{"title":"神经母细胞瘤中免疫基因和免疫相关lncrna的预后特征:基于GEO和TARGET数据集的研究","authors":"Xiaodan Zhong, Ying Tao, Jian Chang, Yutong Zhang, Hao Zhang, Linyu Wang, Yuanning Liu","doi":"10.3389/fonc.2021.631546","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The prognostic value of immune-related genes and lncRNAs in neuroblastoma has not been elucidated, especially in subgroups with different outcomes. This study aimed to explore immune-related prognostic signatures.</p><p><strong>Materials and methods: </strong>Immune-related prognostic genes and lncRNAs were identified by univariate Cox regression analysis in the training set. The top 20 C-index genes and 17 immune-related lncRNAs were included in prognostic model construction, and random forest and the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithms were employed to select features. The risk score model was constructed and assessed using the Kaplan-Meier plot and the receiver operating characteristic curve. Functional enrichment analysis of the immune-related lncRNAs was conducted using the STRING database.</p><p><strong>Results: </strong>In GSE49710, five immune genes (CDK4, PIK3R1, THRA, MAP2K2, and ULBP2) were included in the risk score five genes (RS5_G) signature, and eleven immune-related lncRNAs (LINC00260, FAM13A1OS, AGPAT4-IT1, DUBR, MIAT, TSC22D1-AS1, DANCR, MIR137HG, ERC2-IT1, LINC01184, LINC00667) were brought into risk score LncRNAs (RS_Lnc) signature. Patients were divided into high/low-risk score groups by the median. Overall survival and event/progression-free survival time were shortened in patients with high scores, both in training and validation cohorts. The same results were found in subgroups. In grouping ability assessment, the area under the curves (AUCs) in distinguishing different groups ranged from 0.737 to 0.94, better in discriminating MYCN status and high risk in training cohort (higher than 0.9). Multivariate Cox analysis demonstrated that RS5_G and RS_Lnc were the independent risk factors for overall and event/progression-free survival (all p-values <0.001). Correlation analysis showed that RS5_G and RS_Lnc were negatively associated with aDC, CD8+ T cells, but positively correlated with Th2 cells. Functional enrichment analyzes demonstrated that immune-related lncRNAs are mainly enriched in cancer-related pathways and immune-related pathways.</p><p><strong>Conclusion: </strong>We identified the immune-related prognostic signature RS5_G and RS_Lnc. The predicting and grouping ability is close to being even better than those reported in other studies, especially in subgroups. This study provided prognostic signatures that may help clinicians to choose optimal treatment strategies and showed a new insight for NB treatment. These results need further biological experiments and clinical validation.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":" ","pages":"631546"},"PeriodicalIF":4.3000,"publicationDate":"2021-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985261/pdf/","citationCount":"12","resultStr":"{\"title\":\"Prognostic Signature of Immune Genes and Immune-Related LncRNAs in Neuroblastoma: A Study Based on GEO and TARGET Datasets.\",\"authors\":\"Xiaodan Zhong, Ying Tao, Jian Chang, Yutong Zhang, Hao Zhang, Linyu Wang, Yuanning Liu\",\"doi\":\"10.3389/fonc.2021.631546\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The prognostic value of immune-related genes and lncRNAs in neuroblastoma has not been elucidated, especially in subgroups with different outcomes. This study aimed to explore immune-related prognostic signatures.</p><p><strong>Materials and methods: </strong>Immune-related prognostic genes and lncRNAs were identified by univariate Cox regression analysis in the training set. The top 20 C-index genes and 17 immune-related lncRNAs were included in prognostic model construction, and random forest and the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithms were employed to select features. The risk score model was constructed and assessed using the Kaplan-Meier plot and the receiver operating characteristic curve. Functional enrichment analysis of the immune-related lncRNAs was conducted using the STRING database.</p><p><strong>Results: </strong>In GSE49710, five immune genes (CDK4, PIK3R1, THRA, MAP2K2, and ULBP2) were included in the risk score five genes (RS5_G) signature, and eleven immune-related lncRNAs (LINC00260, FAM13A1OS, AGPAT4-IT1, DUBR, MIAT, TSC22D1-AS1, DANCR, MIR137HG, ERC2-IT1, LINC01184, LINC00667) were brought into risk score LncRNAs (RS_Lnc) signature. Patients were divided into high/low-risk score groups by the median. Overall survival and event/progression-free survival time were shortened in patients with high scores, both in training and validation cohorts. The same results were found in subgroups. In grouping ability assessment, the area under the curves (AUCs) in distinguishing different groups ranged from 0.737 to 0.94, better in discriminating MYCN status and high risk in training cohort (higher than 0.9). Multivariate Cox analysis demonstrated that RS5_G and RS_Lnc were the independent risk factors for overall and event/progression-free survival (all p-values <0.001). Correlation analysis showed that RS5_G and RS_Lnc were negatively associated with aDC, CD8+ T cells, but positively correlated with Th2 cells. Functional enrichment analyzes demonstrated that immune-related lncRNAs are mainly enriched in cancer-related pathways and immune-related pathways.</p><p><strong>Conclusion: </strong>We identified the immune-related prognostic signature RS5_G and RS_Lnc. The predicting and grouping ability is close to being even better than those reported in other studies, especially in subgroups. This study provided prognostic signatures that may help clinicians to choose optimal treatment strategies and showed a new insight for NB treatment. These results need further biological experiments and clinical validation.</p>\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":\" \",\"pages\":\"631546\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2021-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985261/pdf/\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fonc.2021.631546\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fonc.2021.631546","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Prognostic Signature of Immune Genes and Immune-Related LncRNAs in Neuroblastoma: A Study Based on GEO and TARGET Datasets.
Background: The prognostic value of immune-related genes and lncRNAs in neuroblastoma has not been elucidated, especially in subgroups with different outcomes. This study aimed to explore immune-related prognostic signatures.
Materials and methods: Immune-related prognostic genes and lncRNAs were identified by univariate Cox regression analysis in the training set. The top 20 C-index genes and 17 immune-related lncRNAs were included in prognostic model construction, and random forest and the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithms were employed to select features. The risk score model was constructed and assessed using the Kaplan-Meier plot and the receiver operating characteristic curve. Functional enrichment analysis of the immune-related lncRNAs was conducted using the STRING database.
Results: In GSE49710, five immune genes (CDK4, PIK3R1, THRA, MAP2K2, and ULBP2) were included in the risk score five genes (RS5_G) signature, and eleven immune-related lncRNAs (LINC00260, FAM13A1OS, AGPAT4-IT1, DUBR, MIAT, TSC22D1-AS1, DANCR, MIR137HG, ERC2-IT1, LINC01184, LINC00667) were brought into risk score LncRNAs (RS_Lnc) signature. Patients were divided into high/low-risk score groups by the median. Overall survival and event/progression-free survival time were shortened in patients with high scores, both in training and validation cohorts. The same results were found in subgroups. In grouping ability assessment, the area under the curves (AUCs) in distinguishing different groups ranged from 0.737 to 0.94, better in discriminating MYCN status and high risk in training cohort (higher than 0.9). Multivariate Cox analysis demonstrated that RS5_G and RS_Lnc were the independent risk factors for overall and event/progression-free survival (all p-values <0.001). Correlation analysis showed that RS5_G and RS_Lnc were negatively associated with aDC, CD8+ T cells, but positively correlated with Th2 cells. Functional enrichment analyzes demonstrated that immune-related lncRNAs are mainly enriched in cancer-related pathways and immune-related pathways.
Conclusion: We identified the immune-related prognostic signature RS5_G and RS_Lnc. The predicting and grouping ability is close to being even better than those reported in other studies, especially in subgroups. This study provided prognostic signatures that may help clinicians to choose optimal treatment strategies and showed a new insight for NB treatment. These results need further biological experiments and clinical validation.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
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