Development and validation of focal adhesion-related genes signature in gastric cancer
Background: This study aims to build a focal adhesion-related genes-based prognostic signature (FAS) to accurately predict gastric cancer (GC) prognosis and identify key prognostic genes related to gastric cancer.Results: Gene expression and clinical data of gastric cancer patients were sourced from...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2023.1122580/full |
| _version_ | 1811158357628682240 |
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| author | Guanghui Zhao Tianqi Luo Zexian Liu Jianjun Li |
| author_facet | Guanghui Zhao Tianqi Luo Zexian Liu Jianjun Li |
| author_sort | Guanghui Zhao |
| collection | DOAJ |
| description | Background: This study aims to build a focal adhesion-related genes-based prognostic signature (FAS) to accurately predict gastric cancer (GC) prognosis and identify key prognostic genes related to gastric cancer.Results: Gene expression and clinical data of gastric cancer patients were sourced from Gene Expression Omnibus and The Cancer Genome Atlas. Subsequently, the GEO dataset was randomly distributed into training and test cohorts. The TCGA dataset was used to validate the external cohort. Lasso Cox regression was used to detect OS-related genes in the GEO cohort. A risk score model was established according to the screened genes. A nomogram, based on the clinical characteristics and risk score, was generated to predict the prognosis of gastric cancer patients. Using time-dependent receiver operating characteristic (ROC) and calibration performances, we evaluated the models’ validity. The patients were grouped into a high- or low-risk group depending on the risk score. Low-risk patients exhibited higher OS than high-risk patients (entire cohort: p < 0.001; training cohort: p < 0.001, test cohort: p < 0.001). Furthermore, we found a correlation between high-risk gastric cancer and extracellular matrix (ECM) receptor interaction, high infiltration of macrophages, CD44, and HLA-DOA.Conclusion: The generated model based on the genetic characteristics of the focal adhesion prognostic gene can aid in the prognosis of gastric cancer patients in the future. |
| first_indexed | 2024-04-10T05:23:15Z |
| format | Article |
| id | doaj.art-1f34f4d1dfb1443884a55ac4c4fa132f |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-10T05:23:15Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-1f34f4d1dfb1443884a55ac4c4fa132f2023-03-08T05:29:30ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-03-011410.3389/fgene.2023.11225801122580Development and validation of focal adhesion-related genes signature in gastric cancerGuanghui Zhao0Tianqi Luo1Zexian Liu2Jianjun Li3Department of Endoscopy, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, ChinaDepartment of Musculoskeletal Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, ChinaState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, ChinaDepartment of Endoscopy, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, ChinaBackground: This study aims to build a focal adhesion-related genes-based prognostic signature (FAS) to accurately predict gastric cancer (GC) prognosis and identify key prognostic genes related to gastric cancer.Results: Gene expression and clinical data of gastric cancer patients were sourced from Gene Expression Omnibus and The Cancer Genome Atlas. Subsequently, the GEO dataset was randomly distributed into training and test cohorts. The TCGA dataset was used to validate the external cohort. Lasso Cox regression was used to detect OS-related genes in the GEO cohort. A risk score model was established according to the screened genes. A nomogram, based on the clinical characteristics and risk score, was generated to predict the prognosis of gastric cancer patients. Using time-dependent receiver operating characteristic (ROC) and calibration performances, we evaluated the models’ validity. The patients were grouped into a high- or low-risk group depending on the risk score. Low-risk patients exhibited higher OS than high-risk patients (entire cohort: p < 0.001; training cohort: p < 0.001, test cohort: p < 0.001). Furthermore, we found a correlation between high-risk gastric cancer and extracellular matrix (ECM) receptor interaction, high infiltration of macrophages, CD44, and HLA-DOA.Conclusion: The generated model based on the genetic characteristics of the focal adhesion prognostic gene can aid in the prognosis of gastric cancer patients in the future.https://www.frontiersin.org/articles/10.3389/fgene.2023.1122580/fullgastric cancerTCGAfocal adhesionprognosisGEO |
| spellingShingle | Guanghui Zhao Tianqi Luo Zexian Liu Jianjun Li Development and validation of focal adhesion-related genes signature in gastric cancer Frontiers in Genetics gastric cancer TCGA focal adhesion prognosis GEO |
| title | Development and validation of focal adhesion-related genes signature in gastric cancer |
| title_full | Development and validation of focal adhesion-related genes signature in gastric cancer |
| title_fullStr | Development and validation of focal adhesion-related genes signature in gastric cancer |
| title_full_unstemmed | Development and validation of focal adhesion-related genes signature in gastric cancer |
| title_short | Development and validation of focal adhesion-related genes signature in gastric cancer |
| title_sort | development and validation of focal adhesion related genes signature in gastric cancer |
| topic | gastric cancer TCGA focal adhesion prognosis GEO |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2023.1122580/full |
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