MiRNA for indeterminate thyroid nodule diagnosis
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB25356 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Next generation sequencing identifies a highly accurate microRNA panel that distinguishes well-differentiated thyroid cancer from benign thyroid nodules
| PRJNA477765 | ENA
Project description:PURPOSE: Thyroid cancer is frequently difficult to diagnose due to an overlap of cytological features between malignant and benign nodules. This overlap leads to unnecessary removal of the thyroid in patients without cancer. While providing some improvement over cytopathologic diagnostics, molecular methods frequently fail to provide a correct diagnosis for thyroid nodules. These approaches are based on the difference between malignant nodules and normal adjacent thyroid tissue and assume that normal thyroid tissues are the same as benign nodules. However, in contrast to normal thyroid tissues, benign thyroid nodules can contain genetic alterations that can be found in cancerous nodules. PATIENTS AND METHODS: For the development of a new molecular diagnostic test for thyroid cancer, we evaluated DNA methylation in 109 thyroid tissues by using genome wide single base resolution DNA methylation analysis (Reduced Representation Bisulfite Sequencing). The test was validated in the retrospective cohort containing 64 thyroid nodules. RESULTS: By conducting Reduced Representation Bisulfite Sequencing in 109 thyroid specimens, we found significant differences between normal tissue, benign nodules, and cancer. Based on tissue-specific epigenetic signatures for benign and malignant nodules, we developed a new epigenetic approach for thyroid diagnostics. According to the validation cohort, our test has an estimated specificity of 97% (95% CI, 80 to 100), sensitivity of 100% (95% CI, 86 to 100), PPV of 97% (95% CI, 82-100), NPV of 100% (95%, 85 to 100). CONCLUSION: These data show that epigenetic testing can provide outstanding diagnostic accuracy for thyroid nodules by evaluating tissue specific DNA methylation.
2018-11-30 | GSE107738 | GEO
Project description:Thyroid cancer is a common endocrine malignancy; however, its diagnosis is not straightforward. The current gold standard for diagnosing thyroid cancer is fine needle aspiration biopsy (FNAB), but when cytological analysis does not provide viable results or samples belong to less defined categories of diagnosis, patients are often referred to diagnostic surgery. Given that not all these nodules require removal, nor all of them are malignant, patients would not necessarily require surgery had the initial FNAB diagnosis been more conclusive. There is therefore a lack of reliable and specific biomarkers for thyroid cancer malignancy, that can complement and improve the current diagnosing methods. “Omics” approaches have gained much attention in the last decade in the field of biomarker discovery for diagnostic and prognostic characterization of various pathophysiological conditions. In this project, proteomics and metabolomics approaches were applied to the same thyroid nodules from patients with benign and malignant lesions. Tissue analysis provided several interesting biomarkers by both proteomics and metabolomics. The combination of these results demonstrated the high energetic and biomass demand of cancer cells, as well as a biomarker panel including 2 free peptides and 2 proteins with high sensitivity and specificity. Together, these results have contributed to increasing the knowledge of thyroid cancer phenotype and corresponding biochemical profiles, as well as providing potential biomarkers for malignancy, and improving diagnostic methodologies.
2023-10-24 | PXD035583 | Pride
Project description:<p><strong>BACKGROUND:</strong> Novel biomarkers are urgently needed to distinguish between benign and malignant thyroid nodules and detect thyroid cancer in the early stage. The associations between serum IgG N-glycosylation and thyroid cancer risk have been revealed. We aimed to explore the potential of IgG N-glycan traits as biomarkers in the differential diagnosis of thyroid cancer.</p><p><strong>METHODS:</strong> Plasma IgG N-glycome analysis was applied to a discovery cohort followed by independent validation. IgG N-glycan profiles were obtained using a robust quantitative strategy based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. IgG N-glycans were relatively quantified, and classification performance was evaluated based on directly detected and derived glycan traits.</p><p><strong>RESULTS: </strong>Four directly detected glycans were significantly changed in thyroid cancer patients compared to that in non-cancer controls. Derived glycan traits and a classification glycol-panel were generated based on the directly detected glycan traits. In the discovery cohort, derived trait BN (bisecting type neutral N-glycans) and the glyco-panel showed potential in distinguishing between thyroid cancer and non-cancer controls with AUCs of 0.920 and 0.917, respectively. The diagnostic potential was further validated. Derived trait BN and the glycol-panel displayed “accurate” performance (AUC>0.8) in discriminating thyroid cancer from benign thyroid nodules and healthy controls in the validation cohort. Meanwhile, derived trait BN and the glycol-panel also showed diagnostic potential in detecting early-stage thyroid cancer.</p><p><strong>CONCLUSIONS:</strong> IgG N-glycome analysis revealed N-glycomic differences that allow classification of thyroid cancer from non-cancer controls. Our results suggested that derived trait BN and the classification glyco-panel rather than single N-glycans may serve as candidate biomarkers for further validation.</p>
2021-09-01 | MTBLS2935 | MetaboLights
Project description:BACKGROUND: Following fine needle aspiration, 15-30% of thyroid nodules are not clearly benign or malignant. These cytologically indeterminate nodules are often referred for diagnostic surgery, though most prove benign. A novel diagnostic test measuring the expression of 167 genes has shown promise in improving pre-operative risk assessment. We evaluated this test in a prospective, multicenter study. METHODS: Over 19 months, we performed a prospective study at 49 clinical sites enrolling 3,789 patients and collecting 4,812 samples from thyroid nodules >1cm requiring evaluation. We obtained 577 cytologically indeterminate aspirates with corresponding histopathology of excised lesions on 413. Central blinded histopathologic review served as the reference (“gold”) standard. After applying inclusion criteria, gene expression classifier results were obtained for 265 indeterminate nodules used in this analysis, and performance was calculated. RESULTS: 85 of 265 indeterminate nodules were malignant. The gene expression classifier correctly identified 78 of 85 as ‘suspicious’ (92% sensitivity, [84%-97%] 95% CI). Specificity was 52%, [44%-59%]. The negative predictive value was 95%, 94%, and 85%, respectively, for aspirates with AUS/FLUS, FN/SFN, or ‘suspicious’ cytology. Analysis of 7 false negative cases revealed 6 with a paucity of thyroid follicular cells, suggesting that insufficient sampling of the nodule had occurred. CONCLUSIONS: Though individualized clinical care is recommended, these data support consideration of a conservative approach for most patients with indeterminate FNA cytology and benign gene expression classifier results. 265 cytologically indetermine samples, 47 cytologically benign and 55 cytologically malignant samples
2012-06-24 | E-GEOD-34289 | biostudies-arrayexpress
Project description:BACKGROUND: Following fine needle aspiration, 15-30% of thyroid nodules are not clearly benign or malignant. These cytologically indeterminate nodules are often referred for diagnostic surgery, though most prove benign. A novel diagnostic test measuring the expression of 167 genes has shown promise in improving pre-operative risk assessment. We evaluated this test in a prospective, multicenter study. METHODS: Over 19 months, we performed a prospective study at 49 clinical sites enrolling 3,789 patients and collecting 4,812 samples from thyroid nodules >1cm requiring evaluation. We obtained 577 cytologically indeterminate aspirates with corresponding histopathology of excised lesions on 413. Central blinded histopathologic review served as the reference (“gold”) standard. After applying inclusion criteria, gene expression classifier results were obtained for 265 indeterminate nodules used in this analysis, and performance was calculated. RESULTS: 85 of 265 indeterminate nodules were malignant. The gene expression classifier correctly identified 78 of 85 as ‘suspicious’ (92% sensitivity, [84%-97%] 95% CI). Specificity was 52%, [44%-59%]. The negative predictive value was 95%, 94%, and 85%, respectively, for aspirates with AUS/FLUS, FN/SFN, or ‘suspicious’ cytology. Analysis of 7 false negative cases revealed 6 with a paucity of thyroid follicular cells, suggesting that insufficient sampling of the nodule had occurred. CONCLUSIONS: Though individualized clinical care is recommended, these data support consideration of a conservative approach for most patients with indeterminate FNA cytology and benign gene expression classifier results.
2012-06-25 | GSE34289 | GEO
Project description:Background: Fine needle aspiration biopsy (FNAB) is the gold-standard procedure for diagnosing malignant thyroid nodules. Indeterminate cytology is identified in 10-40% of cases and molecular testing may guide management in this setting. Current commercial options are expensive, and are either sensitive or specific. The aim of this study was to utilize next generation sequencing (NGS) technology to identify informative diversities in the microRNA (miRNA) expression profile of benign versus malignant thyroid nodules. Methods: Ex-vivo FNAB samples were obtained from thyroid specimens of patients that underwent thyroidectomy at a referral center. miRNA levels were determined using NGS and multiplexing technologies. Statistical analyses identified differences between normal and malignant samples and miRNA expression profiles that associate with malignancy were established. The accuracy of the miRNA signature in predicting histological malignancy was validated using a group of patient specimens with indeterminate cytology results. Results: 274 samples were obtained from 102 patients undergoing thyroidectomy. Of these samples, 71% were benign and 29% were malignant. Nineteen miRNAs were identified as statistically different between benign and malignant samples and were used to classify 35 additional nodules with indeterminate cytology (validation). The miRNA panel’s sensitivity, specificity, negative and positive predictive values and overall accuracy were 91%, 100%, 87%, 100% and 94%, respectively. Conclusion: Using NGS technology we identified a panel of 19 miRNAs that may be utilized to distinguish benign from malignant thyroid nodules with indeterminate cytology. Impact: Our panel may classify indeterminate thyroid nodules at higher accuracy than commercially available molecular tests.
2018-12-21 | GSE116196 | GEO
Project description:Development of a non-invasive, whole blood microarray gene expression signature that accurately distinguishes malignant from benign lung nodules detected by LDCT and the successful transition of that signature to a custom NanoString panel with no loss of accuracy.
2018-12-20 | GSE108375 | GEO
Project description:Thyroid nodules occur in about 60% of the population. Current diagnostic strategies, however, often fail at distinguishing malignant nodules before surgery, thus leading to unnecessary, invasive treatments. As proteins are involved in all physio/pathological processes, a proteome investigation of biopsied nodules may help correctly classify and identify malignant nodules and discover therapeutic targets. Quantitative mass spectrometry data-independent acquisition (DIA) enables highly reproducible and rapid throughput investigation of proteomes. An exhaustive spectral library of thyroid nodules is essential for DIA yet still unavailable. This study presents a comprehensive thyroid spectral library covering five types of thyroid tissue: multinodular goiter, follicular adenoma, follicular and papillary thyroid carcinoma, and normal thyroid tissue. Our library includes 925,330 transition groups, 157,548 peptide precursors, 121,960 peptides, 9941 protein groups, and 9826 proteins from proteotypic peptides. This library resource was evaluated using three papillary thyroid carcinoma samples and their corresponding adjacent normal thyroid tissue, leading to effective quantification of up to 7863 proteins from biopsy-level thyroid tissues.
2022-05-20 | PXD026395 | Pride
Project description:Anaplastic thyroid carcinomas (ATC) are rare, but represent the most lethal malignancy of the thyroid. Selective molecular markers and drivers distinguishing ATC from other thyroid carcinomas of follicular origin remain largely unknown, limiting advances in diagnosis and treatment. In a retrospective study, we analyzed gene expression in 36 ATC, 18 poorly-differentiated, 132 papillary and 55 follicular thyroid carcinoma, as well as 124 paired and un-paired normal thyroid tissues in three independent cohorts by RNA-sequencing and immunohistochemistry. RNA-sequencing data in the test cohort suggested selective ATC protein biomarkers. Evaluation of these revealed that ATCs are characterized by the de novo expression of various testis antigens, including melanoma-associated antigen A3 (MAGEA3), but most importantly the oncofetal IGF2 mRNA binding protein 1 (IGF2BP1). Shallow whole genome-sequencing essentially excluded, that IGF2BP1 upregulation results from gene copy number alterations. Immunohistochemical analyses in all three tumor cohorts confirmed selective de novo expression of IGF2BP1 protein in ATC. In sum, 75 % (27/36) of all tested ATC and 0.5 % (1/204) of poorly and well-differentiated thyroid carcinoma tissue samples were positive for IGF2BP1 protein. This indicates that IGF2BP1 protein expression identifies ATC with a diagnostic odds ratio of 612 (95 % CI: 74.6 to 5021). In addition, we found that MAGEA3 is exclusively, although less consistently upregulated in ATC, presenting with an odds ratio of 411 (95 % CI: 23.8 to 7098.7). Importantly, we provide confirmatory evidence that IGF2BP1 and MAGEA3 expression distinguishes ATC from partially differentiated thyroid carcinomas (PDTCs). IGF2BP1 furthermore identified ATC foci within low-grade follicular thyroid carcinoma. In conclusion, IGF2BP1 represents the most promising single-gene marker available for ATC, followed by MAGEA3, improving on current techniques. Robust markers are essential to help distinguish this high-grade malignancy from other thyroid carcinomas, to guide surgical decision making, therapy and post-resection/therapy monitoring strategies.
2020-07-07 | GSE126728 | GEO