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pmid:30718962

Combining data from TCGA and GEO databases and reverse transcription quantitative PCR validation to identify gene prognostic markers in lung cancer.

Xiao Liu · Jun Wang · Mei Chen · Shilan Liu · Xiaodan Yu · Fuqiang Wen

OncoTargets and therapy · 2019 doi:10.2147/OTT.S183944

Paper

complete

Experiment

complete

Data

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Analysis

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Execution

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title
Combining data from TCGA and GEO databases and reverse transcription quantitative PCR validation to identify gene prognostic markers in lung cancer.
doi
10.2147/OTT.S183944
pmid
30718962
authors array · 6 items
[0]
Xiao Liu
[1]
Jun Wang
[2]
Mei Chen
[3]
Shilan Liu
[4]
Xiaodan Yu
[5]
Fuqiang Wen
journal
OncoTargets and therapy
year
2019
abstract
BACKGROUND: The aim of this study was to predict and explore the possible mechanism and clinical value of genetic markers in the development of lung cancer with a combined database to screen the prognostic genes of lung cancer. MATERIALS AND METHODS: Common differential genes in two gene expression chips (GSE3268 and GSE10072 datasets) were investigated by collecting and calculating from Gene Expression Omnibus and The Cancer Genome Atlas databases using R language. Five markers of gene composition (ribonucleotide reductase regulatory subunit M2 [RRM2], trophoblast glycoprotein [TPBG], transmembrane protease serine 4[TMPRFF4], chloride intracellular channel 3 [CLIC3], and WNT inhibitory factor-1 [WIF1]) were found by the stepwise Cox regression function when we further screened combinations of gene models, which were more meaningful for prognosis. By analyzing the correlation between gene markers and clinicopathological parameters of lung cancer and its effect on prognosis, the TPBG gene was selected to analyze differential expression, its possible pathways and functions were predicted using gene set enrichment analysis (GSEA), and its protein interaction network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database; then, quantitative PCR and the Oncomine database were used to verify the expression differences of TPBG in lung cancer cells and tissues. RESULTS: The expression levels of five genetic markers were correlated with survival prognosis, and the total survival time of the patients with high expression of the genetic markers was shorter than those with low expression (P<0.001). GSEA showed that these high-expression samples enriched the gene sets of cell adhesion, cytokine receptor interaction pathway, extracellular matrix receptor pathway, adhesion pathway, skeleton protein regulation, cancer pathway and TGF-β pathway. CONCLUSION: The high expression of five gene constituent markers is a poor prognostic factor in lung cancer and may serve as an effective biomarker for predicting metastasis and prognosis of patients with lung cancer.
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Gene expression signature of cigarette smoking and its role in lung adenocarcinoma development and survival
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Correlation analysis between gene markers and survival of lung cancer patients and verification using the TCGA database
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30718962", "kind": "science-record", "revision": 7, "content_hash": "sha256:163cc1958f21a1471c0849025b72773d159a7fd02cf9dbdffd386a2109004409", "created_at": "2026-11-01T15:40:41Z", "updated_at": "2026-11-01T21:21:58Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Combining data from TCGA and GEO databases and reverse transcription quantitative PCR validation to identify gene prognostic markers in lung cancer.", "doi": "10.2147/OTT.S183944", "pmid": "30718962", "authors": ["Xiao Liu", "Jun Wang", "Mei Chen", "Shilan Liu", "Xiaodan Yu", "Fuqiang Wen"], "journal": "OncoTargets and therapy", "year": 2019, "abstract": "BACKGROUND: The aim of this study was to predict and explore the possible mechanism and clinical value of genetic markers in the development of lung cancer with a combined database to screen the prognostic genes of lung cancer.\nMATERIALS AND METHODS: Common differential genes in two gene expression chips (GSE3268 and GSE10072 datasets) were investigated by collecting and calculating from Gene Expression Omnibus and The Cancer Genome Atlas databases using R language. Five markers of gene composition (ribonucleotide reductase regulatory subunit M2 [RRM2], trophoblast glycoprotein [TPBG], transmembrane protease serine 4[TMPRFF4], chloride intracellular channel 3 [CLIC3], and WNT inhibitory factor-1 [WIF1]) were found by the stepwise Cox regression function when we further screened combinations of gene models, which were more meaningful for prognosis. By analyzing the correlation between gene markers and clinicopathological parameters of lung cancer and its effect on prognosis, the TPBG gene was selected to analyze differential expression, its possible pathways and functions were predicted using gene set enrichment analysis (GSEA), and its protein interaction network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database; then, quantitative PCR and the Oncomine database were used to verify the expression differences of TPBG in lung cancer cells and tissues.\nRESULTS: The expression levels of five genetic markers were correlated with survival prognosis, and the total survival time of the patients with high expression of the genetic markers was shorter than those with low expression (P<0.001). GSEA showed that these high-expression samples enriched the gene sets of cell adhesion, cytokine receptor interaction pathway, extracellular matrix receptor pathway, adhesion pathway, skeleton protein regulation, cancer pathway and TGF-β pathway.\nCONCLUSION: The high expression of five gene constituent markers is a poor prognostic factor in lung cancer and may serve as an effective biomarker for predicting metastasis and prognosis of patients with lung cancer.", "claims": [{"id": "claim-data-access", "statement": "The GSE3268 dataset is the cell line data of squamous cell lung cancer patients. Each pair of samples represents a single patient with squamous lung cancer. One is derived from the cancer cells, and the other is from the normal cells. 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There were five patients, and each patient had two arrays."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:30718962"], "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:GSE10072"], "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:GSE10072"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:30718962", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/OTT.S183944", "sha256": "sha256:7c2258e3d891c1bd7990b0c803a32a473afcb129888d3dfd8daf1d88d77f97b0", "bytes": 35070, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/OTT.S183944", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6345189", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE10072", "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=GSE10072", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE10072", "version": null, "note": "The GSE3268 dataset is the cell line data of squamous cell lung cancer patients. Each pair of samples represents a single patient with squamous lung cancer. One is derived from the cancer cells, and the other is from the normal cells. There were five patients, and each patient had two arrays.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The GSE3268 dataset is the cell line data of squamous cell lung cancer patients. Each pair of samples represents a single patient with squamous lung cancer. One is derived from the cancer cells, and the other is from the normal cells. 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There were five patients, and each patient had two arrays.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM73386", "GSM73387", "GSM73388", "GSM73389", "GSM73390", "GSM73391", "GSM73392", "GSM73393", "GSM73394", "GSM73395"], "sample_count": 10, "group_sizes": null, "group_sizes_basis": null, "platform": "96", "taxon": "Homo sapiens", "title": "Squamous Lung Cancer, Paired Samples", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:30718962:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:c2af50c110e99cb3acf18c703628fd3db78def46b8091461c1ff5fa8c8f738d9", "bytes": 1062, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[17]/table-wrap[1]#t1-ott-12-709", "version": null, "note": "Cox regression model analysis of overall survival in ovarian epithelial serous tumors", "structure": {"pmcid": "PMC6345189", "section_index": 17, "section_title": "Correlation analysis between gene markers and survival of lung cancer patients and verification using the TCGA database", "row_count": 10, "column_count": 7}, "table": {"label": "Table 1", "caption": "Cox regression model analysis of overall survival in ovarian epithelial serous tumors", "rows": [["Variables", "Univariate analysis", "P-value", "Multivariate analysis", "P-value"], ["HR", "95% CI of HR", "HR", "95% CI of HR"], [""], ["Age (<60 vs ≥60) (years)", "1.084", "0.7304–1.608", "0.689", "1.5444", "0.9158–2.605", "0.1031"], ["Stage (I–II vs III–IV)", "2.817", "1.945–4.081", "4.28e-08***", "3.4494", "1.237–9.622", "1.80e-02*"], ["mRNA risk score (low vs high)", "1.653", "1.239–2.207", "6.37e-04***", "2.2696", "1.4424–3.571", "3.94e-04***"], ["MI vs M0", "1.828", "0.9734–3.432", "0.0606", "0.6405", "0.2283–1.797", "0.397250"], ["N0 + N1 vs N2 + N3", "2.437", "1.621–3.664", "1.86e-05***", "0.7024", "0.2680–1.841", "0.472320"], ["T1 + T2 vs T3 + T4", "2.439", "1.524–3.902", "2.02e-04***", "1.6833", "0.9192–3.083", "0.091573"], ["Smoke (≥3 vs <3)", "1.191", "0.8041–1.765", "0.383", "1.4059", "0.8924–2.215", "0.141845"]], "row_count": 10, "column_count": 7, "numeric_cells": 46, "header_rows": 2, "locator": "section[17]/table-wrap[1]#t1-ott-12-709"}}], "gaps": ["asset:data:geo:GSE10072 not downloaded", "asset:data:geo:GSE10072 licence not read", "asset:data:geo:GSE3268 not downloaded", "asset:data:geo:GSE3268 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Kaplan-Meier"}}, {"id": "method-2", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Cox regression"}}, {"id": "method-3", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "pathway enrichment"}}], "targets": [], "gaps": []}, "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": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "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": "R1", "reachable": true, "accessions": ["GSE3268", "GSE10072"], "resolved_accessions": ["GSE3268", "GSE10072"], "statements": ["The GSE3268 dataset is the cell line data of squamous cell lung cancer patients. Each pair of samples represents a single patient with squamous lung cancer. One is derived from the cancer cells, and the other is from the normal cells. There were five patients, and each patient had two arrays."], "basis": "The paper names GSE3268, GSE10072 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["survival_km"], "assets": ["source:pmid:30718962", "data:geo:GSE10072", "asset:table:pmid:30718962:1"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE10072"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:41:07Z", "independence": "single_reader"}, "evidence_check": {"method": "absent", "availability": null}, "calls": 3, "usage": {"prompt_tokens": 27930, "completion_tokens": 3261, "cached_tokens": 784}}, "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:30718962", "type": "paper", "label": "pmid:30718962"}, {"id": "source:pmid:30718962", "type": "manuscript", "label": "PMID 30718962 full text"}, {"id": "data:geo:GSE10072", "type": "dataset", "label": "GEO GSE10072"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:30718962", "type": "paper", "label": "pmid:30718962"}, {"id": "source:pmid:30718962", "type": "manuscript", "label": "PMID 30718962 full text"}, {"id": "data:geo:GSE10072", "type": "dataset", "label": "GEO GSE10072"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-30718962", "type": "extraction", "used": ["source:pmid:30718962"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE10072", "type": "accession_resolution", "used": ["data:geo:GSE10072"], "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:30718962", "parent_hash": "sha256:1da4a5a72a9fc7b32874d4bda5cd9429e462aabcf786448a895a7299f729eabe", "fork_of": null, "generation": 6}, "gaps": ["asset:data:geo:GSE10072 licence not read", "asset:data:geo:GSE10072 not downloaded", "asset:data:geo:GSE3268 licence not read", "asset:data:geo:GSE3268 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": ["d Island) supplemented with 10% FBS. All the cell lines were grown in a humidified incubator (5% CO2) at 37°C.", "uangzhou, China). A549 and SPCA-1 cells were cultured in minimal essential medium supplemented with 1", "New York, NY, USA). The 16-HBE-T cells were cultured in RPMI-1640 medium (Grand Island) supplemented", "tter. Cell culture Human lung adenocarcinoma A549 and SPCA-1 cells were purchased from the Ame"], "order_basis": "paper_text_order:2626", "id": "assay:1"}, {"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": 0.8, "evidence": ["Kaplan-Meier"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}