Project description:To assess the function of LDHA in PTCs, we performed transcriptome analysis through high-throughput RNA-Seq of control and LDHA knockdown cells
Project description:Apart from alterations in the RET/PTC-RAS-BRAF pathway, comparatively little is known about the genetics of papillary thyroid carcinoma (PTC). We show that numerous miRNAs are transcriptionally up-regulated in PTC tumors compared with unaffected thyroid tissue. A set of 5 miRNAs including the 3 most upregulated ones (miRs 221, 222, 146) distinguished unequivocally between PTC and normal thyroid. Additionally, miR-221 was upregulated in unaffected thyroid tissue in several PTC patients, presumably an early event in carcinogenesis. Tumors in which the upregulation (11-19 fold) of miRs 221, 222 and 146 was strongest showed dramatic loss of KIT transcript and Kit protein. In five of 10 such cases this was associated with germline single nucleotide changes in the two recognition sequences in KIT for these miRNAs. We conclude that upregulation of several miRs and down regulation of KIT are involved in PTC pathogenesis, and that sequence changes in genes targeted by miRNAs can contribute to their downregulation.
Project description:Here we have performed quantitative and qualitative profiling of the proteome of cystic fluid from human cystic papillary thyroid carcinoma with the aim to identify specific proteins and pathways involved in cystic fluid from human cystic papillary carcinoma, as well as possible diagnostic markers.
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.
Project description:We compared the expression profiles of papillary thyroid tumors from the Chernobyl Tissues Bank (CTB) with tumors from French patients with no history of exposure to radiations. Keywords: papillary thyroid cancer vs. patient-matched healthy adjacent thyroid thyroid papillary cancer vs. patient-matched adjacent nontumor thyroid tissues. -14 tumors from France -12 tumors from Ukraine
Project description:We compared the expression profiles of papillary thyroid tumors from the Chernobyl Tissues Bank (CTB) with tumors from French patients with no history of exposure to radiations. Keywords: papillary thyroid cancer vs. patient-matched healthy adjacent thyroid
Project description:We profiled the microRNA expression of 5 pairs of PTC and normal thyroid tissues. All the tissues were immediately snap-frozen in liquid nitrogen and confirmed as papillary thyroid carcinoma by expert pathologists. Numerous deregulated mature microRNAs were identified comparing PTC tissues versus normal thyroid tissues. Details about the clinical-pathological characteristics of the samples are also provided.
Project description:Papillary thyroid carcinoma (PTC), the most common form of thyroid carcinomas, is a well-differentiated tumor and accounts for about 80% of all thyroid carcinomas. With the advantage of providing comprehensively analysis of global proteins in samples, proteomics techniques are increasingly applied in the field of identifying novel biomarkers in thyroid cancer. In this study, we conducted a TMT labeling-based quantitative proteomics analysis and bioinformatics analysis to compare the alternation of global proteins in tumor tissues and para-tumor tissues between PTC with LNM and without LNM.