Upregulated VEGFA and DLL4 act as potential prognostic genes for clear cell renal cell carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29618931", "kind": "science-record", "revision": 9, "content_hash": "sha256:8f0c78d8d3e024d6926b977a93f1eea6dc3790ccf5447771d69d4f14a18d727c", "created_at": "2026-11-01T15:40:33Z", "updated_at": "2026-11-01T22:43:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Upregulated VEGFA and DLL4 act as potential prognostic genes for clear cell renal cell carcinoma.", "doi": "10.2147/OTT.S150565", "pmid": "29618931", "authors": ["Xilong Wang", "Jun Zhang", "Yangyun Wang", "Minqi Tu", "Ying Wang", "Guowei Shi"], "journal": "OncoTargets and therapy", "year": 2018, "abstract": "PURPOSE: As a typical hypervascular tumor, clear cell renal cell carcinoma (ccRCC) is the most common type of RCC. This study was aimed to explore the prognostic genes for ccRCC, focusing on the roles of vascular endothelial growth factor A (VEGFA) and Delta-like ligand 4 (DLL4) in the disease.\nMATERIALS AND METHODS: The mRNA-sequencing data of kidney renal clear cell carcinoma (KIRC) were obtained from The Cancer Genome Atlas (TCGA) database, including 469 tumor samples and 68 adjacent normal samples. Using limma package, differentially expressed genes (DEGs) were analyzed by differential expression and subgroup analyses and confirmed using validation dataset GSE53757. Followed by enrichment analysis, protein-protein interaction (PPI) network analysis and protein subcellular localization were performed using multifaceted analysis tool for human transcriptome tool, and Cytoscape software and InnateDB database, respectively. Moreover, survival analysis was conducted to identify key prognosis-associated genes. In addition, VEGFA and DLL4 levels were detected using real-time quantitative PCR (qRT-PCR).\nRESULTS: A total of 1,984 DEGs were screened in the KIRC tumor samples. VEGFA was located in extracellular space and could interact with placental growth factor (PGF) and angiopoietin 2 (ANGPT2) in the PPI network. Subgroup analysis suggested that VEGFA was significantly upregulated in stages I, II, and III ccRCC tumor samples. Survival analysis showed that TIMP1 was among the top four prognosis-associated genes. qRT-PCR analysis confirmed that the expression levels of DLL4 and VEGFA were significantly upregulated in tumor samples.\nCONCLUSION: VEGFA and DLL4 might be prognostic genes for ccRCC. Besides, PGF, ANGPT2, and TIMP1 might also be related to the prognosis of ccRCC patients.", "claims": [{"id": "claim-method", "statement": "Finally, differential expression analysis and subgroup analysis were performed separately for the ccRCC tumor samples and adjacent normal samples using limma package18 with FDR <0.05 and |log2FC| >2 as the thresholds.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29618931", "locator": "sections[8] \"Differential expression analysis and subgroup analysis of validation dataset\" paragraph 2", "quote": "Finally, differential expression analysis and subgroup analysis were performed separately for the ccRCC tumor samples and adjacent normal samples using limma package18 with FDR <0.05 and |log2FC| >2 as the thresholds."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The level 3 mRNA-seq data (downloaded in November 2016) of KIRC were downloaded from TCGA (https://cancerge-nome.nih.gov/) database, including 469 tumor samples and 68 adjacent normal samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29618931", "locator": "sections[3] \"Date source\" paragraph 2", "quote": "The level 3 mRNA-seq data (downloaded in November 2016) of KIRC were downloaded from TCGA (https://cancerge-nome.nih.gov/) database, including 469 tumor samples and 68 adjacent normal samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Applying a covariate-adjusted Cox model to DEGs shared between the TCGA cohort and validation dataset GSE53757 identified 40 prognosis-associated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:29618931", "locator": "sections[9] \"Survival analysis\" paragraph 2", "quote": "Using Cox model,31 variables such as age, gender, and tumor stage were adjusted."}, {"asset": "source:pmid:29618931", "locator": "sections[9] \"Survival analysis\" paragraph 2", "quote": "To obtain prognosis-associated genes, the intersection DEGs between TCGA dataset and GSE53757 were identified."}, {"asset": "source:pmid:29618931", "locator": "sections[18] \"Survival analysis\" paragraph 2", "quote": "Then a total of 40 prognosis- associated genes were identified from the intersection DEGs."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Applying a covariate-adjusted Cox model to DEGs shared between the TCGA cohort and validation dataset GSE53757 identified 40 prognosis-associated genes.", "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:29618931"], "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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