Ontology highlight
ABSTRACT:
PROVIDER: PRJNA473626 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Familial thyroid cancer originating from follicular cells accounts for 5-15% of all the thyroid carcinoma cases in humans. Previously, we described thyroid follicular cell carcinomas in a large number of the Dutch German longhaired pointers (GLPs) with likely an autosomal recessive inheritance pattern. Here, we investigated the genetic causes of the disease using a combined approach of genome-wide association study, selective sweep analysis, and ROH analysis based on 170k SNP array genotype data. A region 0-5 Mb on chromosome 17 harboring the TPO gene was identified to be associated with the disease.
2021-06-30 | E-MTAB-10241 | biostudies-arrayexpress
Project description:The aim of the experiment was to explore the RUNX2 genomic functions in the papillary thyroid carcinoma. To this end, we performed Chromatin Immunoprecipitation followed by deep-sequencing using an antibody against RUNX2 in TPC1 thyroid cancer cell line, in order to define the genomic regions bound by this transcription factor.
2023-10-20 | E-MTAB-11051 | biostudies-arrayexpress
Project description:We performed single-cell RNA sequencing (scRNA-seq) on 3 normal thyroid, 7 papillary thyroid cancer (PTC), and 5 anaplstic thyroid cancer (ATC) cases. We used scRNA-seq to analyze serirne/glycine metabolism in thyroid tumors.
2023-10-17 | GSE232237 | GEO
Project description:Familial nonmedullary thyroid cancer (FNMTC) is a disease with the inheritance pattern is autosomal dominant with incomplete penetrance, but the causative gene is not clear. To identify the disease related locus in the FNMTC family, whole-genome SNPs of nine family members (five affected and four unaffected) were genotyped. We analyzed the SNP data with a novel method and mapped the disease-causing gene to several regions on the whole genome.
2017-12-31 | GSE75312 | GEO
Project description:We performed Chromatin Immunoprecipitation followed by deep-sequencing in TPC1 thyroid cancer cell line model, in order to identify the genomic elements enriched in RNA-Polymerase II, the enzymatic complex required for gene transcription. These data were integrated with RUNX2 genomic occupancy to map the RUNX2 responsive elements that are actively transcribed.
2023-10-20 | E-MTAB-11052 | biostudies-arrayexpress
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:We performed Chromatin Immunoprecipitation followed by deep-sequencing in TPC1 thyroid cancer cell line model, in order to profile the genomic distribution of H3K27ac, H3K4me1 and H3K4me3, epigenetic markers of chromatin functional status. These data were integrated with RUNX2 genomic occupancy to define the nature and the activation status of the RUNX2-associated regions.
2023-10-20 | E-MTAB-11050 | biostudies-arrayexpress
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