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pmid:36406134

A panel of seven immune-related genes can serve as a good predictive biomarker for cervical squamous cell carcinoma.

Junshang Dai · Yuwen Pan · Yili Chen · Shuzhong Yao

Frontiers in genetics · 2022 doi:10.3389/fgene.2022.1024508

Paper

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Experiment

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Data

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title
A panel of seven immune-related genes can serve as a good predictive biomarker for cervical squamous cell carcinoma.
doi
10.3389/fgene.2022.1024508
pmid
36406134
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[0]
Junshang Dai
[1]
Yuwen Pan
[2]
Yili Chen
[3]
Shuzhong Yao
journal
Frontiers in genetics
year
2022
abstract
Objective: Cervical cancer is one of the most common gynecological malignancies. The interaction between tumor microenvironment and immune infiltration is closely related to the progression of cervical squamous cell carcinoma (CSCC) and patients' prognosis. Herein, a panel of immune-related genes was established for more accurate prognostic prediction. Methods: The transcriptome information of tumor and normal samples were obtained from TCGA-CSCC and GTEx. Differentially expressed genes (DEGs) were defined from it. Immune-related genes (IRGs) were retrieved from the ImmPort database. After removing the transcriptome data which not mentioned in GSE44001, IR-DEGs were preliminarily identified. Then, TCGA-CSCC samples were divided into training and testing set (3:1) randomly. Univariate Cox analysis, LASSO regression analysis and multivariate Cox analysis were used in turn to construct the signature to predict the overall survival (OS) and disease-free survival (DFS). External validation was performed in GSE44001, and initial clinical validation was performed by qRT-PCR. Function enrichment analysis, immune infiltration analysis and establishment of nomogram were conducted as well. Results: A prognostic prediction signature consisting of seven IR-DEGs was established. High expression of NRP1, IGF2R, SERPINA3, TNF and low expression of ICOS, DES, HCK suggested that CSCC patients had shorter OS (POS<0.001) and DFS (PDFS<0.001). AUC values of 1-, 3-, five- year OS were 0.800, 0.831 and 0.809. Analyses in other validation sets showed good consistency with the results in training set. The signature can serve as an independent prognostic factor for OS (HR = 1.166, p < 0.001). AUC values of 1-, 3-, five- year OS based on the nomogram were 0.769, 0.820 and 0.807. Functional enrichment analysis suggested that these IR-DEGs were associated with receptor interaction and immune cell activity. Immune infiltration analysis indicated that patients in high-risk group had lower immune infiltration, weaker immune function, and were more likely to benefit from immune checkpoint inhibitor therapy. Through qRT-PCR on clinical samples, expression of NRP1, IGF2R, SERPINA3 and TNF were significantly upregulated in tumor tissue, while ICOS and DES were significantly downregulated. Conclusion: To conclude, the immune-related signature can provide strong support for exploration of immune infiltration, prediction of prognosis and response to immunotherapy through stratify CSCC patients into subgroups.
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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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The study established a seven-gene immune-related prognostic signature with 1-, 3-, and 5-year overall-survival AUC values of 0.800, 0.831, and 0.809.
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A prognostic prediction signature consisting of seven IR-DEGs was established.
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AUC values of 1-, 3-, five- year OS were 0.800, 0.831 and 0.809.
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The study established a seven-gene immune-related prognostic signature with 1-, 3-, and 5-year overall-survival AUC values of 0.800, 0.831, and 0.809.
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[1]
asset:data:geo:GSE44001 licence not read
[2]
asset:data:geo:GSE63514 not downloaded
[3]
asset:data:geo:GSE63514 licence not read
analysis object · 4 fields
state
partial
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missing_operations array · 1 item
[0]
group_comparison_wilcoxon
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data_shapes array · 1 item
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two_or_more_groups_continuous
evidence object · 3 fields
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0.8
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quote
Wilcoxon
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method-2
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group_comparison
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anova
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Group comparison
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[0]
group_summary
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welch_t
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[3]
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two_or_more_groups_continuous
evidence object · 3 fields
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0.8
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method-3
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survival_analysis
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kaplan_meier
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Survival analysis
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[0]
survival_km
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data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
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Kaplan-Meier
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method-4
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survival_analysis
specific
cox_proportional_hazards
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Survival analysis
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[0]
cox_ph
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[0]
time_to_event_with_censoring
evidence object · 3 fields
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0.8
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id
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survival_analysis
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log_rank_test
label
Survival analysis
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[0]
logrank_test
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[0]
time_to_event_with_censoring
evidence object · 3 fields
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method.group_comparison_wilcoxon
capability object · 3 fields
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complete
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capability_id
capability:computational_analysis
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Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
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survival_analysis
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statistical_regression
[4]
pca
[5]
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[6]
network_analysis
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[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
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[0]
group_comparison_wilcoxon
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon.
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
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accessions array · 2 items
[0]
GSE44001
[1]
GSE63514
resolved_accessions array · 2 items
[0]
GSE44001
[1]
GSE63514
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 GSE44001, GSE63514 in GEO database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
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assets array · 2 items
[0]
source:pmid:36406134
[1]
data:geo:GSE44001
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group_comparison_wilcoxon
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null
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data:geo:GSE44001
gaps array · 0 items
review object · 5 fields
state
partial
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kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
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minimax
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minimax
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2026-11-01T18:16:23Z
independence
single_reader
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null
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21444
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extraction
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MiniMax-M3.1-Flash
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[1]
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[2]
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pmid:36406134
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paper
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pmid:36406134
[1] object · 3 fields
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source:pmid:36406134
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manuscript
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PMID 36406134 full text
[2] object · 3 fields
id
data:geo:GSE44001
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dataset
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GEO GSE44001
activities array · 3 items
[0] object · 4 fields
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activity-reading-sci-2026-11-01
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classification
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paper
label
pmid:36406134
[1] object · 3 fields
id
source:pmid:36406134
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manuscript
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PMID 36406134 full text
[2] object · 3 fields
id
data:geo:GSE44001
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dataset
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GEO GSE44001
agent
agent:corpus-assay-engine
[1] object · 4 fields
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activity-read-36406134
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extraction
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[0]
source:pmid:36406134
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agent:minimax-reader
[2] object · 4 fields
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activity-resolve-GSE44001
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accession_resolution
used array · 1 item
[0]
data:geo:GSE44001
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agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
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agent:corpus-assay-engine
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Corpus assay engine
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agent:minimax-reader
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MiniMax literature reader
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dsl_catalogue_fingerprint
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capability_table_fingerprint
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lineage object · 4 fields
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null
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[0]
asset:data:geo:GSE44001 licence not read
[1]
asset:data:geo:GSE44001 not downloaded
[2]
asset:data:geo:GSE63514 licence not read
[3]
asset:data:geo:GSE63514 not downloaded
[4]
execution.not_run
[5]
method.group_comparison_wilcoxon
[6]
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assays array · 2 items
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assay_lexicon
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evidence array · 1 item
[0]
of 253 CSCC patients were downloaded. Then, patients were randomly assigned to the training set (n = 190) and the testin
order_basis
paper_text_order:3664
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[1] object · 11 fields
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f2132e96ae6c7a4e
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36406134", "kind": "science-record", "revision": 3, "content_hash": "sha256:d26cd3619e583fbecf9026c82ccb95a335a2d863cec49877b0cb35b183367392", "created_at": "2026-11-01T19:00:52Z", "updated_at": "2026-11-01T22:08:07Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A panel of seven immune-related genes can serve as a good predictive biomarker for cervical squamous cell carcinoma.", "doi": "10.3389/fgene.2022.1024508", "pmid": "36406134", "authors": ["Junshang Dai", "Yuwen Pan", "Yili Chen", "Shuzhong Yao"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Objective: Cervical cancer is one of the most common gynecological malignancies. The interaction between tumor microenvironment and immune infiltration is closely related to the progression of cervical squamous cell carcinoma (CSCC) and patients' prognosis. Herein, a panel of immune-related genes was established for more accurate prognostic prediction. Methods: The transcriptome information of tumor and normal samples were obtained from TCGA-CSCC and GTEx. Differentially expressed genes (DEGs) were defined from it. Immune-related genes (IRGs) were retrieved from the ImmPort database. After removing the transcriptome data which not mentioned in GSE44001, IR-DEGs were preliminarily identified. Then, TCGA-CSCC samples were divided into training and testing set (3:1) randomly. Univariate Cox analysis, LASSO regression analysis and multivariate Cox analysis were used in turn to construct the signature to predict the overall survival (OS) and disease-free survival (DFS). External validation was performed in GSE44001, and initial clinical validation was performed by qRT-PCR. Function enrichment analysis, immune infiltration analysis and establishment of nomogram were conducted as well. Results: A prognostic prediction signature consisting of seven IR-DEGs was established. High expression of NRP1, IGF2R, SERPINA3, TNF and low expression of ICOS, DES, HCK suggested that CSCC patients had shorter OS (POS<0.001) and DFS (PDFS<0.001). AUC values of 1-, 3-, five- year OS were 0.800, 0.831 and 0.809. Analyses in other validation sets showed good consistency with the results in training set. The signature can serve as an independent prognostic factor for OS (HR = 1.166, p < 0.001). AUC values of 1-, 3-, five- year OS based on the nomogram were 0.769, 0.820 and 0.807. Functional enrichment analysis suggested that these IR-DEGs were associated with receptor interaction and immune cell activity. Immune infiltration analysis indicated that patients in high-risk group had lower immune infiltration, weaker immune function, and were more likely to benefit from immune checkpoint inhibitor therapy. Through qRT-PCR on clinical samples, expression of NRP1, IGF2R, SERPINA3 and TNF were significantly upregulated in tumor tissue, while ICOS and DES were significantly downregulated. Conclusion: To conclude, the immune-related signature can provide strong support for exploration of immune infiltration, prediction of prognosis and response to immunotherapy through stratify CSCC patients into subgroups.", "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:36406134", "locator": "sections[28] \"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"}, {"id": "claim-target-result", "statement": "The study established a seven-gene immune-related prognostic signature with 1-, 3-, and 5-year overall-survival AUC values of 0.800, 0.831, and 0.809.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36406134", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A prognostic prediction signature consisting of seven IR-DEGs was established."}, {"asset": "source:pmid:36406134", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "AUC values of 1-, 3-, five- year OS were 0.800, 0.831 and 0.809."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The study established a seven-gene immune-related prognostic signature with 1-, 3-, and 5-year overall-survival AUC values of 0.800, 0.831, and 0.809.", "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:36406134"], "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:GSE44001"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "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:GSE44001"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36406134", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": 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