Construction of an original anoikis-related prognostic model closely related to immune infiltration in gastric cancer
Background: Anoikis is considered as a particular type of programmed cell death, the weakness or resistance of which contributes greatly to the development and progression of most malignant solid tumors. However, the latent impact of anoikis-related genes (ARGs) on gastric cancer (GC) is still ambig...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Genetics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.1087201/full |
| _version_ | 1828072373292630016 |
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| author | Zhihong Zhao Cun Li Ye Peng Rui Liu Qian Li |
| author_facet | Zhihong Zhao Cun Li Ye Peng Rui Liu Qian Li |
| author_sort | Zhihong Zhao |
| collection | DOAJ |
| description | Background: Anoikis is considered as a particular type of programmed cell death, the weakness or resistance of which contributes greatly to the development and progression of most malignant solid tumors. However, the latent impact of anoikis-related genes (ARGs) on gastric cancer (GC) is still ambiguous. Based on these, this study established an anoikis-related prognostic model of GC to identify the prognosis of patients and provide more effective treatment in clinical practice.Methods: First, we extracted four public datasets containing the gene expression and clinicopathological information of GC, which were worked as the training and validating sets, separately. Then, an anoikis-related survival-predicted model of GC was developed via Lasso and COX regression analyses and verified by using the Kaplan-Meier (KM) curve and receiver operating characteristic (ROC) curve analyses. Next, we assigned GC patients to two groups characterized by the risk score calculated and analyzed somatic mutation, functional pathways, and immune infiltration between the different two groups. Finally, a unique nomogram was offered to clinicians to forecast the personal survival probability of GC patients.Results: Based on seven anoikis-related markers screened and identified, a carcinogenic model of risk score was produced. Patients placed in the high-score group suffered significantly worse overall survival (OS) in four cohorts. Additionally, the model revealed a high sensitivity and specificity to prognosticate the prognoses of GC patients [area under the ROC curve (AUC) at 5-year = 0.713; GSE84437, AUC at 5-year = 0.639; GSE15459, AUC at 5-year = 0.672; GSE62254, AUC at 5-year = 0.616]. Apart from the excellent predictive performance, the model was also identified as an independent prediction factor from other clinicopathological characteristics. Combining anoikis-related prognostic model with GC clinical features, we built a more comprehensive nomogram to foresee the likelihood of survival of GC patients in a given year, showing a well-accurate prediction performance.Conclusion: In summary, this study created a new anoikis-related signature for GC, which has potentially provided new critical insights into survival prediction and individualized therapy development. |
| first_indexed | 2024-04-11T01:10:27Z |
| format | Article |
| id | doaj.art-0c72ce626c9b44bfbb496a0d85e0610b |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-11T01:10:27Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-0c72ce626c9b44bfbb496a0d85e0610b2023-01-04T06:51:42ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-01-011310.3389/fgene.2022.10872011087201Construction of an original anoikis-related prognostic model closely related to immune infiltration in gastric cancerZhihong ZhaoCun LiYe PengRui LiuQian LiBackground: Anoikis is considered as a particular type of programmed cell death, the weakness or resistance of which contributes greatly to the development and progression of most malignant solid tumors. However, the latent impact of anoikis-related genes (ARGs) on gastric cancer (GC) is still ambiguous. Based on these, this study established an anoikis-related prognostic model of GC to identify the prognosis of patients and provide more effective treatment in clinical practice.Methods: First, we extracted four public datasets containing the gene expression and clinicopathological information of GC, which were worked as the training and validating sets, separately. Then, an anoikis-related survival-predicted model of GC was developed via Lasso and COX regression analyses and verified by using the Kaplan-Meier (KM) curve and receiver operating characteristic (ROC) curve analyses. Next, we assigned GC patients to two groups characterized by the risk score calculated and analyzed somatic mutation, functional pathways, and immune infiltration between the different two groups. Finally, a unique nomogram was offered to clinicians to forecast the personal survival probability of GC patients.Results: Based on seven anoikis-related markers screened and identified, a carcinogenic model of risk score was produced. Patients placed in the high-score group suffered significantly worse overall survival (OS) in four cohorts. Additionally, the model revealed a high sensitivity and specificity to prognosticate the prognoses of GC patients [area under the ROC curve (AUC) at 5-year = 0.713; GSE84437, AUC at 5-year = 0.639; GSE15459, AUC at 5-year = 0.672; GSE62254, AUC at 5-year = 0.616]. Apart from the excellent predictive performance, the model was also identified as an independent prediction factor from other clinicopathological characteristics. Combining anoikis-related prognostic model with GC clinical features, we built a more comprehensive nomogram to foresee the likelihood of survival of GC patients in a given year, showing a well-accurate prediction performance.Conclusion: In summary, this study created a new anoikis-related signature for GC, which has potentially provided new critical insights into survival prediction and individualized therapy development.https://www.frontiersin.org/articles/10.3389/fgene.2022.1087201/fullgastric canceranoikis-related genespredictionprognosisimmune infiltration |
| spellingShingle | Zhihong Zhao Cun Li Ye Peng Rui Liu Qian Li Construction of an original anoikis-related prognostic model closely related to immune infiltration in gastric cancer Frontiers in Genetics gastric cancer anoikis-related genes prediction prognosis immune infiltration |
| title | Construction of an original anoikis-related prognostic model closely related to immune infiltration in gastric cancer |
| title_full | Construction of an original anoikis-related prognostic model closely related to immune infiltration in gastric cancer |
| title_fullStr | Construction of an original anoikis-related prognostic model closely related to immune infiltration in gastric cancer |
| title_full_unstemmed | Construction of an original anoikis-related prognostic model closely related to immune infiltration in gastric cancer |
| title_short | Construction of an original anoikis-related prognostic model closely related to immune infiltration in gastric cancer |
| title_sort | construction of an original anoikis related prognostic model closely related to immune infiltration in gastric cancer |
| topic | gastric cancer anoikis-related genes prediction prognosis immune infiltration |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.1087201/full |
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