Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer
Background: Gastric cancer (GC) is a prevalent malignancy of the digestive tract globally, demonstrating a substantial occurrence of relapse and metastasis, alongside the absence of efficacious treatment. Tumor progression and the development of cancer are linked to oxidative stress. Our objective w...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-10-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S240584402308012X |
| _version_ | 1827780248441192448 |
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| author | Meng Zhu Ning Zhang Jingwei Ma |
| author_facet | Meng Zhu Ning Zhang Jingwei Ma |
| author_sort | Meng Zhu |
| collection | DOAJ |
| description | Background: Gastric cancer (GC) is a prevalent malignancy of the digestive tract globally, demonstrating a substantial occurrence of relapse and metastasis, alongside the absence of efficacious treatment. Tumor progression and the development of cancer are linked to oxidative stress. Our objective was twofold: first, to determine distinct subcategories based on oxidative stress in GC patients, and second, to establish oxidative stress-related genes that would aid in stratifying the risk for GC patients. Methods: TCGA-STAD and GSE84437 datasets were utilized to obtain the mRNA expression profiles and corresponding clinical information of GC patients. Through consensus clustering analysis, distinct subgroups related to oxidative stress were identified. To uncover the underlying mechanisms, GSEA and GSVA were performed. xCell, CIBERSORT, MCPCounter, and TIMER algorithms were employed to evaluate the immune microenvironment and immune status of the different GC subtypes. A prognostic risk model was developed using the TCGA-STAD dataset and substantiated using the GSE84437 dataset. Furthermore, qRT-PCR was employed to validate the expression of genes associated with prognosis. Results: Two distinct subtypes of oxidative stress were discovered, with markedly different survival rates. The C1 subtype demonstrated an activated immune signal pathway, a significant presence of immune cell infiltration, high immune score, and a high microenvironment score, indicating a poor prognosis. Moreover, a prognostic signature related to oxidative stress (IMPACT and PXDN) was able to accurately estimate the likelihood of survival for patients with gastric cancer. A nomogram incorporating the patients' gender, age, and risk score was able to predict survival in gastric cancer patients. Additionally, the expression of IMPACT and PXDN showed a strong correlation with overall survival and the infiltration of immune cells. Conclusion: Based on signatures related to oxidative stress, we developed an innovative system for categorizing patients with GC. This stratification enables accurate prognostication of individuals with GC. |
| first_indexed | 2024-03-11T15:03:01Z |
| format | Article |
| id | doaj.art-a20e9041a3774e9aa92ba205cfdf5b61 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-11T15:03:01Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-a20e9041a3774e9aa92ba205cfdf5b612023-10-30T06:07:28ZengElsevierHeliyon2405-84402023-10-01910e20804Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancerMeng Zhu0Ning Zhang1Jingwei Ma2College of Basic Medicine, Ningxia Medical University, Ningxia, Yinchuan, 750004, ChinaDepartment of pathology, General Hospital of Ningxia Medical University, Ningxia, Yinchuan, 750004, China; Corresponding author. Department of pathology, General Hospital of Ningxia Medical University, No 804, Shengli Street, Ningxia, 750004, Yinchuan, China.The second department of tumor surgery, General Hospital of Ningxia Medical University, Ningxia, Yinchuan, 750004, ChinaBackground: Gastric cancer (GC) is a prevalent malignancy of the digestive tract globally, demonstrating a substantial occurrence of relapse and metastasis, alongside the absence of efficacious treatment. Tumor progression and the development of cancer are linked to oxidative stress. Our objective was twofold: first, to determine distinct subcategories based on oxidative stress in GC patients, and second, to establish oxidative stress-related genes that would aid in stratifying the risk for GC patients. Methods: TCGA-STAD and GSE84437 datasets were utilized to obtain the mRNA expression profiles and corresponding clinical information of GC patients. Through consensus clustering analysis, distinct subgroups related to oxidative stress were identified. To uncover the underlying mechanisms, GSEA and GSVA were performed. xCell, CIBERSORT, MCPCounter, and TIMER algorithms were employed to evaluate the immune microenvironment and immune status of the different GC subtypes. A prognostic risk model was developed using the TCGA-STAD dataset and substantiated using the GSE84437 dataset. Furthermore, qRT-PCR was employed to validate the expression of genes associated with prognosis. Results: Two distinct subtypes of oxidative stress were discovered, with markedly different survival rates. The C1 subtype demonstrated an activated immune signal pathway, a significant presence of immune cell infiltration, high immune score, and a high microenvironment score, indicating a poor prognosis. Moreover, a prognostic signature related to oxidative stress (IMPACT and PXDN) was able to accurately estimate the likelihood of survival for patients with gastric cancer. A nomogram incorporating the patients' gender, age, and risk score was able to predict survival in gastric cancer patients. Additionally, the expression of IMPACT and PXDN showed a strong correlation with overall survival and the infiltration of immune cells. Conclusion: Based on signatures related to oxidative stress, we developed an innovative system for categorizing patients with GC. This stratification enables accurate prognostication of individuals with GC.http://www.sciencedirect.com/science/article/pii/S240584402308012XGastric cancerImmune cell infiltrationsResponse to oxidative stressIndividualized therapy |
| spellingShingle | Meng Zhu Ning Zhang Jingwei Ma Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer Heliyon Gastric cancer Immune cell infiltrations Response to oxidative stress Individualized therapy |
| title | Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer |
| title_full | Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer |
| title_fullStr | Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer |
| title_full_unstemmed | Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer |
| title_short | Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer |
| title_sort | hierarchical clustering identifies oxidative stress related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer |
| topic | Gastric cancer Immune cell infiltrations Response to oxidative stress Individualized therapy |
| url | http://www.sciencedirect.com/science/article/pii/S240584402308012X |
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