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pmid:34249701

Identification of Prognostic Signature and Gliclazide as Candidate Drugs in Lung Adenocarcinoma.

Yang Cheng · Kezuo Hou · Yizhe Wang · Yang Chen · Xueying Zheng · Jianfei Qi · Bowen Yang · Shiying Tang · Xu Han · Dongyao Shi · Ximing Wang · Yunpeng Liu · Xuejun Hu · Xiaofang Che

Frontiers in oncology · 2021 doi:10.3389/fonc.2021.665276

Paper

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Experiment

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Data

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Analysis

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title
Identification of Prognostic Signature and Gliclazide as Candidate Drugs in Lung Adenocarcinoma.
doi
10.3389/fonc.2021.665276
pmid
34249701
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[0]
Yang Cheng
[1]
Kezuo Hou
[2]
Yizhe Wang
[3]
Yang Chen
[4]
Xueying Zheng
[5]
Jianfei Qi
[6]
Bowen Yang
[7]
Shiying Tang
[8]
Xu Han
[9]
Dongyao Shi
[10]
Ximing Wang
[11]
Yunpeng Liu
[12]
Xuejun Hu
[13]
Xiaofang Che
journal
Frontiers in oncology
year
2021
abstract
BACKGROUND: Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, with high incidence and mortality. To improve the curative effect and prolong the survival of patients, it is necessary to find new biomarkers to accurately predict the prognosis of patients and explore new strategy to treat high-risk LUAD. METHODS: A comprehensive genome-wide profiling analysis was conducted using a retrospective pool of LUAD patient data from the previous datasets of Gene Expression Omnibus (GEO) including GSE18842, GSE19188, GSE40791 and GSE50081 and The Cancer Genome Atlas (TCGA). Differential gene analysis and Cox proportional hazard model were used to identify differentially expressed genes with survival significance as candidate prognostic genes. The Kaplan-Meier with log-rank test was used to assess survival difference. A risk score model was developed and validated using TCGA-LUAD and GSE50081. Additionally, The Connectivity Map (CMAP) was used to predict drugs for the treatment of LUAD. The anti-cancer effect and mechanism of its candidate drugs were studied in LUAD cell lines. RESULTS: We identified a 5-gene signature (KIF20A, KLF4, KRT6A, LIFR and RGS13). Risk Score (RS) based on 5-gene signature was significantly associated with overall survival (OS). Nomogram combining RS with clinical pathology parameters could potently predict the prognosis of patients with LUAD. Moreover, gliclazide was identified as a candidate drug for the treatment of high-RS LUAD. Finally, gliclazide was shown to induce cell cycle arrest and apoptosis in LUAD cells possibly by targeting CCNB1, CCNB2, CDK1 and AURKA. CONCLUSION: This study identified a 5-gene signature that can predict the prognosis of patients with LUAD, and Gliclazide as a potential therapeutic drug for LUAD. It provides a new direction for the prognosis and treatment of patients with LUAD.
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Univariate and multivariate Cox proportional hazard regression analysis was also performed to access the relationship between RS and OS.
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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 authors.
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GSM1001692
[183]
GSM1001693
[184]
GSM1001694
[185]
GSM1001695
[186]
GSM1001696
[187]
GSM1001697
[188]
GSM1001698
[189]
GSM1001699
[190]
GSM1001700
[191]
GSM1001701
[192]
GSM1001702
[193]
GSM1001703
sample_count
194
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Usp44 binds centrin to regulate centrosome positioning and suppress tumorigenesis
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE50081
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=GSE50081
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE50081
version
null
note
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
structure object · 15 fields
repository
GEO
access_route
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 authors.
access_statement_kind
data_availability_statement
sample_accessions array · 181 items
[0]
GSM1213669
[1]
GSM1213670
[2]
GSM1213671
[3]
GSM1213672
[4]
GSM1213673
[5]
GSM1213674
[6]
GSM1213675
[7]
GSM1213676
[8]
GSM1213677
[9]
GSM1213678
[10]
GSM1213679
[11]
GSM1213680
[12]
GSM1213681
[13]
GSM1213682
[14]
GSM1213683
[15]
GSM1213684
[16]
GSM1213685
[17]
GSM1213686
[18]
GSM1213687
[19]
GSM1213688
[20]
GSM1213689
[21]
GSM1213690
[22]
GSM1213691
[23]
GSM1213692
[24]
GSM1213693
[25]
GSM1213694
[26]
GSM1213695
[27]
GSM1213696
[28]
GSM1213697
[29]
GSM1213698
[30]
GSM1213699
[31]
GSM1213700
[32]
GSM1213701
[33]
GSM1213702
[34]
GSM1213703
[35]
GSM1213704
[36]
GSM1213705
[37]
GSM1213706
[38]
GSM1213707
[39]
GSM1213708
[40]
GSM1213709
[41]
GSM1213710
[42]
GSM1213711
[43]
GSM1213712
[44]
GSM1213713
[45]
GSM1213714
[46]
GSM1213715
[47]
GSM1213716
[48]
GSM1213717
[49]
GSM1213718
[50]
GSM1213719
[51]
GSM1213720
[52]
GSM1213721
[53]
GSM1213722
[54]
GSM1213723
[55]
GSM1213724
[56]
GSM1213725
[57]
GSM1213726
[58]
GSM1213727
[59]
GSM1213728
[60]
GSM1213729
[61]
GSM1213730
[62]
GSM1213731
[63]
GSM1213732
[64]
GSM1213733
[65]
GSM1213734
[66]
GSM1213735
[67]
GSM1213736
[68]
GSM1213737
[69]
GSM1213738
[70]
GSM1213739
[71]
GSM1213740
[72]
GSM1213741
[73]
GSM1213742
[74]
GSM1213743
[75]
GSM1213744
[76]
GSM1213745
[77]
GSM1213746
[78]
GSM1213747
[79]
GSM1213748
[80]
GSM1213749
[81]
GSM1213750
[82]
GSM1213751
[83]
GSM1213752
[84]
GSM1213753
[85]
GSM1213754
[86]
GSM1213755
[87]
GSM1213756
[88]
GSM1213757
[89]
GSM1213758
[90]
GSM1213759
[91]
GSM1213760
[92]
GSM1213761
[93]
GSM1213762
[94]
GSM1213763
[95]
GSM1213764
[96]
GSM1213765
[97]
GSM1213766
[98]
GSM1213767
[99]
GSM1213768
[100]
GSM1213769
[101]
GSM1213770
[102]
GSM1213771
[103]
GSM1213772
[104]
GSM1213773
[105]
GSM1213774
[106]
GSM1213775
[107]
GSM1213776
[108]
GSM1213777
[109]
GSM1213778
[110]
GSM1213779
[111]
GSM1213780
[112]
GSM1213781
[113]
GSM1213782
[114]
GSM1213783
[115]
GSM1213784
[116]
GSM1213785
[117]
GSM1213786
[118]
GSM1213787
[119]
GSM1213788
[120]
GSM1213789
[121]
GSM1213790
[122]
GSM1213791
[123]
GSM1213792
[124]
GSM1213793
[125]
GSM1213794
[126]
GSM1213795
[127]
GSM1213796
[128]
GSM1213797
[129]
GSM1213798
[130]
GSM1213799
[131]
GSM1213800
[132]
GSM1213801
[133]
GSM1213802
[134]
GSM1213803
[135]
GSM1213804
[136]
GSM1213805
[137]
GSM1213806
[138]
GSM1213807
[139]
GSM1213808
[140]
GSM1213809
[141]
GSM1213810
[142]
GSM1213811
[143]
GSM1213812
[144]
GSM1213813
[145]
GSM1213814
[146]
GSM1213815
[147]
GSM1213816
[148]
GSM1213817
[149]
GSM1213818
[150]
GSM1213819
[151]
GSM1213820
[152]
GSM1213821
[153]
GSM1213822
[154]
GSM1213823
[155]
GSM1213824
[156]
GSM1213825
[157]
GSM1213826
[158]
GSM1213827
[159]
GSM1213828
[160]
GSM1213829
[161]
GSM1213830
[162]
GSM1213831
[163]
GSM1213832
[164]
GSM1213833
[165]
GSM1213834
[166]
GSM1213835
[167]
GSM1213836
[168]
GSM1213837
[169]
GSM1213838
[170]
GSM1213839
[171]
GSM1213840
[172]
GSM1213841
[173]
GSM1213842
[174]
GSM1213843
[175]
GSM1213844
[176]
GSM1213845
[177]
GSM1213846
[178]
GSM1213847
[179]
GSM1213848
[180]
GSM1213849
sample_count
181
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Validation of a histology-independent prognostic gene signature for early stage, non-small cell lung cancer including stage IA patients
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[5] object · 16 fields
id
asset:table:pmid:34249701:1
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table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:6563a4c16072a26ac0c2c6383a45d90910696a5717c3d33ee46a8693f7646c9b
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626
access
open
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verified
reader
read_table
reader_status
available
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section[16]/table-wrap[1]#T1
version
null
note
Characteristics of the public microarray datasets used in this study.
structure object · 5 fields
pmcid
PMC8264429
section_index
16
section_title
Construction and Assessment of a Five-Gene Prognostic Signature
row_count
6
column_count
5
table object · 8 fields
label
Table 1
caption
Characteristics of the public microarray datasets used in this study.
rows array · 6 items
[0] array · 5 items
[0]
Study
[1]
Species/array platform
[2]
Samples
[3]
Type
[4]
Function
[1] array · 5 items
[0]
TCGA-LUAD
[1]
Human Illumina HiSeq 2000
[2]
332 Cancer
[3]
LUAD
[4]
Training set
[2] array · 5 items
[0]
GSE50081
[1]
(GPL570)
[2]
128 Cancer
[3]
LUAD
[4]
Validation set
[3] array · 5 items
[0]
GSE18842
[1]
(GPL570)
[2]
45 Normal and 46 Cancer
[3]
NSCLC
[4]
For DEGs
[4] array · 5 items
[0]
GSE19188
[1]
(GPL570)
[2]
65 Normal and 91 Cancer
[3]
NSCLC
[4]
For DEGs
[5] array · 5 items
[0]
GSE40791
[1]
(GPL570)
[2]
100 Normal and 94 Cancer
[3]
NSCLC
[4]
For DEGs
locator
section[16]/table-wrap[1]#T1
[6] object · 16 fields
id
asset:table:pmid:34249701:2
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table
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jats-table
media_type
application/vnd.jats.table+json
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null
sha256
sha256:b4cb09c8de08d81942b9938e16b6515606b0bad99af2332af426b05ff12a9197
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657
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[16]/table-wrap[2]#T2
version
null
note
Multivariate Cox regression analysis of the 5-gene signature.
structure object · 5 fields
pmcid
PMC8264429
section_index
16
section_title
Construction and Assessment of a Five-Gene Prognostic Signature
row_count
6
column_count
6
table object · 8 fields
label
Table 2
caption
Multivariate Cox regression analysis of the 5-gene signature.
rows array · 6 items
[0] array · 6 items
[0]
ID
[1]
Coef
[2]
HR
[3]
HR.95L
[4]
HR.95H
[5]
P-value
[1] array · 6 items
[0]
KIF20A
[1]
0.301291283
[2]
1.351602983
[3]
1.103810884
[4]
1.65502139
[5]
0.003547525
[2] array · 6 items
[0]
LIFR
[1]
−0.182264632
[2]
0.833380772
[3]
0.672709557
[4]
1.032427002
[5]
0.095329705
[3] array · 6 items
[0]
RGS13
[1]
−1.100168875
[2]
0.332814875
[3]
0.117059758
[4]
0.946232446
[5]
0.039052759
[4] array · 6 items
[0]
KLF4
[1]
0.240230298
[2]
1.27154195
[3]
1.070939257
[4]
1.509720483
[5]
0.006100447
[5] array · 6 items
[0]
KRT6A
[1]
0.085854478
[2]
1.089647749
[3]
1.012552387
[4]
1.172613123
[5]
0.0218395
locator
section[16]/table-wrap[2]#T2
[7] object · 16 fields
id
asset:table:pmid:34249701:3
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table
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jats-table
media_type
application/vnd.jats.table+json
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null
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sha256:7b5518d8517552ec672cc4ea98632b3703bf996c16d97b10359c4f5ce2f8f3dc
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630
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open
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verified
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read_table
reader_status
available
identifier
section[19]/table-wrap[1]#T3
version
null
note
Eight candidate drugs of connectivity map analysis.
structure object · 5 fields
pmcid
PMC8264429
section_index
19
section_title
Screening of Potential Drugs for LUAD by CMAP Analysis
row_count
10
column_count
4
table object · 8 fields
label
Table 3
caption
Eight candidate drugs of connectivity map analysis.
rows array · 10 items
[0] array · 4 items
[0]
CMAP name
[1]
Mean
[2]
P
[3]
Percent non-null
[1] array · 4 items
[0]
medrysone
[1]
−0.68
[2]
0.00064
[3]
100
[2] array · 4 items
[0]
0175029-0000
[1]
−0.649
[2]
0.00073
[3]
100
[3] array · 4 items
[0]
ginkgolide A
[1]
−0.73
[2]
0.00105
[3]
100
[4] array · 4 items
[0]
repaglinide
[1]
−0.722
[2]
0.00275
[3]
100
[5] array · 4 items
[0]
trioxysalen
[1]
−0.663
[2]
0.00336
[3]
100
[6] array · 4 items
[0]
gliclazide
[1]
−0.66
[2]
0.00432
[3]
100
[7] array · 4 items
[0]
0173570-0000
[1]
−0.734
[2]
0.00465
[3]
100
[8] array · 4 items
[0]
eucatropine
[1]
−0.621
[2]
0.00528
[3]
100
[9] array · 4 items
[0]
0297417-0002B
[1]
−0.658
[2]
0.00863
[3]
100
locator
section[19]/table-wrap[1]#T3
[8] object · 16 fields
id
asset:table:pmid:34249701:4
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table
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jats-table
media_type
application/vnd.jats.table+json
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null
sha256
sha256:3aab4eefc56eef7f51da2e536f28fb06aa54a310527a86c87f1881ad2a09ab52
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323
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open
state
verified
reader
read_table
reader_status
available
identifier
section[21]/table-wrap[1]#T4
version
null
note
Binding energy for targets with their drugs.
structure object · 5 fields
pmcid
PMC8264429
section_index
21
section_title
Identification of the Candidate Targets of Gliclazide by Molecular Docking Analysis
row_count
6
column_count
2
table object · 8 fields
label
Table 4
caption
Binding energy for targets with their drugs.
rows array · 6 items
[0] array · 2 items
[0]
Protein
[1]
Docking score (kcal/mol)
[1] array · 2 items
[0]
[1]
Gliclazide
[2] array · 2 items
[0]
CCNB1
[1]
−8.9
[3] array · 2 items
[0]
CCNB2
[1]
−8.6
[4] array · 2 items
[0]
CDK1
[1]
−8.3
[5] array · 2 items
[0]
AURKA
[1]
−6.9
locator
section[21]/table-wrap[1]#T4
gaps array · 8 items
[0]
asset:data:geo:GSE18842 not downloaded
[1]
asset:data:geo:GSE18842 licence not read
[2]
asset:data:geo:GSE19188 not downloaded
[3]
asset:data:geo:GSE19188 licence not read
[4]
asset:data:geo:GSE40791 not downloaded
[5]
asset:data:geo:GSE40791 licence not read
[6]
asset:data:geo:GSE50081 not downloaded
[7]
asset:data:geo:GSE50081 licence not read
analysis object · 4 fields
state
partial
methods array · 4 items
[0] object · 10 fields
id
method-1
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
[1] object · 10 fields
id
method-2
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
0.7
band
medium
quote
log-rank
[2] object · 10 fields
id
method-3
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
[3] object · 10 fields
id
method-4
family
null
specific
null
label
Univariate and multivariate Cox proportional hazard regression analysis
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
Univariate and multivariate Cox proportional hazard regression analysis was also performed to access the relationship between RS and OS.
targets array · 0 items
gaps array · 1 item
[0]
method.reader_named_unmapped
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]
survival_km
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: kaplan_meier.
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 · 4 items
[0]
GSE18842
[1]
GSE19188
[2]
GSE40791
[3]
GSE50081
resolved_accessions array · 4 items
[0]
GSE18842
[1]
GSE19188
[2]
GSE40791
[3]
GSE50081
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 authors.
basis
The paper names GSE18842, GSE19188, GSE40791, GSE50081 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]
survival_km
assets array · 6 items
[0]
source:pmid:34249701
[1]
data:geo:GSE18842
[2]
asset:table:pmid:34249701:1
[3]
asset:table:pmid:34249701:2
[4]
asset:table:pmid:34249701:3
[5]
asset:table:pmid:34249701:4
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:GSE18842
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
2026-10-31T18:32:07Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
3
usage object · 3 fields
prompt_tokens
29376
completion_tokens
1766
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:34249701
type
paper
label
pmid:34249701
[1] object · 3 fields
id
source:pmid:34249701
type
manuscript
label
PMID 34249701 full text
[2] object · 3 fields
id
data:geo:GSE18842
type
dataset
label
GEO GSE18842
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:34249701
type
paper
label
pmid:34249701
[1] object · 3 fields
id
source:pmid:34249701
type
manuscript
label
PMID 34249701 full text
[2] object · 3 fields
id
data:geo:GSE18842
type
dataset
label
GEO GSE18842
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-34249701
type
extraction
used array · 1 item
[0]
source:pmid:34249701
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE18842
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE18842
agent
agent:corpus-assay-engine
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[0] object · 3 fields
id
agent:corpus-assay-engine
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software
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Corpus assay engine
[1] object · 3 fields
id
agent:minimax-reader
type
software
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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:34249701
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sha256:649023cac97c951efe4bd3bdd12c01bdfd3e86dda0c21e62d33e1b3d6400e85b
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gaps array · 13 items
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asset:data:geo:GSE18842 licence not read
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asset:data:geo:GSE18842 not downloaded
[2]
asset:data:geo:GSE19188 licence not read
[3]
asset:data:geo:GSE19188 not downloaded
[4]
asset:data:geo:GSE40791 licence not read
[5]
asset:data:geo:GSE40791 not downloaded
[6]
asset:data:geo:GSE50081 licence not read
[7]
asset:data:geo:GSE50081 not downloaded
[8]
execution.not_run
[9]
method.reader_named_unmapped
[10]
review.human_critique
[11]
review.independent_reader
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review.machine_critique
assays array · 3 items
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data_generation
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apoptosis_assay
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99e1195c7d6f
confidence
0.69
evidence array · 1 item
[0]
de was shown to induce cell cycle arrest and apoptosis in LUAD cells possibly by targeting CCNB1, C
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paper_text_order:1614
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assay:1
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assay_lexicon
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evidence array · 2 items
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my of Sciences (Shanghai, China). Cells were cultured in RPMI1640 medium supplemented with 10% fetal
[1]
t each experiment. Two human LUAD cell lines A549 and H1299 were purchased from Shanghai Insti
order_basis
paper_text_order:2221
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assay:2
[2] object · 11 fields
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analysis
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survival_km
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dsl_catalogue
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evidence array · 1 item
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Kaplan-Meier
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34249701", "kind": "science-record", "revision": 7, "content_hash": "sha256:c9ccd4d6e1d866f2d53fcaf7210f4dd7d1a0765ea82397e7207a4b61526233ea", "created_at": "2026-11-01T15:41:42Z", "updated_at": "2026-11-01T22:04:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Prognostic Signature and Gliclazide as Candidate Drugs in Lung Adenocarcinoma.", "doi": "10.3389/fonc.2021.665276", "pmid": "34249701", "authors": ["Yang Cheng", "Kezuo Hou", "Yizhe Wang", "Yang Chen", "Xueying Zheng", "Jianfei Qi", "Bowen Yang", "Shiying Tang", "Xu Han", "Dongyao Shi", "Ximing Wang", "Yunpeng Liu", "Xuejun Hu", "Xiaofang Che"], "journal": "Frontiers in oncology", "year": 2021, "abstract": "BACKGROUND: Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, with high incidence and mortality. To improve the curative effect and prolong the survival of patients, it is necessary to find new biomarkers to accurately predict the prognosis of patients and explore new strategy to treat high-risk LUAD.\nMETHODS: A comprehensive genome-wide profiling analysis was conducted using a retrospective pool of LUAD patient data from the previous datasets of Gene Expression Omnibus (GEO) including GSE18842, GSE19188, GSE40791 and GSE50081 and The Cancer Genome Atlas (TCGA). Differential gene analysis and Cox proportional hazard model were used to identify differentially expressed genes with survival significance as candidate prognostic genes. The Kaplan-Meier with log-rank test was used to assess survival difference. A risk score model was developed and validated using TCGA-LUAD and GSE50081. Additionally, The Connectivity Map (CMAP) was used to predict drugs for the treatment of LUAD. The anti-cancer effect and mechanism of its candidate drugs were studied in LUAD cell lines.\nRESULTS: We identified a 5-gene signature (KIF20A, KLF4, KRT6A, LIFR and RGS13). Risk Score (RS) based on 5-gene signature was significantly associated with overall survival (OS). Nomogram combining RS with clinical pathology parameters could potently predict the prognosis of patients with LUAD. Moreover, gliclazide was identified as a candidate drug for the treatment of high-RS LUAD. Finally, gliclazide was shown to induce cell cycle arrest and apoptosis in LUAD cells possibly by targeting CCNB1, CCNB2, CDK1 and AURKA.\nCONCLUSION: This study identified a 5-gene signature that can predict the prognosis of patients with LUAD, and Gliclazide as a potential therapeutic drug for LUAD. It provides a new direction for the prognosis and treatment of patients with LUAD.", "claims": [{"id": "claim-method", "statement": "Univariate and multivariate Cox proportional hazard regression analysis was also performed to access the relationship between RS and OS.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34249701", "locator": "sections[14] \"Statistical Analysis\" paragraph 2", "quote": "Univariate and multivariate Cox proportional hazard regression analysis was also performed to access the relationship between RS and OS."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . 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