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DNA methylation profiling in thyroid cancer in Chinese population

ABSTRACT: DNA methylation profiling in thyroid cancer in Chinese population

PROVIDER: PRJNA976663 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR24746006_1.fastq.gz	Fastqsanger.gz
	SRR24746006_2.fastq.gz	Fastqsanger.gz
	SRR24746007_1.fastq.gz	Fastqsanger.gz
	SRR24746007_2.fastq.gz	Fastqsanger.gz
	SRR24746008_1.fastq.gz	Fastqsanger.gz

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DNA methylation profiling in thyroid cancer in Chinese population

Project description:Around 20-30% of Thyroid cancers are difficult to accurately diagnose with fine needle aspiration (FNA) due to their shared features with benign nodules. Although there are molecular tools to assist the diagnosis, such as the Afirma Gene Expression Classifier and ThyroSeqv3, which are the most widely used in the United States, however, these tests all show low positive predictive value and would lead to unnecessary removal of the thyroid in non-cancer patients. In addition, the prediction model of these tests is trained mainly based on the American population. Therefore, it is required to develop a highly accurate test for thyroid nodule diagnostic which could not only increase the PPV, and reduce the unnecessary surgeries, but also is based on Chinese population datasets. To overcome the potential overfitting issues of the prediction model, here we provide a function-guided DNA methylation biomarker selection method through multi-omics datasets. To develop a novel DNA methylation based diagnostic test for thyroid cancer, we characterized the genome-wide DNA methylation pattern in 49 malignant and benign fresh thyroid tissues by using Reduced Representation Bisulfite Sequencing (RRBS) analysis on a single nucleotide level. And we found a group of differentiated DNA methylation sites that could be used to distinguish thyroid cancer and benign tissues.

2025-05-26 | GSE233560 | GEO

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Project description:While thyroid nodules per se are frequent (4%–50%), thyroid cancer is rare (∼5% of all thyroid nodules). The minimally invasive Fine Needle Aspiration Cytology (FNAC) is the current gold standard for the diagnosis thyroid nodule malignancy. However, proper discrimination of follicular neoplasias often require more invasive diagnostic techniques. To develop a novel molecular classification system for thyroid cancer malignancy, we performed a genome-wide epigenetic profiling of 54 fresh frozen Follicular like thyroid samples using the Illumina Human DNA Methylation EPIC platform.

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Identification of Tissue Specific DNA Methylation Signatures for Thyroid Nodule Diagnostics

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.

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Project description:We perform the first two-stage GWAS on TB in the Chinese population. We examined 900,015 genetic variants in 1,008 TB patients using the HumanOmniZhongHua-8 v1.1 BeadChip.

2019-06-01 | GSE83397 | GEO

Integrative analysis of DNA methylation and gene expression identified follicular thyroid cancer-specific diagnostic biomarkers [Methylation]

Project description:The diagnosis of follicular thyroid carcinoma (FTC) prior surgical resection remains a challenge, as routine screening methods, such as ultrasound or even FNAB, could not diagnose FTC preoperatively. Here, we performed an integrative analysis of DNA methylation and RNA assays data from our own cohort (14 Follicular thyroid carcinoma vs 16 Benign thyroid lesion) to identify thyroid cancer-specific DNA methylation markers. We first identified differentially methylated and expressed genes and examined their correlations. Candidate DNA methylation sites were selected and further verified in validation set. Among all candidate methylation sites, cg06928209 was the most promising site as a molecular marker for early diagnosis, with a sensitivity of 90%, a specificity of 80% and an AUC of 0.77. Overall, our study demonstrates the potential use of methylation markers in FTC diagnosis and may boost the development of new epigenetic therapies.

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