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pmid:39430826
Prognostic biomarkers based on GUF1, EFTUD2 and GSPT1 targets affecting migration of gastric cancer cells.
Haixiu Ma · Lina Suo · Jing Zhao · Ronghua Ma · Qi Wang · Jun Liu · Jinwan Qiao · Juan Wu · Juan An · Yan Liu · Yonghua Xing · Haiyan Wang · Zhanhai Su
Translational cancer research · 2024 doi:10.21037/tcr-24-125
Paper
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Experiment
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Data
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Analysis
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Execution
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Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
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Complete file
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This study aimed to investigate the effects of GUF1, EFTUD2 and GSPT1 on the migration of GC cells.\nMethods: The Oncomine and The Cancer Genome Atlas (TCGA) databases were used to evaluate the expression of GUF1, EFTUD2, GSPT1 and GSPT2 in GC and the association of eEF1A2 family with individual clinical characteristics. Kaplan-Meier (K-M) Plotter hinted the prognostic value of GUF1, EFTUD2, GSPT1 and GSPT2. GSE62254 and GSE66222 datasets were used to validate the expression of GUF1, EFTUD2, GSPT1. AGS cell line and GES line were also used for validating the function of GUF1, EFTUD2, GSPT1. RNA interference (RNAi) of GUF1, EFTUD2 and GSPT1 had been used to query those genes expression pattern and dissect the proliferation and migration in GC cell lines.\nResults: GUF1, EFTUD2 and GSPT1 were significantly up-regulated in GC cell lines. High expression of GUF1, EFTUD2 and GSPT1 was correlated with cell proliferation and migration induced in GC cells. GUF1, EFTUD2 and GSPT1 may be potential novel oncogenes that helps to maintain the survival of GC cells.\nConclusions: This study identified that high levels of GUF1, EFTUD2 and GSPT1 expression are predictive biomarkers for a poor prognosis in GC.", "claims": [{"id": "claim-method", "statement": "Receiver operating characteristic (ROC) curves for each gene are shown in Figure 5.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39430826", "locator": "sections[22] \"Diagnostic capability of GUF1, EFTUD2 and GSPT1 for GC\" paragraph 2", "quote": "Receiver operating characteristic (ROC) curves for each gene are shown in Figure 5."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-125/dss\n10.21037/tcr-24-125", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39430826", "locator": "sections[33] \"Data Sharing Statement\" paragraphs 1-3", "quote": "Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-125/dss\n10.21037/tcr-24-125"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "", "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:39430826"], "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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"sample_count": 400, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Molecular analysis of gastric cancer identifies discrete subtypes associated with distinct clinical characteristics and survival outcomes: the ACRG (Asian Cancer Research Group) study", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE62254 not downloaded", "asset:data:geo:GSE62254 licence not read", "asset:data:geo:GSE66222 not downloaded", "asset:data:geo:GSE66222 licence not read", "asset:data:geo:GSE66229 not downloaded", "asset:data:geo:GSE66229 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": 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