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MiRNA Expression Pattern in Papillary Thyroid Cancer

ABSTRACT: miRNA Expression Pattern in Papillary Thyroid Cancer

PROVIDER: PRJNA789823 | ENA |

REPOSITORIES: ENA

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miRNA Expression Pattern in Papillary Thyroid Cancer

Project description:The aim of this study was to conduct a comparison of tissue miRNA in thyroid cancer (papillary (PTC), follicular (FTC), and microcancer (PTMC)) and healthy thyroid tissue (Control). The expression level of 798 miRNAs using NanoString technology was examined. ROC curve analysis, and logistic regression modeling were performed. Gene ontology (GO), canonical pathways analysis were used to explore the biological functions of the miRNA target genes. The study revealed that 10 miRNAs were deregulated in samples of patients with PTC. Pathway analysis showed that miRNA target genes were mainly significantly enriched in endocrine resistance, EGFR tyrosine kinase inhibitor resistance, and pathways in cancer. ROC analysis demonstrated that miR-146-5p, miR-551b-3p, and miR-222-3p can be introduced as a diagnostic tool for PTC (AUC=0.770; 0.740; 0.720; respectively). Validation by qRT-PCR confirmed our findings. The results suggest that tissue miRNAs can potentially be used as predictive biomarkers of PTC in patients.

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Project description:Paillary thyroid cancer (PTC) is the most common type of thyroid malignancy. Extrathyroidal invasion (ETİ), lymph node metastasis, and distance organ metastasis is poor prognostic factor in PTC. The metastasis is still a leading cause of papillary thyroid cancer death. The early detection of metastatic signature is crucial for identification of thyroid cancer prognosis and personalized therapeutic strategies. In the present study, we present thyroid cancer metastasis and invasivenes related miRNAs identified by comprehensive miRNA expression profiling of formalin-fixed paraffin embedded (FFPE) thyroid tissues obtained from patients belonging to intrathyroidal, invasive and metastatic thyroid carcinoma groups

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Project description:Tumor microenvironment heterogeneity sheltered our understanding of papillary thyroid cancer. However, molecular characteristics of papillary thyroid cancer has not been reported at single cell resolution. The immunological link between papillary thyroid cancer and Hashimoto's thyroiditis is also in doubt.We identified 24 cell clusters in human papillary thyroid cancer based on their heterogeneous gene expression pattern. Follicular epithelial cell subsets in papillary thyroid cancer with Hashimoto's thyroiditis and papillary thyroid cancer without Hashimoto's thyroiditis showed different malignant level. Machine learning model identified potential biomarker to evaluate tumor epithelial cell development. Together with immunostaining, lymphocytes heterogeneity indicated an obvious B cell infiltration pattern in papillary thyroid cancer with Hashimoto's thyroiditis. Additionally, trajectory analysis of B cell and plasma cell suggest the migration potential from normal adjacent tissue of Hashimoto's thyroiditis to papillary thyroid cancer tissue. Our results provide the first single cell landscape of Papillary thyroid cancer. Single cell data resource of Papillary thyroid cancer with Hashimoto's thyroiditis promote our understanding of molecular heterogeneity and immunological link between papillary thyroid cancer and Hashimoto's thyroiditis.

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MiRNA expression patterns in anaplastic thyroid cancer and papillary thyroid cancer cell lines

Project description:Anaplastic thyroid carcinoma (ATC) is a rare but deadly thyroid cancer. In contrast, papillary thyroid carcinoma (PTC) is common and highly curable. Minimally invasive biomarkers are needed to distinguish ATC and PTC. Here, by small RNA-seq we show the differential expression levels of several miRNAs, which include miR-34a and miR-210 in ATC compared to PTC cell lines.

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Project description:Thyroid gland is among the most sensitive organs to ionizing radiation. Whether low-dose radiation-induced papillary thyroid cancer (PTC) differs from sporadic PTC is yet unknown. We used microarrays to identify gene signature of radiation-induced papillary thyroid carcinomas

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