Evidence map›Paper›PMID 40350533›Full record

ArticleJournal of the Egyptian National Cancer Institute2025

Integrative bioinformatic analysis identifies differentially expressed gene targets as potential biomarkers for anaplastic thyroid cancer.

Angel Sebastian Treviño-Juarez, Jose Gerardo Gonzalez-Gonzalez, Rene Rodriguez-Gutierrez, Adriana Sanchez-Garcia, Camilo Daniel Gonzalez-Velazquez

Abstract read
In one paragraph

Article in Journal of the Egyptian National Cancer Institute, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Oncology research · 2026
    Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Angel Sebastian Treviño-JuarezEndocrinology Division, Department of Internal Medicine, University Hospital "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, México. sebastiantrevj@gmail.com.ORCID http://orcid.org/0000-0001-6366-307X
Jose Gerardo Gonzalez-GonzalezEndocrinology Division, Department of Internal Medicine, University Hospital "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, México.
Rene Rodriguez-GutierrezEndocrinology Division, Department of Internal Medicine, University Hospital "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, México.
Adriana Sanchez-GarciaEndocrinology Division, Department of Internal Medicine, University Hospital "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, México.
Camilo Daniel Gonzalez-VelazquezEndocrinology Division, Department of Internal Medicine, University Hospital "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, México.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnaplastic thyroid carcinoma (ATC) is among the most lethal thyroid malignancies, with poor clinical outcomes and limited treatment strategies. To gain insights into the molecular mechanisms involved in its progression, we performed an integrative bioinformatic analysis.

methodsWe analyzed five microarray datasets from the GEO database to compare gene expression profiles between ATC samples and normal thyroid tissues. Differentially expressed genes (DEGs) were identified using GEO2R, and overlapping genes across datasets were detected through Venn diagram analysis. Functional enrichment was performed using DAVID and Metascape. A protein-protein interaction (PPI) network was constructed with STRING, and significant gene modules were identified using the MCODE plugin in Cytoscape. Co-expression analysis was further explored with GeneMANIA.

resultsWe identified 7532 DEGs, of which 3509 were upregulated and 4023 were downregulated. Upregulated genes were mainly involved in cell division and mitotic control, while downregulated genes were related to thyroid hormone production and gland development. Six hub genes stood out for their centrality in the network: TPX2, MAD2L1, CDC20, CDKN3, CENPF, and NEK2.

conclusionOur findings shed light on key genes and pathways that may contribute to ATC pathogenesis. These results provide a foundation for identifying potential diagnostic biomarkers and therapeutic targets for this aggressive cancer.

Indexed as

Biomarkers, TumorComputational BiologyGene Expression Regulation, NeoplasticThyroid Carcinoma, AnaplasticThyroid NeoplasmsDatabases, GeneticGene Expression ProfilingGene Regulatory NetworksHumansProtein Interaction MapsTranscriptomeBiomarkers, TumorAnaplastic thyroid cancerBioinformatics analysisBiomarkersCell divisionDifferentially expressed genes

Identifiers

PMID40350533
PMCPMC13313391

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.