[TRIP13 Enhances Radioresistance of Lung Adenocarcinoma Cells through the Homologous Recombination Pathway].

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38296621", "kind": "science-record", "revision": 3, "content_hash": "sha256:6cc9c3fca72afd0ffdc5338a21478619132c95b688652ae40ad306571379ada1", "created_at": "2026-11-01T19:20:14Z", "updated_at": "2026-11-01T22:11:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "[TRIP13 Enhances Radioresistance of Lung Adenocarcinoma Cells through the Homologous Recombination Pathway].", "doi": "10.3779/j.issn.1009-3419.2023.106.27", "pmid": "38296621", "authors": ["Shutong Ge", "Runchuan Gu", "Xiongtao Yang", "Changdan Xu", "Shijie Wang", "Guangying Zhu"], "journal": "Zhongguo fei ai za zhi = Chinese journal of lung cancer", "year": 2024, "abstract": "BACKGROUND: Radiation therapy is one of the most common treatments for non-small cell lung cancer (NSCLC). However, the insensitivity of some tumor cells to radiation is one of the major reasons for the poor efficacy of radiotherapy and the poor prognosis of patients, and exploring the underlying mechanisms behind radioresistance is the key to solving this clinical challenge. This study aimed to identify the molecules associated with radioresistance in lung adenocarcinoma (LUAD), identified thyroid hormone receptor interactor 13 (TRIP13) as the main target initially, and explored whether TRIP13 is related to radioresistance in LUAD and the specific mechanism, with the aim of providing theoretical basis and potential targets for the combination therapy of LUAD patients receiving radiotherapy in the clinic.\nMETHODS: Three datasets, GSE18842, GSE19188 and GSE33532, were selected from the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (|log FC|>1.5, P<0.05) in each of the three datasets using the R 4.1.3 software, and then Venn diagram was used to find out the differentially expressed genes common to the three datasets. The screened differential genes were then subjected to protein-protein interaction (PPI) analysis and module analysis with the help of STRING online tool and Cytoscape software, and survival prognosis analysis was performed for each gene with the help of Kaplan-Meier Plotter database, and the TRIP13 gene was identified as the main molecule for subsequent studies. Subsequently, the human LUAD cell line H292 was irradiated with multiple X-rays using a sub-lethal dose irradiation method to construct a radioresistant cell line, H292DR. The radioresistance of H292DR cells was verified using cell counting kit-8 (CCK-8) assay and clone formation assay. The expression levels of TRIP13 in H292 and H292DR cells were measured by Western blot. Small interfering RNA (siRNA) was used to silence the expression of TRIP13 in H292DR cells and Western blot assay was performed. The clone formation ability and migration ability of H292DR cells were observed after TRIP13 silencing, followed by the detection of changes in the expression levels of proteins closely related to homologous recombination, such as ataxia telangiectasia mutated (ATM) protein.\nRESULTS: Screening of multiple GEO datasets, validation of external datasets and survival analysis revealed that TRIP13 was highly expressed in LUAD and was associated with poor prognosis in LUAD patients who had received radiation therapy. And the results of gene set enrichment analysis (GSEA) of TRIP13 suggested that TRIP13 might be closely associated with LUAD radioresistance by promoting homologous recombination repair after radiation therapy. Experimentally, TRIP13 expression was found to be upregulated in H292DR, and silencing of TRIP13 was able to increase the sensitivity of H292DR cells to radiation.\nCONCLUSIONS: TRIP13 is associated with poor prognosis in LUAD patients treated with radiation, possibly by promoting a homologous recombination repair pathway to mediate resistance of LUAD cells to radiation.", "claims": [{"id": "claim-method", "statement": "采用Kaplan-Meier方法分析TRIP13与患者的总生存期（overall survival, OS）的关系，采用Spearman相关分析检测TRIP13基因与其他基因之间的相关性。单因素和多因素Cox回归分析评估多个因素对LUAD患者OS的影响。两组间计量资料的比较采用t检验。P<0.05为差异具有统计学意义。", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38296621", "locator": "sections[12] \"1.9 统计学方法\" paragraph 2", "quote": "采用Kaplan-Meier方法分析TRIP13与患者的总生存期（overall survival, OS）的关系，采用Spearman相关分析检测TRIP13基因与其他基因之间的相关性。单因素和多因素Cox回归分析评估多个因素对LUAD患者OS的影响。两组间计量资料的比较采用t检验。P<0.05为差异具有统计学意义。"}], "state": "complete"}, {"id": "claim-data-access", "statement": "使用R 4.1.3软件从基因表达综合数据库（Gene Expression Omnibus, GEO）下载4个非小细胞肺癌（non-small cell lung cancer, NSCLC）的基因表达谱：GSE18842、GSE19188、GSE33532和GSE68465，共计809例样本，其中NSCLC样本660例，正常组织样本149例。将GSE18842、GSE19188、GSE33532 3个数据集用于差异基因的筛选与分析，仅包含LUAD病理亚型和正常组织样本信息的GSE68465数据集用于辅助验证。", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38296621", "locator": "sections[4] \"1.1 数据来源及数据分析\" paragraph 2", "quote": "使用R 4.1.3软件从基因表达综合数据库（Gene Expression Omnibus, GEO）下载4个非小细胞肺癌（non-small cell lung cancer, NSCLC）的基因表达谱：GSE18842、GSE19188、GSE33532和GSE68465，共计809例样本，其中NSCLC样本660例，正常组织样本149例。将GSE18842、GSE19188、GSE33532 3个数据集用于差异基因的筛选与分析，仅包含LUAD病理亚型和正常组织样本信息的GSE68465数据集用于辅助验证。"}], "state": "complete"}, {"id": "claim-target-result", "statement": "TRIP13与接受放疗后的LUAD患者的预后不良有关，可能是通过促进同源重组修复途径来介导LUAD细胞对放射线的抵抗。", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38296621", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "TRIP13与接受放疗后的LUAD患者的预后不良有关，可能是通过促进同源重组修复途径来介导LUAD细胞对放射线的抵抗。"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "TRIP13与接受放疗后的LUAD患者的预后不良有关，可能是通过促进同源重组修复途径来介导LUAD细胞对放射线的抵抗。", "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:38296621"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE18842"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE18842"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38296621", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3779/j.issn.1009-3419.2023.106.27", "sha256": "sha256:b1722a836f9685103f0b7a52e4c27737bf74f06b8da373cb48c61741feaca6f0", "bytes": 18850, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3779/j.issn.1009-3419.2023.106.27", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10895292", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE18842", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE18842", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE18842", "version": null, "note": "使用R 4.1.3软件从基因表达综合数据库（Gene Expression Omnibus, GEO）下载4个非小细胞肺癌（non-small cell lung cancer, 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NSCLC）的基因表达谱：GSE18842、GSE19188、GSE33532和GSE68465，共计809例样本，其中NSCLC样本660例，正常组织样本149例。将GSE18842、GSE19188、GSE33532 3个数据集用于差异基因的筛选与分析，仅包含LUAD病理亚型和正常组织样本信息的GSE68465数据集用于辅助验证。", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM475656", "GSM475657", "GSM475658", "GSM475659", "GSM475660", "GSM475661", "GSM475662", "GSM475663", "GSM475664", "GSM475665", "GSM475666", "GSM475667", "GSM475668", "GSM475669", "GSM475670", "GSM475671", "GSM475672", "GSM475673", "GSM475674", "GSM475675", "GSM475676", "GSM475677", "GSM475678", "GSM475679", "GSM475680", "GSM475681", "GSM475682", "GSM475683", "GSM475684", "GSM475685", "GSM475686", "GSM475687", "GSM475688", "GSM475689", "GSM475690", "GSM475691", "GSM475692", "GSM475693", "GSM475694", "GSM475695", "GSM475696", "GSM475697", "GSM475698", "GSM475699", "GSM475700", "GSM475701", "GSM475702", "GSM475703", "GSM475704", "GSM475705", "GSM475706", "GSM475707", "GSM475708", "GSM475709", "GSM475710", "GSM475711", "GSM475712", 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"reader_required", "identifier": "GSE68465", "version": null, "note": "使用R 4.1.3软件从基因表达综合数据库（Gene Expression Omnibus, GEO）下载4个非小细胞肺癌（non-small cell lung cancer, NSCLC）的基因表达谱：GSE18842、GSE19188、GSE33532和GSE68465，共计809例样本，其中NSCLC样本660例，正常组织样本149例。将GSE18842、GSE19188、GSE33532 3个数据集用于差异基因的筛选与分析，仅包含LUAD病理亚型和正常组织样本信息的GSE68465数据集用于辅助验证。", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "使用R 4.1.3软件从基因表达综合数据库（Gene Expression Omnibus, GEO）下载4个非小细胞肺癌（non-small cell lung cancer, NSCLC）的基因表达谱：GSE18842、GSE19188、GSE33532和GSE68465，共计809例样本，其中NSCLC样本660例，正常组织样本149例。将GSE18842、GSE19188、GSE33532 3个数据集用于差异基因的筛选与分析，仅包含LUAD病理亚型和正常组织样本信息的GSE68465数据集用于辅助验证。", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1672281", "GSM1672282", "GSM1672283", "GSM1672284", "GSM1672285", "GSM1672286", "GSM1672287", "GSM1672288", "GSM1672289", "GSM1672290", "GSM1672291", "GSM1672292", "GSM1672293", "GSM1672294", "GSM1672295", "GSM1672296", 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downloaded", "asset:data:geo:GSE37745 licence not read", "asset:data:geo:GSE68465 not downloaded", "asset:data:geo:GSE68465 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": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}, {"id": "method-2", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}, {"id": "method-3", "family": null, "specific": null, "label": "Kaplan-Meier方法", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "采用Kaplan-Meier方法分析TRIP13与患者的总生存期（overall survival, OS）的关系，采用Spearman相关分析检测TRIP13基因与其他基因之间的相关性。单因素和多因素Cox回归分析评估多个因素对LUAD患者OS的影响。两组间计量资料的比较采用t检验。P<0.05为差异具有统计学意义。"}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE18842", "GSE19188", "GSE33532", "GSE68465", "GSE37745"], "resolved_accessions": ["GSE18842", "GSE19188", "GSE33532", "GSE68465", "GSE37745"], "statements": ["使用R 4.1.3软件从基因表达综合数据库（Gene Expression Omnibus, GEO）下载4个非小细胞肺癌（non-small cell lung cancer, NSCLC）的基因表达谱：GSE18842、GSE19188、GSE33532和GSE68465，共计809例样本，其中NSCLC样本660例，正常组织样本149例。将GSE18842、GSE19188、GSE33532 3个数据集用于差异基因的筛选与分析，仅包含LUAD病理亚型和正常组织样本信息的GSE68465数据集用于辅助验证。"], "basis": "The paper names GSE18842, GSE19188, GSE33532, GSE68465, GSE37745 in 基因表达综合数据库（Gene Expression Omnibus, GEO） and the accession resolves in the repository. 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