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pmid:35070404

Identification of a 3-gene signature for predicting the prognosis of stage II colon cancer based on microsatellite status.

Xiangxiong Huang · Heyang Xu · Yujie Zeng · Qiusheng Lan · Lu Liu · Wei Lai · Zhonghua Chu

Journal of gastrointestinal oncology · 2021 doi:10.21037/jgo-21-405

Paper

complete

Experiment

complete

Data

partial

Analysis

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Execution

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pmid:35070404
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science-record
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2026-11-01T18:04:57Z
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2026-11-01T21:27:03Z
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paper object · 10 fields
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title
Identification of a 3-gene signature for predicting the prognosis of stage II colon cancer based on microsatellite status.
doi
10.21037/jgo-21-405
pmid
35070404
authors array · 7 items
[0]
Xiangxiong Huang
[1]
Heyang Xu
[2]
Yujie Zeng
[3]
Qiusheng Lan
[4]
Lu Liu
[5]
Wei Lai
[6]
Zhonghua Chu
journal
Journal of gastrointestinal oncology
year
2021
abstract
BACKGROUND: Though colon cancer (CC) is one of the most malignant tumors across the world, CC patients with microsatellite instability-high (MSI-H) in stage II seem to have a better prognosis. However, the molecular mechanisms underlying the phenomena haven't been elucidated yet. METHODS: This study enrolled 322 CCs with known microsatellite status from GSE143985, GSE39582 and GSE92921 in the Gene Expression Omnibus (GEO) database. Robust rank aggregation (RRA) analysis, univariate Cox regression analysis and multivariate Cox stepwise regression analysis were performed to identify genes and construct risk score signature. Kaplan-Meier and receiver operating characteristic (ROC) curves analyses were used to evaluate the prognostic value of the signature. The potential mechanisms underlying this signature were assessed in the Metascape database, gene set enrichment analysis (GSEA) and immune infiltration analysis. RESULTS: RRA analysis identified 40 differently expressed genes (DEGs). A 3-gene risk score signature (MKQ signature) associated with disease-free survival (DFS) was generated. DFS was significantly longer in CC patients with lower than higher scores (P=0.0046). The areas under curves (AUCs) of the time-dependent ROC curves of MKQ signature at 1-, 3- and 5-year DFS were 1, 0.963 and 0.961 respectively. Recurrence-free survival (RFS) was significantly longer in patients in GSE39582 with lower than higher risk scores (P=0.032). The AUCs for 1-, 3- and 5-year RFS in GSE39582 were 0.63, 0.618 and 0.583, respectively, validating the value of the MKQ signature. Functional annotation and GSEA revealed that the MKQ signature was associated with multiple immune-related pathways. Immune cell infiltration was found to differ in patients differing in the MKQ signature. CONCLUSIONS: Gene expression and microsatellite status identified a 3-gene signature (MKQ signature) that could facilitate risk-stratified management in patients with stage II CC. Dysregulation of MSMB, KRT23, and QPRT can serve as prognostic markers in stage II CC.
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Robust rank aggregation (RRA) analysis, univariate Cox regression analysis and multivariate Cox stepwise regression analysis were performed to identify genes and construct risk score signature.
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This study enrolled 322 CCs with known microsatellite status from GSE143985, GSE39582 and GSE92921 in the Gene Expression Omnibus (GEO) database.
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RRA analysis identified 40 differently expressed genes (DEGs).
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RRA analysis identified 40 differently expressed genes (DEGs).
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RRA analysis identified 40 differently expressed genes (DEGs).
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Clinical significance of gene signature generated from the grade of tumor budding in colorectal cancer
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sample_count
585
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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[3] object · 15 fields
id
data:geo:GSE92921
role
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media_type
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE92921
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bytes
null
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null
reader_status
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identifier
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version
null
note
This study enrolled 322 CCs with known microsatellite status from GSE143985, GSE39582 and GSE92921 in the Gene Expression Omnibus (GEO) database.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
This study enrolled 322 CCs with known microsatellite status from GSE143985, GSE39582 and GSE92921 in the Gene Expression Omnibus (GEO) database.
access_statement_kind
repository_route_statement
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sample_count
59
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Prognostic Model for Stage II/III Colon Cancer Based on Gene Expression Subtypes and KRAS Mutation Status
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 6 items
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[3]
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[4]
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analysis object · 4 fields
state
complete
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[0] object · 10 fields
id
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cox_proportional_hazards
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[0]
time_to_event_with_censoring
evidence object · 3 fields
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quote
Robust rank aggregation (RRA) analysis, univariate Cox regression analysis and multivariate Cox stepwise regression analysis were performed to identify genes and construct risk score signature.
[1] object · 10 fields
id
method-2
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survival_analysis
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kaplan_meier
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Survival analysis
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[0]
survival_km
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parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.7
band
medium
quote
Kaplan-Meier
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capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
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assay_families array · 9 items
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differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
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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
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cox_ph
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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 · 3 items
[0]
GSE143985
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GSE92921
resolved_accessions array · 3 items
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statements array · 1 item
[0]
This study enrolled 322 CCs with known microsatellite status from GSE143985, GSE39582 and GSE92921 in the Gene Expression Omnibus (GEO) database.
basis
The paper names GSE143985, GSE39582, GSE92921 in Gene Expression Omnibus (GEO) database 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
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cox_ph
assets array · 2 items
[0]
source:pmid:35070404
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data:geo:GSE143985
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run_analysis
must_build object · 5 fields
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readers array · 0 items
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[0]
data:geo:GSE143985
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review object · 5 fields
state
partial
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kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T17:30:35Z
independence
single_reader
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method
verbatim
availability
null
calls
5
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[0] object · 4 fields
id
extraction
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complete
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minimax
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pmid:35070404
type
paper
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pmid:35070404
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id
source:pmid:35070404
type
manuscript
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PMID 35070404 full text
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data:geo:GSE143985
type
dataset
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GEO GSE143985
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[0] object · 4 fields
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type
classification
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paper
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pmid:35070404
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id
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PMID 35070404 full text
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GEO GSE143985
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agent:corpus-assay-engine
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agent:minimax-reader
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lineage object · 4 fields
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role
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dsl_catalogue
f2132e96ae6c7a4e
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[0]
Robust rank aggregation (RRA) analysis, univariate Cox regression analysis and multivariate Cox stepwise regression analysis were performed to identify genes and construct risk score signature.
order_basis
analysis_only
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35070404", "kind": "science-record", "revision": 3, "content_hash": "sha256:7f10c9a8518cf9fcc91a9c6ffb7825bbf12aa762765270467ffc368ad4d16f98", "created_at": "2026-11-01T18:04:57Z", "updated_at": "2026-11-01T21:27:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a 3-gene signature for predicting the prognosis of stage II colon cancer based on microsatellite status.", "doi": "10.21037/jgo-21-405", "pmid": "35070404", "authors": ["Xiangxiong Huang", "Heyang Xu", "Yujie Zeng", "Qiusheng Lan", "Lu Liu", "Wei Lai", "Zhonghua Chu"], "journal": "Journal of gastrointestinal oncology", "year": 2021, "abstract": "BACKGROUND: Though colon cancer (CC) is one of the most malignant tumors across the world, CC patients with microsatellite instability-high (MSI-H) in stage II seem to have a better prognosis. However, the molecular mechanisms underlying the phenomena haven't been elucidated yet.\nMETHODS: This study enrolled 322 CCs with known microsatellite status from GSE143985, GSE39582 and GSE92921 in the Gene Expression Omnibus (GEO) database. Robust rank aggregation (RRA) analysis, univariate Cox regression analysis and multivariate Cox stepwise regression analysis were performed to identify genes and construct risk score signature. Kaplan-Meier and receiver operating characteristic (ROC) curves analyses were used to evaluate the prognostic value of the signature. The potential mechanisms underlying this signature were assessed in the Metascape database, gene set enrichment analysis (GSEA) and immune infiltration analysis.\nRESULTS: RRA analysis identified 40 differently expressed genes (DEGs). A 3-gene risk score signature (MKQ signature) associated with disease-free survival (DFS) was generated. DFS was significantly longer in CC patients with lower than higher scores (P=0.0046). The areas under curves (AUCs) of the time-dependent ROC curves of MKQ signature at 1-, 3- and 5-year DFS were 1, 0.963 and 0.961 respectively. Recurrence-free survival (RFS) was significantly longer in patients in GSE39582 with lower than higher risk scores (P=0.032). The AUCs for 1-, 3- and 5-year RFS in GSE39582 were 0.63, 0.618 and 0.583, respectively, validating the value of the MKQ signature. Functional annotation and GSEA revealed that the MKQ signature was associated with multiple immune-related pathways. Immune cell infiltration was found to differ in patients differing in the MKQ signature.\nCONCLUSIONS: Gene expression and microsatellite status identified a 3-gene signature (MKQ signature) that could facilitate risk-stratified management in patients with stage II CC. 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