ArticleGenes2023
Papillary Thyroid Carcinoma: A thorough Bioinformatic Analysis of Gene Expression and Clinical Data.
Article in Genes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Prognostic value and therapeutic potential of the cuproptosis-related gene LOXL2 in thyroid cancer.Translational oncology · 2026Article
- Identification of Potential Biomarkers and Drugs for Papillary Thyroid Carcinoma Using Computational Analysis and Molecular Docking.Current medicinal chemistry · 2026Article
- Article
- A computational approach to assessing the prognostic implications of BRAF and RAS mutations in patients with papillary thyroid carcinoma.Endocrine · 2024Article
- Optimizing hybrid ensemble feature selection strategies for transcriptomic biomarker discovery in complex diseases.NAR genomics and bioinformatics · 2024Article
- Comprehensive Profiling and Therapeutic Insights into Differentially Expressed Genes in Hepatocellular Carcinoma.Cancers · 2023Article
- Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The likelihood of being diagnosed with thyroid cancer has increased in recent years; it is the fastest-expanding cancer in the United States and it has tripled in the last three decades. In particular, Papillary Thyroid Carcinoma (PTC) is the most common type of cancer affecting the thyroid. It is a slow-growing cancer and, thus, it can usually be cured. However, given the worrying increase in the diagnosis of this type of cancer, the discovery of new genetic markers for accurate treatment and prognostic is crucial. In the present study, the aim is to identify putative genes that may be specifically relevant in PTC through bioinformatic analysis of several gene expression public datasets and clinical information. Two datasets from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) dataset were studied. Statistics and machine learning methods were sequentially employed to retrieve a final small cluster of genes of interest:
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What OpenQuestion holds
Registered trials
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.