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pmid:34290738

Identification and Validation of a Four-Long Non-coding RNA Signature Associated With Immune Infiltration and Prognosis in Colon Cancer.

Yanbo Wang · Jing Liu · Fenghai Ren · Yanjie Chu · Binbin Cui

Frontiers in genetics · 2021 doi:10.3389/fgene.2021.671128

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Identification and Validation of a Four-Long Non-coding RNA Signature Associated With Immune Infiltration and Prognosis in Colon Cancer.
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10.3389/fgene.2021.671128
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34290738
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Yanbo Wang
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Jing Liu
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Fenghai Ren
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Yanjie Chu
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Binbin Cui
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Frontiers in genetics
year
2021
abstract
The emerging evidence has demonstrated the critical roles of long non-coding RNAs (lncRNAs) as regulators in the tumor immune microenvironment (TIME). However, the tumor immune infiltration-associated lncRNAs and their clinical significance in colon cancer have not yet been thoroughly investigated. This study performed an integrative analysis of lncRNA expression profiles and immune cell infiltration profiles and identified 258 immune infiltration-associated lncRNAs. Of them, four lncRNAs (AC008494.3, LINC00926, AC022034.1, and SNHG26) were significantly and independently associated with the patient's overall survival. Finally, we developed a tumor immune infiltration-associated lncRNA signature (TIILncSig) comprising of these four lncRNAs, which can divide colon cancer patients of The Cancer Genome Atlas (TCGA) into high-risk and low-risk groups with a significantly different outcome [Hazard ratio (HR) = 2.718, 95% CI = 1.955-3.779, p < 0.001]. Prognostic performance of the TIILncSig was further validated in another independent colon cancer cohort (HR = 1.832, 95% CI = 1.045-3.21, p = 0.034). Results of multivariate Cox regression and stratification analysis demonstrated that the TIILncSig is an independent predictive factor from other clinical features (HR = 2.687, 95% CI = 1.912-3.776, p < 0.001 for TCGA cohort and HR = 1.837, 95% CI = 1.047-3.223, p = 0.034 for GSE17538 cohort). Literature analysis provided experimental evidence supporting roles of the TIILncSig in cancer carcinogenesis and progression and immune regulation. Summary, our study will help to understand the mechanisms of lncRNAs in immune regulation in the tumor microenvironment and provide novel biomarkers or targets for prognosis prediction and therapy decision-making for patients with colon cancer.
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The association between lncRNA expression and overall survival were evaluated using the univariate and multivariate Cox regression analysis.
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Publicly available datasets were analyzed in this study. This data can be found at: clinical and transcriptome data of colon cancer patients was downloaded from UCSC Xena Browser (http://xena.ucsc.edu/, GDC TCGA Colon Cancer cohort) and Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17536).
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[1] array · 7 items
[0]
ENSG00000271797
[1]
AC008494.3
[2]
Chr5: 115,262,505-115,263,448(+)
[3]
0.205
[4]
0.05–0.842
[5]
−1.584
[6]
0.028
[2] array · 7 items
[0]
ENSG00000247982
[1]
LINC00926
[2]
Chr15: 57,300,365-57,307,769(+)
[3]
1.28
[4]
1.008–1.625
[5]
0.247
[6]
0.043
[3] array · 7 items
[0]
ENSG00000237807
[1]
AC022034.1
[2]
Ch8: 53,493,523-53,524,336(−)
[3]
1.329
[4]
1.145–1.544
[5]
0.285
[6]
<0.001
[4] array · 7 items
[0]
ENSG00000228649
[1]
SNHG26
[2]
Chr7: 22,854,126-22,872,945(+)
[3]
1.549
[4]
1.182–2.03
[5]
0.438
[6]
0.001
locator
section[8]/table-wrap[1]#tab1
gaps array · 4 items
[0]
asset:data:geo:GSE17536 not downloaded
[1]
asset:data:geo:GSE17536 licence not read
[2]
asset:data:geo:GSE17538 not downloaded
[3]
asset:data:geo:GSE17538 licence not read
analysis object · 4 fields
state
complete
methods array · 5 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
The association between lncRNA expression and overall survival were evaluated using the univariate and multivariate Cox regression analysis.
[1] object · 10 fields
id
method-2
family
survival_analysis
specific
kaplan_meier
label
Survival analysis
dsl_operations array · 1 item
[0]
survival_km
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
0.8
band
high
quote
Kaplan-Meier
[2] object · 10 fields
id
method-3
family
survival_analysis
specific
log_rank_test
label
Survival analysis
dsl_operations array · 1 item
[0]
logrank_test
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
0.8
band
high
quote
log-rank
[3] object · 10 fields
id
method-4
family
correlation_analysis
specific
pearson
label
Correlation analysis
dsl_operations array · 1 item
[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
[4] object · 10 fields
id
method-5
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
band
high
quote
ROC curve
targets array · 0 items
gaps array · 0 items
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]
GSE17536
[1]
GSE17538
resolved_accessions array · 2 items
[0]
GSE17536
[1]
GSE17538
statements array · 1 item
[0]
Publicly available datasets were analyzed in this study. This data can be found at: clinical and transcriptome data of colon cancer patients was downloaded from UCSC Xena Browser (http://xena.ucsc.edu/, GDC TCGA Colon Cancer cohort) and Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17536).
basis
The paper names GSE17536, GSE17538 in Gene Expression Omnibus 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 · 3 items
[0]
source:pmid:34290738
[1]
data:geo:GSE17536
[2]
asset:table:pmid:34290738:1
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:GSE17536
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
2026-10-31T18:32:39Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
3
usage object · 3 fields
prompt_tokens
27410
completion_tokens
2088
cached_tokens
784
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:34290738
type
paper
label
pmid:34290738
[1] object · 3 fields
id
source:pmid:34290738
type
manuscript
label
PMID 34290738 full text
[2] object · 3 fields
id
data:geo:GSE17536
type
dataset
label
GEO GSE17536
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
[0] object · 3 fields
id
pmid:34290738
type
paper
label
pmid:34290738
[1] object · 3 fields
id
source:pmid:34290738
type
manuscript
label
PMID 34290738 full text
[2] object · 3 fields
id
data:geo:GSE17536
type
dataset
label
GEO GSE17536
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-34290738
type
extraction
used array · 1 item
[0]
source:pmid:34290738
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE17536
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE17536
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
type
software
label
Corpus assay engine
[1] object · 3 fields
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 object · 4 fields
parent_id
pmid:34290738
parent_hash
sha256:118a98623002b1952406876d925ebc4a9641de1db51a2fe76c14dfda46298a8a
fork_of
null
gaps array · 8 items
[0]
asset:data:geo:GSE17536 licence not read
[1]
asset:data:geo:GSE17536 not downloaded
[2]
asset:data:geo:GSE17538 licence not read
[3]
asset:data:geo:GSE17538 not downloaded
[4]
execution.not_run
[5]
review.human_critique
[6]
review.independent_reader
[7]
review.machine_critique
assays array · 3 items
[0] object · 11 fields
role
data_generation
definition_id
rna_seq
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 4 items
[0]
Browser (GDC TCGA Colon Cancer cohort).1 The RNA-seq gene expression level 3 data [log2(RPKM +1)
[1]
, a total of 3,959 lncRNAs were retained for RNA-seq data. For microarray data, a total of 5,919
[2]
Materials and Methods Clinical and Transcriptomic Data of Colon Cancer Patients Clinical and t
[3]
c Data of Colon Cancer Patients Clinical and transcriptomic data of 512 colon cancer patients were obtai
order_basis
paper_text_order:1937
id
assay:1
[1] object · 11 fields
role
data_generation
definition_id
microarray
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 3 items
[0]
rom Gene Expression Omnibus (GEO) database.2 Microarray data profiled by Affymetrix Human Genome U13
[1]
lncRNAs were retained for RNA-seq data. For microarray data, a total of 5,919 lncRNAs were retained
[2]
(GEO) database.2 Microarray data profiled by Affymetrix Human Genome U133 Plus 2.0 Array was used an
order_basis
paper_text_order:2424
id
assay:2
[2] object · 11 fields
role
analysis
definition_id
survival_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
[0]
cox_ph
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
The association between lncRNA expression and overall survival were evaluated using the univariate and multivariate Cox regression analysis.
order_basis
consumes_earlier_output
id
assay:3
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34290738", "kind": "science-record", "revision": 7, "content_hash": "sha256:a344cfcb624b522bd24dcdb7fe405a7b08de9f7f549a35c5d364bce610d4d904", "created_at": "2026-11-01T15:41:44Z", "updated_at": "2026-11-01T22:04:16Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of a Four-Long Non-coding RNA Signature Associated With Immune Infiltration and Prognosis in Colon Cancer.", "doi": "10.3389/fgene.2021.671128", "pmid": "34290738", "authors": ["Yanbo Wang", "Jing Liu", "Fenghai Ren", "Yanjie Chu", "Binbin Cui"], "journal": "Frontiers in genetics", "year": 2021, "abstract": "The emerging evidence has demonstrated the critical roles of long non-coding RNAs (lncRNAs) as regulators in the tumor immune microenvironment (TIME). However, the tumor immune infiltration-associated lncRNAs and their clinical significance in colon cancer have not yet been thoroughly investigated. This study performed an integrative analysis of lncRNA expression profiles and immune cell infiltration profiles and identified 258 immune infiltration-associated lncRNAs. Of them, four lncRNAs (AC008494.3, LINC00926, AC022034.1, and SNHG26) were significantly and independently associated with the patient's overall survival. Finally, we developed a tumor immune infiltration-associated lncRNA signature (TIILncSig) comprising of these four lncRNAs, which can divide colon cancer patients of The Cancer Genome Atlas (TCGA) into high-risk and low-risk groups with a significantly different outcome [Hazard ratio (HR) = 2.718, 95% CI = 1.955-3.779, p < 0.001]. Prognostic performance of the TIILncSig was further validated in another independent colon cancer cohort (HR = 1.832, 95% CI = 1.045-3.21, p = 0.034). Results of multivariate Cox regression and stratification analysis demonstrated that the TIILncSig is an independent predictive factor from other clinical features (HR = 2.687, 95% CI = 1.912-3.776, p < 0.001 for TCGA cohort and HR = 1.837, 95% CI = 1.047-3.223, p = 0.034 for GSE17538 cohort). Literature analysis provided experimental evidence supporting roles of the TIILncSig in cancer carcinogenesis and progression and immune regulation. Summary, our study will help to understand the mechanisms of lncRNAs in immune regulation in the tumor microenvironment and provide novel biomarkers or targets for prognosis prediction and therapy decision-making for patients with colon cancer.", "claims": [{"id": "claim-method", "statement": "The association between lncRNA expression and overall survival were evaluated using the univariate and multivariate Cox regression analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34290738", "locator": "sections[6] \"Statistical Analysis\" paragraph 2", "quote": "The association between lncRNA expression and overall survival were evaluated using the univariate and multivariate Cox regression analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found at: clinical and transcriptome data of colon cancer patients was downloaded from UCSC Xena Browser (http://xena.ucsc.edu/, GDC TCGA Colon Cancer cohort) and Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17536).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34290738", "locator": "sections[13] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found at: clinical and transcriptome data of colon cancer patients was downloaded from UCSC Xena Browser (http://xena.ucsc.edu/, GDC TCGA Colon Cancer cohort) and Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17536)."}], "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:34290738"], "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:GSE17536"], "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:GSE17536"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34290738", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2021.671128", "sha256": "sha256:64f11bc1f120b61c67508e2513b6039bd9929597417ae7057920c8e6d74ee61a", "bytes": 34715, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2021.671128", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8287327", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE17536", "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=GSE17536", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE17536", "version": null, "note": "Publicly available datasets were analyzed in this study. 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