Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney
Background. Immune-related long noncoding RNAs (IrlncRNAs) are recognized as important prognostic factors in a variety of cancers, but thus far, their prognostic value in pediatric rhabdoid tumor of the kidney (pRTK) has not been reported. Here, we clarified the associations between IrlncRNAs and ov...
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| Veröffentlicht in: | Disease markers 2022-06, Vol.2022, p.1-11 |
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| description | Background. Immune-related long noncoding RNAs (IrlncRNAs) are recognized as important prognostic factors in a variety of cancers, but thus far, their prognostic value in pediatric rhabdoid tumor of the kidney (pRTK) has not been reported. Here, we clarified the associations between IrlncRNAs and overall survival (OS) of pRTK patients and constructed a model to predict their prognosis. Methods. We accessed RNA sequencing data and corresponding clinical data of pRTK from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. An expression profile of immune-related genes (Irgenes) and lncRNAs of pRTK was extracted from the RNA sequencing data. IrlncRNAs were defined by co-expression analysis of lncRNAs and Irgenes. The limma R package was used to identify differential expression IrlncRNAs. Univariate and multivariate Cox regression analyses were conducted to build a prognostic IrlncRNAs model. The performance of this prognostic model was validated by multimethods, like ROC curve analysis. Results. A total of 1097 IrlncRNAs were defined. Univariate Cox regression analysis identified 7 IrlncRNAs (AC004791.2, AP003068.23, RP11-54O7.14, RP11-680F8.1, TBC1D3P1-DHX40P1, TUNAR, and XXbac-BPG308K3.5) and were significantly associated with OS. Multivariate regression analysis constructed the best prognostic model based on the expression of AC004791.2, AP003068.23, RP11-54O7.14, TBC1D3P1-DHX40P1, and TUNAR. According to the prognostic model, a risk score of each patient was calculated, and patients were divided into high-risk and low-risk groups accordingly. The survival time of low-risk patients was significantly better than high-risk patients (p |
| doi_str_mv | 10.1155/2022/4752184 |
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| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9217527</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2680910358</sourcerecordid><originalsourceid>FETCH-LOGICAL-c382t-5c81c5281b97781a5b06b4d4fae861d27096ac6257995a0c460d4078d1ebec833</originalsourceid><addsrcrecordid>eNp90UFrFDEYBuAgil2rN39AwIugY79kkklyEUqxWrq0Zal4DJkk002ZSWoyo_Tfm2UXwR48BfI9vCTfi9BbAp8I4fyEAqUnTHBKJHuGVkQK3siuhedoBVTIBiiDI_SqlHsAQhVTL9FRywXvmIIV-nExTUv0zcaPZvYOr6PdXJ0WbAq-yekupjIHi8-NnVMueEgZ33gXzJzr7WZrepeCw7fLVAdpwPPW48vgon98jV4MZiz-zeE8Rt_Pv9yefWvW118vzk7XjW0lnRtuJbGcStIrISQxvIeuZ44NxsuOOCpAdcZ2lAuluAHLOnAMhHTE997Ktj1Gn_e5D0s_eWd9nLMZ9UMOk8mPOpmg_53EsNV36ZdWlNSdiRrw_hCQ08_Fl1lPoVg_jib6tBRNO0kYA0mg0ndP6H1acqzf2ylQlXBZ1ce9sjmVkv3w9zEE9K4xvWtMHxqr_MOeb0N05nf4v_4DpeOSwg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2680910358</pqid></control><display><type>article</type><title>Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney</title><source>Wiley Online Library Open Access</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Hong, Ye ; Que, Yi ; Hu, Yang ; Shi, Bo-yun ; Zhu, Jia ; Wang, Juan ; Huang, Jun-ting ; Sun, Fei-fei ; Zhang, Lian ; Zhou, Xin-ke ; Lu, Su-ying ; Zhang, Yi-zhuo</creator><contributor>Zeng, Chengwu</contributor><creatorcontrib>Hong, Ye ; Que, Yi ; Hu, Yang ; Shi, Bo-yun ; Zhu, Jia ; Wang, Juan ; Huang, Jun-ting ; Sun, Fei-fei ; Zhang, Lian ; Zhou, Xin-ke ; Lu, Su-ying ; Zhang, Yi-zhuo ; Zeng, Chengwu</creatorcontrib><description>Background. Immune-related long noncoding RNAs (IrlncRNAs) are recognized as important prognostic factors in a variety of cancers, but thus far, their prognostic value in pediatric rhabdoid tumor of the kidney (pRTK) has not been reported. Here, we clarified the associations between IrlncRNAs and overall survival (OS) of pRTK patients and constructed a model to predict their prognosis. Methods. We accessed RNA sequencing data and corresponding clinical data of pRTK from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. An expression profile of immune-related genes (Irgenes) and lncRNAs of pRTK was extracted from the RNA sequencing data. IrlncRNAs were defined by co-expression analysis of lncRNAs and Irgenes. The limma R package was used to identify differential expression IrlncRNAs. Univariate and multivariate Cox regression analyses were conducted to build a prognostic IrlncRNAs model. The performance of this prognostic model was validated by multimethods, like ROC curve analysis. Results. A total of 1097 IrlncRNAs were defined. Univariate Cox regression analysis identified 7 IrlncRNAs (AC004791.2, AP003068.23, RP11-54O7.14, RP11-680F8.1, TBC1D3P1-DHX40P1, TUNAR, and XXbac-BPG308K3.5) and were significantly associated with OS. Multivariate regression analysis constructed the best prognostic model based on the expression of AC004791.2, AP003068.23, RP11-54O7.14, TBC1D3P1-DHX40P1, and TUNAR. According to the prognostic model, a risk score of each patient was calculated, and patients were divided into high-risk and low-risk groups accordingly. The survival time of low-risk patients was significantly better than high-risk patients (p<0.001). Univariate (hazard ratio 1.098, 95% confidence interval 1.048–1.149, p value <0.001) and multivariate (hazard ratio 1.095, 95% confidence interval 1.043–1.150, p value <0.001) analyses confirmed that the prognostic model was reliable and independent in prediction of OS. Time-dependent ROC analysis showed that 1-year survival AUC of prognostic model, stage, age, and sex was 0.824, 0.673, 0.531, and 0.495, respectively, which suggested that the prognostic model was the best predictor of survival in pRTK patients. Conclusions. The prognostic model based on 5 IrlncRNAs was robust and could better predict the survival of pRTK than other clinical factors. Additionally, the mechanism of regulation and action of prognosis-associated lncRNAs could provide new avenues for basic research to explore the mechanism of tumor initiation and development in order to prevent and treat pRTK.</description><identifier>ISSN: 0278-0240</identifier><identifier>EISSN: 1875-8630</identifier><identifier>DOI: 10.1155/2022/4752184</identifier><identifier>PMID: 35756490</identifier><language>eng</language><publisher>Amsterdam: Hindawi</publisher><subject>Cancer therapies ; Cell cycle ; Confidence intervals ; Data processing ; Gene expression ; Gene sequencing ; Genes ; Health hazards ; Kidneys ; Kinases ; Medical prognosis ; Metastasis ; Multivariate analysis ; Non-coding RNA ; Patients ; Pediatrics ; Perl ; Prognosis ; Regression analysis ; Ribonucleic acid ; Risk ; Risk groups ; RNA ; Software ; Statistical analysis ; Survival ; Survival analysis ; Time dependence ; Transcription factors ; Tumor necrosis factor-TNF ; Tumors</subject><ispartof>Disease markers, 2022-06, Vol.2022, p.1-11</ispartof><rights>Copyright © 2022 Ye Hong et al.</rights><rights>Copyright © 2022 Ye Hong 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 Ye Hong et al. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c382t-5c81c5281b97781a5b06b4d4fae861d27096ac6257995a0c460d4078d1ebec833</cites><orcidid>0000-0002-6128-3476 ; 0000-0001-8117-3533</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/PMC9217527/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9217527/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids></links><search><contributor>Zeng, Chengwu</contributor><creatorcontrib>Hong, Ye</creatorcontrib><creatorcontrib>Que, Yi</creatorcontrib><creatorcontrib>Hu, Yang</creatorcontrib><creatorcontrib>Shi, Bo-yun</creatorcontrib><creatorcontrib>Zhu, Jia</creatorcontrib><creatorcontrib>Wang, Juan</creatorcontrib><creatorcontrib>Huang, Jun-ting</creatorcontrib><creatorcontrib>Sun, Fei-fei</creatorcontrib><creatorcontrib>Zhang, Lian</creatorcontrib><creatorcontrib>Zhou, Xin-ke</creatorcontrib><creatorcontrib>Lu, Su-ying</creatorcontrib><creatorcontrib>Zhang, Yi-zhuo</creatorcontrib><title>Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney</title><title>Disease markers</title><description>Background. Immune-related long noncoding RNAs (IrlncRNAs) are recognized as important prognostic factors in a variety of cancers, but thus far, their prognostic value in pediatric rhabdoid tumor of the kidney (pRTK) has not been reported. Here, we clarified the associations between IrlncRNAs and overall survival (OS) of pRTK patients and constructed a model to predict their prognosis. Methods. We accessed RNA sequencing data and corresponding clinical data of pRTK from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. An expression profile of immune-related genes (Irgenes) and lncRNAs of pRTK was extracted from the RNA sequencing data. IrlncRNAs were defined by co-expression analysis of lncRNAs and Irgenes. The limma R package was used to identify differential expression IrlncRNAs. Univariate and multivariate Cox regression analyses were conducted to build a prognostic IrlncRNAs model. The performance of this prognostic model was validated by multimethods, like ROC curve analysis. Results. A total of 1097 IrlncRNAs were defined. Univariate Cox regression analysis identified 7 IrlncRNAs (AC004791.2, AP003068.23, RP11-54O7.14, RP11-680F8.1, TBC1D3P1-DHX40P1, TUNAR, and XXbac-BPG308K3.5) and were significantly associated with OS. Multivariate regression analysis constructed the best prognostic model based on the expression of AC004791.2, AP003068.23, RP11-54O7.14, TBC1D3P1-DHX40P1, and TUNAR. According to the prognostic model, a risk score of each patient was calculated, and patients were divided into high-risk and low-risk groups accordingly. The survival time of low-risk patients was significantly better than high-risk patients (p<0.001). Univariate (hazard ratio 1.098, 95% confidence interval 1.048–1.149, p value <0.001) and multivariate (hazard ratio 1.095, 95% confidence interval 1.043–1.150, p value <0.001) analyses confirmed that the prognostic model was reliable and independent in prediction of OS. Time-dependent ROC analysis showed that 1-year survival AUC of prognostic model, stage, age, and sex was 0.824, 0.673, 0.531, and 0.495, respectively, which suggested that the prognostic model was the best predictor of survival in pRTK patients. Conclusions. The prognostic model based on 5 IrlncRNAs was robust and could better predict the survival of pRTK than other clinical factors. Additionally, the mechanism of regulation and action of prognosis-associated lncRNAs could provide new avenues for basic research to explore the mechanism of tumor initiation and development in order to prevent and treat pRTK.</description><subject>Cancer therapies</subject><subject>Cell cycle</subject><subject>Confidence intervals</subject><subject>Data processing</subject><subject>Gene expression</subject><subject>Gene sequencing</subject><subject>Genes</subject><subject>Health hazards</subject><subject>Kidneys</subject><subject>Kinases</subject><subject>Medical prognosis</subject><subject>Metastasis</subject><subject>Multivariate analysis</subject><subject>Non-coding RNA</subject><subject>Patients</subject><subject>Pediatrics</subject><subject>Perl</subject><subject>Prognosis</subject><subject>Regression analysis</subject><subject>Ribonucleic acid</subject><subject>Risk</subject><subject>Risk groups</subject><subject>RNA</subject><subject>Software</subject><subject>Statistical analysis</subject><subject>Survival</subject><subject>Survival analysis</subject><subject>Time dependence</subject><subject>Transcription factors</subject><subject>Tumor necrosis factor-TNF</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>eNp90UFrFDEYBuAgil2rN39AwIugY79kkklyEUqxWrq0Zal4DJkk002ZSWoyo_Tfm2UXwR48BfI9vCTfi9BbAp8I4fyEAqUnTHBKJHuGVkQK3siuhedoBVTIBiiDI_SqlHsAQhVTL9FRywXvmIIV-nExTUv0zcaPZvYOr6PdXJ0WbAq-yekupjIHi8-NnVMueEgZ33gXzJzr7WZrepeCw7fLVAdpwPPW48vgon98jV4MZiz-zeE8Rt_Pv9yefWvW118vzk7XjW0lnRtuJbGcStIrISQxvIeuZ44NxsuOOCpAdcZ2lAuluAHLOnAMhHTE997Ktj1Gn_e5D0s_eWd9nLMZ9UMOk8mPOpmg_53EsNV36ZdWlNSdiRrw_hCQ08_Fl1lPoVg_jib6tBRNO0kYA0mg0ndP6H1acqzf2ylQlXBZ1ce9sjmVkv3w9zEE9K4xvWtMHxqr_MOeb0N05nf4v_4DpeOSwg</recordid><startdate>20220615</startdate><enddate>20220615</enddate><creator>Hong, Ye</creator><creator>Que, Yi</creator><creator>Hu, Yang</creator><creator>Shi, Bo-yun</creator><creator>Zhu, Jia</creator><creator>Wang, Juan</creator><creator>Huang, Jun-ting</creator><creator>Sun, Fei-fei</creator><creator>Zhang, Lian</creator><creator>Zhou, Xin-ke</creator><creator>Lu, Su-ying</creator><creator>Zhang, Yi-zhuo</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</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/0000-0002-6128-3476</orcidid><orcidid>https://orcid.org/0000-0001-8117-3533</orcidid></search><sort><creationdate>20220615</creationdate><title>Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney</title><author>Hong, Ye ; Que, Yi ; Hu, Yang ; Shi, Bo-yun ; Zhu, Jia ; Wang, Juan ; Huang, Jun-ting ; Sun, Fei-fei ; Zhang, Lian ; Zhou, Xin-ke ; Lu, Su-ying ; Zhang, Yi-zhuo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c382t-5c81c5281b97781a5b06b4d4fae861d27096ac6257995a0c460d4078d1ebec833</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Cancer therapies</topic><topic>Cell cycle</topic><topic>Confidence intervals</topic><topic>Data processing</topic><topic>Gene expression</topic><topic>Gene sequencing</topic><topic>Genes</topic><topic>Health hazards</topic><topic>Kidneys</topic><topic>Kinases</topic><topic>Medical prognosis</topic><topic>Metastasis</topic><topic>Multivariate analysis</topic><topic>Non-coding RNA</topic><topic>Patients</topic><topic>Pediatrics</topic><topic>Perl</topic><topic>Prognosis</topic><topic>Regression analysis</topic><topic>Ribonucleic acid</topic><topic>Risk</topic><topic>Risk groups</topic><topic>RNA</topic><topic>Software</topic><topic>Statistical analysis</topic><topic>Survival</topic><topic>Survival analysis</topic><topic>Time dependence</topic><topic>Transcription factors</topic><topic>Tumor necrosis factor-TNF</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hong, Ye</creatorcontrib><creatorcontrib>Que, Yi</creatorcontrib><creatorcontrib>Hu, Yang</creatorcontrib><creatorcontrib>Shi, Bo-yun</creatorcontrib><creatorcontrib>Zhu, Jia</creatorcontrib><creatorcontrib>Wang, Juan</creatorcontrib><creatorcontrib>Huang, Jun-ting</creatorcontrib><creatorcontrib>Sun, Fei-fei</creatorcontrib><creatorcontrib>Zhang, Lian</creatorcontrib><creatorcontrib>Zhou, Xin-ke</creatorcontrib><creatorcontrib>Lu, Su-ying</creatorcontrib><creatorcontrib>Zhang, Yi-zhuo</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</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>Hong, Ye</au><au>Que, Yi</au><au>Hu, Yang</au><au>Shi, Bo-yun</au><au>Zhu, Jia</au><au>Wang, Juan</au><au>Huang, Jun-ting</au><au>Sun, Fei-fei</au><au>Zhang, Lian</au><au>Zhou, Xin-ke</au><au>Lu, Su-ying</au><au>Zhang, Yi-zhuo</au><au>Zeng, Chengwu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney</atitle><jtitle>Disease markers</jtitle><date>2022-06-15</date><risdate>2022</risdate><volume>2022</volume><spage>1</spage><epage>11</epage><pages>1-11</pages><issn>0278-0240</issn><eissn>1875-8630</eissn><abstract>Background. Immune-related long noncoding RNAs (IrlncRNAs) are recognized as important prognostic factors in a variety of cancers, but thus far, their prognostic value in pediatric rhabdoid tumor of the kidney (pRTK) has not been reported. Here, we clarified the associations between IrlncRNAs and overall survival (OS) of pRTK patients and constructed a model to predict their prognosis. Methods. We accessed RNA sequencing data and corresponding clinical data of pRTK from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. An expression profile of immune-related genes (Irgenes) and lncRNAs of pRTK was extracted from the RNA sequencing data. IrlncRNAs were defined by co-expression analysis of lncRNAs and Irgenes. The limma R package was used to identify differential expression IrlncRNAs. Univariate and multivariate Cox regression analyses were conducted to build a prognostic IrlncRNAs model. The performance of this prognostic model was validated by multimethods, like ROC curve analysis. Results. A total of 1097 IrlncRNAs were defined. Univariate Cox regression analysis identified 7 IrlncRNAs (AC004791.2, AP003068.23, RP11-54O7.14, RP11-680F8.1, TBC1D3P1-DHX40P1, TUNAR, and XXbac-BPG308K3.5) and were significantly associated with OS. Multivariate regression analysis constructed the best prognostic model based on the expression of AC004791.2, AP003068.23, RP11-54O7.14, TBC1D3P1-DHX40P1, and TUNAR. According to the prognostic model, a risk score of each patient was calculated, and patients were divided into high-risk and low-risk groups accordingly. The survival time of low-risk patients was significantly better than high-risk patients (p<0.001). Univariate (hazard ratio 1.098, 95% confidence interval 1.048–1.149, p value <0.001) and multivariate (hazard ratio 1.095, 95% confidence interval 1.043–1.150, p value <0.001) analyses confirmed that the prognostic model was reliable and independent in prediction of OS. Time-dependent ROC analysis showed that 1-year survival AUC of prognostic model, stage, age, and sex was 0.824, 0.673, 0.531, and 0.495, respectively, which suggested that the prognostic model was the best predictor of survival in pRTK patients. Conclusions. The prognostic model based on 5 IrlncRNAs was robust and could better predict the survival of pRTK than other clinical factors. Additionally, the mechanism of regulation and action of prognosis-associated lncRNAs could provide new avenues for basic research to explore the mechanism of tumor initiation and development in order to prevent and treat pRTK.</abstract><cop>Amsterdam</cop><pub>Hindawi</pub><pmid>35756490</pmid><doi>10.1155/2022/4752184</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-6128-3476</orcidid><orcidid>https://orcid.org/0000-0001-8117-3533</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Cancer therapies Cell cycle Confidence intervals Data processing Gene expression Gene sequencing Genes Health hazards Kidneys Kinases Medical prognosis Metastasis Multivariate analysis Non-coding RNA Patients Pediatrics Perl Prognosis Regression analysis Ribonucleic acid Risk Risk groups RNA Software Statistical analysis Survival Survival analysis Time dependence Transcription factors Tumor necrosis factor-TNF Tumors |
| title | Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney |
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