Does the 3-gene assay accurately distinguish benign from malignant thyroid neoplasms?
Department of Surgery, University of California at San Francisco, San Francisco, California 94143-1674, USA. Cancer
(Impact Factor: 4.89).
09/2008; 113(5):930-5. DOI: 10.1002/cncr.23703
A 3-gene (PCSK2, PLAB, CCND2) assay has been reported to have high accuracy for distinguishing benign from malignant thyroid tumors that are often indeterminate on fine-needle aspiration (FNA) biopsy. The aim of the current study was to determine the diagnostic accuracy of the 3-gene assay in thyroid tissue and in FNA biopsy for distinguishing benign from malignant thyroid neoplasms.
The messenger ribonucleic acid (mRNA) expression level of 3 genes (PCSK2, PLAB, CCND2) was analyzed by real-time quantitative reverse transcriptase-polymerase chain reaction in 261 frozen thyroid tissue samples (138 benign and 123 malignant), and prospectively, in 144 clinical thyroid FNA samples. To determine the diagnostic accuracy of the 3-gene assay, the area under the curve (AUC) of the receiver operating characteristic curve for each gene individually and in combination was determined.
PCSK2 and CCND2 mRNA expression levels were found to be significantly different between benign and malignant thyroid tissue samples (P < .0001 and P = .0007, respectively), but PLAB mRNA expression level was not (P = .099). In the thyroid tissue samples, the AUC was 0.67 for PCSK2 and 0.62 for CCND2. In the thyroid FNA samples, PCSK2 and CCND2 were significantly differentially expressed between benign and malignant samples (P = .039 and P = .023, respectively). The AUC was 0.59 for PCSK2 and 0.61 for CCND2.
Although PCSK2 and CCND2 were significantly differentially expressed between benign and malignant thyroid tumors both in tissue and in FNA samples, the diagnostic accuracy of the 3-gene assay was low. These findings demonstrate that it is essential for studies to validate the diagnostic accuracy and clinical utility of emerging candidate diagnostic thyroid cancer markers if they are to be translated into clinically useful markers for making patient care decisions.
Figures in this publication
Available from: Sara Tomei
- "Unfortunately, about 30% of FNAs are indeterminate and often require a diagnostic thyroidectomy to establish the diagnosis on permanent histological examination. Only 20% of diagnostic thyroidectomies in patients with indeterminate FNA cytology demonstrates malignant lesions on permanent histology, and these patients often require a completion thyroidectomy . "
[Show abstract] [Hide abstract]
Thyroid nodules with indeterminate cytological features on fine needle aspiration (FNA) cytology have a 20% risk of thyroid cancer. The aim of the current study was to determine the diagnostic utility of an 8-gene assay to distinguish benign from malignant thyroid neoplasm.
The mRNA expression level of 9 genes (KIT, SYNGR2, C21orf4, Hs.296031, DDI2, CDH1, LSM7, TC1, NATH) was analysed by quantitative PCR (q-PCR) in 93 FNA cytological samples. To evaluate the diagnostic utility of all the genes analysed, we assessed the area under the curve (AUC) for each gene individually and in combination. BRAF exon 15 status was determined by pyrosequencing. An 8-gene computational model (Neural Network Bayesian Classifier) was built and a multiple-variable analysis was then performed to assess the correlation between the markers.
The AUC for each significant marker ranged between 0.625 and 0.900, thus all the significant markers, alone and in combination, can be used to distinguish between malignant and benign FNA samples. The classifier made up of KIT, CDH1, LSM7, C21orf4, DDI2, TC1, Hs.296031 and BRAF had a predictive power of 88.8%. It proved to be useful for risk stratification of the most critical cytological group of the indeterminate lesions for which there is the greatest need of accurate diagnostic markers.
The genetic classification obtained with this model is highly accurate at differentiating malignant from benign thyroid lesions and might be a useful adjunct in the preoperative management of patients with thyroid nodules.
BMC Cancer 09/2012; 12(1):396. DOI:10.1186/1471-2407-12-396 · 3.36 Impact Factor
Available from: Marina A Guvakova
- "Weber et al. proposed that a combination of those three genes allowed the accurate molecular classification of FTC versus FTA with a high specificity and sensitivity. However, Shibru et al. were unable to confirm the diagnostic accuracy of the 3-gene assay either in frozen tissue or in FNAs . The difference is likely attributed to the difference in types of analyzed tissue, as Shibru et al. compared a benign group represented by hyperplastic nodule, FTA, Hürthle cell adenomas (HCAs) with a collective group of thyroid malignancies, including FTC, PTC, follicular variant of PTC, HCC. "
[Show abstract] [Hide abstract]
ABSTRACT: The development of molecular biomarkers (BMs) of follicular thyroid carcinoma is aimed at advancing diagnosis of follicular neoplasm, as histological examination of those tumors does not lend itself to definitive diagnosis of carcinoma. We assessed the relative levels of expression of 6 genes: CCND2, PCSK2, PLAB, RAP2A, TSHR, and IGF-1R in archived thyroid tissue. The quantitative real-time PCR analysis revealed a significant change in 3 genes: PSCK2 (a 22.4-fold decrease, P = 2.81E - 2), PLAB (an 8.3-fold increase, P = 9.81E - 12), and RAP2A (a 6.3-fold increase, P = 9.13E - 10) in carcinoma compared with adenoma. Expression of PCSK2 was equally low, PLAB was equally high, whereas RAP2A expression was significantly higher (25.9-fold, P = 0.039) in microdissected carcinoma cells that have invaded through the thyroid capsule and entered blood vessels than in thyroid tumor cells growing under the capsule. Thus, RAP2A appeared as a unique and worthy of further evaluation candidate BM associated with invasion of thyroid follicular cells.
Journal of Thyroid Research 10/2011; 2011(12):979840. DOI:10.4061/2011/979840
Available from: Giovanni Conzo
[Show abstract] [Hide abstract]
ABSTRACT: Thyroid fine-needle aspiration (FNA) samples that feature a follicular-patterned, monotonous Hurthle (oncocytic) cell population cannot be diagnosed reliably. The authors of this report recently identified cyclin D3 overexpression on histologic sections of Hurthle cell carcinoma. In this study, they assessed the diagnostic value of cyclin D3 immunohistochemistry added to routine cytology.
Fifty-one FNA samples that were suspicious for Hurtle cell neoplasia and that had histologic follow-up (19 malignant cases) were examined. Cyclin D3 expression levels were evaluated in cell block preparations and were compared with levels of the closely related cyclin D1 protein.
Greater than 25% positive cells were used as the cutoff point, as suggested by previous studies. Cyclin D1 and cyclin D3 were highly specific (100% for both) and fairly accurate (75% and 92%, respectively) in distinguishing between benign and malignant oncocytic lesions; the positive predictive value (PPV) for each was 100%. However, both cyclins D1 and D3 had low sensitivity (32% and 79%, respectively) and low negative predictive value (NPV) (71% and 89%, respectively). In contrast, by adopting balanced receiver operating characteristic-derived positive cutoff values, cyclin D1 (>or=6.5%) and cyclin D3 (>or=7.5%) were found to be highly sensitive (100% for both) and accurate (90% and 94%, respectively); and the NPV was 100% for both. In contrast, cyclins D1 and D3 had low specificity (84% and 91%, respectively) and a low PPV (79% and 86%, respectively); however, these values improved in samples that were positive for both cyclins (sensitivity, 100%; specificity, 94%; PPV, 90%; NPV, 100%; and accuracy, 96%).
Cyclin D3 increased the suspicion of malignancy in indeterminate oncocytic lesions; its diagnostic performance depended on the cutoff point used and was enhanced further when combined with cyclin D1.
Cancer 12/2009; 117(6):522-9. DOI:10.1002/cncy.20050 · 4.89 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.