Does the 3-gene diagnostic assay accurately distinguish benign from malignant thyroid neoplasms?
ABSTRACT 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.
SourceAvailable from: I Jolanda M de Vries[Show abstract] [Hide abstract]
ABSTRACT: Dendritic cells (DCs) are a family of professional antigen-presenting cells (APCs) that are able to initiate innate and adaptive immune responses against pathogens and tumor cells. The DC family is heterogeneous and is classically divided into two main subsets, each with its unique phenotypic and functional characteristics: myeloid DCs (mDCs) and plasmacytoid DCs (pDCs). Recent results have provided intriguing evidence that both DC subsets can also function as direct cytotoxic effector cells; in particular, against cancer cells. In this review, we delve into this understudied function of human DCs and discuss why these so-called killer DCs might become important tools in future cancer immunotherapies.Trends in Immunology 11/2013; DOI:10.1016/j.it.2013.10.007 · 12.03 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: Proprotein convertases (PCs) is a protein family which includes nine highly specific subtilisin-like serine endopeptidases in mammals. The system of PCs is involved in carcinogenesis and levels of PC mRNAs alter in cancer, which suggests expression status of PCs as a possible marker for cancer typing and prognosis. The goal of this work was to assess the information value of expression profiling of PC genes. Quantitative polymerase chain reaction was used for the first time to analyze mRNA levels of all PC genes as well as matrix metalloproteinase genes MMP2 and MMP14, which are substrates of PCs, in 30 matched pairs of samples of human lung cancer tumor and adjacent tissues without pathology. Significant changes in the expression of PCs have been revealed in tumor tissues: increased FURIN mRNA level (p<0.00005) and decreased mRNA levels of PCSK2 (p<0.007), PCSK5 (p<0.0002), PCSK7 (p<0.002), PCSK9 (p<0.00008), and MBTPS1 (p<0.00004) as well as a tendency to increase in the level of PCSK1 mRNA. Four distinct groups of samples have been identified by cluster analysis of the expression patterns of PC genes in tumor vs. normal tissue. Three of these groups covering 80% of samples feature a strong elevation in the expression of a single gene in cancer: FURIN, PCSK1, or PCSK6. Thus, the changes in the expression of PC genes have a limited number of scenarios, which may reflect different pathways of tumor development and cryptic features of tumors. This finding allows to consider the mRNAs of PC genes as potentially important tumor markers.PLoS ONE 02/2013; 8(2):e55752. DOI:10.1371/journal.pone.0055752 · 3.53 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: Background 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. Methods 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. Results 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. Conclusion 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 · 3.32 Impact Factor