Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35606717", "kind": "science-record", "revision": 4, "content_hash": "sha256:064389ff7e8a7b5882cb47ea6a0f4582b2ffe721c02b6a1fcb7369a02a7e01a6", "created_at": "2026-11-01T18:14:31Z", "updated_at": "2026-11-01T22:06:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients.", "doi": "10.1186/s12885-022-09575-4", "pmid": "35606717", "authors": ["Hongxu Sheng", "Zhexue Hao", "Linhai Zhu", "Yuan Zeng", "Jianxing He"], "journal": "BMC cancer", "year": 2022, "abstract": "BACKGROUND: Post-translational modification plays an important role in the occurrence and development of various tumors. However, few researches were focusing on the SUMOylation regulatory genes as tumor biomarkers to predict the survival for specific patients. Here, we constructed and validated a two-gene signature to predict the overall survival (OS) of non-small cell lung cancer (NSCLC) patients.\nMETHODS: The datasets analyzed in this study were downloaded from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct the two-gene signature. Gene set enrichment analysis (GSEA) and Gene Ontology (GO) was used to identify hub pathways associated with risk genes. The CCK-8 assay, cell cycle analysis, and transwell assay was used to validate the function of risk genes in NSCLC cell lines.\nRESULTS: Firstly, most of the SUMOylation regulatory genes were highly expressed in various tumors through the R package 'limma' in the TCGA database. Secondly, our study found that the two gene signature constructed by LASSO regression analysis, as an independent prognostic factor, could predict the OS in both the TCGA training cohort and GEO validation cohorts (GSE68465, GSE37745, and GSE30219). Furthermore, functional enrichment analysis suggests that high-risk patients defined by the risk score system were associated with the malignant phenomenon, such as DNA replication, cell cycle regulation, p53 signaling pathway. Finally, the results of the CCK-8 assay, cell cycle analysis, and transwell assay demonstrated that the two risk genes, SAE1 and UBA2, could promote proliferation and migration in non-small cell lung cancer cells.\nCONCLUSIONS: The two-gene signature constructed in our study could predict the OS and may provide valuable clinical guidance for the treatment of NSCLC patients.", "claims": [{"id": "claim-method", "statement": "The LASSO Cox regression analysis was used in the training set to construct a risk scoring system (RSS) by a linear combination of the risk genes defined by their calculated regression coefficients.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35606717", "locator": "sections[6] \"Construction of a risk scoring system\" paragraph 2", "quote": "The LASSO Cox regression analysis was used in the training set to construct a risk scoring system (RSS) by a linear combination of the risk genes defined by their calculated regression coefficients."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used in the current study are openly available in TCGA (https://cancergenome.nih.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/) database and are available in the scienceDB repository (https://www.scidb.cn/s/AFfEva).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35606717", "locator": "sections[31] \"notes\" paragraph 1", "quote": "The datasets used in the current study are openly available in TCGA (https://cancergenome.nih.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/) database and are available in the scienceDB repository (https://www.scidb.cn/s/AFfEva)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:35606717"], "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:GSE37745"], "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:GSE37745"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35606717", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12885-022-09575-4", "sha256": 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The CCK-8 assay, cell cycle analysis, and transwell as", "gnaling pathway. Finally, the results of the CCK-8 assay, cell cycle analysis, and transwell as"], "order_basis": "paper_text_order:824", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ell lines and cell culture The A549 and H838 cell lines were cultured in RPMI-1640 medium (Corning, Inc.) suppleme", "ll culture The A549 and H838 cell lines were cultured in RPMI-1640 medium (Corning, Inc.) supplemente", "issing data. Cell lines and cell culture The A549 and H838 cell lines were cultured in RPMI-16"], "order_basis": "paper_text_order:2592", "id": "assay:2"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The LASSO Cox regression analysis was used in the training set to construct a risk scoring system (RSS) by a linear combination of the risk genes defined by their calculated regression coefficients."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}