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pmid:38589421

Comprehensive bioinformatics analysis unveils THEMIS2 as a carcinogenic indicator related to immune infiltration and prognosis of thyroid cancer.

Jun-Feng Liu · Bing Zou · Cheng Xiang · Hai-Chao Yan

Scientific reports · 2024 doi:10.1038/s41598-024-58943-6

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:38589421
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science-record
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2026-11-01T19:20:33Z
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2026-11-01T22:11:37Z
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title
Comprehensive bioinformatics analysis unveils THEMIS2 as a carcinogenic indicator related to immune infiltration and prognosis of thyroid cancer.
doi
10.1038/s41598-024-58943-6
pmid
38589421
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[0]
Jun-Feng Liu
[1]
Bing Zou
[2]
Cheng Xiang
[3]
Hai-Chao Yan
journal
Scientific reports
year
2024
abstract
The aim of this study was to identify biomarkers associated with the initiation and prognosis of thyroid cancer and elucidate the underlying pathogenic mechanisms. We obtained expression profiles and clinical information from the Cancer Genome Atlas (TCGA)-THCA and three datasets (GSE53157, GSE82208, and GSE76039). The three microarray datasets were combined using Perl and the sva package in R and termed 'merged dataset'. Weighted gene co-expression network analysis (WGCNA) identified 15 gene co-expression modules in the merged dataset and 235 hub genes. Venn diagram analysis revealed 232 overlapping genes between the merged and THCA datasets. Overlapping genes were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The least absolute shrinkage and selection operator (LASSO) regression identified THEMIS2 as a candidate hub gene. Cox, Kaplan-Meier (K-M) survival and gene set enrichment analysis (GSEA) confirmed the correlation of THEMIS2 with overall survival, its enrichment in immunologic processes, and its association with the p53 and JAK-STAT signaling pathways. Its expression was positively correlated with those of immune checkpoints and the infiltration level of immune cells. Receiver operating characteristic curve (ROC) analysis confirmed that THEMIS2, a diagnostic biomarker, could distinguish between tumor and normal specimens. The nomogram (ROC or DCA) model containing THEMIS2, age, and stage predicted favourable prognoses. Thus, THEMIS2 was a biomarker of immune infiltration and prognosis in thyroid cancer.
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Both univariate and multivariate Cox regression analyses were performed to determine independent prognostic factors associated with OS.
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sections[14] "Assessment of THEMIS2 as a prognostic value for thyroid cancer" paragraph 2
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Both univariate and multivariate Cox regression analyses were performed to determine independent prognostic factors associated with OS.
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All data generated or analysed during this study are included in this supplementary information files.
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Finally, we defined THEMIS2 as a diagnostic biomarker of thyroid cancer because AUC exceeded 0.65 (AUC = 0.677; Fig. 5G).
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Finally, we defined THEMIS2 as a diagnostic biomarker of thyroid cancer because AUC exceeded 0.65 (AUC = 0.677; Fig. 5G).
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sections[23] "THEMIS2 is a reliable diagnostic biomarker" paragraph 2
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Finally, we defined THEMIS2 as a diagnostic biomarker of thyroid cancer because AUC exceeded 0.65 (AUC = 0.677; Fig. 5G).
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Finally, we defined THEMIS2 as a diagnostic biomarker of thyroid cancer because AUC exceeded 0.65 (AUC = 0.677; Fig. 5G).
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Gene expression profiling associated with the progression to poorly differentiated thyroid carcinomas
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Genomic and Transcriptomic Hallmarks of Poorly-Differentiated and Anaplastic Thyroid Cancers
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Gene expression markers differentiating between malignant and benign follicular thyroid tumors
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Complete file
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We obtained expression profiles and clinical information from the Cancer Genome Atlas (TCGA)-THCA and three datasets (GSE53157, GSE82208, and GSE76039). The three microarray datasets were combined using Perl and the sva package in R and termed 'merged dataset'. Weighted gene co-expression network analysis (WGCNA) identified 15 gene co-expression modules in the merged dataset and 235 hub genes. Venn diagram analysis revealed 232 overlapping genes between the merged and THCA datasets. Overlapping genes were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The least absolute shrinkage and selection operator (LASSO) regression identified THEMIS2 as a candidate hub gene. Cox, Kaplan-Meier (K-M) survival and gene set enrichment analysis (GSEA) confirmed the correlation of THEMIS2 with overall survival, its enrichment in immunologic processes, and its association with the p53 and JAK-STAT signaling pathways. Its expression was positively correlated with those of immune checkpoints and the infiltration level of immune cells. Receiver operating characteristic curve (ROC) analysis confirmed that THEMIS2, a diagnostic biomarker, could distinguish between tumor and normal specimens. The nomogram (ROC or DCA) model containing THEMIS2, age, and stage predicted favourable prognoses. Thus, THEMIS2 was a biomarker of immune infiltration and prognosis in thyroid cancer.", "claims": [{"id": "claim-method", "statement": "Both univariate and multivariate Cox regression analyses were performed to determine independent prognostic factors associated with OS.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38589421", "locator": "sections[14] \"Assessment of THEMIS2 as a prognostic value for thyroid cancer\" paragraph 2", "quote": "Both univariate and multivariate Cox regression analyses were performed to determine independent prognostic factors associated with OS."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data generated or analysed during this study are included in this supplementary information files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38589421", "locator": "sections[35] \"notes\" paragraph 1", "quote": "All data generated or analysed during this study are included in this supplementary information files."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Finally, we defined THEMIS2 as a diagnostic biomarker of thyroid cancer because AUC exceeded 0.65 (AUC = 0.677; Fig. 5G).", "kind": "quantitative", "target": {"value": 0.677, "unit": "auc", "tolerance": null, "source": "Finally, we defined THEMIS2 as a diagnostic biomarker of thyroid cancer because AUC exceeded 0.65 (AUC = 0.677; Fig. 5G)."}, "evidence": [{"asset": "source:pmid:38589421", "locator": "sections[23] \"THEMIS2 is a reliable diagnostic biomarker\" paragraph 2", "quote": "Finally, we defined THEMIS2 as a diagnostic biomarker of thyroid cancer because AUC exceeded 0.65 (AUC = 0.677; Fig. 5G)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Finally, we defined THEMIS2 as a diagnostic biomarker of thyroid cancer because AUC exceeded 0.65 (AUC = 0.677; Fig. 5G).", "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:38589421"], "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. 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