; Biomarkers ; Cancer ; Colon ; Colorectal cancer ; Datasets ; Gene expression ; Medical prognosis ; MicroRNAs ; Non-coding RNA ; Ontology ; Patients ; Regulatory mechanisms (biology) ; Ribonucleic acid ; RNA ; Software ; Survival analysis ; Therapeutic targets ; Tumor microenvironment ; Tumors</subject><ispartof>Disease markers, 2022, Vol.2022, p.4235305-12</ispartof><rights>Copyright © 2022 Yalin Tong et al.</rights><rights>Copyright © 2022 Yalin Tong 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 © 2022 Yalin Tong et al. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3635-124e8ca22f2e82253781fbe8127d38069c34882ca874864e13202163f6e559663</citedby><cites>FETCH-LOGICAL-c3635-124e8ca22f2e82253781fbe8127d38069c34882ca874864e13202163f6e559663</cites><orcidid>0000-0001-5032-3260</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/PMC9124109/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9124109/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,4022,27922,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35607443$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Zhang, Yuanwei</contributor><contributor>Yuanwei Zhang</contributor><creatorcontrib>Tong, Yalin</creatorcontrib><creatorcontrib>Peng, Mengle</creatorcontrib><creatorcontrib>Li, Jinbei</creatorcontrib><creatorcontrib>Niu, Ying</creatorcontrib><title>Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma</title><title>Disease markers</title><addtitle>Dis Markers</addtitle><description>Although recent clinical investigations emphasize the roles of myriad diversities of RNAs in stromal and immune components in the tumor microenvironment, especially in colon adenocarcinoma, however, analyses of “competing endogenous RNAs (ceRNA)” network in association with stromal and immune scores have yet to be determined. This study was conducted to explore the regulatory mechanisms of a stromal-immune score-based ceRNA network in colon adenocarcinoma. Stromal and immune scores of colon adenocarcinoma tumor samples were calculated by using the ESTIMATE algorithm. Differential expression analysis between samples with high/low stromal and immune scores was performed, followed by functional annotation for the overlapping DEmRNAs. The ceRNA network was constructed by differential expression analysis, prediction of RNA-RNA interaction, and correlation with clinicopathological parameters of the patients, which were further verified by external datasets and experiments. Colon adenocarcinoma patients having higher immune scores exhibited prolonged overall survival. RNA dataset analyses from TCGA revealed aberrant expressions of a total of 2052 mRNAs, 108 lncRNAs, and 70 miRNAs between high and low stromal/immune groups. Functional annotation mapped the differentially overexpressed mRNAs for immune-associated GO terms. To construct the ceRNA network, a total of 48 lncRNAs, 40 miRNAs, and 199 mRNAs were sorted out. A dysregulated ceRNA network consisting of 6 lncRNAs, 11 miRNAs, and 39 mRNAs was constructed by comparing RNA expressions between cancer as well as adjacent normal tissues. The ceRNA regulatory axis “MIAT/miR-532-3p/STC1” was regarded as a potential hit by the comprehensive analysis. The RT-qPCR assay showed upregulation of MIAT and STC1 while downregulation of hsa-miR-532-3p expression in cancer. Thus, our study highlights the potential role of a stromal-immune score-based ceRNA network in the colon adenocarcinoma microenvironment. The ceRNA axis MIAT/miR-532-3p/STC1 could serve as a promising therapeutic target for colon adenocarcinoma.</description><subject>Adenocarcinoma</subject><subject>Algorithms</subject><subject>Annotations</subject><subject>Biomarkers</subject><subject>Cancer</subject><subject>Colon</subject><subject>Colorectal cancer</subject><subject>Datasets</subject><subject>Gene expression</subject><subject>Medical prognosis</subject><subject>MicroRNAs</subject><subject>Non-coding RNA</subject><subject>Ontology</subject><subject>Patients</subject><subject>Regulatory mechanisms (biology)</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>Software</subject><subject>Survival analysis</subject><subject>Therapeutic targets</subject><subject>Tumor microenvironment</subject><subject>Tumors</subject><issn>0278-0240</issn><issn>1875-8630</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><recordid>eNp9kU1vEzEQhi0EoqFw44wscUGiS_293gtSFPUjUlWkFs6W651NXHbtYO-26r_HaUJFOXDyYZ55xjMvQu8p-UKplMeMMHYsGJecyBdoRnUtK604eYlmhNW6IkyQA_Qm51tCKGtE8xodcKlILQSfoc0iDpsEawjZ3wGeB9s_ZMg4dvh6THGwfbUchikAvnYxQXUFvR2hxds2GH1Y4ZPQxhWEOGV8dTnHlzDex_Qz42UoUB8Dnrel6mxyPhTfW_Sqs32Gd_v3EP04Pfm-OK8uvp0tF_OLynHFZUWZAO0sYx0DzZjktabdDWjK6pZrohrHhdbMWV0LrQRQXu5AFe8USNkoxQ_R1513M90M0DoIY7K92SQ_2PRgovXmeSX4tVnFO9OU0ZQ0RfBpL0jx1wR5NIPPDvreBijLGqaULqyidUE__oPeximVUz5StWKKUF6oox3lUsw5Qff0GUrMNkqzjdLsoyz4h78XeIL_ZFeAzztg7UNr7_3_db8BaqylKQ</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Tong, Yalin</creator><creator>Peng, Mengle</creator><creator>Li, Jinbei</creator><creator>Niu, Ying</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</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>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-5032-3260</orcidid></search><sort><creationdate>2022</creationdate><title>Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma</title><author>Tong, Yalin ; Peng, Mengle ; Li, Jinbei ; Niu, Ying</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3635-124e8ca22f2e82253781fbe8127d38069c34882ca874864e13202163f6e559663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adenocarcinoma</topic><topic>Algorithms</topic><topic>Annotations</topic><topic>Biomarkers</topic><topic>Cancer</topic><topic>Colon</topic><topic>Colorectal cancer</topic><topic>Datasets</topic><topic>Gene expression</topic><topic>Medical prognosis</topic><topic>MicroRNAs</topic><topic>Non-coding RNA</topic><topic>Ontology</topic><topic>Patients</topic><topic>Regulatory mechanisms (biology)</topic><topic>Ribonucleic acid</topic><topic>RNA</topic><topic>Software</topic><topic>Survival analysis</topic><topic>Therapeutic targets</topic><topic>Tumor microenvironment</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tong, Yalin</creatorcontrib><creatorcontrib>Peng, Mengle</creatorcontrib><creatorcontrib>Li, Jinbei</creatorcontrib><creatorcontrib>Niu, Ying</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</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>MEDLINE - Academic</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>Tong, Yalin</au><au>Peng, Mengle</au><au>Li, Jinbei</au><au>Niu, Ying</au><au>Zhang, Yuanwei</au><au>Yuanwei Zhang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma</atitle><jtitle>Disease markers</jtitle><addtitle>Dis Markers</addtitle><date>2022</date><risdate>2022</risdate><volume>2022</volume><spage>4235305</spage><epage>12</epage><pages>4235305-12</pages><issn>0278-0240</issn><eissn>1875-8630</eissn><abstract>Although recent clinical investigations emphasize the roles of myriad diversities of RNAs in stromal and immune components in the tumor microenvironment, especially in colon adenocarcinoma, however, analyses of “competing endogenous RNAs (ceRNA)” network in association with stromal and immune scores have yet to be determined. This study was conducted to explore the regulatory mechanisms of a stromal-immune score-based ceRNA network in colon adenocarcinoma. Stromal and immune scores of colon adenocarcinoma tumor samples were calculated by using the ESTIMATE algorithm. Differential expression analysis between samples with high/low stromal and immune scores was performed, followed by functional annotation for the overlapping DEmRNAs. The ceRNA network was constructed by differential expression analysis, prediction of RNA-RNA interaction, and correlation with clinicopathological parameters of the patients, which were further verified by external datasets and experiments. Colon adenocarcinoma patients having higher immune scores exhibited prolonged overall survival. RNA dataset analyses from TCGA revealed aberrant expressions of a total of 2052 mRNAs, 108 lncRNAs, and 70 miRNAs between high and low stromal/immune groups. Functional annotation mapped the differentially overexpressed mRNAs for immune-associated GO terms. To construct the ceRNA network, a total of 48 lncRNAs, 40 miRNAs, and 199 mRNAs were sorted out. A dysregulated ceRNA network consisting of 6 lncRNAs, 11 miRNAs, and 39 mRNAs was constructed by comparing RNA expressions between cancer as well as adjacent normal tissues. The ceRNA regulatory axis “MIAT/miR-532-3p/STC1” was regarded as a potential hit by the comprehensive analysis. The RT-qPCR assay showed upregulation of MIAT and STC1 while downregulation of hsa-miR-532-3p expression in cancer. Thus, our study highlights the potential role of a stromal-immune score-based ceRNA network in the colon adenocarcinoma microenvironment. The ceRNA axis MIAT/miR-532-3p/STC1 could serve as a promising therapeutic target for colon adenocarcinoma.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>35607443</pmid><doi>10.1155/2022/4235305</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-5032-3260</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adenocarcinoma Algorithms Annotations Biomarkers Cancer Colon Colorectal cancer Datasets Gene expression Medical prognosis MicroRNAs Non-coding RNA Ontology Patients Regulatory mechanisms (biology) Ribonucleic acid RNA Software Survival analysis Therapeutic targets Tumor microenvironment Tumors |
title | Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma |
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