← All .science files
pmid:35912258
A Novel Pyroptosis-Related Gene Signature for Predicting the Prognosis and the Associated Immune Infiltration in Colon Adenocarcinoma.
Zhiyuan Chen · Zheng Han · Han Nan · Jianing Fan · Jingfei Zhan · Yu Zhang · He Zhu · Yu Cao · Xian Shen · Xiangyang Xue · Kezhi Lin
Frontiers in oncology · 2022 doi:10.3389/fonc.2022.904464
Paper
complete
Experiment
complete
Data
partial
Analysis
complete
Execution
absent
Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
paper object · 10 fields
authors array · 11 items
claims array · 3 items
[0] object · 6 fields
evidence array · 1 item
[0] object · 3 fields
[1] object · 6 fields
evidence array · 1 item
[0] object · 3 fields
gaps array · 0 items
experiment object · 8 fields
steps array · 3 items
[0] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[1] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[2] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
materials array · 0 items
instruments array · 0 items
reagents array · 0 items
conditions object · 0 fields
gaps array · 0 items
data object · 3 fields
assets array · 2 items
[0] object · 15 fields
structure object · 4 fields
[1] object · 15 fields
structure object · 15 fields
sample_accessions array · 55 items
gaps array · 2 items
analysis object · 4 fields
methods array · 2 items
[0] object · 10 fields
dsl_operations array · 1 item
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[1] object · 10 fields
dsl_operations array · 1 item
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
targets array · 0 items
gaps array · 0 items
capability object · 3 fields
requirements array · 1 item
[0] object · 6 fields
assay_families array · 9 items
gaps array · 0 items
readiness object · 8 fields
axes object · 3 fields
method object · 5 fields
required_operations array · 1 item
missing_operations array · 0 items
capability object · 4 fields
data object · 6 fields
accessions array · 1 item
resolved_accessions array · 1 item
statements array · 1 item
can_run object · 3 fields
dsl_operations array · 1 item
assets array · 2 items
steps array · 1 item
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
gaps array · 0 items
review object · 5 fields
machine_critique object · 5 fields
reader object · 5 fields
evidence_check object · 2 fields
usage object · 3 fields
stages array · 1 item
[0] object · 4 fields
gaps array · 3 items
provenance object · 7 fields
entities array · 3 items
activities array · 3 items
[0] object · 4 fields
used array · 3 items
[0] object · 3 fields
[1] object · 3 fields
[2] object · 3 fields
[1] object · 4 fields
agents array · 2 items
lineage object · 4 fields
gaps array · 6 items
assays array · 2 items
[0] object · 11 fields
required_operations array · 0 items
source_hashes object · 1 field
evidence array · 1 item
[1] object · 11 fields
required_operations array · 1 item
source_hashes object · 1 field
evidence array · 1 item
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35912258", "kind": "science-record", "revision": 3, "content_hash": "sha256:aeb569f9f602b3246da47e0b5339504150fd6f4da469faba5273be776e5fd21d", "created_at": "2026-11-01T18:15:00Z", "updated_at": "2026-11-01T21:28:31Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Novel Pyroptosis-Related Gene Signature for Predicting the Prognosis and the Associated Immune Infiltration in Colon Adenocarcinoma.", "doi": "10.3389/fonc.2022.904464", "pmid": "35912258", "authors": ["Zhiyuan Chen", "Zheng Han", "Han Nan", "Jianing Fan", "Jingfei Zhan", "Yu Zhang", "He Zhu", "Yu Cao", "Xian Shen", "Xiangyang Xue", "Kezhi Lin"], "journal": "Frontiers in oncology", "year": 2022, "abstract": "Background: Pyroptosis has been demonstrated to be an inflammatory form of programmed cell death recently. However, the expression of pyroptosis-related genes (PRGs) in colon adenocarcinoma (COAD) and their correlations with prognosis remain unclear.\nMethods: Data of COAD patients were obtained from The Cancer Genome Atlas (TCGA) database to screen differentially expressed genes (DEGs). Univariate Cox regression analysis and the LASSO Cox regression analysis were applied to construct a gene signature. All COAD patients in TCGA cohort were separated into low-risk subgroup or high-risk subgroup via the risk score. Kaplan-Meier survival analysis and receiver operator characteristic (ROC) curves were adopted to assess its prognostic efficiency. COAD data from the GSE17537 datasets was used for validation. A prognostic nomogram was established to predict individual survival. The correlation between PRGs and immune cell infiltration in COAD was verified based on TIMER database. CIBERSORT analysis was utilized on risk subgroup as defined by model. The protein and mRNA expression level of PRGs were verified by HPA database and qPCR.\nResults: A total of 51 differentially expressed PRGs were identified in TCGA cohort. Through univariate Cox regression analysis and LASSO Cox regression analysis, a prognostic model containing 7 PRGs was constructed. Kaplan-Meier survival analysis indicated that patients in the low-risk subgroup exhibited better prognosis compared to those in the high-risk subgroup. Additionally, the area under the curve (AUC) of ROC is 0.60, 0.63, and 0.73 for 1-, 3-, and 5-year survival in TCGA cohort and 0.63, 0.65, and 0.64 in validation set. TIMER database showed a strong correlation between 7 PRGs and tumor microenvironment in COAD. Moreover, CIBERSORT showed significant differences in the infiltration of plasma cells, M0 macrophages, resting dendritic cells, and eosinophils between low-risk subgroup and high-risk subgroup. HPA database showed that protein expression level of SDHB, GZMA, BTK, EEF2K, and NR1H2 was higher in normal tissues. And the transcriptional level of CASP5, BTK, SDHB, GZMA, and RIPK3 was high in normal tissues.\nConclusions: Our study identified a novel PRGs signature that could be used to predict the prognosis of COAD patients, which might provide a new therapeutic target for the treatment of COAD patients.", "claims": [{"id": "claim-method", "statement": "Then, using R package “glmnet”, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed in order to select candidate PRGs and develop a pyroptosis-related prognostic gene model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35912258", "locator": "sections[7] \"Development of a Pyroptosis-Related Prognostic Gene Model\" paragraph 2", "quote": "Then, using R package “glmnet”, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed in order to select candidate PRGs and develop a pyroptosis-related prognostic gene model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35912258", "locator": "sections[26] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The 7-gene pyroptosis-related prognostic model had TCGA AUCs of 0.60, 0.63, and 0.73 for 1-, 3-, and 5-year survival and validation-set AUCs of 0.63, 0.65, and 0.64.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35912258", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Additionally, the area under the curve (AUC) of ROC is 0.60, 0.63, and 0.73 for 1-, 3-, and 5-year survival in TCGA cohort and 0.63, 0.65, and 0.64 in validation set."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The 7-gene pyroptosis-related prognostic model had TCGA AUCs of 0.60, 0.63, and 0.73 for 1-, 3-, and 5-year survival and validation-set AUCs of 0.63, 0.65, and 0.64.", "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:35912258"], "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:GSE17537"], "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:GSE17537"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35912258", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2022.904464", "sha256": "sha256:fb0b3fdbd30a113a7f72fc4963d8f1374950c0ad3d747ee6bcdc3d3554f59944", "bytes": 51447, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2022.904464", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9330598", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE17537", "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=GSE17537", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE17537", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM437270", "GSM437271", "GSM437272", "GSM437273", "GSM437274", "GSM437275", "GSM437276", "GSM437277", "GSM437278", "GSM437279", "GSM437280", "GSM437281", "GSM437282", "GSM437283", "GSM437284", "GSM437285", "GSM437286", "GSM437287", "GSM437288", "GSM437289", "GSM437290", "GSM437291", "GSM437292", "GSM437293", "GSM437294", "GSM437295", "GSM437296", "GSM437297", "GSM437298", "GSM437299", "GSM437300", "GSM437301", "GSM437302", "GSM437303", "GSM437304", "GSM437305", "GSM437306", "GSM437307", "GSM437308", "GSM437309", "GSM437310", "GSM437311", "GSM437312", "GSM437313", "GSM437314", "GSM437315", "GSM437316", "GSM437317", "GSM437318", "GSM437319", "GSM437320", "GSM437321", "GSM437322", "GSM437323", "GSM437324"], "sample_count": 55, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients (VMC Samples)", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE17537 not downloaded", "asset:data:geo:GSE17537 licence not read"]}, "analysis": {"state": "complete", "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": "Then, using R package “glmnet”, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed in order to select candidate PRGs and develop a pyroptosis-related prognostic gene model."}}, {"id": "method-2", "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": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}], "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": ["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": ["GSE17537"], "resolved_accessions": ["GSE17537"], "statements": ["The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."], "basis": "The paper names GSE17537 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:35912258", "data:geo:GSE17537"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE17537"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:58:07Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 15729, "completion_tokens": 2296, "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:35912258", "type": "paper", "label": "pmid:35912258"}, {"id": "source:pmid:35912258", "type": "manuscript", "label": "PMID 35912258 full text"}, {"id": "data:geo:GSE17537", "type": "dataset", "label": "GEO GSE17537"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35912258", "type": "paper", "label": "pmid:35912258"}, {"id": "source:pmid:35912258", "type": "manuscript", "label": "PMID 35912258 full text"}, {"id": "data:geo:GSE17537", "type": "dataset", "label": "GEO GSE17537"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35912258", "type": "extraction", "used": ["source:pmid:35912258"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE17537", "type": "accession_resolution", "used": ["data:geo:GSE17537"], "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:35912258", "parent_hash": "sha256:870a58a442366f9cda7646eb973b503a7b557be3ba24ac87d2f81298015f7048", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE17537 licence not read", "asset:data:geo:GSE17537 not downloaded", "execution.not_run", "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": 0.93, "evidence": ["el of PRGs were verified by HPA database and qPCR. Results: A total of 51 differentially expre"], "order_basis": "paper_text_order:1227", "id": "assay:1"}, {"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": ["Then, using R package “glmnet”, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed in order to select candidate PRGs and develop a pyroptosis-related prognostic gene model."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}