Comprehensive Analysis of a ceRNA Network Identifies lncR-C3orf35 Associated with Poor Prognosis in Osteosarcoma
Osteosarcoma is a highly malignant bone cancer which primarily occurs in children and young adults. Increasing evidence indicates that long noncoding RNAs (lncRNAs), which function as competing endogenous RNAs (ceRNAs) that sponge microRNAs (miRNAs) and messenger RNAs (mRNAs), play a pivotal role in...
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| creator | Wang, Kun He, Ronghan Li, Jinze Liu, Yuangao Wang, Zhe Zhang, Wenhui Zhuang, Ze Ren, Jianhua Shi, Yi Liang, Tangzhao |
| description | Osteosarcoma is a highly malignant bone cancer which primarily occurs in children and young adults. Increasing evidence indicates that long noncoding RNAs (lncRNAs), which function as competing endogenous RNAs (ceRNAs) that sponge microRNAs (miRNAs) and messenger RNAs (mRNAs), play a pivotal role in the pathogenesis and progression of cancers. The regulatory mechanisms of lncRNA-mediated ceRNAs in osteosarcoma have not been fully elucidated. In this study, we identified differentially expressed lncRNAs, miRNAs, and mRNAs in osteosarcoma based on RNA microarray profiles in the Gene Expression Omnibus (GEO) database. A ceRNA network was constructed utilizing bioinformatic tools. Kaplan-Meier survival analysis showed that lncR-C3orf35 and HMGB1 were associated with poor prognosis of osteosarcoma patients. Furthermore, results of Gene Set Enrichment Analysis (GSEA) suggested that lncR-C3orf35 may be involved in cellular invasion, the Toll-like receptor signaling pathway, and immune cell infiltration in the tumor microenvironment. Further analysis showed that patients with osteosarcoma metastasis expressed higher levels of lncR-C3orf35 and HMGB1 compared to metastasis-free patients. Moreover, the metastasis-free survival rate of the high lncR-C3orf35/HMGB1 expression group was significantly lower than that of the low expression group. The ESTIMATE algorithm was used to calculate the immune score and stromal scores for each sample. High lncR-C3orf35 and HMGB1 levels were correlated with low immune scores. ImmuCellAI analysis revealed that a low proportion of macrophage infiltration was associated with high lncR-C3orf35 and HMGB1 expression. The differential expression of lncR-C3orf35, miR-142-3p, and HMGB1 was further verified by quantitative real-time PCR. This study indicates that lncR-C3orf35 could be considered as a novel potential biomarker and therapeutic target of osteosarcoma, which may contribute to a better understanding of ceRNA regulatory mechanisms. |
| doi_str_mv | 10.1155/2020/3178037 |
| format | Article |
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Increasing evidence indicates that long noncoding RNAs (lncRNAs), which function as competing endogenous RNAs (ceRNAs) that sponge microRNAs (miRNAs) and messenger RNAs (mRNAs), play a pivotal role in the pathogenesis and progression of cancers. The regulatory mechanisms of lncRNA-mediated ceRNAs in osteosarcoma have not been fully elucidated. In this study, we identified differentially expressed lncRNAs, miRNAs, and mRNAs in osteosarcoma based on RNA microarray profiles in the Gene Expression Omnibus (GEO) database. A ceRNA network was constructed utilizing bioinformatic tools. Kaplan-Meier survival analysis showed that lncR-C3orf35 and HMGB1 were associated with poor prognosis of osteosarcoma patients. Furthermore, results of Gene Set Enrichment Analysis (GSEA) suggested that lncR-C3orf35 may be involved in cellular invasion, the Toll-like receptor signaling pathway, and immune cell infiltration in the tumor microenvironment. Further analysis showed that patients with osteosarcoma metastasis expressed higher levels of lncR-C3orf35 and HMGB1 compared to metastasis-free patients. Moreover, the metastasis-free survival rate of the high lncR-C3orf35/HMGB1 expression group was significantly lower than that of the low expression group. The ESTIMATE algorithm was used to calculate the immune score and stromal scores for each sample. High lncR-C3orf35 and HMGB1 levels were correlated with low immune scores. ImmuCellAI analysis revealed that a low proportion of macrophage infiltration was associated with high lncR-C3orf35 and HMGB1 expression. The differential expression of lncR-C3orf35, miR-142-3p, and HMGB1 was further verified by quantitative real-time PCR. This study indicates that lncR-C3orf35 could be considered as a novel potential biomarker and therapeutic target of osteosarcoma, which may contribute to a better understanding of ceRNA regulatory mechanisms.</description><identifier>ISSN: 2314-6133</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2020/3178037</identifier><identifier>PMID: 33015161</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Adolescent ; Adult ; Algorithms ; Analysis ; Biomarkers ; Biomarkers, Tumor - genetics ; Biomedical materials ; Bone cancer ; Cancer ; Cancer in children ; Care and treatment ; Child ; Children ; Chromosomal proteins ; Datasets ; Diagnosis ; DNA microarrays ; Epigenetics ; Female ; Gene expression ; Gene Expression Profiling - methods ; Gene Expression Regulation, Neoplastic - genetics ; Gene Ontology ; Gene Regulatory Networks - genetics ; Gene set enrichment analysis ; HMGB1 protein ; Humans ; Immune system ; Infiltration ; Kaplan-Meier Estimate ; Macrophages ; Male ; Medical prognosis ; Metastases ; Metastasis ; Microarray Analysis - methods ; MicroRNA ; MicroRNAs ; miRNA ; Osteosarcoma ; Osteosarcoma - genetics ; Osteosarcoma - mortality ; Osteosarcoma - pathology ; Pathogenesis ; Prevention ; Prognosis ; Proteins ; Regression analysis ; Regulatory mechanisms (biology) ; Risk factors ; RNA, Long Noncoding - genetics ; Sarcoma ; Signal transduction ; Software ; Survival ; Survival analysis ; Survival Rate ; Toll-like receptors ; Tumor Microenvironment - immunology ; Young Adult ; Young adults</subject><ispartof>BioMed research international, 2020, Vol.2020 (2020), p.1-13</ispartof><rights>Copyright © 2020 Yi Shi et al.</rights><rights>COPYRIGHT 2020 John Wiley & Sons, Inc.</rights><rights>Copyright © 2020 Yi Shi 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 © 2020 Yi Shi et al. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c499t-ed35a5ef34678988a5a1acd94a29106aca2317fc71975c3edbe0f72cc573583b3</citedby><cites>FETCH-LOGICAL-c499t-ed35a5ef34678988a5a1acd94a29106aca2317fc71975c3edbe0f72cc573583b3</cites><orcidid>0000-0001-6331-438X ; 0000-0003-1396-6325</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/PMC7525295/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7525295/$$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/33015161$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Niu, Bing</contributor><contributor>Bing Niu</contributor><creatorcontrib>Wang, Kun</creatorcontrib><creatorcontrib>He, Ronghan</creatorcontrib><creatorcontrib>Li, Jinze</creatorcontrib><creatorcontrib>Liu, Yuangao</creatorcontrib><creatorcontrib>Wang, Zhe</creatorcontrib><creatorcontrib>Zhang, Wenhui</creatorcontrib><creatorcontrib>Zhuang, Ze</creatorcontrib><creatorcontrib>Ren, Jianhua</creatorcontrib><creatorcontrib>Shi, Yi</creatorcontrib><creatorcontrib>Liang, Tangzhao</creatorcontrib><title>Comprehensive Analysis of a ceRNA Network Identifies lncR-C3orf35 Associated with Poor Prognosis in Osteosarcoma</title><title>BioMed research international</title><addtitle>Biomed Res Int</addtitle><description>Osteosarcoma is a highly malignant bone cancer which primarily occurs in children and young adults. Increasing evidence indicates that long noncoding RNAs (lncRNAs), which function as competing endogenous RNAs (ceRNAs) that sponge microRNAs (miRNAs) and messenger RNAs (mRNAs), play a pivotal role in the pathogenesis and progression of cancers. The regulatory mechanisms of lncRNA-mediated ceRNAs in osteosarcoma have not been fully elucidated. In this study, we identified differentially expressed lncRNAs, miRNAs, and mRNAs in osteosarcoma based on RNA microarray profiles in the Gene Expression Omnibus (GEO) database. A ceRNA network was constructed utilizing bioinformatic tools. Kaplan-Meier survival analysis showed that lncR-C3orf35 and HMGB1 were associated with poor prognosis of osteosarcoma patients. Furthermore, results of Gene Set Enrichment Analysis (GSEA) suggested that lncR-C3orf35 may be involved in cellular invasion, the Toll-like receptor signaling pathway, and immune cell infiltration in the tumor microenvironment. Further analysis showed that patients with osteosarcoma metastasis expressed higher levels of lncR-C3orf35 and HMGB1 compared to metastasis-free patients. Moreover, the metastasis-free survival rate of the high lncR-C3orf35/HMGB1 expression group was significantly lower than that of the low expression group. The ESTIMATE algorithm was used to calculate the immune score and stromal scores for each sample. High lncR-C3orf35 and HMGB1 levels were correlated with low immune scores. ImmuCellAI analysis revealed that a low proportion of macrophage infiltration was associated with high lncR-C3orf35 and HMGB1 expression. The differential expression of lncR-C3orf35, miR-142-3p, and HMGB1 was further verified by quantitative real-time PCR. This study indicates that lncR-C3orf35 could be considered as a novel potential biomarker and therapeutic target of osteosarcoma, which may contribute to a better understanding of ceRNA regulatory mechanisms.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biomedical materials</subject><subject>Bone cancer</subject><subject>Cancer</subject><subject>Cancer in children</subject><subject>Care and treatment</subject><subject>Child</subject><subject>Children</subject><subject>Chromosomal proteins</subject><subject>Datasets</subject><subject>Diagnosis</subject><subject>DNA microarrays</subject><subject>Epigenetics</subject><subject>Female</subject><subject>Gene expression</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Expression Regulation, Neoplastic - genetics</subject><subject>Gene Ontology</subject><subject>Gene Regulatory Networks - genetics</subject><subject>Gene set enrichment analysis</subject><subject>HMGB1 protein</subject><subject>Humans</subject><subject>Immune system</subject><subject>Infiltration</subject><subject>Kaplan-Meier Estimate</subject><subject>Macrophages</subject><subject>Male</subject><subject>Medical prognosis</subject><subject>Metastases</subject><subject>Metastasis</subject><subject>Microarray Analysis - methods</subject><subject>MicroRNA</subject><subject>MicroRNAs</subject><subject>miRNA</subject><subject>Osteosarcoma</subject><subject>Osteosarcoma - genetics</subject><subject>Osteosarcoma - mortality</subject><subject>Osteosarcoma - pathology</subject><subject>Pathogenesis</subject><subject>Prevention</subject><subject>Prognosis</subject><subject>Proteins</subject><subject>Regression analysis</subject><subject>Regulatory mechanisms (biology)</subject><subject>Risk factors</subject><subject>RNA, Long Noncoding - genetics</subject><subject>Sarcoma</subject><subject>Signal transduction</subject><subject>Software</subject><subject>Survival</subject><subject>Survival analysis</subject><subject>Survival Rate</subject><subject>Toll-like receptors</subject><subject>Tumor Microenvironment - 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genetics</topic><topic>Biomedical materials</topic><topic>Bone cancer</topic><topic>Cancer</topic><topic>Cancer in children</topic><topic>Care and treatment</topic><topic>Child</topic><topic>Children</topic><topic>Chromosomal proteins</topic><topic>Datasets</topic><topic>Diagnosis</topic><topic>DNA microarrays</topic><topic>Epigenetics</topic><topic>Female</topic><topic>Gene expression</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Expression Regulation, Neoplastic - genetics</topic><topic>Gene Ontology</topic><topic>Gene Regulatory Networks - genetics</topic><topic>Gene set enrichment analysis</topic><topic>HMGB1 protein</topic><topic>Humans</topic><topic>Immune system</topic><topic>Infiltration</topic><topic>Kaplan-Meier Estimate</topic><topic>Macrophages</topic><topic>Male</topic><topic>Medical prognosis</topic><topic>Metastases</topic><topic>Metastasis</topic><topic>Microarray Analysis - methods</topic><topic>MicroRNA</topic><topic>MicroRNAs</topic><topic>miRNA</topic><topic>Osteosarcoma</topic><topic>Osteosarcoma - genetics</topic><topic>Osteosarcoma - mortality</topic><topic>Osteosarcoma - pathology</topic><topic>Pathogenesis</topic><topic>Prevention</topic><topic>Prognosis</topic><topic>Proteins</topic><topic>Regression analysis</topic><topic>Regulatory mechanisms (biology)</topic><topic>Risk factors</topic><topic>RNA, Long Noncoding - genetics</topic><topic>Sarcoma</topic><topic>Signal transduction</topic><topic>Software</topic><topic>Survival</topic><topic>Survival analysis</topic><topic>Survival Rate</topic><topic>Toll-like receptors</topic><topic>Tumor Microenvironment - immunology</topic><topic>Young Adult</topic><topic>Young adults</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Kun</creatorcontrib><creatorcontrib>He, Ronghan</creatorcontrib><creatorcontrib>Li, Jinze</creatorcontrib><creatorcontrib>Liu, Yuangao</creatorcontrib><creatorcontrib>Wang, Zhe</creatorcontrib><creatorcontrib>Zhang, Wenhui</creatorcontrib><creatorcontrib>Zhuang, Ze</creatorcontrib><creatorcontrib>Ren, Jianhua</creatorcontrib><creatorcontrib>Shi, Yi</creatorcontrib><creatorcontrib>Liang, Tangzhao</creatorcontrib><collection>الدوريات العلمية والإحصائية - 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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>Wang, Kun</au><au>He, Ronghan</au><au>Li, Jinze</au><au>Liu, Yuangao</au><au>Wang, Zhe</au><au>Zhang, Wenhui</au><au>Zhuang, Ze</au><au>Ren, Jianhua</au><au>Shi, Yi</au><au>Liang, Tangzhao</au><au>Niu, Bing</au><au>Bing Niu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comprehensive Analysis of a ceRNA Network Identifies lncR-C3orf35 Associated with Poor Prognosis in Osteosarcoma</atitle><jtitle>BioMed research international</jtitle><addtitle>Biomed Res Int</addtitle><date>2020</date><risdate>2020</risdate><volume>2020</volume><issue>2020</issue><spage>1</spage><epage>13</epage><pages>1-13</pages><issn>2314-6133</issn><eissn>2314-6141</eissn><abstract>Osteosarcoma is a highly malignant bone cancer which primarily occurs in children and young adults. Increasing evidence indicates that long noncoding RNAs (lncRNAs), which function as competing endogenous RNAs (ceRNAs) that sponge microRNAs (miRNAs) and messenger RNAs (mRNAs), play a pivotal role in the pathogenesis and progression of cancers. The regulatory mechanisms of lncRNA-mediated ceRNAs in osteosarcoma have not been fully elucidated. In this study, we identified differentially expressed lncRNAs, miRNAs, and mRNAs in osteosarcoma based on RNA microarray profiles in the Gene Expression Omnibus (GEO) database. A ceRNA network was constructed utilizing bioinformatic tools. Kaplan-Meier survival analysis showed that lncR-C3orf35 and HMGB1 were associated with poor prognosis of osteosarcoma patients. Furthermore, results of Gene Set Enrichment Analysis (GSEA) suggested that lncR-C3orf35 may be involved in cellular invasion, the Toll-like receptor signaling pathway, and immune cell infiltration in the tumor microenvironment. Further analysis showed that patients with osteosarcoma metastasis expressed higher levels of lncR-C3orf35 and HMGB1 compared to metastasis-free patients. Moreover, the metastasis-free survival rate of the high lncR-C3orf35/HMGB1 expression group was significantly lower than that of the low expression group. The ESTIMATE algorithm was used to calculate the immune score and stromal scores for each sample. High lncR-C3orf35 and HMGB1 levels were correlated with low immune scores. ImmuCellAI analysis revealed that a low proportion of macrophage infiltration was associated with high lncR-C3orf35 and HMGB1 expression. The differential expression of lncR-C3orf35, miR-142-3p, and HMGB1 was further verified by quantitative real-time PCR. This study indicates that lncR-C3orf35 could be considered as a novel potential biomarker and therapeutic target of osteosarcoma, which may contribute to a better understanding of ceRNA regulatory mechanisms.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>33015161</pmid><doi>10.1155/2020/3178037</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-6331-438X</orcidid><orcidid>https://orcid.org/0000-0003-1396-6325</orcidid><oa>free_for_read</oa></addata></record> |
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| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7525295 |
| source | MEDLINE; PubMed Central Open Access; Wiley-Blackwell Open Access Titles; PubMed Central; Alma/SFX Local Collection |
| subjects | Adolescent Adult Algorithms Analysis Biomarkers Biomarkers, Tumor - genetics Biomedical materials Bone cancer Cancer Cancer in children Care and treatment Child Children Chromosomal proteins Datasets Diagnosis DNA microarrays Epigenetics Female Gene expression Gene Expression Profiling - methods Gene Expression Regulation, Neoplastic - genetics Gene Ontology Gene Regulatory Networks - genetics Gene set enrichment analysis HMGB1 protein Humans Immune system Infiltration Kaplan-Meier Estimate Macrophages Male Medical prognosis Metastases Metastasis Microarray Analysis - methods MicroRNA MicroRNAs miRNA Osteosarcoma Osteosarcoma - genetics Osteosarcoma - mortality Osteosarcoma - pathology Pathogenesis Prevention Prognosis Proteins Regression analysis Regulatory mechanisms (biology) Risk factors RNA, Long Noncoding - genetics Sarcoma Signal transduction Software Survival Survival analysis Survival Rate Toll-like receptors Tumor Microenvironment - immunology Young Adult Young adults |
| title | Comprehensive Analysis of a ceRNA Network Identifies lncR-C3orf35 Associated with Poor Prognosis in Osteosarcoma |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T01%3A35%3A37IST&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%20a%20ceRNA%20Network%20Identifies%20lncR-C3orf35%20Associated%20with%20Poor%20Prognosis%20in%20Osteosarcoma&rft.jtitle=BioMed%20research%20international&rft.au=Wang,%20Kun&rft.date=2020&rft.volume=2020&rft.issue=2020&rft.spage=1&rft.epage=13&rft.pages=1-13&rft.issn=2314-6133&rft.eissn=2314-6141&rft_id=info:doi/10.1155/2020/3178037&rft_dat=%3Cgale_pubme%3EA697114272%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=2448264102&rft_id=info:pmid/33015161&rft_galeid=A697114272&rfr_iscdi=true |