A Novel Pyroptosis-Related Gene Signature for Early-Stage Lung Squamous Cell Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34675612", "kind": "science-record", "revision": 4, "content_hash": "sha256:7e14a84e2878fc0c3c7eb21efcfca29f64afbfb0ac4d92ea9e08caf46fb19b4f", "created_at": "2026-11-01T17:36:20Z", "updated_at": "2026-11-01T22:04:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Novel Pyroptosis-Related Gene Signature for Early-Stage Lung Squamous Cell Carcinoma.", "doi": "10.2147/IJGM.S331975", "pmid": "34675612", "authors": ["Xiaoyan Li", "Jie He"], "journal": "International journal of general medicine", "year": 2021, "abstract": "BACKGROUND: Diagnosis of early stage lung squamous cell carcinoma (LUSC) has improved; however, a comprehensive analysis of prognostic signatures is needed.\nPURPOSE: To identify, establish, and validate a signature model based on pyroptosis-related genes for prognostic predictions of early stage LUSC.\nPATIENTS AND METHODS: Two independent cohorts were included. RNA-seq transcriptome data from patients with early stage LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Thirty-three pyroptosis-related genes were analyzed between early stage LUSC and normal lung tissues. Cox regression analysis, random survival forest, and least absolute shrinkage and selection operator algorithms established a three-gene signature. Kaplan-Meier survival and receiver-operating characteristic curves assessed the prognostic efficacy of the model. Single-sample gene set enrichment analysis (ssGSEA) assessed the relationship between pyroptosis and immune cells. Patients with early stage LUSC from the GSE74777 dataset were used for validation. Pyroptosis-related genes were verified by RT-qPCR and Western blotting.\nRESULTS: Twenty-three differentially expressed pyroptosis-related genes were identified in the LUSC and adjacent normal tissues. Three differentially expressed pyroptosis-related genes were identified as hub genes in early stage LUSC. Patients with early stage LUSC in the TCGA cohort were classified into low- and high-risk subgroups according to the risk score. Overall survival (OS) was significantly short in the high-risk subgroup versus the low-risk subgroup. A similar result was found for the GSE74777 dataset. ssGSEA of immune cells and immune-related pathways between the low- and high-risk subgroups may explain the different OS for patients with early-stage LUSC. IL-6 expression was upregulated, which was inconsistent with the bioinformatic analysis. NOD1 and CASP4 were downregulated in LUSC (all P < 0.05) versus normal lung tissues.\nCONCLUSION: Differentially expressed pyroptosis-related genes may be involved in early stage LUSC. Pyroptosis-related genes are important in tumor immunity and may be potential prognostic predictors for early stage LUSC.", "claims": [{"id": "claim-method", "statement": "Univariate Cox regression, random survival forest, and LASSO algorithm analyses were used to evaluate the correlations between the factors and OS through the “survival,” “glmnet” and “randomForestSRC” package in R.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34675612", "locator": "sections[10] \"Statistical Analysis\" paragraph 2", "quote": "Univariate Cox regression, random survival forest, and LASSO algorithm analyses were used to evaluate the correlations between the factors and OS through the “survival,” “glmnet” and “randomForestSRC” package in R."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data can be retrieved from the TCGA and GEO databases (GEO database https://www.ncbi.nlm.nih.gov/GEO/query/acc.cgi?acc=gse74777, TCGA database https://portal.gdc.cancer.gov/). The codes used in this study can be obtained from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34675612", "locator": "sections[22] \"Data Acquisition\" paragraph 2", "quote": "Data can be retrieved from the TCGA and GEO databases (GEO database https://www.ncbi.nlm.nih.gov/GEO/query/acc.cgi?acc=gse74777, TCGA database https://portal.gdc.cancer.gov/). The codes used in this study can be obtained from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The high-risk subgroup had significantly shorter overall survival than the low-risk subgroup in the TCGA cohort (P = 0.013).", "kind": "quantitative", "target": {"value": 0.013, "unit": "p-value", "tolerance": null, "source": "A significant difference in OS time was detected between the two groups (P = 0.013, Figure 6E)."}, "evidence": [{"asset": "source:pmid:34675612", "locator": "sections[13] \"Prognostic Signature Model in the TCGA Cohort\" paragraph 2", "quote": "A significant difference in OS time was detected between the two groups (P = 0.013, Figure 6E)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The high-risk subgroup had significantly shorter overall survival than the low-risk subgroup in the TCGA cohort (P = 0.013).", "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:34675612"], "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:GSE74777"], "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:GSE74777"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34675612", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/IJGM.S331975", "sha256": "sha256:956dae0b7e4d6b5ff2d3445f7a2edf5cb0675f505c6111a2cbf0d178da606d12", "bytes": 46166, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/IJGM.S331975", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8502038", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE74777", "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=GSE74777", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE74777", "version": null, "note": "Data can be retrieved from the TCGA and GEO databases (GEO database https://www.ncbi.nlm.nih.gov/GEO/query/acc.cgi?acc=gse74777, TCGA database https://portal.gdc.cancer.gov/). 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RNA-seq transcriptome data from patients with early", "o independent cohorts were included. RNA-seq transcriptome data from patients with early stage LUSC wer"], "order_basis": "paper_text_order:407", "id": "assay:1"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["n. Pyroptosis-related genes were verified by RT-qPCR and Western blotting. RESULTS: Twenty-three", "Pyroptosis-related genes were verified by RT-qPCR and Western blotting. RESULTS: Twenty-three"], "order_basis": "paper_text_order:1134", "id": "assay:2"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["s-related genes were verified by RT-qPCR and Western blotting. RESULTS: Twenty-three differentially expres", "linical samples were evaluated by RT-PCR and Western blotting. The clinicopathological variables of the pa"], "order_basis": "paper_text_order:1146", "id": "assay:3"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Univariate Cox regression, random survival forest, and LASSO algorithm analyses were used to evaluate the correlations between the factors and OS through the “survival,” “glmnet” and “randomForestSRC” package in R."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}