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pmid:31832020

Expression profile analysis identifies IER3 to predict overall survival and promote lymph node metastasis in tongue cancer.

Fang Xiao · Yinhua Dai · Yujiao Hu · Mengmeng Lu · Qun Dai

Cancer cell international · 2019 doi:10.1186/s12935-019-1028-2

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:31832020
kind
science-record
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sha256:4d5919d7017198d3764b2de3d47e1aba28bd2c1535abfe54661d5c52f4ecb9cd
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T15:40:53Z
updated_at
2026-11-01T22:44:24Z
generator object · 2 fields
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corpus-assay-engine
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reading-sci-2026-11-01
paper object · 10 fields
state
complete
title
Expression profile analysis identifies IER3 to predict overall survival and promote lymph node metastasis in tongue cancer.
doi
10.1186/s12935-019-1028-2
pmid
31832020
authors array · 5 items
[0]
Fang Xiao
[1]
Yinhua Dai
[2]
Yujiao Hu
[3]
Mengmeng Lu
[4]
Qun Dai
journal
Cancer cell international
year
2019
abstract
BACKGROUND: Lymph node metastasis is one of the most important factors affecting the prognosis of tongue cancer, and the molecular mechanism regulating lymph node metastasis of tongue cancer is poorly known. METHODS: The gene expression dataset GSE2280 and The Cancer Genome Atlas (TCGA) tongue cancer dataset were downloaded. R software was used to identify the differentially expressed hallmark gene sets and individual genes between metastatic lymph node tissues and primary tongue cancer tissues, and the Kaplan-Meier method was used to evaluate the association with overall survival. The screening and validation of functional genes was performed using western blot, q-PCR, CCK-8, migration and invasion assays, and lymphangiogenesis was examined by using a tube formation assay. RESULTS: Thirteen common hallmark gene sets were found based on Gene Set Variation Analysis (GSVA) and then subjected to differential gene expression analysis, by which 76 deregulated genes were found. Gene coexpression network analysis and survival analysis further confirmed that IER3 was the key gene associated with the prognosis and lymph node metastasis of tongue cancer patients. Knockdown of IER3 with siRNA inhibited the proliferation, colony formation, migration and invasion of Tca-8113 cells in vitro and it also inhibited the secretion and expression of VEGF-C in these cells. The culture supernatant of Tca-8113 cells could promote lymphangiogenesis and migration of lymphatic endothelial cells, and knockdown of IER3 in Tca-8113 cells suppressed these processes. CONCLUSION: Our study demonstrated that IER3 plays important roles in lymphangiogenesis regulation and prognosis in tongue cancer and might be a potential therapeutic target.
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Student’s t-test was used to calculate the P-value when comparing two groups. A one-way analysis of variance (ANOVA) was used when comparing more than two groups.
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methodological
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null
evidence array · 1 item
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source:pmid:31832020
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sections[14] "Statistical analysis" paragraph 2
quote
Student’s t-test was used to calculate the P-value when comparing two groups. A one-way analysis of variance (ANOVA) was used when comparing more than two groups.
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complete
[1] object · 6 fields
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claim-data-access
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The datasets used and/or analyzed during the study are available from the corresponding author on reasonable request.
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methodological
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null
evidence array · 1 item
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source:pmid:31832020
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sections[29] "Availability of data and materials" paragraph 2
quote
The datasets used and/or analyzed during the study are available from the corresponding author on reasonable request.
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read_published_estimate
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Read the published estimate from the source
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other
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The claim, method and evidence span published with the source article.
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inputs array · 1 item
[0]
source:pmid:31832020
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the published estimate and its evidence
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Obtain the source data from the named repository
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The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.
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[0]
data:geo:GSE2280
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the source data with its repository provenance
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Run the published analysis
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Apply the paper's statistical method to the resolved series and compare the result with the published target.
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data:geo:GSE2280
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the replicated result and its comparison
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https://doi.org/10.1186/s12935-019-1028-2
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10.1186/s12935-019-1028-2
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pmcid
PMC6873470
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europe_pmc_fulltext
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whole_body
text_hash_scope
rendered_section_body
[1] object · 15 fields
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data:geo:GSE2280
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raw
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geo-series
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application/vnd.ncbi.geo-series+json
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE2280
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The datasets used and/or analyzed during the study are available from the corresponding author on reasonable request.
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GEO
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GEO accession URL
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The datasets used and/or analyzed during the study are available from the corresponding author on reasonable request.
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GSM42246
[1]
GSM42247
[2]
GSM42248
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GSM42249
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GSM42250
[5]
GSM42251
[6]
GSM42252
[7]
GSM42253
[8]
GSM42254
[9]
GSM42255
[10]
GSM42256
[11]
GSM42257
[12]
GSM42258
[13]
GSM42259
[14]
GSM42260
[15]
GSM42261
[16]
GSM42262
[17]
GSM42263
[18]
GSM42264
[19]
GSM42265
[20]
GSM42266
[21]
GSM42267
[22]
GSM42268
[23]
GSM42269
[24]
GSM42270
[25]
GSM42271
[26]
GSM42272
sample_count
27
group_sizes
null
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null
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96
taxon
Homo sapiens
title
Prediction of lymphatic metastasis from primary squamous cell carcinoma of the oral cavity
resolution_checked_at
2026-11-01T15:39:54Z
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identifier_resolution_only_no_download_no_licence_read
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A total of 76 deregulated genes were identified in 1839 primary tumor versus metastatic lymph node genes
structure object · 5 fields
pmcid
PMC6873470
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17
section_title
Screening of hub genes involved in lymph node metastasis
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77
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4
table object · 8 fields
label
Table 1
caption
A total of 76 deregulated genes were identified in 1839 primary tumor versus metastatic lymph node genes
rows array · 77 items
[0] array · 4 items
[0]
Gene symbol
[1]
logFC
[2]
P value
[3]
Hallmark
[1] array · 4 items
[0]
MBL2
[1]
1.836355
[2]
0.016409
[3]
ALLOGRAFT_REJECTION
[2] array · 4 items
[0]
ITGAL
[1]
1.09615
[2]
0.029208
[3]
ALLOGRAFT_REJECTION
[3] array · 4 items
[0]
CD3G
[1]
1.084988
[2]
0.023672
[3]
ALLOGRAFT_REJECTION
[4] array · 4 items
[0]
FLNA
[1]
1.003019
[2]
0.037726
[3]
ALLOGRAFT_REJECTION
[5] array · 4 items
[0]
GLMN
[1]
− 1.11045
[2]
0.044154
[3]
ALLOGRAFT_REJECTION
[6] array · 4 items
[0]
VAV2
[1]
1.222483
[2]
0.037575
[3]
ANGIOGENESIS, APICAL_JUNCTION
[7] array · 4 items
[0]
ACTA1
[1]
− 4.81243
[2]
0.007734
[3]
APICAL_JUNCTION
[8] array · 4 items
[0]
EFHC1
[1]
− 1.33106
[2]
0.001242
[3]
BILE_ACID_METABOLISM
[9] array · 4 items
[0]
DIO2
[1]
− 1.48714
[2]
0.003577
[3]
BILE_ACID_METABOLISM
[10] array · 4 items
[0]
SMC6
[1]
− 1.01378
[2]
0.036294
[3]
E2F_TARGETS
[11] array · 4 items
[0]
ORC2
[1]
− 1.02171
[2]
0.039099
[3]
E2F_TARGETS
[12] array · 4 items
[0]
LUC7L3
[1]
− 1.21609
[2]
0.002313
[3]
E2F_TARGETS
[13] array · 4 items
[0]
MRE11A
[1]
− 1.23003
[2]
0.045764
[3]
E2F_TARGETS
[14] array · 4 items
[0]
ABCA3
[1]
− 1.4387
[2]
0.009719
[3]
ESTROGEN_RESPONSE_EARLY, ESTROGEN_RESPONSE_LATE
[15] array · 4 items
[0]
TTC39A
[1]
− 1.90927
[2]
0.002779
[3]
ESTROGEN_RESPONSE_EARLY
[16] array · 4 items
[0]
NPY1R
[1]
2.020464
[2]
0.03779
[3]
ESTROGEN_RESPONSE_LATE, ESTROGEN_RESPONSE_EARLY
[17] array · 4 items
[0]
GAL
[1]
1.468347
[2]
0.023249
[3]
ESTROGEN_RESPONSE_LATE
[18] array · 4 items
[0]
EGR3
[1]
1.177485
[2]
0.036595
[3]
ESTROGEN_RESPONSE_LATE, ESTROGEN_RESPONSE_EARLY, KRAS_SIGNALING_UP
[19] array · 4 items
[0]
CASC5
[1]
1.897606
[2]
0.036429
[3]
G2M_CHECKPOINT
[20] array · 4 items
[0]
CASP8AP2
[1]
− 1.09086
[2]
0.016979
[3]
G2M_CHECKPOINT
[21] array · 4 items
[0]
EZH2
[1]
− 1.18721
[2]
0.018306
[3]
G2M_CHECKPOINT, E2F_TARGETS
[22] array · 4 items
[0]
MNAT1
[1]
− 1.27108
[2]
0.027402
[3]
G2M_CHECKPOINT
[23] array · 4 items
[0]
SMC2
[1]
− 1.33982
[2]
0.04864
[3]
G2M_CHECKPOINT
[24] array · 4 items
[0]
SERPINE1
[1]
1.733088
[2]
0.021088
[3]
HYPOXIA
[25] array · 4 items
[0]
FOS
[1]
1.543577
[2]
0.005153
[3]
HYPOXIA
[26] array · 4 items
[0]
IER3
[1]
1.387516
[2]
0.015602
[3]
HYPOXIA, APOPTOSIS
[27] array · 4 items
[0]
ANGPTL4
[1]
1.261686
[2]
0.018984
[3]
HYPOXIA, KRAS_SIGNALING_UP, ADIPOGENESIS
[28] array · 4 items
[0]
SLC2A5
[1]
− 2.14747
[2]
0.047968
[3]
HYPOXIA
[29] array · 4 items
[0]
SOCS3
[1]
1.72843
[2]
0.019538
[3]
IL6_JAK_STAT3_SIGNALING
[30] array · 4 items
[0]
INHBE
[1]
− 1.17054
[2]
0.031406
[3]
IL6_JAK_STAT4_SIGNALING
[31] array · 4 items
[0]
ZNF639
[1]
2.511151
[2]
0.001222
[3]
KRAS_SIGNALING_UP
[32] array · 4 items
[0]
RBP4
[1]
2.229625
[2]
0.033045
[3]
KRAS_SIGNALING_UP
[33] array · 4 items
[0]
CD37
[1]
1.547497
[2]
0.019287
[3]
KRAS_SIGNALING_UP
[34] array · 4 items
[0]
GFPT2
[1]
1.031506
[2]
0.042835
[3]
KRAS_SIGNALING_UP
[35] array · 4 items
[0]
SLMO2
[1]
− 1.00092
[2]
0.02985
[3]
KRAS_SIGNALING_UP
[36] array · 4 items
[0]
CFH
[1]
− 1.6692
[2]
0.040962
[3]
KRAS_SIGNALING_UP
[37] array · 4 items
[0]
SLPI
[1]
− 1.67431
[2]
0.014661
[3]
KRAS_SIGNALING_UP
[38] array · 4 items
[0]
BTC
[1]
− 2.14105
[2]
0.00012
[3]
KRAS_SIGNALING_UP
[39] array · 4 items
[0]
TMEM158
[1]
− 2.44114
[2]
0.000586
[3]
KRAS_SIGNALING_UP
[40] array · 4 items
[0]
SVIL
[1]
− 1.15372
[2]
0.004237
[3]
MYOGENESIS
[41] array · 4 items
[0]
IFRD1
[1]
− 1.29777
[2]
0.000871
[3]
MYOGENESIS
[42] array · 4 items
[0]
AGL
[1]
− 1.34563
[2]
0.006822
[3]
MYOGENESIS
[43] array · 4 items
[0]
FABP3
[1]
− 1.39162
[2]
0.018123
[3]
MYOGENESIS
[44] array · 4 items
[0]
CKMT2
[1]
− 1.43326
[2]
0.0434
[3]
MYOGENESIS
[45] array · 4 items
[0]
MYH8
[1]
− 1.48548
[2]
0.015832
[3]
MYOGENESIS
[46] array · 4 items
[0]
DMD
[1]
− 1.53731
[2]
0.006311
[3]
MYOGENESIS, G2M_CHECKPOINT
[47] array · 4 items
[0]
MYOZ1
[1]
− 1.74048
[2]
0.041979
[3]
MYOGENESIS
[48] array · 4 items
[0]
CHRNA1
[1]
− 1.8081
[2]
0.017455
[3]
MYOGENESIS
[49] array · 4 items
[0]
HRC
[1]
− 2.02106
[2]
0.038865
[3]
MYOGENESIS
[50] array · 4 items
[0]
FHL1
[1]
− 2.03688
[2]
0.035865
[3]
MYOGENESIS
[51] array · 4 items
[0]
SLN
[1]
− 2.11469
[2]
0.041452
[3]
MYOGENESIS
[52] array · 4 items
[0]
ACTC1
[1]
− 2.90968
[2]
0.011697
[3]
MYOGENESIS
[53] array · 4 items
[0]
DES
[1]
− 3.03388
[2]
0.031095
[3]
MYOGENESIS
[54] array · 4 items
[0]
MYBPH
[1]
− 3.21711
[2]
0.003079
[3]
MYOGENESIS
[55] array · 4 items
[0]
TNNT1
[1]
− 3.34517
[2]
0.024009
[3]
MYOGENESIS
[56] array · 4 items
[0]
MYH2
[1]
− 3.3503
[2]
0.042848
[3]
MYOGENESIS
[57] array · 4 items
[0]
MB
[1]
− 3.35038
[2]
0.010556
[3]
MYOGENESIS
[58] array · 4 items
[0]
TCAP
[1]
− 3.38871
[2]
0.029364
[3]
MYOGENESIS
[59] array · 4 items
[0]
MYLPF
[1]
− 3.50266
[2]
0.020669
[3]
MYOGENESIS
[60] array · 4 items
[0]
TNNC2
[1]
− 3.52148
[2]
0.020435
[3]
MYOGENESIS
[61] array · 4 items
[0]
MYL2
[1]
− 3.59938
[2]
0.011658
[3]
MYOGENESIS
[62] array · 4 items
[0]
ACTN2
[1]
− 4.31463
[2]
0.01354
[3]
MYOGENESIS
[63] array · 4 items
[0]
TNNI2
[1]
− 4.42965
[2]
0.011318
[3]
MYOGENESIS
[64] array · 4 items
[0]
MYL1
[1]
− 4.54843
[2]
0.006995
[3]
MYOGENESIS
[65] array · 4 items
[0]
CKM
[1]
− 4.71858
[2]
0.011289
[3]
MYOGENESIS
[66] array · 4 items
[0]
TNNI1
[1]
− 4.77636
[2]
0.0062
[3]
MYOGENESIS
[67] array · 4 items
[0]
TNNC1
[1]
− 5.64825
[2]
0.007417
[3]
MYOGENESIS
[68] array · 4 items
[0]
CSRP3
[1]
− 5.77325
[2]
0.012999
[3]
MYOGENESIS
[69] array · 4 items
[0]
PPP2R1B
[1]
1.171797
[2]
0.042423
[3]
PI3K_AKT_MTOR_SIGNALING
[70] array · 4 items
[0]
FGF17
[1]
− 1.34021
[2]
0.032683
[3]
PI3K_AKT_MTOR_SIGNALING
[71] array · 4 items
[0]
IL4
[1]
− 1.52042
[2]
0.040415
[3]
PI5K_AKT_MTOR_SIGNALING, IL6_JAK_STAT3_SIGNALING
[72] array · 4 items
[0]
ADCY2
[1]
− 1.91434
[2]
0.025949
[3]
PI6K_AKT_MTOR_SIGNALING
[73] array · 4 items
[0]
SH3GL2
[1]
1.508413
[2]
0.042024
[3]
PROTEIN_SECRETION
[74] array · 4 items
[0]
OCRL
[1]
− 1.09672
[2]
0.008807
[3]
PROTEIN_SECRETION
[75] array · 4 items
[0]
JUNB
[1]
1.047607
[2]
0.019591
[3]
REACTIVE_OXIGEN_SPECIES_PATHWAY
[76] array · 4 items
[0]
GCLM
[1]
− 1.71176
[2]
0.003821
[3]
REACTIVE_OXIGEN_SPECIES_PATHWAY, BILE_ACID_METABOLISM
locator
section[17]/table-wrap[1]#Tab1
[3] object · 16 fields
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asset:table:pmid:31832020:2
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jats-table
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read_table
reader_status
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section[17]/table-wrap[2]#Tab2
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null
note
Top 10 hubgenes in 76 deregulated genes
structure object · 5 fields
pmcid
PMC6873470
section_index
17
section_title
Screening of hub genes involved in lymph node metastasis
row_count
11
column_count
5
table object · 8 fields
label
Table 2
caption
Top 10 hubgenes in 76 deregulated genes
rows array · 11 items
[0] array · 5 items
[0]
Gene
[1]
logFC
[2]
AveExpr
[3]
t
[4]
P value
[1] array · 5 items
[0]
ACTA1
[1]
− 4.81243
[2]
8.399569
[3]
− 2.99088
[4]
0.007734
[2] array · 5 items
[0]
AGL
[1]
− 1.34563
[2]
7.828326
[3]
− 3.04814
[4]
0.006822
[3] array · 5 items
[0]
CKMT2
[1]
− 1.43326
[2]
6.654878
[3]
− 2.16996
[4]
0.0434
[4] array · 5 items
[0]
DIO2
[1]
− 1.48714
[2]
7.679014
[3]
− 3.34018
[4]
0.003577
[5] array · 5 items
[0]
DMD
[1]
− 1.53731
[2]
6.485171
[3]
− 3.08362
[4]
0.006311
[6] array · 5 items
[0]
FABP3
[1]
− 1.39162
[2]
5.339507
[3]
− 2.59505
[4]
0.018123
[7] array · 5 items
[0]
IER3
[1]
1.387516
[2]
10.10791
[3]
2.665727
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0.015602
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Overall survival analysis of the top 10 hub genes of TCGA tongue cancer patients
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Subsequent screening and validation of the hub genes using TCGA data
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Overall survival analysis of the top 10 hub genes of TCGA tongue cancer patients
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1.21–3.36
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0.89–2.54
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1.56
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0.92–2.64
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0.082
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1.44
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0.84–2.49
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h node metastasis of tongue cancer patients. Knockdown of IER3 with siRNA inhibited the proliferati
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igration of lymphatic endothelial cells, and knockdown of IER3 in Tca-8113 cells suppressed these p
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ical Science (Beijing, China). Tongue cancer cell lines were cultured in DMEM (Gibco, USA) with 10% fetal bovine s
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31832020", "kind": "science-record", "revision": 8, "content_hash": "sha256:4d5919d7017198d3764b2de3d47e1aba28bd2c1535abfe54661d5c52f4ecb9cd", "created_at": "2026-11-01T15:40:53Z", "updated_at": "2026-11-01T22:44:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Expression profile analysis identifies IER3 to predict overall survival and promote lymph node metastasis in tongue cancer.", "doi": "10.1186/s12935-019-1028-2", "pmid": "31832020", "authors": ["Fang Xiao", "Yinhua Dai", "Yujiao Hu", "Mengmeng Lu", "Qun Dai"], "journal": "Cancer cell international", "year": 2019, "abstract": "BACKGROUND: Lymph node metastasis is one of the most important factors affecting the prognosis of tongue cancer, and the molecular mechanism regulating lymph node metastasis of tongue cancer is poorly known.\nMETHODS: The gene expression dataset GSE2280 and The Cancer Genome Atlas (TCGA) tongue cancer dataset were downloaded. R software was used to identify the differentially expressed hallmark gene sets and individual genes between metastatic lymph node tissues and primary tongue cancer tissues, and the Kaplan-Meier method was used to evaluate the association with overall survival. The screening and validation of functional genes was performed using western blot, q-PCR, CCK-8, migration and invasion assays, and lymphangiogenesis was examined by using a tube formation assay.\nRESULTS: Thirteen common hallmark gene sets were found based on Gene Set Variation Analysis (GSVA) and then subjected to differential gene expression analysis, by which 76 deregulated genes were found. Gene coexpression network analysis and survival analysis further confirmed that IER3 was the key gene associated with the prognosis and lymph node metastasis of tongue cancer patients. Knockdown of IER3 with siRNA inhibited the proliferation, colony formation, migration and invasion of Tca-8113 cells in vitro and it also inhibited the secretion and expression of VEGF-C in these cells. The culture supernatant of Tca-8113 cells could promote lymphangiogenesis and migration of lymphatic endothelial cells, and knockdown of IER3 in Tca-8113 cells suppressed these processes.\nCONCLUSION: Our study demonstrated that IER3 plays important roles in lymphangiogenesis regulation and prognosis in tongue cancer and might be a potential therapeutic target.", "claims": [{"id": "claim-method", "statement": "Student’s t-test was used to calculate the P-value when comparing two groups. 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{"label": "Table 2", "caption": "Top 10 hubgenes in 76 deregulated genes", "rows": [["Gene", "logFC", "AveExpr", "t", "P value"], ["ACTA1", "− 4.81243", "8.399569", "− 2.99088", "0.007734"], ["AGL", "− 1.34563", "7.828326", "− 3.04814", "0.006822"], ["CKMT2", "− 1.43326", "6.654878", "− 2.16996", "0.0434"], ["DIO2", "− 1.48714", "7.679014", "− 3.34018", "0.003577"], ["DMD", "− 1.53731", "6.485171", "− 3.08362", "0.006311"], ["FABP3", "− 1.39162", "5.339507", "− 2.59505", "0.018123"], ["IER3", "1.387516", "10.10791", "2.665727", "0.015602"], ["MYL1", "− 4.54843", "8.410023", "− 3.03672", "0.006995"], ["SVIL", "− 1.15372", "9.014868", "− 3.26402", "0.004237"], ["TNNC2", "− 3.52148", "6.850598", "− 2.53798", "0.020435"]], "row_count": 11, "column_count": 5, "numeric_cells": 40, "header_rows": 1, "locator": "section[17]/table-wrap[2]#Tab2"}}, {"id": "asset:table:pmid:31832020:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, 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