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pmid:32457603

Identification of Prognostic miRNA Signature and Lymph Node Metastasis-Related Key Genes in Cervical Cancer.

Shuoling Chen · Chang Gao · Yangyuan Wu · Zunnan Huang

Frontiers in pharmacology · 2020 doi:10.3389/fphar.2020.00544

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Experiment

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Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:32457603
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2026-11-01T15:41:02Z
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title
Identification of Prognostic miRNA Signature and Lymph Node Metastasis-Related Key Genes in Cervical Cancer.
doi
10.3389/fphar.2020.00544
pmid
32457603
authors array · 4 items
[0]
Shuoling Chen
[1]
Chang Gao
[2]
Yangyuan Wu
[3]
Zunnan Huang
journal
Frontiers in pharmacology
year
2020
abstract
BACKGROUND: miRNAs and genes can serve as biomarkers for the prognosis and therapy of cervical tumors whose metastasis into lymph nodes is closely associated with disease progression and poor prognosis. METHODS: R software and Bioconductor packages were employed to identify differentially expressed miRNAs (DEMs) from The Cancer Genome Atlas (TCGA) database. GEO2R detected differentially expressed genes (DEGs) in the GSE7410 dataset originating from the Gene Expression Omnibus (GEO). A Cox proportional hazard regression model was established to select prognostic miRNA biomarkers. Online tools such as TargetScan and miRDB predicted target genes, and overlapping DEGs and target genes were defined as consensus genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) function annotations were performed to discern the potential functions of consensus genes. STRING and Cytoscape screened key genes and constructed a regulatory network. RESULTS: A combination of four miRNAs (down-regulated miR-502 and miR-145, up-regulated miR-142 and miR-33b) was identified as an independent prognostic signature of cervical cancer. A total of 94 consensus genes were significantly enriched in 7 KEGG pathways and 19 GO function annotations including the cAMP signaling pathway, the plasma membrane, integral components of the plasma membrane, cell adhesion, etc. The module analysis suggested that CXCL12, IGF1, PTPRC CDH5, RAD51B, REV3L, and WDHD1 are key genes that significantly correlate with cervical cancer lymph node metastasis. CONCLUSIONS: This study demonstrates that a four-miRNA signature can be a prognostic biomarker, and seven key genes are significantly associated with lymph node metastasis in cervical cancer patients. These miRNAs and key genes have the potential to be therapeutic targets for cervical cancer. Among them, two miRNAs (miR-502 and miR-33b) and two key genes (PTPRC and CDH5) were first reported to be potential novel biomarkers for cervical cancer. The current study further characterizes the progression of lymph node metastasis and mechanism of cervical tumors; therefore, it provides a novel diagnostic indicator and therapeutic targets for future clinical treatments.
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The Cox proportional hazard regression model (George et al., 2014) was established to analyze the association between DEMs and overall survival.
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Publicly available datasets were analyzed in this study. These data can be found here: https://portal.gdc.cancer.gov/, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7410.
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sections[21] "Data Availability Statement" paragraph 2
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Publicly available datasets were analyzed in this study. These data can be found here: https://portal.gdc.cancer.gov/, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7410.
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Univariate analysis of cervical cancer patients.
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miRNA-Based Signature Identification as a Prognostic Biomarker
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Univariate analysis of cervical cancer patients.
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miRNA-Based Signature Identification as a Prognostic Biomarker
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Multivariate analysis of cervical cancer patients.
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Consensus genes of four prognostic miRNAs discovered in the overlap between predicted target genes and DEGs related to cervical cancer lymph node metastasis.
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The expression of key genes reported from previous experimental studies.
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agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-32457603
type
extraction
used array · 1 item
[0]
source:pmid:32457603
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-None
type
accession_resolution
used array · 1 item
[0]
data:geo:None
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:32457603
parent_hash
sha256:1ead5b1358282583097abffde65e53da73572f3814f955d7d366c4a670651f07
fork_of
null
gaps array · 6 items
[0]
execution.not_run
[1]
method.reader_named_unmapped
[2]
review.human_critique
[3]
review.independent_reader
[4]
review.machine_critique
[5]
step:obtain_source_data blocked on data:accession_absent
assays array · 1 item
[0] object · 11 fields
role
analysis
definition_id
network_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
PPI
order_basis
analysis_only
id
assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32457603", "kind": "science-record", "revision": 7, "content_hash": "sha256:d1ca0d197e1604e7c824e05c4f795aaaf3ea4f26dfd115ec80dcb5ccff709202", "created_at": "2026-11-01T15:41:02Z", "updated_at": "2026-11-01T22:01:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Prognostic miRNA Signature and Lymph Node Metastasis-Related Key Genes in Cervical Cancer.", "doi": "10.3389/fphar.2020.00544", "pmid": "32457603", "authors": ["Shuoling Chen", "Chang Gao", "Yangyuan Wu", "Zunnan Huang"], "journal": "Frontiers in pharmacology", "year": 2020, "abstract": "BACKGROUND: miRNAs and genes can serve as biomarkers for the prognosis and therapy of cervical tumors whose metastasis into lymph nodes is closely associated with disease progression and poor prognosis.\nMETHODS: R software and Bioconductor packages were employed to identify differentially expressed miRNAs (DEMs) from The Cancer Genome Atlas (TCGA) database. GEO2R detected differentially expressed genes (DEGs) in the GSE7410 dataset originating from the Gene Expression Omnibus (GEO). A Cox proportional hazard regression model was established to select prognostic miRNA biomarkers. Online tools such as TargetScan and miRDB predicted target genes, and overlapping DEGs and target genes were defined as consensus genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) function annotations were performed to discern the potential functions of consensus genes. STRING and Cytoscape screened key genes and constructed a regulatory network.\nRESULTS: A combination of four miRNAs (down-regulated miR-502 and miR-145, up-regulated miR-142 and miR-33b) was identified as an independent prognostic signature of cervical cancer. A total of 94 consensus genes were significantly enriched in 7 KEGG pathways and 19 GO function annotations including the cAMP signaling pathway, the plasma membrane, integral components of the plasma membrane, cell adhesion, etc. The module analysis suggested that CXCL12, IGF1, PTPRC CDH5, RAD51B, REV3L, and WDHD1 are key genes that significantly correlate with cervical cancer lymph node metastasis.\nCONCLUSIONS: This study demonstrates that a four-miRNA signature can be a prognostic biomarker, and seven key genes are significantly associated with lymph node metastasis in cervical cancer patients. These miRNAs and key genes have the potential to be therapeutic targets for cervical cancer. Among them, two miRNAs (miR-502 and miR-33b) and two key genes (PTPRC and CDH5) were first reported to be potential novel biomarkers for cervical cancer. The current study further characterizes the progression of lymph node metastasis and mechanism of cervical tumors; therefore, it provides a novel diagnostic indicator and therapeutic targets for future clinical treatments.", "claims": [{"id": "claim-method", "statement": "The Cox proportional hazard regression model (George et al., 2014) was established to analyze the association between DEMs and overall survival.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32457603", "locator": "sections[4] \"Establishment of a Cox Proportional Hazard Regression Model\" paragraph 2", "quote": "The Cox proportional hazard regression model (George et al., 2014) was established to analyze the association between DEMs and overall survival."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. These data can be found here: https://portal.gdc.cancer.gov/, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7410.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32457603", "locator": "sections[21] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": [], "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": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32457603", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fphar.2020.00544", "sha256": 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["miR-504", "0.757023197", "−2.003615093", "0.045111308"], ["miR-99a", "0.879776376", "−1.986775064", "0.046947329"], ["miR-331", "0.691475709", "−1.965107538", "0.049401792"]], "row_count": 16, "column_count": 4, "numeric_cells": 60, "header_rows": 1, "locator": "section[13]/table-wrap[1]#T1"}}, {"id": "asset:table:pmid:32457603:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:4dc37578da29a561b5b4586712e78719ddc88253b45ab106eccd3f997817349c", "bytes": 476, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[13]/table-wrap[2]#T2", "version": null, "note": "Multivariate analysis of cervical cancer patients.", "structure": {"pmcid": "PMC7226536", "section_index": 13, "section_title": "miRNA-Based Signature Identification as a Prognostic Biomarker", "row_count": 5, "column_count": 6}, "table": {"label": "Table 2", "caption": "Multivariate analysis of cervical cancer patients.", "rows": [["", "Coef", "Exp (Coef)", "Se (Coef)", "z", "P"], ["miR-502", "−0.676", "0.509", "0.156", "−4.33", "1.50E-05"], ["miR-142", "−0.297", "0.743", "0.106", "−2.82", "0.0049"], ["miR-145", "−0.29", "0.748", "0.101", "−2.87", "0.0042"], ["miR-33b", "−0.209", "0.811", "0.101", "−2.07", "0.0382"]], "row_count": 5, "column_count": 6, "numeric_cells": 24, "header_rows": 1, "locator": "section[13]/table-wrap[2]#T2"}}, {"id": "asset:table:pmid:32457603:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:4217c9e89eb5f5367f6470c6e66435f6e14a3ec4b30cec8fe2b72bc0ed3a805f", "bytes": 1327, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#T3", "version": null, "note": "Consensus genes of four prognostic miRNAs discovered in the overlap between predicted target genes and DEGs related to cervical cancer lymph node metastasis.", "structure": {"pmcid": "PMC7226536", "section_index": 15, "section_title": "Target Gene Prediction for the Four Prognostic miRNAs", "row_count": 22, "column_count": 6}, "table": {"label": "Table 3", "caption": "Consensus genes of four prognostic miRNAs discovered in the overlap between predicted target genes and DEGs related to cervical cancer lymph node metastasis.", "rows": [["miRNA", "Consensus Genes"], ["miR-502", "ATP1A2", "DLGAP2", "FILIP1L", "C12orf54", "TLR6"], ["", "DAPK1", "DCLK1", "DONSON", "SLIT3", "WDHD1"], ["", "FBN2", "DCUN1D5", "CHST11", "SLC7A14", "LAMA3"], ["", "BCL7A", "CDH5", "ZNF471", "CNTN2", "PLXNA4"], ["", "COL10A1", "DOK6", "GLP1R", "PGM5", "SYNPO2"], ["", "EML6", "MLLT6", "ACSS3", "HS6ST2", "NUDT10"], ["", "RCC2", "PHOX2B", "SAMD4B", "", ""], ["miR-142", "GDNF", "ZFPM2", "TRIM36", "NBEA", "IGF1"], ["", "FOXO4", "FAM199X", "HDLBP", "TMTC1", "GK"], ["", "BNC2", "REV3L", "SLC2A13", "PDLIM5", "SP2"], ["", "TNRC18", "SACS", "ST6GALNAC3", "EGLN3", 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