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pmid:33569302

A prognostic nomogram for lung adenocarcinoma based on immune-infiltrating Treg-related genes: from bench to bedside.

Xiaofei Wang · Zengtuan Xiao · Jialin Gong · Zuo Liu · Mengzhe Zhang · Zhenfa Zhang

Translational lung cancer research · 2021 doi:10.21037/tlcr-20-822

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Experiment

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Data

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Analysis

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title
A prognostic nomogram for lung adenocarcinoma based on immune-infiltrating Treg-related genes: from bench to bedside.
doi
10.21037/tlcr-20-822
pmid
33569302
authors array · 6 items
[0]
Xiaofei Wang
[1]
Zengtuan Xiao
[2]
Jialin Gong
[3]
Zuo Liu
[4]
Mengzhe Zhang
[5]
Zhenfa Zhang
journal
Translational lung cancer research
year
2021
abstract
BACKGROUND: Accumulating evidence suggests that lymphocyte infiltration in the tumor microenvironment is positively correlated with tumorigenesis and development, while the role of Tregs (regulatory T cells) has been controversial. Therefore, we attempted to discover the possible value of Tregs for lung adenocarcinoma (LUAD). METHODS: The gene-sequencing data of LUAD were applied from three Gene Expression Omnibus (GEO) datasets-GSE10072, GSE32863 and GSE43458; the corresponding fractions of tumor-infiltrating immune cells were extracted from the CIBERSORTx portal. Weighted gene coexpression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis were conducted to identify the significant module and candidate genes related to Tregs. The role of candidate genes in LUAD was further verified using data from The Cancer Genome Atlas (TCGA) database. Finally, we constructed a nomogram model to predict the prognosis of LUAD by plotting Kaplan-Meier (K-M), receiver operating characteristic (ROC) and calibration curves, which elucidated the performance of the nomogram. RESULTS: In total, 10,047 genes in 333 samples (196 tumor and 137 normal samples) from the GEO database were included. By WGCNA and PPI analysis, we identified a significant black module and 36 candidate genes related to Treg. Next, the candidate genes were verified using TCGA data by Cox regression analysis to screen 13 hub genes that stratified LUAD patients into low- or high-risk groups. Low-risk patients showed a significantly longer overall survival (OS) than high-risk patients (3-year OS: 70.2% vs. 35.2%; 5-year OS: 36.6% vs. 0; P=1.651E-09), and the areas under the ROC curves (AUCs) showed good (3-year AUC: 0.733; 5-year AUC: 0.777). Next, we constructed a survival nomogram combining the hub genes and clinical parameters; the low-risk patients still showed a favorable prognosis compared with that of the high-risk patients (P=7.073E-13), and the AUCs were better (3-year AUC: 0.763; 5-year AUC: 0.873). CONCLUSIONS: We revealed the role of immune-infiltrating Treg-related genes in LUAD and constructed a prognostic nomogram, which may help clinicians make optimal therapeutic decisions and help patients obtain better outcomes.
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sections[11] "Statistical analysis" paragraph 2
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A Cox proportional hazards model was applied to identify survival genes related to Tregs.
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The LUAD sequencing data were applied from three GEO (http://www.ncbi.nlm.nih.gov/geo/) datasets, GSE10072, GSE32863, and GSE43458.
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Univariate and multivariate cox regression analyses of Treg-related genes in lung adenocarcinoma
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Verification of the role of Treg-related genes in LUAD
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Univariate and multivariate cox regression analyses of Treg-related genes in lung adenocarcinoma
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AURKA
[1]
1.2579 (1.0781, 1.4677)
[2]
0.0036
[3]
[4]
0.7174 (0.5122, 1.0049)
[5]
0.0534
[6]
−0.3321
[29] array · 7 items
[0]
PAICS
[1]
1.4356 (1.1493, 1.7933)
[2]
0.0014
[3]
[4]
[5]
[6]
[30] array · 7 items
[0]
MELK
[1]
1.3452 (1.1507, 1.5726)
[2]
0.0002
[3]
[4]
[5]
[6]
[31] array · 7 items
[0]
HMMR
[1]
1.4166 (1.1914, 1.6844)
[2]
0.0001
[3]
[4]
1.4713 (1.0176, 2.1274)
[5]
0.0401
[6]
0.3862
[32] array · 7 items
[0]
TTK
[1]
1.3397 (1.1229, 1.5984)
[2]
0.0012
[3]
[4]
[5]
[6]
[33] array · 7 items
[0]
PBK
[1]
1.2934 (1.1217, 1.4914)
[2]
0.0004
[3]
[4]
[5]
[6]
[34] array · 7 items
[0]
CCNB1
[1]
1.3997 (1.1978, 1.6355)
[2]
0.0000
[3]
[4]
[5]
[6]
locator
section[15]/table-wrap[1]#t1
[4] object · 16 fields
id
asset:table:pmid:33569302:2
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:8d9c312c10d3866095975b314e21d96e906baf36a24ad38fb1be0be974eee63f
bytes
4501
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[17]/table-wrap[1]#t2
version
null
note
GO and KEGG pathway enrichment analysis of candidate genes in the most significant terms
structure object · 5 fields
pmcid
PMC7867791
section_index
17
section_title
GO and KEGG pathway enrichment analyses
row_count
41
column_count
7
table object · 8 fields
label
Table 2
caption
GO and KEGG pathway enrichment analysis of candidate genes in the most significant terms
rows array · 41 items
[0] array · 7 items
[0]
Terms
[1]
ID
[2]
Description
[3]
Gene ratio
[4]
Padjust
[5]
Gene ID
[6]
Count
[1] array · 7 items
[0]
Biological process
[1]
GO:0000280
[2]
Nuclear division
[3]
15/35
[4]
4.15E-14
[5]
CENPF/TPX2/UBE2C/KIF11/CDC20/CENPE/TOP2A/ASPM/TRIP13/NUSAP1/PRC1/KNTC1/AURKA/TTK/CCNB1
[6]
15
[2] array · 6 items
[0]
GO:0048285
[1]
Organelle fission
[2]
15/35
[3]
8.22E-14
[4]
CENPF/TPX2/UBE2C/KIF11/CDC20/CENPE/TOP2A/ASPM/TRIP13/NUSAP1/PRC1/KNTC1/AURKA/TTK/CCNB1
[5]
15
[3] array · 6 items
[0]
GO:0140014
[1]
Mitotic nuclear division
[2]
13/35
[3]
8.22E-14
[4]
CENPF/TPX2/UBE2C/KIF11/CDC20/CENPE/TRIP13/NUSAP1/PRC1/KNTC1/AURKA/TTK/CCNB1
[5]
13
[4] array · 6 items
[0]
GO:0007088
[1]
Regulation of mitotic nuclear division
[2]
11/35
[3]
6.79E-13
[4]
CENPF/UBE2C/KIF11/CDC20/CENPE/TRIP13/NUSAP1/KNTC1/AURKA/TTK/CCNB1
[5]
11
[5] array · 6 items
[0]
GO:0051783
[1]
Regulation of nuclear division
[2]
11/35
[3]
2.50E-12
[4]
CENPF/UBE2C/KIF11/CDC20/CENPE/TRIP13/NUSAP1/KNTC1/AURKA/TTK/CCNB1
[5]
11
[6] array · 6 items
[0]
GO:0007051
[1]
Spindle organization
[2]
10/35
[3]
2.06E-11
[4]
TPX2/KIF11/CDC20/CENPE/ASPM/STIL/PRC1/AURKA/TTK/CCNB1
[5]
10
[7] array · 6 items
[0]
GO:1902850
[1]
Microtubule cytoskeleton organization involved in mitosis
[2]
9/35
[3]
1.01E-10
[4]
TPX2/KIF11/CDC20/CENPE/STIL/NUSAP1/PRC1/TTK/CCNB1
[5]
9
[8] array · 6 items
[0]
GO:0007059
[1]
Chromosome segregation
[2]
11/35
[3]
2.72E-10
[4]
CENPF/ECT2/CDC20/CENPE/TOP2A/BUB1/TRIP13/NUSAP1/PRC1/TTK/CCNB1
[5]
11
[9] array · 6 items
[0]
GO:0051983
[1]
Regulation of chromosome segregation
[2]
8/35
[3]
6.96E-10
[4]
CENPF/ECT2/CDC20/CENPE/BUB1/TRIP13/TTK/CCNB1
[5]
8
[10] array · 6 items
[0]
GO:0098813
[1]
Nuclear chromosome segregation
[2]
10/35
[3]
6.96E-10
[4]
CENPF/ECT2/CDC20/CENPE/BUB1/TRIP13/NUSAP1/PRC1/TTK/CCNB1
[5]
10
[11] array · 7 items
[0]
Cellular component
[1]
GO:0005819
[2]
Spindle
[3]
13/35
[4]
8.73E-13
[5]
CENPF/ECT2/TPX2/KIF11/CDC20/CENPE/KIF20A/ASPM/PRC1/KNTC1/AURKA/TTK/CCNB1
[6]
13
[12] array · 6 items
[0]
GO:0000922
[1]
Spindle pole
[2]
9/35
[3]
2.76E-10
[4]
CENPF/TPX2/KIF11/CDC20/ASPM/PRC1/KNTC1/AURKA/CCNB1
[5]
9
[13] array · 6 items
[0]
GO:0030496
[1]
Midbody
[2]
8/35
[3]
2.02E-08
[4]
CENPF/ECT2/CENPE/CEP55/KIF20A/ASPM/PRC1/AURKA
[5]
8
[14] array · 6 items
[0]
GO:0098687
[1]
Chromosomal region
[2]
9/35
[3]
1.62E-07
[4]
CENPF/CENPE/BUB1/MCM4/MCM6/MCM2/KNTC1/TTK/CCNB1
[5]
9
[15] array · 6 items
[0]
GO:0072686
[1]
Mitotic spindle
[2]
6/35
[3]
3.66E-07
[4]
ECT2/TPX2/KIF11/CENPE/ASPM/AURKA
[5]
6
[16] array · 6 items
[0]
GO:0005876
[1]
Spindle microtubule
[2]
5/35
[3]
5.84E-07
[4]
KIF11/CENPE/PRC1/KNTC1/AURKA
[5]
5
[17] array · 6 items
[0]
GO:0000776
[1]
Kinetochore
[2]
6/35
[3]
1.48E-06
[4]
CENPF/CENPE/BUB1/KNTC1/TTK/CCNB1
[5]
6
[18] array · 6 items
[0]
GO:0005813
[1]
Centrosome
[2]
9/35
[3]
1.48E-06
[4]
CCNB2/CENPF/CDC20/CEP55/ASPM/STIL/AURKA/HMMR/CCNB1
[5]
9
[19] array · 6 items
[0]
GO:0042555
[1]
MCM complex
[2]
3/35
[3]
7.85E-06
[4]
MCM4/MCM6/MCM2
[5]
3
[20] array · 6 items
[0]
GO:0000775
[1]
Chromosome, centromeric region
[2]
6/35
[3]
7.85E-06
[4]
CENPF/CENPE/BUB1/KNTC1/TTK/CCNB1
[5]
6
[21] array · 7 items
[0]
Molecular function
[1]
GO:0004674
[2]
Protein serine/threonine kinase activity
[3]
6/35
[4]
9.86E-03
[5]
BUB1/AURKA/CDK4/MELK/TTK/PBK
[6]
6
[22] array · 6 items
[0]
GO:0008094
[1]
DNA-dependent ATPase activity
[2]
3/35
[3]
2.04E-02
[4]
TOP2A/MCM4/MCM6
[5]
3
[23] array · 6 items
[0]
GO:0016538
[1]
Cyclin-dependent protein serine/threonine kinase regulator activity
[2]
2/35
[3]
2.04E-02
[4]
CDK4/CCNB1
[5]
2
[24] array · 6 items
[0]
GO:0003697
[1]
Single-stranded DNA binding
[2]
3/35
[3]
2.07E-02
[4]
RAD51AP1/MCM4/MCM6
[5]
3
[25] array · 6 items
[0]
GO:0004003
[1]
ATP-dependent DNA helicase activity
[2]
2/35
[3]
3.66E-02
[4]
MCM4/MCM6
[5]
2
[26] array · 6 items
[0]
GO:0004386
[1]
Helicase activity
[2]
3/35
[3]
3.80E-02
[4]
MCM4/MCM6/MCM2
[5]
3
[27] array · 6 items
[0]
GO:0004712
[1]
Protein serine/threonine/tyrosine kinase activity
[2]
2/35
[3]
4.11E-02
[4]
AURKA/TTK
[5]
2
[28] array · 6 items
[0]
GO:0003678
[1]
DNA helicase activity
[2]
2/35
[3]
4.11E-02
[4]
MCM4/MCM6
[5]
2
[29] array · 6 items
[0]
GO:0140097
[1]
Catalytic activity, acting on DNA
[2]
3/35
[3]
4.11E-02
[4]
TOP2A/MCM4/MCM6
[5]
3
[30] array · 6 items
[0]
GO:0008026
[1]
ATP-dependent helicase activity
[2]
2/35
[3]
4.62E-02
[4]
MCM4/MCM6
[5]
2
[31] array · 7 items
[0]
KEGG pathways
[1]
hsa04110
[2]
Cell cycle
[3]
10/17
[4]
9.47E-15
[5]
CCNB2/CDC20/BUB1/PTTG1/MCM4/MCM6/MCM2/CDK4/TTK/CCNB1
[6]
10
[32] array · 6 items
[0]
hsa04114
[1]
Oocyte meiosis
[2]
6/17
[3]
1.56E-07
[4]
CCNB2/CDC20/BUB1/PTTG1/AURKA/CCNB1
[5]
6
[33] array · 6 items
[0]
hsa04914
[1]
Progesterone-mediated oocyte maturation
[2]
4/17
[3]
4.57E-05
[4]
CCNB2/BUB1/AURKA/CCNB1
[5]
4
[34] array · 6 items
[0]
hsa03030
[1]
DNA replication
[2]
3/17
[3]
5.39E-05
[4]
MCM4/MCM6/MCM2
[5]
3
[35] array · 6 items
[0]
hsa04115
[1]
p53 signaling pathway
[2]
3/17
[3]
4.47E-04
[4]
CCNB2/CDK4/CCNB1
[5]
3
[36] array · 6 items
[0]
hsa05166
[1]
Human T-cell leukemia virus 1 infection
[2]
4/17
[3]
9.68E-04
[4]
CCNB2/CDC20/PTTG1/CDK4
[5]
4
[37] array · 6 items
[0]
hsa04218
[1]
Cellular senescence
[2]
3/17
[3]
4.00E-03
[4]
CCNB2/CDK4/CCNB1
[5]
3
[38] array · 6 items
[0]
hsa04068
[1]
FoxO signaling pathway
[2]
2/17
[3]
3.06E-02
[4]
CCNB2/CCNB1
[5]
2
[39] array · 6 items
[0]
hsa04120
[1]
Ubiquitin mediated proteolysis
[2]
2/17
[3]
3.46E-02
[4]
UBE2C/CDC20
[5]
2
[40] array · 6 items
[0]
hsa00670
[1]
One carbon pool by folate
[2]
1/17
[3]
4.15E-02
[4]
TYMS
[5]
1
locator
section[17]/table-wrap[1]#t2
gaps array · 4 items
[0]
asset:data:geo:GSE10072 not downloaded
[1]
asset:data:geo:GSE10072 licence not read
[2]
asset:data:geo:GSE32863 not downloaded
[3]
asset:data:geo:GSE32863 licence not read
analysis object · 4 fields
state
complete
methods array · 6 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
A Cox proportional hazards model was applied to identify survival genes related to Tregs.
[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
0.7
band
medium
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
network_analysis
specific
ppi_network
label
Network / pathway analysis
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
protein-protein interaction
[4] object · 10 fields
id
method-5
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
pathway enrichment
[5] object · 10 fields
id
method-6
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 · 3 items
[0]
GSE10072
[1]
GSE32863
[2]
and GSE43458
resolved_accessions array · 2 items
[0]
GSE10072
[1]
GSE32863
statements array · 1 item
[0]
The LUAD sequencing data were applied from three GEO (http://www.ncbi.nlm.nih.gov/geo/) datasets, GSE10072, GSE32863, and GSE43458.
basis
The paper names GSE10072, GSE32863 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 · 4 items
[0]
source:pmid:33569302
[1]
data:geo:GSE10072
[2]
asset:table:pmid:33569302:1
[3]
asset:table:pmid:33569302:2
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:GSE10072
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
2026-10-31T18:26:52Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
3
usage object · 3 fields
prompt_tokens
29211
completion_tokens
1776
cached_tokens
792
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:33569302
type
paper
label
pmid:33569302
[1] object · 3 fields
id
source:pmid:33569302
type
manuscript
label
PMID 33569302 full text
[2] object · 3 fields
id
data:geo:GSE10072
type
dataset
label
GEO GSE10072
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:33569302
type
paper
label
pmid:33569302
[1] object · 3 fields
id
source:pmid:33569302
type
manuscript
label
PMID 33569302 full text
[2] object · 3 fields
id
data:geo:GSE10072
type
dataset
label
GEO GSE10072
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-33569302
type
extraction
used array · 1 item
[0]
source:pmid:33569302
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE10072
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE10072
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:33569302
parent_hash
sha256:ab645eed571102aa132a219ae867f91025bb3e92d6c2c5bc6bc221c7771c6c39
fork_of
null
gaps array · 8 items
[0]
asset:data:geo:GSE10072 licence not read
[1]
asset:data:geo:GSE10072 not downloaded
[2]
asset:data:geo:GSE32863 licence not read
[3]
asset:data:geo:GSE32863 not downloaded
[4]
execution.not_run
[5]
review.human_critique
[6]
review.independent_reader
[7]
review.machine_critique
assays array · 1 item
[0] 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]
A Cox proportional hazards model was applied to identify survival genes related to Tregs.
order_basis
analysis_only
id
assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33569302", "kind": "science-record", "revision": 8, "content_hash": "sha256:493b06656f02daac4dbd3c77c35ce4ea528d442ed4016adfe791cc717b5aec49", "created_at": "2026-11-01T15:41:25Z", "updated_at": "2026-11-01T22:03:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A prognostic nomogram for lung adenocarcinoma based on immune-infiltrating Treg-related genes: from bench to bedside.", "doi": "10.21037/tlcr-20-822", "pmid": "33569302", "authors": ["Xiaofei Wang", "Zengtuan Xiao", "Jialin Gong", "Zuo Liu", "Mengzhe Zhang", "Zhenfa Zhang"], "journal": "Translational lung cancer research", "year": 2021, "abstract": "BACKGROUND: Accumulating evidence suggests that lymphocyte infiltration in the tumor microenvironment is positively correlated with tumorigenesis and development, while the role of Tregs (regulatory T cells) has been controversial. Therefore, we attempted to discover the possible value of Tregs for lung adenocarcinoma (LUAD).\nMETHODS: The gene-sequencing data of LUAD were applied from three Gene Expression Omnibus (GEO) datasets-GSE10072, GSE32863 and GSE43458; the corresponding fractions of tumor-infiltrating immune cells were extracted from the CIBERSORTx portal. Weighted gene coexpression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis were conducted to identify the significant module and candidate genes related to Tregs. The role of candidate genes in LUAD was further verified using data from The Cancer Genome Atlas (TCGA) database. Finally, we constructed a nomogram model to predict the prognosis of LUAD by plotting Kaplan-Meier (K-M), receiver operating characteristic (ROC) and calibration curves, which elucidated the performance of the nomogram.\nRESULTS: In total, 10,047 genes in 333 samples (196 tumor and 137 normal samples) from the GEO database were included. By WGCNA and PPI analysis, we identified a significant black module and 36 candidate genes related to Treg. Next, the candidate genes were verified using TCGA data by Cox regression analysis to screen 13 hub genes that stratified LUAD patients into low- or high-risk groups. Low-risk patients showed a significantly longer overall survival (OS) than high-risk patients (3-year OS: 70.2% vs. 35.2%; 5-year OS: 36.6% vs. 0; P=1.651E-09), and the areas under the ROC curves (AUCs) showed good (3-year AUC: 0.733; 5-year AUC: 0.777). Next, we constructed a survival nomogram combining the hub genes and clinical parameters; the low-risk patients still showed a favorable prognosis compared with that of the high-risk patients (P=7.073E-13), and the AUCs were better (3-year AUC: 0.763; 5-year AUC: 0.873).\nCONCLUSIONS: We revealed the role of immune-infiltrating Treg-related genes in LUAD and constructed a prognostic nomogram, which may help clinicians make optimal therapeutic decisions and help patients obtain better outcomes.", "claims": [{"id": "claim-method", "statement": "A Cox proportional hazards model was applied to identify survival genes related to Tregs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33569302", "locator": "sections[11] \"Statistical analysis\" paragraph 2", "quote": "A Cox proportional hazards model was applied to identify survival genes related to Tregs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The LUAD sequencing data were applied from three GEO (http://www.ncbi.nlm.nih.gov/geo/) datasets, GSE10072, GSE32863, and GSE43458.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33569302", "locator": "sections[3] \"Data source and processing\" paragraph 2", "quote": "The LUAD sequencing data were applied from three GEO (http://www.ncbi.nlm.nih.gov/geo/) datasets, GSE10072, GSE32863, and GSE43458."}], "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:33569302"], "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:GSE10072"], "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:GSE10072"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33569302", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tlcr-20-822", "sha256": 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"PMC7867791", "section_index": 17, "section_title": "GO and KEGG pathway enrichment analyses", "row_count": 41, "column_count": 7}, "table": {"label": "Table 2", "caption": "GO and KEGG pathway enrichment analysis of candidate genes in the most significant terms", "rows": [["Terms", "ID", "Description", "Gene ratio", "Padjust", "Gene ID", "Count"], ["Biological process", "GO:0000280", "Nuclear division", "15/35", "4.15E-14", "CENPF/TPX2/UBE2C/KIF11/CDC20/CENPE/TOP2A/ASPM/TRIP13/NUSAP1/PRC1/KNTC1/AURKA/TTK/CCNB1", "15"], ["GO:0048285", "Organelle fission", "15/35", "8.22E-14", "CENPF/TPX2/UBE2C/KIF11/CDC20/CENPE/TOP2A/ASPM/TRIP13/NUSAP1/PRC1/KNTC1/AURKA/TTK/CCNB1", "15"], ["GO:0140014", "Mitotic nuclear division", "13/35", "8.22E-14", "CENPF/TPX2/UBE2C/KIF11/CDC20/CENPE/TRIP13/NUSAP1/PRC1/KNTC1/AURKA/TTK/CCNB1", "13"], ["GO:0007088", "Regulation of mitotic nuclear division", "11/35", "6.79E-13", "CENPF/UBE2C/KIF11/CDC20/CENPE/TRIP13/NUSAP1/KNTC1/AURKA/TTK/CCNB1", "11"], ["GO:0051783", "Regulation of nuclear division", "11/35", "2.50E-12", "CENPF/UBE2C/KIF11/CDC20/CENPE/TRIP13/NUSAP1/KNTC1/AURKA/TTK/CCNB1", "11"], ["GO:0007051", "Spindle organization", "10/35", "2.06E-11", "TPX2/KIF11/CDC20/CENPE/ASPM/STIL/PRC1/AURKA/TTK/CCNB1", "10"], ["GO:1902850", "Microtubule cytoskeleton organization involved in mitosis", "9/35", "1.01E-10", "TPX2/KIF11/CDC20/CENPE/STIL/NUSAP1/PRC1/TTK/CCNB1", "9"], ["GO:0007059", "Chromosome segregation", "11/35", "2.72E-10", "CENPF/ECT2/CDC20/CENPE/TOP2A/BUB1/TRIP13/NUSAP1/PRC1/TTK/CCNB1", "11"], ["GO:0051983", "Regulation of chromosome segregation", "8/35", "6.96E-10", "CENPF/ECT2/CDC20/CENPE/BUB1/TRIP13/TTK/CCNB1", "8"], ["GO:0098813", "Nuclear chromosome segregation", "10/35", "6.96E-10", "CENPF/ECT2/CDC20/CENPE/BUB1/TRIP13/NUSAP1/PRC1/TTK/CCNB1", "10"], ["Cellular component", "GO:0005819", "Spindle", "13/35", "8.73E-13", "CENPF/ECT2/TPX2/KIF11/CDC20/CENPE/KIF20A/ASPM/PRC1/KNTC1/AURKA/TTK/CCNB1", "13"], ["GO:0000922", "Spindle pole", "9/35", "2.76E-10", "CENPF/TPX2/KIF11/CDC20/ASPM/PRC1/KNTC1/AURKA/CCNB1", "9"], ["GO:0030496", "Midbody", "8/35", "2.02E-08", "CENPF/ECT2/CENPE/CEP55/KIF20A/ASPM/PRC1/AURKA", "8"], ["GO:0098687", "Chromosomal region", "9/35", "1.62E-07", "CENPF/CENPE/BUB1/MCM4/MCM6/MCM2/KNTC1/TTK/CCNB1", "9"], ["GO:0072686", "Mitotic spindle", "6/35", "3.66E-07", "ECT2/TPX2/KIF11/CENPE/ASPM/AURKA", "6"], ["GO:0005876", "Spindle microtubule", "5/35", "5.84E-07", "KIF11/CENPE/PRC1/KNTC1/AURKA", "5"], ["GO:0000776", "Kinetochore", "6/35", "1.48E-06", "CENPF/CENPE/BUB1/KNTC1/TTK/CCNB1", "6"], ["GO:0005813", "Centrosome", "9/35", "1.48E-06", "CCNB2/CENPF/CDC20/CEP55/ASPM/STIL/AURKA/HMMR/CCNB1", "9"], ["GO:0042555", "MCM complex", "3/35", "7.85E-06", "MCM4/MCM6/MCM2", "3"], ["GO:0000775", "Chromosome, centromeric region", "6/35", "7.85E-06", "CENPF/CENPE/BUB1/KNTC1/TTK/CCNB1", "6"], ["Molecular function", "GO:0004674", "Protein serine/threonine kinase activity", "6/35", "9.86E-03", 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