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pmid:37636564
Neutrophil extracellular traps-related signature predicts the prognosis and immune infiltration in gastric cancer.
Mingzhe Li · Zidan Zhao · Tsz Kin Mak · Xiaoqun Wang · Jingyao Chen · Hui Ren · Zhiwei Yu · Changhua Zhang
Frontiers in medicine · 2023 doi:10.3389/fmed.2023.1174764
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Complete file
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Neutrophil extracellular traps (NETs) are a reticulated structure of DNA, histones, and antimicrobial peptides produced by active neutrophils that trap pathogens. Even though NETs are associated with poorer recurrence-free survival (RFS) and overall survival (OS), the specifics of this interaction between NETs and cancer cells are yet unknown.\nMethods: The keywords \"neutrophil extracellular traps and gastric cancer\" were used in the GEO database for retrieval, and the GSE188741 dataset was selected to obtain the NETs-related gene. 27 NETs-related genes were screened by univariate Cox regression analysis (p < 0.05). 27 NETs-related genes were employed to identify and categorize NETs-subgroups of GC patients under the Consensus clustering analysis. 808 GC patients in TCGA-STAD combined with GES84437 were randomly divided into a training group (n = 403) and a test group (n = 403) at a ratio of 1:1 to validate the NETs-related signature.\nResults: Based on Multivariate Cox regression and LASSO regression analysis to develop a NETs-related prognosis model. We developed a very specific nomogram to improve the NETs-clinical score's usefulness. Similarly, we also performed a great result in pan-cancer study with NETs-score. Low NETs scores were linked to higher MSI-H (microsatellite instability-high), mutation load, and immune activity. The cancer stem cell (CSC) index and chemotherapeutic treatment sensitivity were also connected to the NET score. Our comprehensive analysis of NETs in GC suggests that NETs have a role in the tumor microenvironment, clinicopathological features, and prognosis.\nDiscussion: The NETs-score risk model provides a basis for better prognosis and therapy outcomes in GC patients.", "claims": [{"id": "claim-method", "statement": "Based on R 4.1.1, we used the “survival” and “glmnet” packages for Multivariate Cox regression and LASSO regression analysis to develop a NETs-related prognosis model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37636564", "locator": "sections[7] \"Construction and validation of the NETs-related prognostic model\" paragraph 2", "quote": "Based on R 4.1.1, we used the “survival” and “glmnet” packages for Multivariate Cox regression and LASSO regression analysis to develop a NETs-related prognosis model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37636564", "locator": "sections[27] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A NETs-related prognostic model was constructed using differential analysis, univariate Cox regression, multivariate Cox regression, and LASSO regression and validated using internal and external cohorts and consensus clustering analysis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37636564", "locator": "sections[1] \"Introduction\" paragraph 4", "quote": "The GC prognostic model based on seven NETs-related differential expression genes (DEGs) was constructed using differential analysis, univariate Cox, Multivariate cox, and most minor absolute shrinkage and selection operator (LASSO) analysis, and the predictive efficacy of the model was validated using internal cohort, external cohort, and consensus clustering analysis."}, {"asset": "source:pmid:37636564", "locator": "sections[18] \"Establishment of risk assessment model and survival outcomes in GC\" paragraph 2", "quote": "Seven genes (SERPINE1, LAMC2, MYLK, IL21R, KRT81, MAMDC2, and PAEP) were ultimately retrieved after multivariate Cox regression analysis to create the risk score, known as the “NETs-score.”"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A NETs-related prognostic model was constructed using differential analysis, univariate Cox regression, multivariate Cox regression, and LASSO regression and validated using internal and external cohorts and consensus clustering analysis.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:37636564"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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