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pmid:36221049

Novel six-gene prognostic signature based on colon adenocarcinoma immune-related genes.

Rui Zhou · Zhuowei Gao · Yongle Ju

BMC bioinformatics · 2022 doi:10.1186/s12859-022-04909-2

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Experiment

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title
Novel six-gene prognostic signature based on colon adenocarcinoma immune-related genes.
doi
10.1186/s12859-022-04909-2
pmid
36221049
authors array · 3 items
[0]
Rui Zhou
[1]
Zhuowei Gao
[2]
Yongle Ju
journal
BMC bioinformatics
year
2022
abstract
BACKGROUND: Colon adenocarcinoma (COAD) is one of the most common gastrointestinal tumors worldwide, and immunotherapy is one of the most promising treatments for it. Identifying immune genes involved in the development and maintenance of cancer is key to the use of tumor immunotherapy. This study aimed to determine the prognostic value of immune genes in patients with COAD and to establish an immune-related gene signature. Differentially expressed genes, immune-related genes (DEIGs), and transcription factors (DETFs) were screened using the following databases: Cistrome, The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and InnateDB. We constructed a network showing the regulation of DEIGs by DETFs. Using weighted gene co-expression network analysis, we prepared 5 co-expressed gene modules; 6 hub genes (CD1A, CD1B, FGF9, GRP, SERPINE1, and F2RL2) obtained using univariate and multivariate regression analysis were used to construct a risk model. Patients from TCGA database were divided into high- and low-risk groups based on whether their risk score was greater or less than the mean; the public dataset GSE40967, which contains gene expression profiles of 566 colon cancer patients, was used for validation. RESULTS: Survival analysis, somatic gene mutations, and tumor-infiltrating immune cells differed significantly between the high- and low-risk groups. CONCLUSIONS: This immune-related gene signature could play an important role in guiding treatment, making prognoses, and potentially developing future clinical applications.
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Based on the expression of screened genes from the previous step, a risk model was built using multivariate Cox regression model analysis, calculated as follows: Risk score = Expgene1 × coefgene1 + Expgene2 × coefgene2 + … + Expgenen × coefgenen.
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sections[23] "Prognostic model construction" paragraph 2
quote
Based on the expression of screened genes from the previous step, a risk model was built using multivariate Cox regression model analysis, calculated as follows: Risk score = Expgene1 × coefgene1 + Expgene2 × coefgene2 + … + Expgenen × coefgenen.
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The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb).
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sections[35] "notes" paragraph 1
quote
The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb).
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The results showed that our model exhibited the highest C-index value (0.704; Fig. 9K).
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sections[12] "Comparison with other models" paragraph 2
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The results showed that our model exhibited the highest C-index value (0.704; Fig. 9K).
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The results showed that our model exhibited the highest C-index value (0.704; Fig. 9K).
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The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb).
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The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb).
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sample_count
1048
group_sizes
null
group_sizes_basis
null
platform
16070;570
taxon
Homo sapiens
title
Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 2 items
[0]
asset:data:geo:GSE40967 not downloaded
[1]
asset:data:geo:GSE40967 licence not read
analysis object · 4 fields
state
partial
methods array · 4 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
dsl_operations array · 1 item
[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
band
verbatim
quote
Based on the expression of screened genes from the previous step, a risk model was built using multivariate Cox regression model analysis, calculated as follows: Risk score = Expgene1 × coefgene1 + Expgene2 × coefgene2 + … + Expgenen × coefgenen.
[1] object · 10 fields
id
method-2
family
group_comparison
specific
wilcoxon
label
Group comparison
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
0.8
band
high
quote
Wilcoxon
[2] object · 10 fields
id
method-3
family
network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
[0]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.8
band
high
quote
GO enrichment
[3] object · 10 fields
id
method-4
family
diagnostic_evaluation
specific
roc
label
Diagnostic test evaluation
dsl_operations array · 6 items
[0]
confusion_counts
[1]
roc_curve
[2]
sensitivity_specificity
[3]
solve_confusion_matrix
[4]
classification_metrics
[5]
published_precision_envelope
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
reference_standard_and_test
evidence object · 3 fields
score
0.8
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The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb).
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nscription factors (DETFs) The transcriptome RNA sequencing data and clinical materials of 514 patients
[1]
ds Evaluation and analysis of risk model The RNA sequencing data of patients with COAD were obtained fro
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DEGs), and transcription factors (DETFs) The transcriptome RNA sequencing data and clinical materials o
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Based on the expression of screened genes from the previous step, a risk model was built using multivariate Cox regression model analysis, calculated as follows: Risk score = Expgene1 × coefgene1 + Expgene2 × coefgene2 + … + Expgenen × coefgenen.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36221049", "kind": "science-record", "revision": 4, "content_hash": "sha256:c1251d643b6a71d1390bc17c502463d4481e18bd8a77792521e318cd1ecfd853", "created_at": "2026-11-01T18:15:34Z", "updated_at": "2026-11-01T22:07:47Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Novel six-gene prognostic signature based on colon adenocarcinoma immune-related genes.", "doi": "10.1186/s12859-022-04909-2", "pmid": "36221049", "authors": ["Rui Zhou", "Zhuowei Gao", "Yongle Ju"], "journal": "BMC bioinformatics", "year": 2022, "abstract": "BACKGROUND: Colon adenocarcinoma (COAD) is one of the most common gastrointestinal tumors worldwide, and immunotherapy is one of the most promising treatments for it. Identifying immune genes involved in the development and maintenance of cancer is key to the use of tumor immunotherapy. This study aimed to determine the prognostic value of immune genes in patients with COAD and to establish an immune-related gene signature. Differentially expressed genes, immune-related genes (DEIGs), and transcription factors (DETFs) were screened using the following databases: Cistrome, The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and InnateDB. We constructed a network showing the regulation of DEIGs by DETFs. Using weighted gene co-expression network analysis, we prepared 5 co-expressed gene modules; 6 hub genes (CD1A, CD1B, FGF9, GRP, SERPINE1, and F2RL2) obtained using univariate and multivariate regression analysis were used to construct a risk model. Patients from TCGA database were divided into high- and low-risk groups based on whether their risk score was greater or less than the mean; the public dataset GSE40967, which contains gene expression profiles of 566 colon cancer patients, was used for validation.\nRESULTS: Survival analysis, somatic gene mutations, and tumor-infiltrating immune cells differed significantly between the high- and low-risk groups.\nCONCLUSIONS: This immune-related gene signature could play an important role in guiding treatment, making prognoses, and potentially developing future clinical applications.", "claims": [{"id": "claim-method", "statement": "Based on the expression of screened genes from the previous step, a risk model was built using multivariate Cox regression model analysis, calculated as follows: Risk score = Expgene1 × coefgene1 + Expgene2 × coefgene2 + … + Expgenen × coefgenen.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36221049", "locator": "sections[23] \"Prognostic model construction\" paragraph 2", "quote": "Based on the expression of screened genes from the previous step, a risk model was built using multivariate Cox regression model analysis, calculated as follows: Risk score = Expgene1 × coefgene1 + Expgene2 × coefgene2 + … + Expgenen × coefgenen."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36221049", "locator": "sections[35] \"notes\" paragraph 1", "quote": "The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The results showed that our model exhibited the highest C-index value (0.704; Fig. 9K).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36221049", "locator": "sections[12] \"Comparison with other models\" paragraph 2", "quote": "The results showed that our model exhibited the highest C-index value (0.704; Fig. 9K)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The results showed that our model exhibited the highest C-index value (0.704; Fig. 9K).", "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:36221049"], "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:GSE40967"], "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:GSE40967"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36221049", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12859-022-04909-2", "sha256": "sha256:2a62ae701fe2feae239b3c6ad34fa811af9a0751e2fb8cf030b5777ea3eb6200", "bytes": 34323, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12859-022-04909-2", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9552517", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE40967", "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=GSE40967", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE40967", "version": null, "note": "The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1005664", "GSM1005665", "GSM1005666", "GSM1005667", "GSM1005668", "GSM1005669", "GSM1005670", "GSM1005671", "GSM1005672", "GSM1005673", "GSM1005674", "GSM1005675", "GSM1005676", "GSM1005677", "GSM1005678", "GSM1005679", "GSM1005680", "GSM1005681", "GSM1005682", "GSM1005683", "GSM1005684", "GSM1005685", "GSM1005686", "GSM1005687", "GSM1005688", "GSM1005689", "GSM1005690", "GSM1005691", "GSM1005692", "GSM1005693", "GSM1005694", "GSM1005695", "GSM1005696", "GSM1005697", "GSM1005698", "GSM1005699", "GSM1005700", "GSM1005701", "GSM1005702", "GSM1005703", "GSM1005704", "GSM1005705", "GSM1005706", "GSM1005707", "GSM1005708", 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downloaded", "asset:data:geo:GSE40967 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": "Based on the expression of screened genes from the previous step, a risk model was built using multivariate Cox regression model analysis, calculated as follows: Risk score = Expgene1 × coefgene1 + Expgene2 × coefgene2 + … + Expgenen × coefgenen."}}, {"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": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "GO enrichment"}}, {"id": "method-4", "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": 0.8, "band": "high", "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": ["GSE40967"], "resolved_accessions": ["GSE40967"], "statements": ["The entire sequencing profile data and the clinical data of the patients with COAD in this study come from the TCGA (https://cancergenome.nih.gov/) and GEO databases (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40967). The TFs were obtained from the Cistrome Project (http://cistrome.org/CistromeCancer/CancerTarget/). The genes in the tumor microenvironment were obtained from the TIMER web tool (http://timer.cistrome.org/), and the immune-related genes were obtained from ImmPORT (https://www.immport.org/shared/genelists) and InnateDB databases (https://www.innatedb.ca/annotatedGenes.do?type=innatedb)."], "basis": "The paper names GSE40967 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:36221049", "data:geo:GSE40967"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE40967"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:10:07Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10008, "completion_tokens": 3532, "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:36221049", "type": "paper", "label": "pmid:36221049"}, {"id": "source:pmid:36221049", "type": "manuscript", "label": "PMID 36221049 full text"}, {"id": "data:geo:GSE40967", "type": "dataset", "label": "GEO GSE40967"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36221049", "type": "paper", "label": "pmid:36221049"}, {"id": "source:pmid:36221049", "type": "manuscript", "label": "PMID 36221049 full text"}, {"id": "data:geo:GSE40967", "type": "dataset", "label": "GEO GSE40967"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36221049", "type": "extraction", "used": ["source:pmid:36221049"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE40967", "type": "accession_resolution", "used": ["data:geo:GSE40967"], "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:36221049", "parent_hash": "sha256:8cef581a4ff93157b4f9f5ee0d0a88d65334faa04dad5ba6d71dbdedf2074e8c", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE40967 licence not read", "asset:data:geo:GSE40967 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": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["nscription factors (DETFs) The transcriptome RNA sequencing data and clinical materials of 514 patients", "ds Evaluation and analysis of risk model The RNA sequencing data of patients with COAD were obtained fro", "DEGs), and transcription factors (DETFs) The transcriptome RNA sequencing data and clinical materials o"], "order_basis": "paper_text_order:1764", "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": ["Based on the expression of screened genes from the previous step, a risk model was built using multivariate Cox regression model analysis, calculated as follows: Risk score = Expgene1 × coefgene1 + Expgene2 × coefgene2 + … + Expgenen × coefgenen."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}