Construction and Validation of a Prognostic Risk Prediction Model for Lactate Metabolism-Related lncRNA in Endometrial Cancer
Endometrial cancer (EC) is a common group of malignant epithelial tumors that mainly occur in the female endometrium. Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to es...
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| Veröffentlicht in: | Biochemical genetics 2024-04, Vol.62 (2), p.741-760 |
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| creator | Chang, Fenghua Liu, Hongyang Wan, Junhu Gao, Ya Wang, Zhiting Zhang, Lindong Feng, Quanling |
| description | Endometrial cancer (EC) is a common group of malignant epithelial tumors that mainly occur in the female endometrium. Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to establish a prognostic risk model for EC based on lactate metabolism-related lncRNA to forecast the prognosis of EC patients. First, we found that 38 lactate metabolism-associated lncRNAs were significantly overall survival through univariate Cox regression analysis. Using minimum absolute contraction and selection operator (LASSO) regression analysis and multivariate Cox regression analysis, six lactate metabolism-related lncRNAs were established as independent predictor in EC patients and were used to establish a prognostic risk signature. We next used multifactorial COX regression analysis and receiver operating characteristic (ROC) curve analysis to confirm that risk score was an independent prognostic factor of overall patient survival. The survival time of patients with EC in different high-risk populations was obviously related to clinicopathological factors. In addition, lactate metabolism-related lncRNA in high-risk population participated in multiple aspects of EC malignant progress through Gene Set Enrichment Analysis, Genomes pathway and Kyoto Encyclopedia of Genes and Gene Ontology. And risk scores were strongly associated with tumor mutation burden, immunotherapy response and microsatellite instability. Finally, we chose a lncRNA SRP14-AS1 to validate the model we have constructed. Interestingly, we observed that the expression degree of SRP14-AS1 was lower in tumor tissues of EC patients than in normal tissues, which was consistent with our findings in the TCGA database. In conclusion, our study constructed a prognostic risk model through lactate metabolism-related lncRNA and validated the model, confirming that the model can be used to predict the prognosis of EC patients and providing a molecular analysis of potential prognostic lncRNA for EC. |
| doi_str_mv | 10.1007/s10528-023-10443-4 |
| format | Article |
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Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to establish a prognostic risk model for EC based on lactate metabolism-related lncRNA to forecast the prognosis of EC patients. First, we found that 38 lactate metabolism-associated lncRNAs were significantly overall survival through univariate Cox regression analysis. Using minimum absolute contraction and selection operator (LASSO) regression analysis and multivariate Cox regression analysis, six lactate metabolism-related lncRNAs were established as independent predictor in EC patients and were used to establish a prognostic risk signature. We next used multifactorial COX regression analysis and receiver operating characteristic (ROC) curve analysis to confirm that risk score was an independent prognostic factor of overall patient survival. The survival time of patients with EC in different high-risk populations was obviously related to clinicopathological factors. In addition, lactate metabolism-related lncRNA in high-risk population participated in multiple aspects of EC malignant progress through Gene Set Enrichment Analysis, Genomes pathway and Kyoto Encyclopedia of Genes and Gene Ontology. And risk scores were strongly associated with tumor mutation burden, immunotherapy response and microsatellite instability. Finally, we chose a lncRNA SRP14-AS1 to validate the model we have constructed. Interestingly, we observed that the expression degree of SRP14-AS1 was lower in tumor tissues of EC patients than in normal tissues, which was consistent with our findings in the TCGA database. In conclusion, our study constructed a prognostic risk model through lactate metabolism-related lncRNA and validated the model, confirming that the model can be used to predict the prognosis of EC patients and providing a molecular analysis of potential prognostic lncRNA for EC.</description><identifier>ISSN: 0006-2928</identifier><identifier>ISSN: 1573-4927</identifier><identifier>EISSN: 1573-4927</identifier><identifier>DOI: 10.1007/s10528-023-10443-4</identifier><identifier>PMID: 37423972</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>at-risk population ; Biochemistry ; Biomedical and Life Sciences ; Biomedicine ; Cancer ; Carcinoma ; Encyclopedias ; Endometrial cancer ; Endometrial Neoplasms - genetics ; Endometrium ; epithelium ; Female ; females ; gene ontology ; Gene set enrichment analysis ; genes ; Genomes ; Human Genetics ; Humans ; Immunotherapy ; Lactic Acid ; Medical Microbiology ; Medical prognosis ; Metabolism ; Microsatellite instability ; microsatellite repeats ; model validation ; mutation ; Non-coding RNA ; Original Article ; patients ; Prediction models ; Prognosis ; Regression analysis ; risk ; RNA, Long Noncoding - genetics ; Survival ; Tumors ; Uterine cancer ; uterine neoplasms ; Zoology</subject><ispartof>Biochemical genetics, 2024-04, Vol.62 (2), p.741-760</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c359t-84508addc3b2cdd4385d3b518957a02c474640670083565dad55774313ae4ffd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10528-023-10443-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10528-023-10443-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37423972$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chang, Fenghua</creatorcontrib><creatorcontrib>Liu, Hongyang</creatorcontrib><creatorcontrib>Wan, Junhu</creatorcontrib><creatorcontrib>Gao, Ya</creatorcontrib><creatorcontrib>Wang, Zhiting</creatorcontrib><creatorcontrib>Zhang, Lindong</creatorcontrib><creatorcontrib>Feng, Quanling</creatorcontrib><title>Construction and Validation of a Prognostic Risk Prediction Model for Lactate Metabolism-Related lncRNA in Endometrial Cancer</title><title>Biochemical genetics</title><addtitle>Biochem Genet</addtitle><addtitle>Biochem Genet</addtitle><description>Endometrial cancer (EC) is a common group of malignant epithelial tumors that mainly occur in the female endometrium. Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to establish a prognostic risk model for EC based on lactate metabolism-related lncRNA to forecast the prognosis of EC patients. First, we found that 38 lactate metabolism-associated lncRNAs were significantly overall survival through univariate Cox regression analysis. Using minimum absolute contraction and selection operator (LASSO) regression analysis and multivariate Cox regression analysis, six lactate metabolism-related lncRNAs were established as independent predictor in EC patients and were used to establish a prognostic risk signature. We next used multifactorial COX regression analysis and receiver operating characteristic (ROC) curve analysis to confirm that risk score was an independent prognostic factor of overall patient survival. The survival time of patients with EC in different high-risk populations was obviously related to clinicopathological factors. In addition, lactate metabolism-related lncRNA in high-risk population participated in multiple aspects of EC malignant progress through Gene Set Enrichment Analysis, Genomes pathway and Kyoto Encyclopedia of Genes and Gene Ontology. And risk scores were strongly associated with tumor mutation burden, immunotherapy response and microsatellite instability. Finally, we chose a lncRNA SRP14-AS1 to validate the model we have constructed. Interestingly, we observed that the expression degree of SRP14-AS1 was lower in tumor tissues of EC patients than in normal tissues, which was consistent with our findings in the TCGA database. In conclusion, our study constructed a prognostic risk model through lactate metabolism-related lncRNA and validated the model, confirming that the model can be used to predict the prognosis of EC patients and providing a molecular analysis of potential prognostic lncRNA for EC.</description><subject>at-risk population</subject><subject>Biochemistry</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Cancer</subject><subject>Carcinoma</subject><subject>Encyclopedias</subject><subject>Endometrial cancer</subject><subject>Endometrial Neoplasms - genetics</subject><subject>Endometrium</subject><subject>epithelium</subject><subject>Female</subject><subject>females</subject><subject>gene ontology</subject><subject>Gene set enrichment analysis</subject><subject>genes</subject><subject>Genomes</subject><subject>Human Genetics</subject><subject>Humans</subject><subject>Immunotherapy</subject><subject>Lactic Acid</subject><subject>Medical Microbiology</subject><subject>Medical prognosis</subject><subject>Metabolism</subject><subject>Microsatellite instability</subject><subject>microsatellite repeats</subject><subject>model validation</subject><subject>mutation</subject><subject>Non-coding RNA</subject><subject>Original Article</subject><subject>patients</subject><subject>Prediction models</subject><subject>Prognosis</subject><subject>Regression analysis</subject><subject>risk</subject><subject>RNA, Long Noncoding - genetics</subject><subject>Survival</subject><subject>Tumors</subject><subject>Uterine cancer</subject><subject>uterine neoplasms</subject><subject>Zoology</subject><issn>0006-2928</issn><issn>1573-4927</issn><issn>1573-4927</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkU9PHSEUxUlTU1-1X8CFIXHTzVT-DszSvGjb5GmbF9st4QFjUAYUmEUX_e6ljm0TF3YFh_u754Z7ADjC6ANGSJwWjDiRHSK0w4gx2rFXYIW5aJeBiNdghRDqOzIQuQ_elnLb5NC4N2CfCkboIMgK_FynWGqeTfUpQh0t_K6Dt_pRphFq-DWnm5hK9QZufblr2lm_4JfJugDHlOFGm6qrg5eu6l0Kvkzd1oX2YmGIZnt1Bn2E59GmydXsdYBrHY3Lh2Bv1KG4d0_nAfh2cX69_tRtvnz8vD7bdIbyoXaScSS1tYbuiLGWUckt3XEsBy40IoYJ1jPUC4Qk5T232nIuBKOYasfG0dID8H7xvc_pYXalqskX40LQ0aW5KIo57YlktP8vSiRvq24saejJM_Q2zTm2jyiKGO6bH0aNIgtlciolu1HdZz_p_ENhpH7nqJYcVctRPeaoWGs6frKed5Ozf1v-BNcAugClleKNy_9mv2D7C2PUpxQ</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>Chang, Fenghua</creator><creator>Liu, Hongyang</creator><creator>Wan, Junhu</creator><creator>Gao, Ya</creator><creator>Wang, Zhiting</creator><creator>Zhang, Lindong</creator><creator>Feng, Quanling</creator><general>Springer US</general><general>Springer Nature B.V</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>7SS</scope><scope>7TK</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20240401</creationdate><title>Construction and Validation of a Prognostic Risk Prediction Model for Lactate Metabolism-Related lncRNA in Endometrial Cancer</title><author>Chang, Fenghua ; Liu, Hongyang ; Wan, Junhu ; Gao, Ya ; Wang, Zhiting ; Zhang, Lindong ; Feng, Quanling</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-84508addc3b2cdd4385d3b518957a02c474640670083565dad55774313ae4ffd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>at-risk population</topic><topic>Biochemistry</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Cancer</topic><topic>Carcinoma</topic><topic>Encyclopedias</topic><topic>Endometrial cancer</topic><topic>Endometrial Neoplasms - genetics</topic><topic>Endometrium</topic><topic>epithelium</topic><topic>Female</topic><topic>females</topic><topic>gene ontology</topic><topic>Gene set enrichment analysis</topic><topic>genes</topic><topic>Genomes</topic><topic>Human Genetics</topic><topic>Humans</topic><topic>Immunotherapy</topic><topic>Lactic Acid</topic><topic>Medical Microbiology</topic><topic>Medical prognosis</topic><topic>Metabolism</topic><topic>Microsatellite instability</topic><topic>microsatellite repeats</topic><topic>model validation</topic><topic>mutation</topic><topic>Non-coding RNA</topic><topic>Original Article</topic><topic>patients</topic><topic>Prediction models</topic><topic>Prognosis</topic><topic>Regression analysis</topic><topic>risk</topic><topic>RNA, Long Noncoding - genetics</topic><topic>Survival</topic><topic>Tumors</topic><topic>Uterine cancer</topic><topic>uterine neoplasms</topic><topic>Zoology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chang, Fenghua</creatorcontrib><creatorcontrib>Liu, Hongyang</creatorcontrib><creatorcontrib>Wan, Junhu</creatorcontrib><creatorcontrib>Gao, Ya</creatorcontrib><creatorcontrib>Wang, Zhiting</creatorcontrib><creatorcontrib>Zhang, Lindong</creatorcontrib><creatorcontrib>Feng, Quanling</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Biochemical genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chang, Fenghua</au><au>Liu, Hongyang</au><au>Wan, Junhu</au><au>Gao, Ya</au><au>Wang, Zhiting</au><au>Zhang, Lindong</au><au>Feng, Quanling</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Construction and Validation of a Prognostic Risk Prediction Model for Lactate Metabolism-Related lncRNA in Endometrial Cancer</atitle><jtitle>Biochemical genetics</jtitle><stitle>Biochem Genet</stitle><addtitle>Biochem Genet</addtitle><date>2024-04-01</date><risdate>2024</risdate><volume>62</volume><issue>2</issue><spage>741</spage><epage>760</epage><pages>741-760</pages><issn>0006-2928</issn><issn>1573-4927</issn><eissn>1573-4927</eissn><abstract>Endometrial cancer (EC) is a common group of malignant epithelial tumors that mainly occur in the female endometrium. Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to establish a prognostic risk model for EC based on lactate metabolism-related lncRNA to forecast the prognosis of EC patients. First, we found that 38 lactate metabolism-associated lncRNAs were significantly overall survival through univariate Cox regression analysis. Using minimum absolute contraction and selection operator (LASSO) regression analysis and multivariate Cox regression analysis, six lactate metabolism-related lncRNAs were established as independent predictor in EC patients and were used to establish a prognostic risk signature. We next used multifactorial COX regression analysis and receiver operating characteristic (ROC) curve analysis to confirm that risk score was an independent prognostic factor of overall patient survival. The survival time of patients with EC in different high-risk populations was obviously related to clinicopathological factors. In addition, lactate metabolism-related lncRNA in high-risk population participated in multiple aspects of EC malignant progress through Gene Set Enrichment Analysis, Genomes pathway and Kyoto Encyclopedia of Genes and Gene Ontology. And risk scores were strongly associated with tumor mutation burden, immunotherapy response and microsatellite instability. Finally, we chose a lncRNA SRP14-AS1 to validate the model we have constructed. Interestingly, we observed that the expression degree of SRP14-AS1 was lower in tumor tissues of EC patients than in normal tissues, which was consistent with our findings in the TCGA database. In conclusion, our study constructed a prognostic risk model through lactate metabolism-related lncRNA and validated the model, confirming that the model can be used to predict the prognosis of EC patients and providing a molecular analysis of potential prognostic lncRNA for EC.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>37423972</pmid><doi>10.1007/s10528-023-10443-4</doi><tpages>20</tpages></addata></record> |
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| subjects | at-risk population Biochemistry Biomedical and Life Sciences Biomedicine Cancer Carcinoma Encyclopedias Endometrial cancer Endometrial Neoplasms - genetics Endometrium epithelium Female females gene ontology Gene set enrichment analysis genes Genomes Human Genetics Humans Immunotherapy Lactic Acid Medical Microbiology Medical prognosis Metabolism Microsatellite instability microsatellite repeats model validation mutation Non-coding RNA Original Article patients Prediction models Prognosis Regression analysis risk RNA, Long Noncoding - genetics Survival Tumors Uterine cancer uterine neoplasms Zoology |
| title | Construction and Validation of a Prognostic Risk Prediction Model for Lactate Metabolism-Related lncRNA in Endometrial Cancer |
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