Identification and validation of autophagy-related gene expression for predicting prognosis in patients with idiopathic pulmonary fibrosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36211385", "kind": "science-record", "revision": 4, "content_hash": "sha256:f936d759020426795f1fb7decc192619f9ed5a8c61cd2c49e946051f22bdf8e5", "created_at": "2026-11-01T18:15:32Z", "updated_at": "2026-11-01T22:07:45Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of autophagy-related gene expression for predicting prognosis in patients with idiopathic pulmonary fibrosis.", "doi": "10.3389/fimmu.2022.997138", "pmid": "36211385", "authors": ["Guichuan Huang", "Xin Xu", "Chunrong Ju", "Nanshan Zhong", "Jianxing He", "Xiao Xiao Tang"], "journal": "Frontiers in immunology", "year": 2022, "abstract": "Background: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and fatal fibrotic pulmonary disease with unknow etiology. Owing to lack of reliable prognostic biomarkers and effective treatment measures, patients with IPF usually exhibit poor prognosis. The aim of this study is to establish a risk score prognostic model for predicting the prognosis of patients with IPF based on autophagy-related genes.\nMethods: The GSE70866 dataset was obtained from the gene expression omnibus (GEO) database. The autophagy-related genes were collected from the Molecular Signatures Database (MSigDB). Gene enrichment analysis for differentially expressed genes (DEGs) was performed to explore the function of DEGs. Univariate, least absolute shrinkage and selection operator (LASSO), as well as multivariate Cox regression analyses were conducted to identify a multi-gene prognostic model. Receiver operating characteristic (ROC) curve was applied to assess the prediction accuracy of the model. The expression of genes screened from the prognostic model was validated in clinical samples and human lung fibroblasts by qPCR and western blot assays.\nResults: Among the 514 autophagy-related genes, a total of 165 genes were identified as DEGs. These DEGs were enriched in autophagy-related processes and pathways. Based on the univariate, LASSO, and multivariate Cox regression analyses, two genes (MET and SH3BP4) were included for establishing the risk score prognostic model. According to the median value of the risk score, patients with IPF were stratified into high-risk and low-risk groups. Patients in high-risk group had shorter overall survival (OS) than low-risk group in both training and test cohorts. Multivariate regression analysis indicated that prognostic model can act as an independent prognostic indicator for IPF. ROC curve analysis confirmed the reliable predictive value of prognostic model. In the validation experiments, upregulated MET expression and downregulated SH3BP4 expression were observed in IPF lung tissues and TGF-β1-activated human lung fibroblasts, which is consistent with results from microarray data analysis.\nConclusion: These findings indicated that the risk score prognostic model based on two autophagy-related genes can effectively predict the prognosis of patients with IPF.", "claims": [{"id": "claim-method", "statement": "First, the prognosis-related genes from autophagy-associated DEGs were identified utilizing a univariate Cox regression analysis in the training set. Then, in order to avoid overfitting, we adopted the LASSO regression analysis to obtain the crucial autophagy-associated DEGs. Finally, a multivariate Cox regression analysis was conducted to select the autophagy-associated genes for establishing a risk score prognostic model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36211385", "locator": "sections[5] \"Construction of risk score prognostic model\" paragraph 2", "quote": "First, the prognosis-related genes from autophagy-associated DEGs were identified utilizing a univariate Cox regression analysis in the training set. Then, in order to avoid overfitting, we adopted the LASSO regression analysis to obtain the crucial autophagy-associated DEGs. Finally, a multivariate Cox regression analysis was conducted to select the autophagy-associated genes for establishing a risk score prognostic model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36211385", "locator": "sections[26] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study established a two-gene autophagy-related risk score model, based on MET and SH3BP4, that effectively predicted prognosis in patients with idiopathic pulmonary fibrosis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36211385", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "These findings indicated that the risk score prognostic model based on two autophagy-related genes can effectively predict the prognosis of patients with IPF."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study established a two-gene autophagy-related risk score model, based on MET and SH3BP4, that effectively predicted prognosis in patients with idiopathic pulmonary fibrosis.", "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:36211385"], "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:GSE70866"], "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:GSE70866"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36211385", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2022.997138", "sha256": "sha256:7c0c19cd74585118e785ef76205fb68b72e173440f9bc1af765ba8b86095e17c", "bytes": 36027, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2022.997138", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9533718", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE70866", "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=GSE70866", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE70866", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1820719", "GSM1820720", "GSM1820721", "GSM1820722", "GSM1820723", "GSM1820724", "GSM1820725", "GSM1820726", "GSM1820727", "GSM1820728", "GSM1820729", "GSM1820730", "GSM1820731", "GSM1820732", "GSM1820733", "GSM1820734", "GSM1820735", "GSM1820736", "GSM1820737", "GSM1820738", "GSM1820739", "GSM1820740", "GSM1820741", "GSM1820742", "GSM1820743", "GSM1820744", "GSM1820745", "GSM1820746", "GSM1820747", "GSM1820748", "GSM1820749", "GSM1820750", "GSM1820751", "GSM1820752", "GSM1820753", "GSM1820754", "GSM1820755", "GSM1820756", "GSM1820757", "GSM1820758", "GSM1820759", "GSM1820760", "GSM1820761", "GSM1820762", "GSM1820763", "GSM1820764", "GSM1820765", "GSM1820766", "GSM1820767", "GSM1820768", "GSM1820769", "GSM1820770", "GSM1820771", "GSM1820772", "GSM1820773", "GSM1820774", "GSM1820775", "GSM1820776", "GSM1820777", "GSM1820778", "GSM1820779", "GSM1820780", "GSM1820781", "GSM1820782", "GSM1820783", "GSM1820784", "GSM1820785", "GSM1820786", "GSM1820787", "GSM1820788", "GSM1820789", "GSM1820790", "GSM1820791", "GSM1820792", "GSM1820793", "GSM1820794", "GSM1820795", "GSM1820796", "GSM1820797", "GSM1820798", "GSM1820799", "GSM1820800", "GSM1820801", "GSM1820802", "GSM1820803", "GSM1820804", "GSM1820805", "GSM1820806", "GSM1820807", "GSM1820808", "GSM1820809", "GSM1820810", "GSM1820811", "GSM1820812", "GSM1820813", "GSM1820814", "GSM1820815", "GSM1820816", "GSM1820817", "GSM1820818", "GSM1820819", "GSM1820820", "GSM1820821", "GSM1820822", "GSM1820823", "GSM1820824", "GSM1820825", "GSM1820826", "GSM1820827", "GSM1820828", "GSM1820829", "GSM1820830", "GSM1820831", "GSM1820832", "GSM1820833", "GSM1820834", "GSM1820835", "GSM1820836", "GSM1820837", "GSM1820838", "GSM1820839", "GSM1820840", "GSM1820841", "GSM1820842", "GSM1820843", "GSM1820844", "GSM1820845", "GSM1820846", "GSM1820847", "GSM1820848", "GSM1820849", "GSM1820850", "GSM1820851", "GSM1820852", "GSM1820853", "GSM1820854", "GSM1820855", "GSM1820856", "GSM1820857", "GSM1820858", "GSM1820859", "GSM1820860", "GSM1820861", "GSM1820862", "GSM1820863", "GSM1820864", "GSM1820865", "GSM1820866", "GSM1820867", "GSM1820868", "GSM1820869", "GSM1820870", "GSM1820871", "GSM1820872", "GSM1820873", "GSM1820874", "GSM1820875", "GSM1820876", "GSM1820877", "GSM1820878", "GSM1820879", "GSM1820880", "GSM1820881", "GSM1820882", "GSM1820883", "GSM1820884", "GSM1820885", "GSM1820886", "GSM1820887", "GSM1820888", "GSM1820889", "GSM1820890", "GSM1820891", "GSM1820892", "GSM1820893", "GSM1820894", "GSM1820895", "GSM1820896", "GSM1820897", "GSM1820898", "GSM1820899", "GSM1820900", "GSM1820901", "GSM1820902", "GSM1820903", "GSM1820904", "GSM1820905", "GSM1820906", "GSM1820907", "GSM1820908", "GSM1820909", "GSM1820910", "GSM1820911", "GSM1820912", "GSM1820913", "GSM1820914"], "sample_count": 196, "group_sizes": null, "group_sizes_basis": null, "platform": "17077;14550", "taxon": "Homo sapiens", "title": "BAL cell gene expression is predictive of Mortality in Idiopathic Pulmonary Fibrosis and enriched for Genes of Airway Basal Cells (II)", "resolution_checked_at": "2026-11-01T17:30:42Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE70866 not downloaded", "asset:data:geo:GSE70866 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "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": 1.0, "band": "verbatim", "quote": "First, the prognosis-related genes from autophagy-associated DEGs were identified utilizing a univariate Cox regression analysis in the training set. Then, in order to avoid overfitting, we adopted the LASSO regression analysis to obtain the crucial autophagy-associated DEGs. Finally, a multivariate Cox regression analysis was conducted to select the autophagy-associated genes for establishing a risk score prognostic model."}}, {"id": "method-2", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "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-4", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"id": "method-5", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.7, "band": "medium", "quote": "ROC curve"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["GSE70866"], "resolved_accessions": ["GSE70866"], "statements": ["The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors."], "basis": "The paper names GSE70866 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": ["cox_ph"], "assets": ["source:pmid:36211385", "data:geo:GSE70866"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE70866"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:09:19Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10121, "completion_tokens": 1354, "cached_tokens": 256}}, "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:36211385", "type": "paper", "label": "pmid:36211385"}, {"id": "source:pmid:36211385", "type": "manuscript", "label": "PMID 36211385 full text"}, {"id": "data:geo:GSE70866", "type": "dataset", "label": "GEO GSE70866"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36211385", "type": "paper", "label": "pmid:36211385"}, {"id": "source:pmid:36211385", "type": "manuscript", "label": "PMID 36211385 full text"}, {"id": "data:geo:GSE70866", "type": "dataset", "label": "GEO GSE70866"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36211385", "type": "extraction", "used": ["source:pmid:36211385"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE70866", "type": "accession_resolution", "used": ["data:geo:GSE70866"], "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:36211385", "parent_hash": "sha256:a0ecf77c36c0e8a5d6b3149b46edd3322dee99955098e012d13bbb0bc9332609", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE70866 licence not read", "asset:data:geo:GSE70866 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": ["inical samples and human lung fibroblasts by qPCR and western blot assays. Results: Among the", "e risk score prognostic model. Raw data from qPCR and western blot analysis were presented as"], "order_basis": "paper_text_order:1215", "id": "assay:1"}, {"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": ["mples and human lung fibroblasts by qPCR and western blot assays. Results: Among the 514 autophagy-rel", "ore prognostic model. Raw data from qPCR and western blot analysis were presented as “mean ± standard"], "order_basis": "paper_text_order:1224", "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": ["lasts, which is consistent with results from microarray data analysis. Conclusion: These findings in"], "order_basis": "paper_text_order:2222", "id": "assay:3"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["sts were purchased from the ATCC. Cells were cultured in DMEM medium supplemented with 10% fetal bovi"], "order_basis": "paper_text_order:2909", "id": "assay:4"}, {"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": ["First, the prognosis-related genes from autophagy-associated DEGs were identified utilizing a univariate Cox regression analysis in the training set. Then, in order to avoid overfitting, we adopted the LASSO regression analysis to obtain the crucial autophagy-associated DEGs. Finally, a multivariate Cox regression analysis was conducted to select the autophagy-associated genes for establishing a risk score prognostic model."], "order_basis": "consumes_earlier_output", "id": "assay:5"}]}