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pmid:34434214

Ferroptosis-Related Genes in Lung Adenocarcinoma: Prognostic Signature and Immune, Drug Resistance, Mutation Analysis.

Ziyuan Ren · Minghui Hu · Zhonglin Wang · Junpeng Ge · Xiaoyan Zhou · Guoming Zhang · Hongying Zheng

Frontiers in genetics · 2021 doi:10.3389/fgene.2021.672904

Paper

complete

Experiment

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Data

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Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:34434214
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2026-11-01T15:41:49Z
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2026-11-01T22:04:34Z
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title
Ferroptosis-Related Genes in Lung Adenocarcinoma: Prognostic Signature and Immune, Drug Resistance, Mutation Analysis.
doi
10.3389/fgene.2021.672904
pmid
34434214
authors array · 7 items
[0]
Ziyuan Ren
[1]
Minghui Hu
[2]
Zhonglin Wang
[3]
Junpeng Ge
[4]
Xiaoyan Zhou
[5]
Guoming Zhang
[6]
Hongying Zheng
journal
Frontiers in genetics
year
2021
abstract
It is reported that ferroptosis has close relation with tumorigenesis and drug resistance. However, the clinical significance of ferroptosis in lung adenocarcinoma (LUAD) remains elusive, and the potential targets for ferroptosis-based treatment are limited. In this study, we constructed a 15-gene prognostic signature predicting overall survival based on ferroptosis-related genes (ferroptosis driver genes VDAC2, GLS2, FLT3, TLR4, PHKG2, phosphogluconate dehydrogenase (PGD), PANX1, KRAS, PEBP1, ALOX15, and ALOX12B, and suppressor genes ACSL3, CISD1, FANCD2, and SLC3A2) in The Cancer Genome Atlas (TCGA)-LUAD cohort. The signature's predictive ability was validated in the GSE68465 and GSE72094 cohorts by survival analysis and independent prognostic analysis with clinical features. Nomograms were provided for clinical reference. Functional analysis revealed that ferroptosis was closely related to cell cycle, cell metabolism, and immune pathways. Pan-cancer analysis comprehensively analyzed these 15 genes in 33 cancer types, indicating that the heterogeneity of 15 genes was evident across different cancer types. Besides, these genes were critical regulators modulating drug resistance, tumor microenvironment infiltration, and cancer stemness. Then, we screened 10 genes (TLR4, PHKG2, PEBP1, GLS2, FLT3, ALOX15, ACSL3, CISD1, FANCD2, and SLC3A2) as potential targets for further research because their biological functions in ferroptosis were consistent with their prognostic significance. Somatic mutation and copy number variation analysis revealed that the alteration rates of KRAS, PGD, and ALOX15 were more than 1% and significantly associated with overall survival in LUAD. Moreover, the expression of KRAS and PGD was positively related to tumor mutation burden, indicating that KRAS and PGD could serve as novel biomarkers for predicting immunotherapy response rate. Our study identified and validated a ferroptosis-related gene signature for LUAD, provided a 10-gene set for future research, and screened KRAS and PGD as potential novel immunotherapy biomarkers.
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Multivariate Cox regression of the 27 FRDEGs established a 15-gene signature. The risk score was calculated using the formula: Risk score = 0.063ACSL3 + 0.224ALOX12B-0.011 ALOX15 + 0.155CISD1 + 0.104FANCD2-0.308FLT3-0.569 GLS2 + 0.066KRAS + 0.118PANX1-0.358PEBP1 + 0.010PGD-0.251PHKG2 + 0.093SLC3A2-0.176TLR4 + 0.012VDAC2 {the gene symbol means the expression of the gene [log2(normalized gene expression + 1)]}.
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sections[12] "Construction of the Prognostic Model" paragraph 2
quote
Multivariate Cox regression of the 27 FRDEGs established a 15-gene signature. The risk score was calculated using the formula: Risk score = 0.063ACSL3 + 0.224ALOX12B-0.011 ALOX15 + 0.155CISD1 + 0.104FANCD2-0.308FLT3-0.569 GLS2 + 0.066KRAS + 0.118PANX1-0.358PEBP1 + 0.010PGD-0.251PHKG2 + 0.093SLC3A2-0.176TLR4 + 0.012VDAC2 {the gene symbol means the expression of the gene [log2(normalized gene expression + 1)]}.
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The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
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sections[20] "Data Availability Statement" paragraph 2
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The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
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96
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Homo sapiens
title
caArray_jacob-00182: Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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note
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
structure object · 15 fields
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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 author.
access_statement_kind
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sample_count
442
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null
platform
15048
taxon
Homo sapiens
title
KRAS mutation-associated gene expression, p53 and STK11 mutations, proliferation and immune surveillance in lung adenocarcinoma
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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gaps array · 4 items
[0]
asset:data:geo:GSE68465 not downloaded
[1]
asset:data:geo:GSE68465 licence not read
[2]
asset:data:geo:GSE72094 not downloaded
[3]
asset:data:geo:GSE72094 licence not read
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state
partial
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[0] object · 10 fields
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method-1
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survival_analysis
specific
cox_proportional_hazards
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Survival analysis
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[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
1
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verbatim
quote
Multivariate Cox regression of the 27 FRDEGs established a 15-gene signature. The risk score was calculated using the formula: Risk score = 0.063ACSL3 + 0.224ALOX12B-0.011 ALOX15 + 0.155CISD1 + 0.104FANCD2-0.308FLT3-0.569 GLS2 + 0.066KRAS + 0.118PANX1-0.358PEBP1 + 0.010PGD-0.251PHKG2 + 0.093SLC3A2-0.176TLR4 + 0.012VDAC2 {the gene symbol means the expression of the gene [log2(normalized gene expression + 1)]}.
[1] object · 10 fields
id
method-2
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group_comparison
specific
anova
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Group comparison
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[0]
group_summary
[1]
welch_t
[2]
bootstrap_mean_difference
[3]
group_comparison_anova
missing_operations array · 0 items
parameters object · 0 fields
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[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
0.8
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high
quote
analysis of variance
[2] object · 10 fields
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method-3
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regression_modelling
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logistic
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Regression modelling
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[0]
glm_logit_fit
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
predictors_and_outcome
evidence object · 3 fields
score
0.8
band
high
quote
logistic regression
[3] object · 10 fields
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method-4
family
correlation_analysis
specific
pearson
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Correlation analysis
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[0]
pearson_r
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
paired_numeric_columns
evidence object · 3 fields
score
0.8
band
high
quote
Pearson correlation
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method-5
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correlation_analysis
specific
spearman
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Correlation analysis
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[0]
spearman_rho
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
paired_numeric_columns
evidence object · 3 fields
score
0.8
band
high
quote
Spearman correlation
[5] object · 10 fields
id
method-6
family
contingency_analysis
specific
chi_square
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Categorical (contingency table) analysis
dsl_operations array · 1 item
[0]
chi_square_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
categorical_cross_tabulation
evidence object · 3 fields
score
0.8
band
high
quote
Chi-square
[6] object · 10 fields
id
method-7
family
multi_omics_integration
specific
pathway_progeny
label
Multi-omics integration
dsl_operations array · 2 items
[0]
multiomics_factor_analysis
[1]
joint_pathway_score
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
aligned_multi_layer_matrices
evidence object · 3 fields
score
0.8
band
high
quote
progeny
targets array · 0 items
gaps array · 1 item
[0]
method.reader_differs_from_extractor
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
capability object · 4 fields
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 object · 6 fields
tier
R1
reachable
true
accessions array · 2 items
[0]
GSE68465
[1]
GSE72094
resolved_accessions array · 2 items
[0]
GSE68465
[1]
GSE72094
statements array · 1 item
[0]
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
basis
The paper names GSE68465, GSE72094 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
[0]
cox_ph
assets array · 2 items
[0]
source:pmid:34434214
[1]
data:geo:GSE68465
steps array · 1 item
[0]
run_analysis
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
[0]
data:geo:GSE68465
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:34:19Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
3
usage object · 3 fields
prompt_tokens
61058
completion_tokens
3568
cached_tokens
776
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
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[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
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null
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gaps array · 1 item
[0]
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provenance object · 7 fields
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Multivariate Cox regression of the 27 FRDEGs established a 15-gene signature. The risk score was calculated using the formula: Risk score = 0.063ACSL3 + 0.224ALOX12B-0.011 ALOX15 + 0.155CISD1 + 0.104FANCD2-0.308FLT3-0.569 GLS2 + 0.066KRAS + 0.118PANX1-0.358PEBP1 + 0.010PGD-0.251PHKG2 + 0.093SLC3A2-0.176TLR4 + 0.012VDAC2 {the gene symbol means the expression of the gene [log2(normalized gene expression + 1)]}.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34434214", "kind": "science-record", "revision": 7, "content_hash": "sha256:85bd0c5eed3ce13e9503c9eb18050930748b4ff2ed84faffb1c367830c8dc15f", "created_at": "2026-11-01T15:41:49Z", "updated_at": "2026-11-01T22:04:34Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Ferroptosis-Related Genes in Lung Adenocarcinoma: Prognostic Signature and Immune, Drug Resistance, Mutation Analysis.", "doi": "10.3389/fgene.2021.672904", "pmid": "34434214", "authors": ["Ziyuan Ren", "Minghui Hu", "Zhonglin Wang", "Junpeng Ge", "Xiaoyan Zhou", "Guoming Zhang", "Hongying Zheng"], "journal": "Frontiers in genetics", "year": 2021, "abstract": "It is reported that ferroptosis has close relation with tumorigenesis and drug resistance. However, the clinical significance of ferroptosis in lung adenocarcinoma (LUAD) remains elusive, and the potential targets for ferroptosis-based treatment are limited. In this study, we constructed a 15-gene prognostic signature predicting overall survival based on ferroptosis-related genes (ferroptosis driver genes VDAC2, GLS2, FLT3, TLR4, PHKG2, phosphogluconate dehydrogenase (PGD), PANX1, KRAS, PEBP1, ALOX15, and ALOX12B, and suppressor genes ACSL3, CISD1, FANCD2, and SLC3A2) in The Cancer Genome Atlas (TCGA)-LUAD cohort. The signature's predictive ability was validated in the GSE68465 and GSE72094 cohorts by survival analysis and independent prognostic analysis with clinical features. Nomograms were provided for clinical reference. Functional analysis revealed that ferroptosis was closely related to cell cycle, cell metabolism, and immune pathways. Pan-cancer analysis comprehensively analyzed these 15 genes in 33 cancer types, indicating that the heterogeneity of 15 genes was evident across different cancer types. Besides, these genes were critical regulators modulating drug resistance, tumor microenvironment infiltration, and cancer stemness. Then, we screened 10 genes (TLR4, PHKG2, PEBP1, GLS2, FLT3, ALOX15, ACSL3, CISD1, FANCD2, and SLC3A2) as potential targets for further research because their biological functions in ferroptosis were consistent with their prognostic significance. Somatic mutation and copy number variation analysis revealed that the alteration rates of KRAS, PGD, and ALOX15 were more than 1% and significantly associated with overall survival in LUAD. Moreover, the expression of KRAS and PGD was positively related to tumor mutation burden, indicating that KRAS and PGD could serve as novel biomarkers for predicting immunotherapy response rate. Our study identified and validated a ferroptosis-related gene signature for LUAD, provided a 10-gene set for future research, and screened KRAS and PGD as potential novel immunotherapy biomarkers.", "claims": [{"id": "claim-method", "statement": "Multivariate Cox regression of the 27 FRDEGs established a 15-gene signature. The risk score was calculated using the formula: Risk score = 0.063ACSL3 + 0.224ALOX12B-0.011 ALOX15 + 0.155CISD1 + 0.104FANCD2-0.308FLT3-0.569 GLS2 + 0.066KRAS + 0.118PANX1-0.358PEBP1 + 0.010PGD-0.251PHKG2 + 0.093SLC3A2-0.176TLR4 + 0.012VDAC2 {the gene symbol means the expression of the gene [log2(normalized gene expression + 1)]}.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34434214", "locator": "sections[12] \"Construction of the Prognostic Model\" paragraph 2", "quote": "Multivariate Cox regression of the 27 FRDEGs established a 15-gene signature. The risk score was calculated using the formula: Risk score = 0.063ACSL3 + 0.224ALOX12B-0.011 ALOX15 + 0.155CISD1 + 0.104FANCD2-0.308FLT3-0.569 GLS2 + 0.066KRAS + 0.118PANX1-0.358PEBP1 + 0.010PGD-0.251PHKG2 + 0.093SLC3A2-0.176TLR4 + 0.012VDAC2 {the gene symbol means the expression of the gene [log2(normalized gene expression + 1)]}."}], "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 author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34434214", "locator": "sections[20] \"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 author."}], "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:34434214"], "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:GSE68465"], "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:GSE68465"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34434214", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2021.672904", "sha256": 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"GSM1855209", "GSM1855210", "GSM1855211", "GSM1855212", "GSM1855213", "GSM1855214", "GSM1855215", "GSM1855216", "GSM1855217", "GSM1855218", "GSM1855219", "GSM1855220", "GSM1855221", "GSM1855222", "GSM1855223", "GSM1855224", "GSM1855225", "GSM1855226", "GSM1855227", "GSM1855228", "GSM1855229", "GSM1855230", "GSM1855231", "GSM1855232", "GSM1855233", "GSM1855234", "GSM1855235", "GSM1855236", "GSM1855237", "GSM1855238"], "sample_count": 442, "group_sizes": null, "group_sizes_basis": null, "platform": "15048", "taxon": "Homo sapiens", "title": "KRAS mutation-associated gene expression, p53 and STK11 mutations, proliferation and immune surveillance in lung adenocarcinoma", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE68465 not downloaded", "asset:data:geo:GSE68465 licence not read", "asset:data:geo:GSE72094 not downloaded", "asset:data:geo:GSE72094 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": "Multivariate Cox regression of the 27 FRDEGs established a 15-gene signature. The risk score was calculated using the formula: Risk score = 0.063ACSL3 + 0.224ALOX12B-0.011 ALOX15 + 0.155CISD1 + 0.104FANCD2-0.308FLT3-0.569 GLS2 + 0.066KRAS + 0.118PANX1-0.358PEBP1 + 0.010PGD-0.251PHKG2 + 0.093SLC3A2-0.176TLR4 + 0.012VDAC2 {the gene symbol means the expression of the gene [log2(normalized gene expression + 1)]}."}}, {"id": "method-2", "family": "group_comparison", "specific": "anova", "label": "Group comparison", "dsl_operations": ["group_summary", "welch_t", "bootstrap_mean_difference", "group_comparison_anova"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "analysis of variance"}}, {"id": "method-3", "family": "regression_modelling", "specific": "logistic", "label": "Regression modelling", "dsl_operations": ["glm_logit_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 0.8, "band": "high", "quote": "logistic regression"}}, {"id": "method-4", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Pearson correlation"}}, {"id": "method-5", "family": "correlation_analysis", "specific": "spearman", "label": "Correlation analysis", "dsl_operations": ["spearman_rho"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Spearman correlation"}}, {"id": "method-6", "family": "contingency_analysis", "specific": "chi_square", "label": "Categorical (contingency table) analysis", "dsl_operations": ["chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.8, "band": "high", "quote": "Chi-square"}}, {"id": "method-7", "family": "multi_omics_integration", "specific": "pathway_progeny", "label": "Multi-omics integration", "dsl_operations": ["multiomics_factor_analysis", "joint_pathway_score"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["aligned_multi_layer_matrices"], "evidence": {"score": 0.8, "band": "high", "quote": "progeny"}}], "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": ["GSE68465", "GSE72094"], "resolved_accessions": ["GSE68465", "GSE72094"], "statements": ["The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author."], "basis": "The paper names GSE68465, GSE72094 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:34434214", "data:geo:GSE68465"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE68465"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:34:19Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 61058, "completion_tokens": 3568, "cached_tokens": 776}}, "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:34434214", "type": "paper", "label": "pmid:34434214"}, {"id": "source:pmid:34434214", "type": "manuscript", "label": "PMID 34434214 full text"}, {"id": "data:geo:GSE68465", "type": "dataset", "label": "GEO GSE68465"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:34434214", "type": "paper", "label": "pmid:34434214"}, {"id": "source:pmid:34434214", "type": "manuscript", "label": "PMID 34434214 full text"}, {"id": "data:geo:GSE68465", "type": "dataset", "label": "GEO GSE68465"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-34434214", "type": "extraction", "used": ["source:pmid:34434214"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE68465", "type": "accession_resolution", "used": ["data:geo:GSE68465"], "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:34434214", "parent_hash": "sha256:2a76d2bc171889d65600fe0e938d2a1d334dfdd48168bda8c50d62a1888b34bb", "fork_of": null, "generation": 6}, "gaps": ["asset:data:geo:GSE68465 licence not read", "asset:data:geo:GSE68465 not downloaded", "asset:data:geo:GSE72094 licence not read", "asset:data:geo:GSE72094 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": ["Multivariate Cox regression of the 27 FRDEGs established a 15-gene signature. The risk score was calculated using the formula: Risk score = 0.063ACSL3 + 0.224ALOX12B-0.011 ALOX15 + 0.155CISD1 + 0.104FANCD2-0.308FLT3-0.569 GLS2 + 0.066KRAS + 0.118PANX1-0.358PEBP1 + 0.010PGD-0.251PHKG2 + 0.093SLC3A2-0.176TLR4 + 0.012VDAC2 {the gene symbol means the expression of the gene [log2(normalized gene expression + 1)]}."], "order_basis": "analysis_only", "id": "assay:1"}]}