A prognostic risk model based on DNA methylation levels of genes and lncRNAs in lung squamous cell carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35356464", "kind": "science-record", "revision": 3, "content_hash": "sha256:dfc31947edc9c9843e4b475edff973b8f4dd584537d870dd7a6b8e03bba68386", "created_at": "2026-11-01T18:14:09Z", "updated_at": "2026-11-01T21:27:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A prognostic risk model based on DNA methylation levels of genes and lncRNAs in lung squamous cell carcinoma.", "doi": "10.7717/peerj.13057", "pmid": "35356464", "authors": ["Weiqing Wang", "Ming Xiang", "Hui Liu", "Xiao Chu", "Zhaoyun Sun", "Liang Feng"], "journal": "PeerJ", "year": 2022, "abstract": "Background: Recurrence is a risk factor for the prognosis of lung squamous carcinoma (LUSC). DNA methylation levels of RNAs are also associated with LUSC prognosis. This study aimed to construct a prognostic model with high performance in predicting LUSC prognosis using the methylation levels of lncRNAs and genes.\nMethods: The differentially expressed RNAs (DERs) and differentially methylated RNAs (DMRs) between the recurrent and non-recurrent LUSC tissues in The Cancer Genome Atlas (TCGA; training dataset) were identified. Weighted correlation network analysis was performed to identify co-methylation networks. Differentially methylated genes and lncRNAs with opposite expression-methylation levels were used for the screening of prognosis-associated RNAs. The prognostic model was constructed and its performance was validated in the GSE39279 dataset.\nResults: A total of 664 DERs and 981 DMRs (including 972 genes) in recurrent LUSC tissues were identified. Three co-methylation modules, including 226 differentially methylated genes, were significantly associated with LUSC. Among prognosis-associated RNAs, 18 DERs/DMRs with opposite methylation-expression levels were included in the methylation prognostic risk model. LUSC patients with high risk scores had a poor prognosis compared with patients who had low risk scores (TCGA: HR = 3.856, 95% CI [2.297-6.471]; GSE39279: HR = 3.040, 95% CI [1.435-6.437]). This model had a high accuracy in predicting the prognosis (AUC = 0.903 and 0.800, respectively), equivalent to the nomogram model inclusive of clinical variables.\nConclusions: Referring to the methylation levels of the 16-RNAs might help to predict the survival outcomes in LUSC.", "claims": [{"id": "claim-method", "statement": "The optimal methylation combination was subsequently identified using the Cox-Proportional Hazards (Cox-PH) model (L1-penalized least absolute shrinkage and selection operator, LASSO) in the R penalized package (version 0.9-50, http://bioconductor.org/packages/penalized/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35356464", "locator": "sections[6] \"Construction of methylation prognostic model\" paragraph 2", "quote": "The optimal methylation combination was subsequently identified using the Cox-Proportional Hazards (Cox-PH) model (L1-penalized least absolute shrinkage and selection operator, LASSO) in the R penalized package (version 0.9-50, http://bioconductor.org/packages/penalized/)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:\nThe original LUSC RNA-seq (Illumina HiSeq 2000 RNA Sequencing) and methylation profile data (Illumina Infinium Human Methylation 450 BeadChip) are available at The Cancer Genome Atlas (TCGA LUSC; https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga) and the original microarray data is available at the Gene Expression Omnibus: GSE39279.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35356464", "locator": "sections[31] \"Data Availability Statement\" paragraphs 1-3", "quote": "The following information was supplied regarding data availability:\nThe original LUSC RNA-seq (Illumina HiSeq 2000 RNA Sequencing) and methylation profile data (Illumina Infinium Human Methylation 450 BeadChip) are available at The Cancer Genome Atlas (TCGA LUSC; https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga) and the original microarray data is available at the Gene Expression Omnibus: GSE39279."}], "state": "complete"}, {"id": "claim-target-result", "statement": "An 18-RNA methylation prognostic model constructed with Cox-PH LASSO using TCGA LUSC data distinguished high- from low-risk patients and was validated in GSE39279.", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "LUSC patients with high risk scores had a poor prognosis compared with patients who had low risk scores (TCGA: HR = 3.856, 95% CI [2.297–6.471]; GSE39279: HR = 3.040, 95% CI [1.435–6.437]). This model had a high accuracy in predicting the prognosis (AUC = 0.903 and 0.800, respectively), equivalent to the nomogram model inclusive of clinical variables."}, "evidence": [{"asset": "source:pmid:35356464", "locator": "sections[14] \"Construction of the methylation prognostic model\" paragraph 2", "quote": "An optimized methylation prognostic combination was identified using the Cox-PH model based on the 26 prognosis-associated DMRs. Eighteen DMRs, including two lncRNAs and 16 genes, were included in this methylation prognostic combination (Table 2)."}, {"asset": "source:pmid:35356464", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The prognostic model was constructed and its performance was validated in the GSE39279 dataset."}, {"asset": "source:pmid:35356464", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "LUSC patients with high risk scores had a poor prognosis compared with patients who had low risk scores (TCGA: HR = 3.856, 95% CI [2.297–6.471]; GSE39279: HR = 3.040, 95% CI [1.435–6.437]). This model had a high accuracy in predicting the prognosis (AUC = 0.903 and 0.800, respectively), equivalent to the nomogram model inclusive of clinical variables."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "An 18-RNA methylation prognostic model constructed with Cox-PH LASSO using TCGA LUSC data distinguished high- from low-risk patients and was validated in GSE39279.", "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:35356464"], "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:GSE39279"], "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:GSE39279"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35356464", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7717/peerj.13057", "sha256": 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No tolerance is published because the paper states none."}], "gaps": ["method.reader_named_unmapped"]}, "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": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "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": ["GSE39279"], "resolved_accessions": ["GSE39279"], "statements": ["The following information was supplied regarding data availability:\nThe original LUSC RNA-seq (Illumina HiSeq 2000 RNA Sequencing) and methylation profile data (Illumina Infinium Human Methylation 450 BeadChip) are available at The Cancer Genome Atlas (TCGA LUSC; https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga) and the original microarray data is available at the Gene Expression Omnibus: GSE39279."], "basis": "The paper names GSE39279 in Gene Expression Omnibus and the accession resolves in the repository. 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