A novel cuproptosis-related lncRNA prognostic risk score model for gastric cancer based on bioinformatics
Objective To establish an effective cuproptosis-related long non-coding ribonucleic acid (lncRNA) (CRL) prognostic risk score (RS) model (CRLPRSM) for the prediction of the outcomes of patients with gastric cancer (GC). Introduction Cuproptosis is an up-to-date mode of cell death, and its action mec...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2022-09-01
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| Series: | European Journal of Inflammation |
| Online Access: | https://doi.org/10.1177/1721727X221128266 |
| _version_ | 1811182274502197248 |
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| author | Xue Du Yu Xiao Chunbao Chen Lu Yang Yu Cui Tingting Wu Bangxian Tan |
| author_facet | Xue Du Yu Xiao Chunbao Chen Lu Yang Yu Cui Tingting Wu Bangxian Tan |
| author_sort | Xue Du |
| collection | DOAJ |
| description | Objective To establish an effective cuproptosis-related long non-coding ribonucleic acid (lncRNA) (CRL) prognostic risk score (RS) model (CRLPRSM) for the prediction of the outcomes of patients with gastric cancer (GC). Introduction Cuproptosis is an up-to-date mode of cell death, and its action mechanism is different from all other known mechanisms that regulate cell death. LncRNAs are RNA species that are over 200 nt long and do not encode proteins. They have prominent actions in tumor onset and development, and their involvement in a variety of intracellular regulatory processes is vital for cell proliferation and differentiation, so they may serve as prognostic biomarkers in tumor patients. Methods We retrieved cuproptosis-associated clinical and lncRNA expression data of GC cases from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD). Then a CRLPRSM was built based on univariate and multivariate Cox regression (UCR and MCR) analyses. As per the RS, the patients fell into high- and low-risk group. Later, the predictive efficacy of the CRLPRSM was confirmed with the aid of Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC) curve analysis. Next, combining independent prognostic factors in clinical characteristics, we plotted a prognosis-related nomogram to predict one-year, three-year and five-year overall survival (OS) in GC patients. Finally, we implemented Gene Ontology enrichment analysis (GOEA) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis (KEGGEA) for clarifying the possible biological actions and molecular mechanisms. Results The constructed CRLPRSM consisted of 3 CRLs, namely, AC092574.1, MAGI2-AS3, AC090204.1. It was found that the hazard ratio (HR) was 1.911 (1.337–2.731) ( p < 0.001) in UCR analysis and 1.852 (1.286–1.668) ( p < 0.001) in MCR analysis, and the AUC of the CRLPRSM was 0.649. Moreover, the KM analysis showed a pronounced intergroup difference in survival, and the nomogram illustrated some clinical benefits of CRLPRSM. Furthermore, GO terms and KEGG pathways were unveiled to be significantly enriched. Conclusion The constructed CRLPRSM has a significant predicted value for GC patient prognosis, and CRLs may become novel hallmarks for clinical treatment of GC. |
| first_indexed | 2024-04-11T09:30:06Z |
| format | Article |
| id | doaj.art-55500c0ab403486a81b503484d2cb50f |
| institution | Directory Open Access Journal |
| issn | 2058-7392 |
| language | English |
| last_indexed | 2024-04-11T09:30:06Z |
| publishDate | 2022-09-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | European Journal of Inflammation |
| spelling | doaj.art-55500c0ab403486a81b503484d2cb50f2022-12-22T04:31:55ZengSAGE PublishingEuropean Journal of Inflammation2058-73922022-09-012010.1177/1721727X221128266A novel cuproptosis-related lncRNA prognostic risk score model for gastric cancer based on bioinformaticsXue DuYu XiaoChunbao ChenLu YangYu CuiTingting WuBangxian TanObjective To establish an effective cuproptosis-related long non-coding ribonucleic acid (lncRNA) (CRL) prognostic risk score (RS) model (CRLPRSM) for the prediction of the outcomes of patients with gastric cancer (GC). Introduction Cuproptosis is an up-to-date mode of cell death, and its action mechanism is different from all other known mechanisms that regulate cell death. LncRNAs are RNA species that are over 200 nt long and do not encode proteins. They have prominent actions in tumor onset and development, and their involvement in a variety of intracellular regulatory processes is vital for cell proliferation and differentiation, so they may serve as prognostic biomarkers in tumor patients. Methods We retrieved cuproptosis-associated clinical and lncRNA expression data of GC cases from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD). Then a CRLPRSM was built based on univariate and multivariate Cox regression (UCR and MCR) analyses. As per the RS, the patients fell into high- and low-risk group. Later, the predictive efficacy of the CRLPRSM was confirmed with the aid of Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC) curve analysis. Next, combining independent prognostic factors in clinical characteristics, we plotted a prognosis-related nomogram to predict one-year, three-year and five-year overall survival (OS) in GC patients. Finally, we implemented Gene Ontology enrichment analysis (GOEA) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis (KEGGEA) for clarifying the possible biological actions and molecular mechanisms. Results The constructed CRLPRSM consisted of 3 CRLs, namely, AC092574.1, MAGI2-AS3, AC090204.1. It was found that the hazard ratio (HR) was 1.911 (1.337–2.731) ( p < 0.001) in UCR analysis and 1.852 (1.286–1.668) ( p < 0.001) in MCR analysis, and the AUC of the CRLPRSM was 0.649. Moreover, the KM analysis showed a pronounced intergroup difference in survival, and the nomogram illustrated some clinical benefits of CRLPRSM. Furthermore, GO terms and KEGG pathways were unveiled to be significantly enriched. Conclusion The constructed CRLPRSM has a significant predicted value for GC patient prognosis, and CRLs may become novel hallmarks for clinical treatment of GC.https://doi.org/10.1177/1721727X221128266 |
| spellingShingle | Xue Du Yu Xiao Chunbao Chen Lu Yang Yu Cui Tingting Wu Bangxian Tan A novel cuproptosis-related lncRNA prognostic risk score model for gastric cancer based on bioinformatics European Journal of Inflammation |
| title | A novel cuproptosis-related lncRNA prognostic risk score model for gastric cancer based on bioinformatics |
| title_full | A novel cuproptosis-related lncRNA prognostic risk score model for gastric cancer based on bioinformatics |
| title_fullStr | A novel cuproptosis-related lncRNA prognostic risk score model for gastric cancer based on bioinformatics |
| title_full_unstemmed | A novel cuproptosis-related lncRNA prognostic risk score model for gastric cancer based on bioinformatics |
| title_short | A novel cuproptosis-related lncRNA prognostic risk score model for gastric cancer based on bioinformatics |
| title_sort | novel cuproptosis related lncrna prognostic risk score model for gastric cancer based on bioinformatics |
| url | https://doi.org/10.1177/1721727X221128266 |
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