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pmid:33767977

A 15-Gene Signature and Prognostic Nomogram for Predicting Overall Survival in Non-Distant Metastatic Oral Tongue Squamous Cell Carcinoma.

Muyuan Liu · Litian Tong · Bin Liang · Xuhong Song · Lingzhu Xie · Hanwei Peng · Dongyang Huang

Frontiers in oncology · 2021 doi:10.3389/fonc.2021.587548

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Data

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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2026-11-01T15:41:30Z
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paper object · 10 fields
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title
A 15-Gene Signature and Prognostic Nomogram for Predicting Overall Survival in Non-Distant Metastatic Oral Tongue Squamous Cell Carcinoma.
doi
10.3389/fonc.2021.587548
pmid
33767977
authors array · 7 items
[0]
Muyuan Liu
[1]
Litian Tong
[2]
Bin Liang
[3]
Xuhong Song
[4]
Lingzhu Xie
[5]
Hanwei Peng
[6]
Dongyang Huang
journal
Frontiers in oncology
year
2021
abstract
BACKGROUND: Oral tongue squamous cell carcinoma (OTSCC) is a devastating tumor with poor prognosis. There is an urgent need for reliable biomarkers to help predict prognosis and guide treatment for OTSCC. In the current study, we aimed to develop a robust multi-gene signature and prognostic nomogram to predict the prognosis of patients with non-distant metastatic OTSCC. METHODS: OTSCC-related differentially-expressed genes were screened from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression based on 1,000 bootstrap replicates, LASSO regression and stepwise multivariate Cox regression were utilized to develop a novel multi-mRNA signature for predicting overall survival in OTSCC. The concordance index, area under receiver operating characteristic (ROC AUC) and calibration curve were employed to assess the prediction capacity of the novel multi-gene model. In addition, a prognostic nomogram was constructed to facilitate the clinical use of the fitted model. The Kaplan-Meier with log-rank test was employed to assess differences in overall survival. RESULTS: We successfully established a novel 15-mRNA prognostic model for predicting overall survival of non-distant metastatic OTSCC, involving ADTRP, ITGA3, RFC4, CCDC96, CYP2J2, NELL2, SPHK1, SPAG16, HBEGF, S100A9, EGFL6, ADGRG6, PDE4D, ABCA4, and CTTN. The prediction ability of this 15-gene signature was independent of other clinicopathological factors, with an HR of 11.5 (95% CI: 4.70-28.3). Moreover, internal validation by bootstrap analysis yielded a C-index of 0.849, with a 3-year AUC of 0.907 and 5-year AUC of 0.944, which implied excellent prediction accuracy of the fitted model. In addition, external validation by using the GEO dataset (GSE41116) yielded a C-index of 0.804, with a 3-year AUC of 0.868 and 5-year AUC of 0.855, which also indicated good prediction ability of the 15-gene model. Finally, a prognostic nomogram integrating risk group, grade, T stage and N stage was established. CONCLUSION: Our results demonstrate our 15-gene signature was independently associated with overall survival in non-distant metastatic OTSCC. Moreover, the prognostic nomogram integrating the 15-gene signature and clinicopathological factors has potential to be developed as a prognostic tool.
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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 author.
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sections[17] "Data Availability Statement" paragraph 2
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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 author.
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Integrative genomic characterization of oral squamous cell carcinoma identifies frequent somatic drivers (mRNA)
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Clinicopathological characteristics of the patients included in the training set and validating set.
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Clinical Characteristics of Oral Tongue Squamous Cell Carcinoma Patient Cohorts in The Cancer Genome Atlas and GEO
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Clinicopathological characteristics of the patients included in the training set and validating set.
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Forty-one significantly differentially-expressed cancer-related genes selected by univariate Cox regression analysis.
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Univariate Cox Regression Based on 1,000 Bootstrap Replicates
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Table 2
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Forty-one significantly differentially-expressed cancer-related genes selected by univariate Cox regression analysis.
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15-gene signature selected by stepwise multivariate Cox regression.
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PMC7985252
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Establishment of a 15-Gene Signature by Least Absolute Shrinkage and Selection Operator Regression and Stepwise Multivariate Cox Hazard Ratio Regression Modeling
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Table 3
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15-gene signature selected by stepwise multivariate Cox regression.
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<0.001
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0.01
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2017
[3]
2.47 (1.15–5.29)
[4]
0.02
[6] array · 5 items
[0]
HBEGF
[1]
Heparin Binding EGF Like Growth Factor
[2]
1839
[3]
2.39 (1.20–4.78)
[4]
0.013
[7] array · 5 items
[0]
S100A9
[1]
S100 Calcium Binding Protein A9
[2]
6280
[3]
0.49 (0.23–1.04)
[4]
0.064
[8] array · 5 items
[0]
ADTRP
[1]
Androgen Dependent TFPI Regulating Protein
[2]
84830
[3]
2.15 (1.06–4.35)
[4]
0.034
[9] array · 5 items
[0]
CYP2J2
[1]
Cytochrome P450 Family 2 Subfamily J Member 2
[2]
1573
[3]
0.43 (0.21–0.87)
[4]
0.019
[10] array · 5 items
[0]
RFC4
[1]
Replication Factor C Subunit 4
[2]
5984
[3]
2.16 (1.07–4.36)
[4]
0.032
[11] array · 5 items
[0]
SPAG16
[1]
Sperm Associated Antigen 16
[2]
79582
[3]
0.46 (0.24–0.90)
[4]
0.023
[12] array · 5 items
[0]
SPHK1
[1]
Sphingosine Kinase 1
[2]
8877
[3]
0.50 (0.25–1.01)
[4]
0.055
[13] array · 5 items
[0]
ABCA4
[1]
ATP Binding Cassette Subfamily A Member 4
[2]
24
[3]
0.48 (0.25–0.92)
[4]
0.028
[14] array · 5 items
[0]
EGFL6
[1]
EGF Like Domain Multiple 6
[2]
25975
[3]
0.57 (0.30–1.08)
[4]
0.085
[15] array · 5 items
[0]
ITGA3
[1]
Integrin Subunit Alpha 3
[2]
3675
[3]
1.93 (1.00–3.70)
[4]
0.049
locator
section[11]/table-wrap[1]#T3
gaps array · 2 items
[0]
asset:data:geo:GSE41116 not downloaded
[1]
asset:data:geo:GSE41116 licence not read
analysis object · 4 fields
state
complete
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
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
0.7
band
medium
quote
Cox regression
[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
0.7
band
medium
quote
log-rank
[3] object · 10 fields
id
method-4
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]
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 · 1 item
[0]
GSE41116
resolved_accessions array · 1 item
[0]
GSE41116
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 author.
basis
The paper names GSE41116 in GEO database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
[0]
survival_km
assets array · 5 items
[0]
source:pmid:33767977
[1]
data:geo:GSE41116
[2]
asset:table:pmid:33767977:1
[3]
asset:table:pmid:33767977:2
[4]
asset:table:pmid:33767977:3
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:GSE41116
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
2026-10-31T19:29:18Z
independence
single_reader
evidence_check object · 2 fields
method
absent
availability
verbatim
calls
3
usage object · 3 fields
prompt_tokens
25004
completion_tokens
1755
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:33767977
type
paper
label
pmid:33767977
[1] object · 3 fields
id
source:pmid:33767977
type
manuscript
label
PMID 33767977 full text
[2] object · 3 fields
id
data:geo:GSE41116
type
dataset
label
GEO GSE41116
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:33767977
type
paper
label
pmid:33767977
[1] object · 3 fields
id
source:pmid:33767977
type
manuscript
label
PMID 33767977 full text
[2] object · 3 fields
id
data:geo:GSE41116
type
dataset
label
GEO GSE41116
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-33767977
type
extraction
used array · 1 item
[0]
source:pmid:33767977
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE41116
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE41116
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:33767977
parent_hash
sha256:9708982bb4b2886e28c9f225979bf17b74a62cb8f442d1bd4337a08cd2f274e8
fork_of
null
gaps array · 6 items
[0]
asset:data:geo:GSE41116 licence not read
[1]
asset:data:geo:GSE41116 not downloaded
[2]
execution.not_run
[3]
review.human_critique
[4]
review.independent_reader
[5]
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assays array · 2 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
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0.93
evidence array · 1 item
[0]
nd GEO For the training cohort, clinical and RNA sequencing data of 13 normal tongue tissues and 127 OTS
order_basis
paper_text_order:3664
id
assay:1
[1] object · 11 fields
role
analysis
definition_id
survival_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
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survival_km
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
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Kaplan-Meier
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assay:2
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33767977", "kind": "science-record", "revision": 7, "content_hash": "sha256:966a2d6520f93e848192d519501f379f15228d88669cc727dc4aa2500e498c90", "created_at": "2026-11-01T15:41:30Z", "updated_at": "2026-11-01T22:03:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A 15-Gene Signature and Prognostic Nomogram for Predicting Overall Survival in Non-Distant Metastatic Oral Tongue Squamous Cell Carcinoma.", "doi": "10.3389/fonc.2021.587548", "pmid": "33767977", "authors": ["Muyuan Liu", "Litian Tong", "Bin Liang", "Xuhong Song", "Lingzhu Xie", "Hanwei Peng", "Dongyang Huang"], "journal": "Frontiers in oncology", "year": 2021, "abstract": "BACKGROUND: Oral tongue squamous cell carcinoma (OTSCC) is a devastating tumor with poor prognosis. There is an urgent need for reliable biomarkers to help predict prognosis and guide treatment for OTSCC. In the current study, we aimed to develop a robust multi-gene signature and prognostic nomogram to predict the prognosis of patients with non-distant metastatic OTSCC.\nMETHODS: OTSCC-related differentially-expressed genes were screened from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression based on 1,000 bootstrap replicates, LASSO regression and stepwise multivariate Cox regression were utilized to develop a novel multi-mRNA signature for predicting overall survival in OTSCC. The concordance index, area under receiver operating characteristic (ROC AUC) and calibration curve were employed to assess the prediction capacity of the novel multi-gene model. In addition, a prognostic nomogram was constructed to facilitate the clinical use of the fitted model. The Kaplan-Meier with log-rank test was employed to assess differences in overall survival.\nRESULTS: We successfully established a novel 15-mRNA prognostic model for predicting overall survival of non-distant metastatic OTSCC, involving ADTRP, ITGA3, RFC4, CCDC96, CYP2J2, NELL2, SPHK1, SPAG16, HBEGF, S100A9, EGFL6, ADGRG6, PDE4D, ABCA4, and CTTN. The prediction ability of this 15-gene signature was independent of other clinicopathological factors, with an HR of 11.5 (95% CI: 4.70-28.3). Moreover, internal validation by bootstrap analysis yielded a C-index of 0.849, with a 3-year AUC of 0.907 and 5-year AUC of 0.944, which implied excellent prediction accuracy of the fitted model. In addition, external validation by using the GEO dataset (GSE41116) yielded a C-index of 0.804, with a 3-year AUC of 0.868 and 5-year AUC of 0.855, which also indicated good prediction ability of the 15-gene model. Finally, a prognostic nomogram integrating risk group, grade, T stage and N stage was established.\nCONCLUSION: Our results demonstrate our 15-gene signature was independently associated with overall survival in non-distant metastatic OTSCC. Moreover, the prognostic nomogram integrating the 15-gene signature and clinicopathological factors has potential to be developed as a prognostic tool.", "claims": [{"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33767977", "locator": "sections[17] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author."}], "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:33767977"], "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:GSE41116"], "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:GSE41116"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33767977", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2021.587548", "sha256": "sha256:b551d43206d25330cd9faa7f3410c828f874e1c8b1f7cbf210f7d7829a5f7145", "bytes": 32760, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2021.587548", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7985252", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE41116", "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=GSE41116", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE41116", "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 author.", "structure": {"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 author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1008824", "GSM1008825", "GSM1008826", "GSM1008827", "GSM1008828", "GSM1008829", "GSM1008830", "GSM1008831", "GSM1008832", "GSM1008833", "GSM1008834", "GSM1008835", "GSM1008836", "GSM1008837", "GSM1008838", "GSM1008839", "GSM1008840", "GSM1008841", "GSM1008842", "GSM1008843", "GSM1008844", "GSM1008845", "GSM1008846", "GSM1008847", "GSM1008848", "GSM1008849", "GSM1008850", "GSM1008851", "GSM1008852", "GSM1008853", "GSM1008854", "GSM1008855", "GSM1008856", "GSM1008857", "GSM1008858", "GSM1008859", "GSM1008860", "GSM1008861", "GSM1008862", "GSM1008863", "GSM1008864", "GSM1008865", "GSM1008866"], "sample_count": 43, "group_sizes": null, "group_sizes_basis": null, "platform": "5175", "taxon": "Homo sapiens", "title": "Integrative genomic characterization of oral squamous cell carcinoma identifies frequent somatic drivers (mRNA)", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:33767977:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:5803f2c3d18a07f19fa8def60b288966cd33552b2779e6466c1536967f8a2769", "bytes": 783, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[7]/table-wrap[1]#T1", "version": null, "note": "Clinicopathological characteristics of the patients included in the training set and validating set.", "structure": {"pmcid": "PMC7985252", "section_index": 7, "section_title": "Clinical Characteristics of Oral Tongue Squamous Cell Carcinoma Patient Cohorts in The Cancer Genome Atlas and GEO", "row_count": 15, "column_count": 3}, "table": {"label": "Table 1", "caption": "Clinicopathological characteristics of the patients included in the training set and validating set.", "rows": [["Clinicopathological parameters", "Training Set (TCGA dataset, n = 127)", "Validating Set (GEO dataset, n = 28)"], ["Sex", "", ""], ["Male", "83 (65.4%)", "18 (64.3%)"], ["Female", "44 (34.6%)", "10 (35.7%)"], ["Age", "57 (y, median)", "60 (y, median)"], ["T Stage", "", ""], ["T1-2", "67 (52.7%)", "6 (21.4%)"], ["T3-4", "60 (47.3%)", "22 (78.6%)"], ["N Stage", "", ""], ["N−", "57 (44.9%)", "9 (32.1%)"], ["N+", "70 (55.1%)", "19 (67.9%)"], ["Grade", "", ""], ["Well", "17 (13.4%)", "2 (7.1%)"], ["Moderate", "86 (67.7%)", "19 (67.9%)"], ["Poor", "24 (18.9%)", "7 (25.0%)"]], "row_count": 15, "column_count": 3, "numeric_cells": 24, "header_rows": 1, "locator": "section[7]/table-wrap[1]#T1"}}, {"id": "asset:table:pmid:33767977:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:f02aaca9b8873be53557caa6af7638817b02ce2c2490b90800d524cc6390ed2a", "bytes": 3002, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[1]#T2", "version": null, "note": "Forty-one significantly differentially-expressed cancer-related genes selected by univariate Cox regression analysis.", "structure": {"pmcid": "PMC7985252", "section_index": 10, "section_title": "Univariate Cox Regression Based on 1,000 Bootstrap Replicates", "row_count": 43, "column_count": 6}, "table": {"label": "Table 2", "caption": "Forty-one significantly differentially-expressed cancer-related genes selected by univariate Cox regression analysis.", "rows": [["Gene", "HR", "Perc", "BCa"], ["95% CI_lower", "95% CI_upper", "95% CI_lower", "95% CI_upper"], ["KLF7", "2.051967", "1.181178", "4.013881", "1.169583", "4.006894"], ["TPTEP1", "0.489758", "0.254359", "0.833391", "0.282388", "0.892341"], ["ADTRP", "2.185642", "1.280026", "4.108594", "1.101236", "3.597496"], ["MAGIX", "0.395979", "0.196065", "0.691413", "0.211579", "0.735964"], ["ITGA3", "2.003327", "1.103321", "3.727782", "1.025672", "3.542512"], ["RFC4", "1.887744", "1.034734", "3.317223", "1.078374", "3.395053"], ["CCDC96", "0.430815", "0.241363", "0.775666", "0.24291", "0.776434"], ["SLC16A1", "2.302277", "1.254623", "4.446845", "1.143051", "3.997884"], ["BUB1", "1.883744", "1.068125", "3.44771", "1.082299", "3.56022"], ["ECT2", "2.064229", "1.193709", "3.845979", "1.167009", "3.664635"], ["MYO10", "1.872354", "1.074121", "3.459864", "1.077746", "3.487003"], ["STARD4", "1.97469", "1.129966", "3.52473", "1.120917", "3.502698"], ["ADAM8", "1.91557", "1.077973", "3.428193", "1.054494", "3.28236"], ["CYP2J2", "0.492253", "0.27153", "0.903332", "0.262146", "0.885367"], ["ANKRD6", "0.527813", "0.283685", "0.905571", "0.28838", "0.91253"], ["ZNF43", "0.418219", "0.215498", "0.759636", "0.227062", "0.774721"], ["NELL2", "1.942154", "1.131742", "3.661527", "1.131149", "3.648482"], ["HMMR", "2.0045", "1.141503", "3.624981", 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