Novel biomarker SYT12 may contribute to predicting papillary thyroid cancer outcomes.
ABSTRACT: Aim:To investigate biomarkers for predicting papillary thyroid cancer outcomes. Materials & methods:The expression of biomarkers (ITGA2, SYT12 and CDH3) was studied in a prospective cohort of patients with papillary thyroid cancer. Three outcomes of initial metastases, baseline status and longitudinal status were analyzed and correlated with the biomarkers. Results:SYT12 provided the best prediction of initial metastasis (sensitivity: 72%; specificity: 54%). SYT12 had the highest accuracy for predicting longitudinal status (sensitivity: 100%; specificity: 47%). The best performance for longitudinal status resulted from combining SYT12 with American Thyroid Association risk stratification, with sensitivity and specificity of 88 and 73%, respectively. Conclusion:SYT12 has some prognostic significance in papillary thyroid cancer. Further validation studies in larger populations are warranted.
Project description:Even though the majority of well-differentiated thyroid carcinoma (WDTC) is indolent, a number of cases display an aggressive behavior. Cumulative evidence suggests that the deregulation of DNA methylation has the potential to point out molecular markers associated with worse prognosis.To identify a prognostic epigenetic signature in thyroid cancer.Genome-wide DNA methylation assays (450k platform, Illumina) were performed in a cohort of 50 nonneoplastic thyroid tissues (NTs), 17 benign thyroid lesions (BTLs), and 74 thyroid carcinomas (60 papillary, 8 follicular, 2 Hürthle cell, 1 poorly differentiated, and 3 anaplastic). A prognostic classifier for WDTC was developed via diagonal linear discriminant analysis. The results were compared with The Cancer Genome Atlas (TCGA) database.A specific epigenetic profile was detected according to each histological subtype. BTLs and follicular carcinomas showed a greater number of methylated CpG in comparison with NTs, whereas hypomethylation was predominant in papillary and undifferentiated carcinomas. A prognostic classifier based on 21 DNA methylation probes was able to predict poor outcome in patients with WDTC (sensitivity 63%, specificity 92% for internal data; sensitivity 64%, specificity 88% for TCGA data). High-risk score based on the classifier was considered an independent factor of poor outcome (Cox regression, P < 0.001).The methylation profile of thyroid lesions exhibited a specific signature according to the histological subtype. A meaningful algorithm composed of 21 probes was capable of predicting the recurrence in WDTC.
Project description:Background: Amide proton transfer-weighted (ATPw) imaging is a novel MRI technique that has been used to identify benign and malignant tumors. The present study evaluated the role of APTw imaging in differentiating papillary thyroid carcinoma from predominantly solid adenomatous nodule.Methods: This study included 24 cases of solitary papillary thyroid carcinoma, and 20 cases of solid adenomatous nodules. Normal thyroid tissues were examined in 12 healthy subjects. The healthy subjects, eight cases of adenomatous nodule with cystic degeneration, and 12 cases of thyroid goiter, were only considered in the descriptive analysis, not included in our statistical analysis. The mean APTw value and the apparent diffusion coefficients (ADCs) of papillary thyroid carcinoma and solid adenomatous nodule were compared via a Mann-Whitney U test and receiver operating characteristic (ROC)-curve analyses.Results: The adenomatous nodule (3.3 ± 1.3%) exhibited significantly higher APTw value (p < 0.05) than that of the papillary thyroid carcinoma (1.8 ± 0.7%). The optimal cut-off value of the mean APTw value in differentiating papillary thyroid carcinoma from adenomatous nodule was 3.15%, with a sensitivity of 60% and a specificity of 100%. The mean ADC of papillary thyroid carcinoma (1.2 ± 0.2 × 10?3 mm2/s) was significantly lower than that of adenomatous nodule (2.0 ± 0.4 × 10?3 mm2/s). The optimal cut-off value of the mean ADC was 1.35 × 10?3 mm2/s, with a sensitivity of 100% and a specificity of 75%. Based on the ROC-curve analysis of APT and ADC, the ADC showed a higher area under the curve (AUC) than that of APT (AUCAPT = 0.84, AUCADC = 0.95).Conclusion: APTw imaging may be as useful as DWI for the differentiation of papillary thyroid carcinoma from predominantly solid adenomatous nodule. Although the sensitivity of ADC was greater than that of APT, APT had greater specificity.
Project description:BACKGROUND:Papillary thyroid carcinoma is a type of indolent tumor with a dramatically increasing incidence rate and stably high survival rate. Reducing the overdiagnosis and overtreatment of papillary thyroid carcinoma is clinically emergent and important. A radiomics model is proposed in this article to predict lymph node metastasis, the most important risk factor of papillary thyroid carcinoma, based on noninvasive routine preoperative ultrasound images. METHODS:Four hundred fifty ultrasound manually segmented images of patients with papillary thyroid carcinoma with lymph node status obtained from pathology report were enrolled in our retrospective study. A radiomics evaluation of 614 high-throughput features were calculated, including size, shape, margin, boundary, orientation, position, echo pattern, posterior acoustic pattern, and calcification features. Then, combined feature selection strategy was used to select features with the greatest ability to discriminate lymph node status. A support vector machine classifier was employed to build and validate the prediction model. Another independent testing cohort was used to further evaluate the performance of the radiomics model. RESULTS:Among 614 radiomics features, 50 selected features most reflecting echo pattern, posterior acoustic pattern, and calcification showed the superior lymph node status distinguishable performance with area under the receiver operating characteristic curve of 0.753, 0.740, and 0.743 separately when using each type of features predicting the lymph node status. The results of model based on all 50 final features predicting the lymph node status shown an area under the receiver operating characteristic curve of 0.782, and accuracy of 0.712. In the independent testing cohort, the proposed approach showed similar results, with area under the receiver operating characteristic curve of 0.727 and accuracy of 0.710. CONCLUSION:Papillary thyroid carcinoma with lymph node metastasis usually shows a complex echo pattern, posterior region homogeneity, and macrocalcification or multiple calcification. The radiomics model proposed in this article is a promising method for assessing the risk of papillary thyroid carcinoma metastasis noninvasively.
Project description:Context: Papillary thyroid cancer (PTC) is the most common thyroid cancer with dramatically increasing worldwide. Accurate diagnosis is crucial to avoid unnecessary overtreatment for low-risk patients, but the currently available markers are still insufficient. tRNA-derived fragments (tRFs) are emerging as a new class of small non-coding RNAs due to their potential roles as novel biomarkers and therapeutic targets in cancer. However, their involvement in papillary thyroid carcinoma (PTC) is still unclear. Objectives: This study was performed to identify differentially expressed tRFs in PTC and investigate the role of serum tRFs to discriminate PTC from nodular goiters (NGs).Methods and Materials: tRF expression profiles were measured in pooled sera from patients with PTCs (n=6), NGs (n=6) and healthy subjects (n=6) using high-throughput sequencing (cohort1). One selected tRF candidate was validated in the same individual samples (cohort1) by qRT-PCR. The confirmed tRF was further validated in a larger second cohort including patients with PTCs (n=30), NGs (n=20) and healthy individuals (n=18).Results: Our sequencing results showed that circulating tRFs were differentially expressed in patients with PTC compared with those with NG and healthy people. After the validation in individual samples, tRF-Pro-AGG-018 was confirmed as differentially elevated in serum samples of patients with PTC. These results were further confirmed in a larger second cohort. Moreover, tRF-Pro-AGG-018 exhibited good diagnostic performance with a sensitivity of 0.7222 and a specificity of 0.8846 for PTC and it was associated with several targeted genes of PTC. Conclusions: Our study identified that the serum tRFs were differentially expressed in PTC compared with NG and healthy individuals. Notably, circulating tRF-Pro-AGG-018 was found to have a significant elevation in patients with PTC and exhibited good diagnostic performance with relatively high sensitivity and specificity for PTC. Our findings suggest tRFs might serve as novel circulating biomarkers in predicting patients with PTC, which may prevent unnecessary thyroid surgeries for low-risk and benefit from optimal Overall design: tRF expression profiles were measured in pooled sera from patients with PTCs (n=6), NGs (n=6) and healthy subjects (n=6) using high-throughput sequencing (cohort1). One selected tRF candidate was validated in the same individual samples (cohort1) by qRT-PCR. The confirmed tRF was further validated in a larger second cohort including patients with PTCs (n=30), NGs (n=20) and healthy individuals (n=18).
Project description:Cancer arises through accumulation of epigenetic and genetic alteration. Aberrant promoter methylation is a common epigenetic mechanism of gene silencing in cancer cells. We here performed genome-wide analysis of DNA methylation of promoter regions by Infinium HumanMethylation27 BeadChip, using 14 clinical papillary thyroid cancer samples and 10 normal thyroid samples. Among the 14 papillary cancer cases, 11 showed frequent aberrant methylation, but the other three cases showed no aberrant methylation at all. Distribution of the hypermethylation among cancer samples was non-random, which implied existence of a subset of preferentially methylated papillary thyroid cancer. Among 25 frequently methylated genes, methylation status of six genes (HIST1H3J, POU4F2, SHOX2, PHKG2, TLX3, HOXA7) was validated quantitatively by pyrosequencing. Epigenetic silencing of these genes in methylated papillary thyroid cancer cell lines was confirmed by gene re-expression following treatment with 5-aza-2'-deoxycytidine and trichostatin A, and detected by real-time RT-PCR. Methylation of these six genes was validated by analysis of additional 20 papillary thyroid cancer and 10 normal samples. Among the 34 cancer samples in total, 26 cancer samples with preferential methylation were significantly associated with mutation of BRAF/RAS oncogene (P = 0.04, Fisher's exact test). Thus, we identified new genes with frequent epigenetic hypermethylation in papillary thyroid cancer, two subsets of either preferentially methylated or hardly methylated papillary thyroid cancer, with a concomitant occurrence of oncogene mutation and gene methylation. These hypermethylated genes may constitute potential biomarkers for papillary thyroid cancer.
Project description:Papillary thyroid carcinoma (PTC) is the most common endocrine cancer with a significantly increase of the incidence recently. Several cytokines, such as thyroid peroxidase (TPO), cluster of differentiation 56 (CD56), Galectin-3, mesothelial cell (MC), cytokeratin 19 (CK19) and BRAF (B-raf) were recommended to be tested by immunohistochemistry (IHC) for a definitive diagnosis, but were still limited in clinical use because of their relative lower sensitivity and specificity. MicroRNA (miRNA), as a new molecular biomarkers, however, has not been reported yet so far. To address this, hsa-miR-200a-5p, a miRNA, was selected and detected in PTC patients by in situ hybrization with benign thyroid tumor with papillary hyperplasia as a control, and the differential expression of hsa-miR-200a-5p between fresh PTC tissues and control was detected by qRT-PCR. Expressive levels of cytokines of TPO, CD56, Galectin-3, MC, CK19 and B-raf were also detected by immunohistochemistry. The correlation was analyzed by SPSS software using Spearman methods. As expected, the hsa-miR-200a-5p expressive level was significantly increased in PTC patients, compared to that of control, and was consistent with that of TPO, CD56, Galectin-3, MC, CK19 and B-raf. In addition, expression of hsa-miR-200a-5p showed negative correlation to that of TPO (rs = - 0.734; **: P < 0.01) and CD56 (rs = - 0.570; **: P < 0.01), but positive correlation to that of Galectin-3 (rs = 0.601; **: P < 0.01), MC (rs = 0.508; **: P < 0.01), CK19 (rs = 0.712; **: P < 0.01) and B-raf (rs = 0.378; **: P < 0.01). PTC and papillary benign thyroid papillary hyperplasia are difficult to distinguish in morphology, so requiring immunohistochemistry to further differentiate the diagnosis, however, for the existing clinical common diagnostic marker for immunohistochemistry, the sensitivity and accuracy are low, it is easy to miss diagnosis. Therefore, there is an urgent need for a rapid and sensitive molecular marker. So miR-200a-5p can be used to assist in the diagnosis of PTC at the molecular level, and as a biomarker, can be effectively used to distinguish between PTC and benign thyroid tumor with papillary hyperplasia.
Project description:<h4>Background</h4>Aim of this meta-analysis was to evaluate the overall diagnostic value of circulating mini miRNAs for papillary thyroid carcinoma (PTC) and to find the possible molecular marker with higher diagnostic value for PTC.<h4>Methods</h4>We searched the Pubmed, Cochrane and Embase database until June 2020. We selected relevant literatures associated with the diagnosis of PTC with circulating miRNAs. The number of cases in experimental group and the control group, sensitivity and specificity could be extracted from the literatures.<h4>Results</h4>We got 9 literatures including 2114 cases of PTC. Comprehensive sensitivity was 0.79, comprehensive specificity was 0.82, positive likelihood ratio was 4.3, negative likelihood ratio was 0.26, diagnostic advantage ratio was 16. The summary receiver operating characteristic curve was drawn and the Area Under the Curve was 0.87.<h4>Conclusions</h4>Circulating microRNAs may be promising molecular markers for the diagnosis of papillary thyroid carcinoma. Combined detection of certain serum microRNAs can improve the diagnostic accuracy of papillary thyroid carcinoma. Especially MiR-222 and miR-146b may be prime candidates for the diagnosis of PTC in Asian population.
Project description:Background:Thyroid cancer represents approximately 90% of endocrine cancers. Difficulties in diagnosis and low inter-observer agreement are sometimes encountered, especially in the distinction between the follicular variant of papillary thyroid carcinoma (fvptc) and other follicular-patterned lesions, and can present significant challenges. In the present proof-of-concept study, we report a gene-expression assay using NanoString nCounter technology (NanoString Technologies, Seattle, WA, U.S.A.) that might aid in the differential diagnosis of thyroid neoplasms based on gene-expression signatures. Methods:Our cohort included 29 patients with classical papillary thyroid carcinoma (ptc), 13 patients with fvptc, 14 patients with follicular thyroid carcinoma (ftc), 14 patients with follicular adenoma (fa), and 14 patients without any abnormality. We developed a 3-step classifier that shows good correlation with the pathologic diagnosis of various thyroid neoplasms. Step 1 differentiates normal from abnormal thyroid tissue; step 2 differentiates benign from malignant lesions; and step 3 differentiates the common malignant entities ptc, ftc, and fvptc. Results:Using our 3-step classifier approach based on selected genes, we developed an algorithm that attempts to differentiate thyroid lesions with varying levels of sensitivity and specificity. Three genes-namely SDC4, PLCD3, and NECTIN4/PVRL4-were the most informative in distinguishing normal from abnormal tissue with a sensitivity and a specificity of 100%. One gene, SDC4, was important for differentiating benign from malignant lesions with a sensitivity of 89% and a specificity of 92%. Various combinations of genes were required to classify specific thyroid neoplasms. Conclusions:This preliminary proof-of-concept study suggests a role for nCounter technology, a digital gene expression analysis technique, as an adjunct assay for the molecular diagnosis of thyroid neoplasms.
Project description:To evaluate the effectiveness of the number of central compartment lymph nodes (CLNs) on ultrasound (US) in predicting CLN metastasis (CLNM). We prospectively studied 309 papillary thyroid cancer (PTC) patients who underwent thyroidectomy with CLN dissection at our center from May 2017 to July 2017. The number and features of CLNs were evaluated preoperatively via US. All US examinations were performed using a Philips iU 22 or a GE Logiq 9 machine. Correlations between CLNs observed via preoperative US and amount of CLNM were evaluated. We found that ?2 CLNs on the preoperative US was associated with CLNM (P < 0.01). For this feature, the sensitivity, specificity, and area under the curve (AUC) were 54.3%, 66.1%, and 0.61, respectively. The presence of both suspected metastasis and ?2 CLNs on US had a specificity of 86.5%. In addition, ?3 CLNs on preoperative US was associated with large-volume CLNM (>5 metastatic CLNs) (P < 0.01). For this feature, the sensitivity, specificity and AUC were 54.8%, 74.5% and 0.65, respectively. The presence of both suspected metastasis and ?3 CLNs on US had a specificity of 84.9%. The presence of suspected metastasis and/or ?3 CLNs had a sensitivity of 80.6%. Our results suggest that ?2 and???3 CLNs on preoperative US may serve as ancillary preoperative markers for predicting CLNM.
Project description:Fine-needle aspiration biopsy (FNA) is usually applied to distinguish benign from malignant thyroid nodules. However, cytological analysis cannot always allow a proper diagnosis. We believe that the improvement of the diagnostic capability of pre-surgical FNA could avoid unnecessary thyroidectomy. In a previous study, we performed a proteome analysis to examine FNA collected after thyroidectomy. With the present study, we examined the applicability of these results on pre-surgical FNA. We collected pre-surgical FNA from 411 consecutive patients, and to obtain a correct comparison with our previous results, we processed only benign (n=114), papillary classical variant (cPTC) (n=34) and papillary tall cell variant (TcPTC) (n=14) FNA. We evaluated levels of five proteins previously found up-regulated in thyroid cancer with respect to benign nodules. ELISA and western blot (WB) analysis were used to assay levels of L-lactate dehydrogenase B chain (LDHB), Ferritin heavy chain, Ferritin light chain, Annexin A1 (ANXA1), and Moesin in FNA. ELISA assays and WB analysis confirmed the increase of LDHB, Moesin, and ANXA1 in pre-surgical FNA of thyroid papillary cancer. Sensitivity and specificity of ANXA1 were respectively 87 and 94% for cPTC, 85 and 100% for TcPTC. In conclusion, a proteomic analysis of FNA from patients with thyroid nodules may help to distinguish benign versus malignant thyroid nodules. Moreover, ANXA1 appears to be an ideal candidate given the high sensitivity and specificity obtained from ROC curve analysis.