A systems biology approach for investigating significantly expressed genes among COVID-19, hepatocellular carcinoma, and chronic hepatitis B.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37521843", "kind": "science-record", "revision": 4, "content_hash": "sha256:1e8f830c82913238e072c15f458f4286011a1af100d08e330f78a28feffcf84d", "created_at": "2026-11-01T19:02:18Z", "updated_at": "2026-11-01T22:52:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A systems biology approach for investigating significantly expressed genes among COVID-19, hepatocellular carcinoma, and chronic hepatitis B.", "doi": "10.1186/s43042-022-00360-3", "pmid": "37521843", "authors": ["Babak Sokouti"], "journal": "The Egyptian journal of medical human genetics", "year": 2022, "abstract": "Background: Worldwide, COVID-19's death rate is about 2%, considering the incidence and mortality. However, the information on its complications in other organs, specifically the liver and its disorders, is limited in mild or severe cases. In this study, we aimed to computationally investigate the typical relationships between liver-related diseases [i.e., hepatocellular carcinoma (HCC), and chronic hepatitis B (CHB)] and COVID-19, considering the involved significant genes and their molecular mechanisms.\nMethods: We investigated two GEO microarray datasets (GSE164805 and GSE58208) to identify differentially expressed genes (DEGs) among the generated four datasets for mild/severe COVID-19, HCC, and CHB. Then, the overlapping genes among them were identified for GO and KEGG enrichment analyses, protein-protein interaction network construction, hub genes determination, and their associations with immune cell infiltration.\nResults: A total of 22 significant genes (i.e., ACTB, ATM, CDC42, DHX15, EPRS, GAPDH, HIF1A, HNRNPA1, HRAS, HSP90AB1, HSPA8, IL1B, JUN, POLR2B, PTPRC, RPS27A, SFRS1, SMARCA4, SRC, TNF, UBE2I, and VEGFA) were found to play essential roles among mild/severe COVID-19 associated with HCC and CHB. Moreover, the analysis of immune cell infiltration revealed that these genes are mostly positively correlated with tumor immune and inflammatory responses.\nConclusions: In summary, the current study demonstrated that 22 identified DEGs might play an essential role in understanding the associations between the mild/severe COVID-19 patients with HCC and CHB. So, the HCC and CHB patients involved in different types of COVID-19 can benefit from immune-based targets for therapeutic interventions.\nSupplementary Information: The online version contains supplementary material available at 10.1186/s43042-022-00360-3.", "claims": [{"id": "claim-method", "statement": "By comparing patients infected with mild and severe SARS-CoV-2, CHB, and HCC and their corresponding control samples, differentially expressed genes (DEGs) were identified using the GEO2R tool as well as “umap,” “GEOquery,” and “limma” packages [15]. Next, we selected the statistically significant DEGs (|log2(FoldChange)|≥ 0.5) with a p value of less than 0.05 and Benjamini & Hochberg (False discovery rate) criterion for p value adjustment.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37521843", "locator": "sections[4] \"Identification of DEGs\" paragraph 2", "quote": "By comparing patients infected with mild and severe SARS-CoV-2, CHB, and HCC and their corresponding control samples, differentially expressed genes (DEGs) were identified using the GEO2R tool as well as “umap,” “GEOquery,” and “limma” packages [15]. Next, we selected the statistically significant DEGs (|log2(FoldChange)|≥ 0.5) with a p value of less than 0.05 and Benjamini & Hochberg (False discovery rate) criterion for p value adjustment."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Availability of data and materialsNot applicable.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37521843", "locator": "sections[20] \"notes\" paragraph 1", "quote": "Availability of data and materialsNot applicable."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 22 significant genes (i.e., ACTB, ATM, CDC42, DHX15, EPRS, GAPDH, HIF1A, HNRNPA1, HRAS, HSP90AB1, HSPA8, IL1B, JUN, POLR2B, PTPRC, RPS27A, SFRS1, SMARCA4, SRC, TNF, UBE2I, and VEGFA) were found to play essential roles among mild/severe COVID-19 associated with HCC and CHB.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37521843", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 22 significant genes (i.e., ACTB, ATM, CDC42, DHX15, EPRS, GAPDH, HIF1A, HNRNPA1, HRAS, HSP90AB1, HSPA8, IL1B, JUN, POLR2B, PTPRC, RPS27A, SFRS1, SMARCA4, SRC, TNF, UBE2I, and VEGFA) were found to play essential roles among mild/severe COVID-19 associated with HCC and CHB."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 22 significant genes (i.e., ACTB, ATM, CDC42, DHX15, EPRS, GAPDH, HIF1A, HNRNPA1, HRAS, HSP90AB1, HSPA8, IL1B, JUN, POLR2B, PTPRC, RPS27A, SFRS1, SMARCA4, SRC, TNF, UBE2I, and VEGFA) were found to play essential roles among mild/severe COVID-19 associated with HCC and CHB.", "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:37521843"], "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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