Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancer
Abstract Background Esophageal cancer (EC), one highly malignant gastrointestinal cancer, is the 6th leading cause of cancer-related deaths worldwide. Necroptosis and long non-coding RNA (lncRNA) play important roles in the occurrence and development of EC, but the research on the role of necroptosi...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-07-01
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| Series: | BMC Gastroenterology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12876-022-02421-8 |
| _version_ | 1818474044133998592 |
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| author | Yang Liu Hongyu Hao Lin Kang Guona Zheng Xiaowan Guo Bingjie Li Huanfen Zhao Han Hao |
| author_facet | Yang Liu Hongyu Hao Lin Kang Guona Zheng Xiaowan Guo Bingjie Li Huanfen Zhao Han Hao |
| author_sort | Yang Liu |
| collection | DOAJ |
| description | Abstract Background Esophageal cancer (EC), one highly malignant gastrointestinal cancer, is the 6th leading cause of cancer-related deaths worldwide. Necroptosis and long non-coding RNA (lncRNA) play important roles in the occurrence and development of EC, but the research on the role of necroptosis-related lncRNA in EC is not conclusive. This study aims to use bioinformatics to investigate the prognostic value of necroptosis-related lncRNA in EC. Methods Transcriptome data containing EC and normal samples, and clinical information were obtained from the Cancer Genome Atlas database. 102 necroptosis-related genes were obtained from Kanehisa Laboratories. Necroptosis-related lncRNAs were screened out via univariate, multivariate Cox and the least absolute shrinkage and selection operator regression analyses to construct the risk predictive model. The reliability of the risk model was evaluated mainly through quantitative real-time PCR (qRT-PCR), the receiver operating characteristic (ROC) curves and the constructed nomogram. KEGG pathways were explored in the high- and low-risk groups of EC patients via gene set enrichment analyses (GSEA) software. Immune microenvironment and potential therapeutic agents in risk groups were also analyzed. Results A 6 necroptosis-related lncRNAs risk model composed of AC022211.2, Z94721.1, AC007991.2, SAMD12-AS1, AL035461.2 and AC051619.4 was established to predict the prognosis level of EC patients. qRT-PCR analysis showed upregulated Z94721.1 and AL035461.2 mRNA levels and downregulated AC051619.4 mRNA level in EC tissues compared with normal tissues. According to clinical characteristics, the patients in the high-risk group had a shorter overall survival than the low-risk group. The ROC curve and nomogram confirmed this model as one independent and predominant predictor. GSEA analysis showed metabolic and immune-related pathways enriched in the risk model. Most of the immune cells and immune checkpoints were positively correlated with the risk model, mainly active in the high-risk group. For the prediction of potential therapeutic drugs, 16 compounds in the high-risk group and 2 compounds in the low-risk group exhibited higher sensitivity. Conclusions Our results supported the necroptosis-related lncRNA signature could independently predict prognosis of EC patients, and provided theoretical basis for improving the clinical treatment of EC. |
| first_indexed | 2024-04-14T04:31:19Z |
| format | Article |
| id | doaj.art-139afde094eb4921ace058ba4a31761d |
| institution | Directory Open Access Journal |
| issn | 1471-230X |
| language | English |
| last_indexed | 2024-04-14T04:31:19Z |
| publishDate | 2022-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Gastroenterology |
| spelling | doaj.art-139afde094eb4921ace058ba4a31761d2022-12-22T02:12:01ZengBMCBMC Gastroenterology1471-230X2022-07-0122111810.1186/s12876-022-02421-8Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancerYang Liu0Hongyu Hao1Lin Kang2Guona Zheng3Xiaowan Guo4Bingjie Li5Huanfen Zhao6Han Hao7Department of Pathology, Hebei General HospitalDepartment of Neurology, Hebei General HospitalDepartment of Pathology, Hebei General HospitalDepartment of Pathology, Hebei General HospitalDepartment of Radiology, Hebei General HospitalDepartment of Pathology, Hebei General HospitalDepartment of Pathology, Hebei General HospitalDepartment of Pharmacology, The Key Laboratory of New Drug Pharmacology and Toxicology, Center of Innovative Drug Research and Evaluation, Hebei Medical UniversityAbstract Background Esophageal cancer (EC), one highly malignant gastrointestinal cancer, is the 6th leading cause of cancer-related deaths worldwide. Necroptosis and long non-coding RNA (lncRNA) play important roles in the occurrence and development of EC, but the research on the role of necroptosis-related lncRNA in EC is not conclusive. This study aims to use bioinformatics to investigate the prognostic value of necroptosis-related lncRNA in EC. Methods Transcriptome data containing EC and normal samples, and clinical information were obtained from the Cancer Genome Atlas database. 102 necroptosis-related genes were obtained from Kanehisa Laboratories. Necroptosis-related lncRNAs were screened out via univariate, multivariate Cox and the least absolute shrinkage and selection operator regression analyses to construct the risk predictive model. The reliability of the risk model was evaluated mainly through quantitative real-time PCR (qRT-PCR), the receiver operating characteristic (ROC) curves and the constructed nomogram. KEGG pathways were explored in the high- and low-risk groups of EC patients via gene set enrichment analyses (GSEA) software. Immune microenvironment and potential therapeutic agents in risk groups were also analyzed. Results A 6 necroptosis-related lncRNAs risk model composed of AC022211.2, Z94721.1, AC007991.2, SAMD12-AS1, AL035461.2 and AC051619.4 was established to predict the prognosis level of EC patients. qRT-PCR analysis showed upregulated Z94721.1 and AL035461.2 mRNA levels and downregulated AC051619.4 mRNA level in EC tissues compared with normal tissues. According to clinical characteristics, the patients in the high-risk group had a shorter overall survival than the low-risk group. The ROC curve and nomogram confirmed this model as one independent and predominant predictor. GSEA analysis showed metabolic and immune-related pathways enriched in the risk model. Most of the immune cells and immune checkpoints were positively correlated with the risk model, mainly active in the high-risk group. For the prediction of potential therapeutic drugs, 16 compounds in the high-risk group and 2 compounds in the low-risk group exhibited higher sensitivity. Conclusions Our results supported the necroptosis-related lncRNA signature could independently predict prognosis of EC patients, and provided theoretical basis for improving the clinical treatment of EC.https://doi.org/10.1186/s12876-022-02421-8ECNecroptosislncRNAPrognosisImmune |
| spellingShingle | Yang Liu Hongyu Hao Lin Kang Guona Zheng Xiaowan Guo Bingjie Li Huanfen Zhao Han Hao Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancer BMC Gastroenterology EC Necroptosis lncRNA Prognosis Immune |
| title | Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancer |
| title_full | Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancer |
| title_fullStr | Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancer |
| title_full_unstemmed | Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancer |
| title_short | Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancer |
| title_sort | construction of a novel necroptosis related lncrna signature for prognosis prediction in esophageal cancer |
| topic | EC Necroptosis lncRNA Prognosis Immune |
| url | https://doi.org/10.1186/s12876-022-02421-8 |
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