Identification of potential tumor-educated platelets RNA biomarkers in non-small-cell lung cancer by integrated bioinformatical analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29665143", "kind": "science-record", "revision": 2, "content_hash": "sha256:b1309864f4e1833557828326b966d81815f2619b0d3a6771ddddda0c0c81a621", "created_at": "2026-11-01T15:40:33Z", "updated_at": "2026-11-01T18:49:26Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of potential tumor-educated platelets RNA biomarkers in non-small-cell lung cancer by integrated bioinformatical analysis.", "doi": "10.1002/jcla.22450", "pmid": "29665143", "authors": ["Linlin Xue", "Li Xie", "Xingguo Song", "Xianrang Song"], "journal": "Journal of clinical laboratory analysis", "year": 2018, "abstract": "BACKGROUND: Platelets have emerged as key players in tumorigenesis and tumor progression. Tumor-educated platelet (TEP) RNA profile has the potential to diagnose non-small-cell lung cancer (NSCLC). The objective of this study was to identify potential TEP RNA biomarkers for the diagnosis of NSCLC and to explore the mechanisms in alternations of TEP RNA profile.\nMETHODS: The RNA-seq datasets GSE68086 and GSE89843 were downloaded from Gene Expression Omnibus DataSets (GEO DataSets). Then, the functional enrichment of the differentially expressed mRNAs was analyzed by the Database for Annotation Visualization and Integrated Discovery (DAVID). The miRNAs which regulated the differential mRNAs and the target mRNAs of miRNAs were identified by miRanda and miRDB. Then, the miRNA-mRNA regulatory network was visualized via Cytoscape software.\nRESULTS: Twenty consistently altered mRNAs (2 up-regulated and 18 down-regulated) were identified from the two GSE datasets, and they were significantly enriched in several biological processes, including transport and establishment of localization. Twenty identical miRNAs were found between exosomal miRNA-seq dataset and 229 miRNAs that regulated 20 consistently differential mRNAs in platelets. We also analyzed 13 spliceosomal mRNAs and their miRNA predictions; there were 27 common miRNAs between 206 differential exosomal miRNAs and 338 miRNAs that regulated 13 distinct spliceosomal mRNAs.\nCONCLUSION: This study identified 20 potential TEP RNA biomarkers in NSCLC for diagnosis by integrated bioinformatical analysis, and alternations in TEP RNA profile may be related to the post-transcriptional regulation and the splicing metabolisms of spliceosome.", "claims": [{"id": "claim-target-result", "statement": "The study identified 20 potential TEP RNA biomarkers for NSCLC diagnosis. The abstract does not specify a statistical method; it reports that the RNA-seq datasets GSE68086 and GSE89843 were downloaded from GEO DataSets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:29665143", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "This study identified 20 potential TEP RNA biomarkers in NSCLC for diagnosis by integrated bioinformatical analysis, and alternations in TEP RNA profile may be related to the post‐transcriptional regulation and the splicing metabolisms of spliceosome."}, {"asset": "source:pmid:29665143", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The RNA‐seq datasets GSE68086 and GSE89843 were downloaded from Gene Expression Omnibus DataSets (GEO DataSets)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The study identified 20 potential TEP RNA biomarkers for NSCLC diagnosis. The abstract does not specify a statistical method; it reports that the RNA-seq datasets GSE68086 and GSE89843 were downloaded from GEO DataSets.", "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:29665143"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "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": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:29665143", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1002/jcla.22450", "sha256": "sha256:6c41b83d96f101f853289b33c46466cbc3ae8a6f2af458e70f7a66df95a4be35", "bytes": 1678, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1002/jcla.22450", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6817076", "source": "ncbi_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "absent", "methods": [], "targets": [], "gaps": ["method", "operations"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R4", "expressible": false, "required_operations": [], "missing_operations": [], "basis": "The reader quoted the method the paper names (not named), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": [], "basis": "The paper names no accession to its source data, so the data has to come from the authors."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:29665143"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:None"]}, "gaps": ["data:accession_absent"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:34:14Z", "independence": "single_reader"}, "evidence_check": {"method": null, "availability": null}, "calls": 2, "usage": {"prompt_tokens": 1692, "completion_tokens": 941, "cached_tokens": 520}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:29665143", "type": "paper", "label": "pmid:29665143"}, {"id": "source:pmid:29665143", "type": "manuscript", "label": "PMID 29665143 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:29665143", "type": "paper", "label": "pmid:29665143"}, {"id": "source:pmid:29665143", "type": "manuscript", "label": "PMID 29665143 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-29665143", "type": "extraction", "used": ["source:pmid:29665143"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-None", "type": "accession_resolution", "used": ["data:geo:None"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:29665143", "parent_hash": "sha256:5fc5b78a938787aac74997380b9ef426d5bace811af82325ba3e14b60f68fa00", "fork_of": null, "generation": 1}, "gaps": ["execution.not_run", "method", "operations", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:obtain_source_data blocked on data:accession_absent"], "assays": [{"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["lternations of TEP RNA profile. 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