Construction of a circRNA-miRNA-mRNA Regulatory Network for the Immune Regulation of Lung Adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40211126", "kind": "science-record", "revision": 4, "content_hash": "sha256:4d7edccaf10037f9d2040286f3c39794828cfd3e6eb032296bc56d3cce963622", "created_at": "2026-11-01T20:30:22Z", "updated_at": "2026-11-01T22:56:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction of a circRNA-miRNA-mRNA Regulatory Network for the Immune Regulation of Lung Adenocarcinoma.", "doi": "10.1186/s12575-025-00275-4", "pmid": "40211126", "authors": ["Hanyi Li", "Xin Jin", "Wei Li", "Fan Ren", "Tong Li", "Xuanguang Li", "Haochuan Yu", "Dianxun Fu", "Zuoqing Song", "Song Xu"], "journal": "Biological procedures online", "year": 2025, "abstract": "BACKGROUND: Recent research has highlighted the significance of circular RNAs (circRNAs) as pivotal regulators in the progression of tumors and the therapeutic response in non-small cell lung cancer (NSCLC). These circRNAs function through a sponge mechanism, interacting with microRNAs (miRNAs) to modulate mRNA expression levels. Nevertheless, the precise role of the circRNA-miRNA-mRNA regulatory network in immune regulation within lung adenocarcinoma (LUAD) remains inadequately understood.\nMETHODS AND MATERIALS: We utilized microarray datasets from the GEO NCBI database (GSE101586) to identify differentially expressed circRNAs (DEcircRNAs) in LUAD. CircBank was employed to predict the target miRNAs of DEcircRNAs, which were subsequently intersected with miRNAs from the GSE36681 database. The identified miRNAs were then predicted to target mRNAs using miRDB and miWalk, and intersections with immune-related genes from the IMMPORT database were analyzed. Protein-protein interaction (PPI) networks were constructed using Cytoscape software. The DAVID functional annotation tool was utilized to explore potential biological processes, molecular functions, and KEGG pathways associated with LUAD. Gene expression and Kaplan-Meier survival analyses were conducted to establish a key regulatory network and to assess immune cell infiltration and Pearson correlation for significant target genes. Finally, we selected the most significantly upregulated circRNA with differential expression for validation through in vitro experiments.\nRESULTS: Our analysis identified a total of 7 upregulated and 42 downregulated circRNAs, along with 10 significant miRNAs and 20 target mRNAs. KEGG enrichment analysis indicated that these components are primarily enriched in the ErbB signaling pathway. Furthermore, Gene Ontology (GO) analysis revealed significant enrichment in responses to organic substances, cytokine-mediated signaling pathways, cellular responses to cytokines, responses to chemical stimuli, steroid hormone receptor activity, ErbB-3 class receptor binding, oxysterol binding, signal receptor activity, and molecular transducer activity. Notable core mRNAs identified included OAS1, VIPR1, and PIK3R1. Subsequently, we constructed a regulatory network comprising 6 DEcircRNAs, 3 DEmiRNAs, and 3 DEmRNAs. Through ssGSEA and CIBERSORT analyses, we observed significant differences in immune cell infiltration levels between the NSCLC cohort and the control group. Knocking down the expression of hsa_circ_0079557 significantly inhibited the viability, proliferation, migration, and invasion of LUAD cells.\nCONCLUSION: We have established a circRNA-miRNA-mRNA regulatory network that offers novel insights into the molecular mechanisms governing immune regulation in LUAD. Future research should aim to translate these findings into clinical applications to enhance patient outcomes.", "claims": [{"id": "claim-method", "statement": "Differentially expressed circRNAs (DEcircRNAs) and miRNAs (DEmiRNAs) were identified using the limma package in R.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40211126", "locator": "sections[4] \"Differential Expression Analysis and Venn Analysis\" paragraph 2", "quote": "Differentially expressed circRNAs (DEcircRNAs) and miRNAs (DEmiRNAs) were identified using the limma package in R."}], "state": "complete"}, {"id": "claim-data-access", "statement": "No datasets were generated or analysed during the current study.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40211126", "locator": "sections[28] \"Data Availability\" paragraph 2", "quote": "No datasets were generated or analysed during the current study."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our analysis identified a total of 7 upregulated and 42 downregulated circRNAs, along with 10 significant miRNAs and 20 target mRNAs.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40211126", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Our analysis identified a total of 7 upregulated and 42 downregulated circRNAs, along with 10 significant miRNAs and 20 target mRNAs."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Our analysis identified a total of 7 upregulated and 42 downregulated circRNAs, along with 10 significant miRNAs and 20 target mRNAs.", "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:40211126"], "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:GSE101586"], "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:GSE101586"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40211126", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12575-025-00275-4", "sha256": 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METHODS AND MATERIALS: We utilized microarray datasets from the GEO NCBI database (GSE1015"], "order_basis": "paper_text_order:592", "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": ["CC). The BEAS-2B, H1299, and A549 cells were cultured in RPMI-1640 medium (Gibco, Grand Island, NY, U", "elial cells (BEAS-2B) and LUAD cells (H1299, A549) from the American Tissue Culture Collection", "e Collection (ATCC). The BEAS-2B, H1299, and A549 cells were cultured in RPMI-1640 medium (Gib"], "order_basis": "paper_text_order:4628", "id": "assay:2"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Differentially expressed circRNAs (DEcircRNAs) and miRNAs (DEmiRNAs) were identified using the limma package in R."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}