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Thyroid Cancer Screening Using Tumor-Associated DN T Cells as Immunogenomic Markers.
Shahnawaz Imam1,2, Rodis D Paparodis1,2,3, Shafiya Imtiaz Rafiqi1,2
1Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States.
Frontiers in Oncology
|June 13, 2022
Summary
Double-negative T (DN T) cells in thyroid fine-needle aspiration (FNA) samples can predict thyroid cancer risk. High proportions of DN T cells indicate malignancy, offering a specific diagnostic signature to avoid unnecessary surgeries.
Area of Science:
- Immunology
- Oncology
- Endocrinology
Background:
- Thyroid nodules are common, but distinguishing malignant potential is challenging.
- Current methods for predicting malignancy lack specificity, leading to unnecessary surgeries.
- Thyroid cancer microenvironments show increased immune invasion, particularly by double-negative T (DN T) lymphocytes.
Purpose of the Study:
- To evaluate the proportion of DN T cells in fine-needle aspiration (FNA) samples as a predictor of thyroid cancer malignancy.
- To assess the diagnostic accuracy of DN T cell proportions in preoperative thyroid FNA samples.
Main Methods:
- Recruited 127 patients with thyroid nodules, collecting FNA samples.
- Analyzed 46 FNA samples from patients who underwent thyroidectomy using flow cytometry to quantify DN T cells (CD3+CD4-CD8-).
- Correlated DN T cell proportions with postoperative histological diagnoses.
Main Results:
- DN T cells were significantly more abundant in thyroid cancer cases than benign nodules (p < 0.0001).
- A threshold of 9.14% DN T cells predicted cancer with 96.6% sensitivity and 100% specificity for benign disease.
- A proportion below 9.14% was not found in any benign cases, indicating high specificity.
Conclusions:
- The proportion of DN T cells in FNA samples serves as a preoperative diagnostic signature for thyroid cancer.
- This method shows high specificity, potentially reducing false-positive diagnoses and unnecessary surgeries.
- Integration with RNA transcriptomics could lead to a simplified, PCR-based diagnostic assay.
