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MicroRNA-Based Risk Score for Predicting Tumor Progression Following Radioactive Iodine Ablation in
Eman A Toraih1,2, Manal S Fawzy3,4, Mohammad H Hussein1
1Department of Surgery, Tulane University School of Medicine, New Orleans, LA 70112, USA.
Cancers
|September 28, 2021
Summary
This study identified three microRNAs (miRNAs) that accurately predict aggressive behavior in differentiated thyroid cancer (DTC) patients. The new miRNA-based risk score significantly outperforms the ATA risk score in predicting tumor progression and survival.
Area of Science:
- Molecular Oncology
- Genomics
- Cancer Biomarkers
Background:
- Accurate prediction of aggressive tumor behavior in differentiated thyroid cancer (DTC) is crucial for surgical planning.
- Existing risk stratification models, such as the American Thyroid Association (ATA) risk score, may have limitations in predicting tumor progression.
Purpose of the Study:
- To identify novel molecular markers, specifically microRNAs (miRNAs), capable of predicting aggressive tumor behavior in DTC patients at the time of surgery.
- To develop and validate a miRNA-based risk score and nomogram for improved prognostic accuracy in DTC.
Main Methods:
- Propensity-score matching analysis of archived DTC specimens to create comparable patient cohorts.
- Quantification of bioinformatically selected miRNAs (miR-221-3p, miR-222-3p, miR-204-5p) using quantitative reverse transcription polymerase chain reaction (qRT-PCR).
- Development of a miRNA-based risk score using Cox regression, validated with ROC, C-statistic, Brier score, and external validation; Bayesian nomogram construction.
Main Results:
- Upregulation of miR-221-3p and miR-222-3p, and downregulation of miR-204-5p were observed in DTC tissues (p < 0.001).
- The miRNA-based risk score demonstrated high accuracy in predicting tumor progression (AUC = 0.944) and was superior to the ATA risk score (AUC = 0.518).
- Patients with a high miRNA risk score exhibited a three-fold increased risk of progression and significantly shorter survival times.
Conclusions:
- A prognostic signature of three miRNAs (miR-221-3p, miR-222-3p, miR-204-5p) can accurately predict tumor progression and survival in DTC.
- The developed miRNA-based risk score and Bayesian nomogram offer excellent predictive accuracy for progression-free survival, aiding clinical decision-making.
