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pmid:31583243

Identification and Validation of Core Genes Involved in the Development of Papillary Thyroid Carcinoma via Bioinformatics Analysis.

Xiaoyan Li · Jing He · Mingxia Zhou · Yun Cao · Yiting Jin · Qiang Zou

International journal of genomics · 2019 doi:10.1155/2019/5894926

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

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:31583243
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science-record
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created_at
2026-11-01T15:40:50Z
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2026-11-01T22:00:53Z
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paper object · 10 fields
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title
Identification and Validation of Core Genes Involved in the Development of Papillary Thyroid Carcinoma via Bioinformatics Analysis.
doi
10.1155/2019/5894926
pmid
31583243
authors array · 6 items
[0]
Xiaoyan Li
[1]
Jing He
[2]
Mingxia Zhou
[3]
Yun Cao
[4]
Yiting Jin
[5]
Qiang Zou
journal
International journal of genomics
year
2019
abstract
BACKGROUND: Papillary thyroid carcinoma (PTC) is a common endocrine malignant neoplasm, and its incidence increases continuously worldwide in the recent years. However, efficient clinical biomarkers were still deficient; the present research is aimed at exploring significant core genes of PTC. METHODS: We integrated three cohorts to identify hub genes and pathways associated with PTC by comprehensive bioinformatics analysis. Expression profiles GSE33630, GSE35570, and GSE60542, including 114 PTC tissues and 126 normal tissues, were enrolled in this research. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to search for the crucial biological behaviors and pathways involved in PTC carcinogenesis. Protein-protein interaction (PPI) network was constructed, and significant modules were deeply studied. RESULTS: A total of 831 differentially expressed genes (DEGs) were discovered, comprising 410 upregulated and 421 downregulated genes in PTC tissues compared to normal thyroid tissues. PPI network analysis demonstrated the interactions between those DEGs, and top 10 pivotal genes (TGFB1, CXCL8, LRRK2, CD44, CCND1, JUN, DCN, BCL2, ACACB, and CXCL12) with highest degree of connectivity were extracted from the network and verified by TCGA dataset and RT-PCR experiment of PTC samples. Four of the hub genes (CXCL8, DCN, BCL2, and ACACB) were linked to the prognosis of PTC patients and considered as clinically relevant core genes via survival analysis. CONCLUSION: In conclusion, we propose a series of key genes associated with PTC development and these genes could serve as the diagnostic biomarkers or therapeutic targets in the future treatment for PTC.
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The expression of related genes was presented as mean ± SD and analyzed using the paired t-test.
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sections[9] "2.7. Statistical Analysis" paragraph 2
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The expression of related genes was presented as mean ± SD and analyzed using the paired t-test.
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The data used to support the findings of this study are included within the article.
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Normal thyrocytes vs papillary vs anaplastic thyroid carcinomas
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2026-11-01T15:39:54Z
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116
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Homo sapiens
title
Gene signature of the post-Chernobyl papillary thyroid cancer
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31583243", "kind": "science-record", "revision": 4, "content_hash": "sha256:b1dc1cb971b89b34e2d22fa458c83ca016ea0d023689c23373871c2bf6d9409e", "created_at": "2026-11-01T15:40:50Z", "updated_at": "2026-11-01T22:00:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Core Genes Involved in the Development of Papillary Thyroid Carcinoma via Bioinformatics Analysis.", "doi": "10.1155/2019/5894926", "pmid": "31583243", "authors": ["Xiaoyan Li", "Jing He", "Mingxia Zhou", "Yun Cao", "Yiting Jin", "Qiang Zou"], "journal": "International journal of genomics", "year": 2019, "abstract": "BACKGROUND: Papillary thyroid carcinoma (PTC) is a common endocrine malignant neoplasm, and its incidence increases continuously worldwide in the recent years. However, efficient clinical biomarkers were still deficient; the present research is aimed at exploring significant core genes of PTC.\nMETHODS: We integrated three cohorts to identify hub genes and pathways associated with PTC by comprehensive bioinformatics analysis. Expression profiles GSE33630, GSE35570, and GSE60542, including 114 PTC tissues and 126 normal tissues, were enrolled in this research. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to search for the crucial biological behaviors and pathways involved in PTC carcinogenesis. Protein-protein interaction (PPI) network was constructed, and significant modules were deeply studied.\nRESULTS: A total of 831 differentially expressed genes (DEGs) were discovered, comprising 410 upregulated and 421 downregulated genes in PTC tissues compared to normal thyroid tissues. PPI network analysis demonstrated the interactions between those DEGs, and top 10 pivotal genes (TGFB1, CXCL8, LRRK2, CD44, CCND1, JUN, DCN, BCL2, ACACB, and CXCL12) with highest degree of connectivity were extracted from the network and verified by TCGA dataset and RT-PCR experiment of PTC samples. Four of the hub genes (CXCL8, DCN, BCL2, and ACACB) were linked to the prognosis of PTC patients and considered as clinically relevant core genes via survival analysis.\nCONCLUSION: In conclusion, we propose a series of key genes associated with PTC development and these genes could serve as the diagnostic biomarkers or therapeutic targets in the future treatment for PTC.", "claims": [{"id": "claim-method", "statement": "The expression of related genes was presented as mean ± SD and analyzed using the paired t-test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31583243", "locator": "sections[9] \"2.7. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE33630"], "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:GSE33630"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:31583243", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2019/5894926", "sha256": 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