EP101 – A new highly sensitive and specific miRNA-profiling molecular diagnostic test for classification of thyroid nodules

     

    Gama, Ricardo Ribeiro²; Santos, Marcos Tadeu dos1; Buzolin, Ana Lígia¹; Barreto, Miguel³; Hall, Mathew³; Faustino, Pedro³; Dufloth, Rozany Mucha²; Silva, Eduardo Caetano Albino da²; Ventura, Luis Marcelo² and Carvalho, André Lopes²
    1 ONKOS Diagnósticos Moleculares Inc, Ribeirão Preto, SP, Brazil
    2 Hospital de Câncer de Barretos, Barretos, SP, Brazil
    3 SimplicityBio Inc, Monthey, Switzerland 

     

    Background/purpose: Thyroid nodules can be identified, by ultrasound, in up to 64% of the population [1]. Currently, fine-needle aspiration (FNA) represents the gold standard for the initial assessment of malignancy diagnosing. However, FNA cannot classify 15%-30% of nodules, known as indeterminate (Bethesda III, IV or V) [2], which are often referred for thyroidectomy due to the risk of malignancy. For this particular category the surgical pathology report reclassifies 70%-80% of cases as benign, highlighting the considerable rate of unnecessary surgeries [2-7]. Although clinically useful, current available molecular classifiers cannot offer both, high sensitivity and specificity, limiting its use and clinical application [8-11].

    Objectives: We sought to develop a miRNA-profiling-based molecular diagnostic test able to classify indeterminate thyroid nodules into benign or malignant, with high sensitivity and specificity.

    Methods: The expression of 96 miRNA was analyzed by qPCR from 80 FNA samples with indeterminate citology (final surgical pathology – 40 benign and 40 malignant). The cytology slides and pathology tissues were double-blinded revised by independent pathologists. Expression data was used for biomarkers selection and signatures generation for the molecular classifier development.

    Results: A molecular signature based on the expression of 18 miRNAs achieved 93% sensibility and 86% specificity to predict the final pathology report. The observed area under the curve (AUC) was 0.944.

    Discussion & Conclusion: We successfully developed a new miRNA-profiling-based molecular classifier with higher sensitive and specificity compared to commercially available tests. A multicenter clinical validation study using FNA smears slides as primary material for testing, is ongoing.

     

    References:

    1. Bohace K, Linda et al. Diagnostic Accuracy of Surgeon-Performed Ultrasound-Guided Fine-Needle Aspiration of Thyroid NodulesAnnals Of Surgical Oncology. 2011;19(1):45-51.
    2. Maia FFR, Zantut-Wittmann DE. Thyroid Nodule Management: Clinical, Ultrasound And Cytopathological Parameters For Predicting Malignancy. CLINICS. 2012;67(8):945-954.
    3. Eng CY, Quraishi MS, Bradley PJ. Management Of Thyroid Nodules In Adult Patients. Head & Neck Oncology. 2010;2(11):1-5.
    4. Hegedus L. Clinical Practice. The Thyroid Nodule. N Engl J Med. 2004; 351(17):1764-71.
    5. Tysome JR, Chandra A, Chang F, Puwanarajah P, Elliott M, Caroll P, et al. Improving Prediction Of Malignancy Of Cytologically Indeterminate Thyroid Nodules. Br J Surg. 2009;96(12):1400-5.
    6. Bartolazzi I, Gasbarri A, Papotti M, et al. Application Of An Immunodiagnostic Method For Improving Preoperative Diagnosis Of Nodular Thyroid Lesions. Lancet. 2001;357(9269):1644-50.
    7. Kim SW, In Lee J, Kim JW, Ki CS, Oh YL, Choi YL, et al. BRAFV600E Mutation Analysis In Fine-Needle Aspiration Cytology Specimens For Evaluation Of Thyroid Nodule: A Large Series In A BRAF V600E Prevalent Population. J Clin Endocrinol Metab. 2010;95(8):3693-700.
    8. Nikiforov YE, Ohori NP, Hodak SP, Et Al. Impact Of Mutational Testing On The Diagnosis And Management Of Patients With Cytologically Indeterminate Thyroid Nodules: A Prospective Analysis Of 1056 FNA Samples. J Clin Endocrinol Metab. 2011;96:3390-7.
    9. Milas M, Shin J, Gupta M, Novosel T, Nasr C, Brainard J, et al. A 2010 Circulating Thyrotropin Receptor mRNA As A Novel Marker Of Thyroid Cancer: Clinical Applications Learned From 1758 Samples. 2010 Ann Surg 252:253–263.
    10. Chudova D, Wilde JI, Wang ET, Wang H, et al. Molecular Classification Of Thyroid Nodules Using High-Dimensionality Genomic Data. J Clin Endocrinol Metab. 2010;95(12):5296-304.
    11. Beaudenon-Huibregtse S, Alexander EK, Guttler RB, et al. Centralized molecular testing for oncogenic gene mutations complements the local cytopathological diagnosis of thyroid nodules. Thyroid. 2014;24(10):1479-1487.

 

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