CDC20 May Serve as a Potential Biomarker-Based Risk Score System in Predicting the Prognosis of Patients with Hepatocellular Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36193067", "kind": "science-record", "revision": 4, "content_hash": "sha256:0d9e745060f2d2e8f908a28209307c60013a17be03e2d2d6f2dc0853544a7b98", "created_at": "2026-11-01T18:15:30Z", "updated_at": "2026-11-01T22:07:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "CDC20 May Serve as a Potential Biomarker-Based Risk Score System in Predicting the Prognosis of Patients with Hepatocellular Carcinoma.", "doi": "10.1155/2022/8421813", "pmid": "36193067", "authors": ["Qiliu Peng", "Hai Huang", "Chunling Zhu", "Qingqing Hou", "Shangmou Wei", "Yi Xiao", "Zhi Zhang", "Xing Sun"], "journal": "Oxidative medicine and cellular longevity", "year": 2022, "abstract": "Background: The specificity and sensitivity of hepatocellular carcinoma (HCC) diagnostic markers are limited, hindering the early diagnosis and treatment of HCC patients. Therefore, improving prognostic biomarkers for patients with HCC is urgently needed.\nMethods: HCC-related datasets were downloaded from the public databases. Differentially expressed genes (DEGs) between HCC and adjacent nontumor liver tissues were then identified. Moreover, the intersection of DEGs in four datasets (GSE138178, GSE77509, GSE84006, and TCGA) was used in the functional enrichment, and module genes were obtained by a coexpression network. Cox and Kaplan-Meier analyses were used to identify overall survival- (OS-) related genes from module genes. Area under the curve (AUC) > 0.9 of OS-related genes was then carried out in order to perform the protein-protein interaction network. The feature genes were identified by least absolute shrinkage and selection operator (LASSO). Furthermore, the hub gene was identified through the univariate Cox model, after which the correlation analysis between the hub gene and pathways was explored. Finally, infiltration in immune cell types in HCC was analyzed.\nResults: A total of 2,227 upregulated genes and 1,501 downregulated DEGs were obtained in all four datasets, which were mainly found to be involved in the cell cycle and retinol metabolism. Accordingly, 998 OS-related genes were screened to construct the LASSO model. Finally, 8 feature genes (BUB1, CCNB1, CCNB2, CCNA2, AURKB, CDC20, OIP5, and TTK) were obtained. CDC20 was shown to serve as a poor prognostic gene in HCC and was mainly involved in the cell cycle. Moreover, a positive correlation was noted between the high degree of infiltration with Th2 and CDC20.\nConclusion: High expression of CDC20 predicted poor survival, as potential target in the treatment for HCC.", "claims": [{"id": "claim-method", "statement": "Univariate Cox regression analysis is mainly used to explore the independent prognostic effects of individual genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36193067", "locator": "sections[8] \"2.6. Construction of Least Absolute Shrinkage and Selection Operator (LASSO) Model and Univariate Cox Regression Model\" paragraph 3", "quote": "Univariate Cox regression analysis is mainly used to explore the independent prognostic effects of individual genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The dataset used and analysed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36193067", "locator": "sections[25] \"Data Availability\" paragraph 2", "quote": "The dataset used and analysed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Finally, 8 feature genes (BUB1, CCNB1, CCNB2, CCNA2, AURKB, CDC20, OIP5, and TTK) were obtained.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36193067", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Finally, 8 feature genes (BUB1, CCNB1, CCNB2, CCNA2, AURKB, CDC20, OIP5, and TTK) were obtained."}, {"asset": "source:pmid:36193067", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "CDC20 was shown to serve as a poor prognostic gene in HCC and was mainly involved in the cell cycle."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Finally, 8 feature genes (BUB1, CCNB1, CCNB2, CCNA2, AURKB, CDC20, OIP5, and TTK) were obtained.", "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:36193067"], "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:GSE138178"], "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:GSE138178"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36193067", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/8421813", "sha256": 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