Identification of lncRNA dual targeting PD-L1 and PD-L2 as a novel prognostic predictor for gastric cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39525623", "kind": "science-record", "revision": 4, "content_hash": "sha256:3e11ba10608dc9d8af34b64e216d0cdd01e9e68ced976c0b84b73738565a8fc5", "created_at": "2026-11-01T20:29:47Z", "updated_at": "2026-11-01T22:55:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of lncRNA dual targeting PD-L1 and PD-L2 as a novel prognostic predictor for gastric cancer.", "doi": "10.3389/fonc.2024.1341056", "pmid": "39525623", "authors": ["Li-Na Zhang", "Jiong-Yu Chen", "Yu-Xin Liu", "Yue Zhang", "Liang-Li Hong", "Xin-Xin Li", "Shu-Hui Liu", "Shu-Qin Chen", "Lin Peng", "Yi-Teng Huang"], "journal": "Frontiers in oncology", "year": 2024, "abstract": "Background: Although breakthroughs have been achieved in gastric cancer (GC) therapy with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1), the acquisition of high response rate remains a huge challenge for clinicians. It is imperative to identify novel biomarkers for predicting response to immunotherapy and explore alternative therapeutic strategy for GC.\nMethods: The transcriptomic profiles and clinical information of GC patients from The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) database was used to screen differentially expressed lncRNAs between the tumor specimens and the paracancerous tissues. The TargetScan, miRDB and miRcode database were then utilized to construct competing endogenous RNA (ceRNA) networks and identify pivotal lncRNAs. An independent dataset from GEO (GSE70880) and 23 pairs of GC specimens of our cohort were subsequently performed for external validity. The relationship between clinical variables and gene expression were evaluated by Kruskal-wallis test and Wilcoxon signed-rank. The prognostic value of the candidate genes was assessed using Kaplan-Meier analysis and Cox regression models. CIBERSORT and Gene set enrichment analysis (GSEA) were used to determine immune cell infiltration. Gastric adenocarcinoma AGS cells and human embryonic kidney 293T (HEK293T) cells with knockdown of LINC01094 were generated by siRNA transfection, followed by detecting the alteration of the target miRNA and PD-L1/PD-L2 by RT-qPCR. Besides, the interaction between lncRNA and the miRNA-PD-L1/PD-L2 axis were verified by dual luciferase reporter assay.\nResults: Twenty-two intersecting lncRNAs were identified to be PD-L1/PD-L2-related lncRNAs and LINC01094-miR-17-5p-PD-L1/PD-L2 was constructed as a potential ceRNA network. LINC01094 was increased in tumor specimens than adjacent normal samples and was positively associated with advanced tumor stages and EBV and MSI status. Furthermore, LINC01094 expression was an independent risk factor for poor overall survival (OS) in GC patients. CD8+ T cell exhaustion-related genes were enriched in high-LINC01094 tissues and high-PD-L2 group. A strong positive association of LINC01094 expression was established with M2 macrophages, IL-10+ TAM, as well as PD-L1 and PD-L2 levels, therefore a LINC01094-miR-17-5p-IL-10 network was proposed in macrophages. Using the exoRBase database, LINC01094 was assumed in blood exosomes of GC patients The results of knockdown experiments and luciferase reporter assays revealed that LINC01094 interacted with miR-17-5p and served as a miRNA sponge to regulate the expression of PD-L1 and PD-L2.\nConclusion: LINC01094 dually regulates the expression of PD-L1 and PD-L2 and shapes the immunosuppressive tumor microenvironment via sponging miR-17-5p. LINC01094 may serve as a potential prognostic predictor and therapeutic target in GC.", "claims": [{"id": "claim-method", "statement": "We applied the “limma” R package for the entire lncRNA data to identify the differentially-expressed lncRNAs (DE lncRNAs) between tumor and paracancerous specimens, with screening criteria set at |log fold change (logFC)| > 1 and adjusted p-value < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39525623", "locator": "sections[4] \"Identification of PD-L1/PD-L2-related differentially-expressed lncRNAs\" paragraph 2", "quote": "We applied the “limma” R package for the entire lncRNA data to identify the differentially-expressed lncRNAs (DE lncRNAs) between tumor and paracancerous specimens, with screening criteria set at |log fold change (logFC)| > 1 and adjusted p-value < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: https://portal.gdc.cancer.gov/; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70880.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39525623", "locator": "sections[28] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: https://portal.gdc.cancer.gov/; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70880."}], "state": "complete"}, {"id": "claim-target-result", "statement": "LINC01094 was identified as a GC-associated lncRNA that dually regulates PD-L1 and PD-L2 through miR-17-5p and is associated with poor prognosis and an immunosuppressive tumor microenvironment.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39525623", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "LINC01094 dually regulates the expression of PD-L1 and PD-L2 and shapes the immunosuppressive tumor microenvironment via sponging miR-17-5p. LINC01094 may serve as a potential prognostic predictor and therapeutic target in GC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "LINC01094 was identified as a GC-associated lncRNA that dually regulates PD-L1 and PD-L2 through miR-17-5p and is associated with poor prognosis and an immunosuppressive tumor microenvironment.", "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:39525623"], "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:GSE70880"], "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:GSE70880"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39525623", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2024.1341056", "sha256": "sha256:fae571a56123d651c956b1fae3c23f874dfecdeb7cc63bed383ac7cec6826c03", "bytes": 42294, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2024.1341056", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11544118", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE70880", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70880", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE70880", "version": null, "note": "Publicly available datasets were analyzed in this study. 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Besides, the interaction between lncRNA and", "on of the target miRNA and PD-L1/PD-L2 by RT-qPCR. Besides, the interaction between lncRNA and", "70880 datasets ( Figure 4A ). Similarly, the RT-qPCR results of our cohort showed LINC01094 level", "), Relative LINC01094 expression detected by RT-qPCR in 23 paired gastric cancer and noncancerous"], "order_basis": "paper_text_order:1592", "id": "assay:2"}, {"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["s study is shown in Figure 1 . In total, 375 microarray profiles obtained from the dataset in TCGA-S"], "order_basis": "paper_text_order:4696", "id": "assay:3"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["We applied the “limma” R package for the entire lncRNA data to identify the differentially-expressed lncRNAs (DE lncRNAs) between tumor and paracancerous specimens, with screening criteria set at |log fold change (logFC)| > 1 and adjusted p-value < 0.05."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}