ArticleTechnology in cancer research & treatment
The Integrated Analyses of Driver Genes Identify Key Biomarkers in Thyroid Cancer.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Identification of potential targetable genes in papillary, follicular, and anaplastic thyroid carcinoma using bioinformatics analysis.Endocrine · 2024Article
- ITGAL infers adverse prognosis and correlates with immunity in acute myeloid leukemia.Cancer cell international · 2022Article
- In silico Analysis of Publicly Available Transcriptomics Data Identifies Putative Prognostic and Therapeutic Molecular Targets for Papillary Thyroid Carcinoma.International journal of general medicine · 2022Article
- Integrative Analyses of Genes Associated with Hashimoto's Thyroiditis.Journal of immunology research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThyroid cancer is the most common endocrine cancer, the incidence rate has continuously increased worldwide. However, there are still lack of effective molecular biomarkers for the diagnosis and treatment of the disease. The study was conducted to identify driver genes that may serve as potential biomarkers for the disease.
methodsThe computational tools oncodriveCLUST, oncodriveFM, icages and drgap were used to detect driver genes in thyroid cancer using somatic mutations from The Cancer Genome Atlas database. Integrated analyses were performed on the driver genes using multiomics data from the TCGA database.
resultsA set of 291 driver genes were identified in thyroid cancer.
conclusionsThe set of cancer genes and subgroups of patients shed insight on the tumorigenesis of thyroid cancer and open up avenues for developing prognostic biomarkers and driver gene-targeted therapies in thyroid cancer.
Indexed as
Identifiers
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.