Project description:Transcriptional analysis of 49 primary medullary thyroid carcinoma tumors. Comparisons MTCM918T vs MTC634 and MTCM918T vs MTCWT. 49 (52 hybridized tumors with 3 replicates) primary Medullary Thyroid Carcinoma (MTC) cases were hybridized onto a cDNA microarray in order to identify the unique markers for specific genetic classes of MTC.
Project description:Genome profiling was compared between medullary breast carcinoma (MBC) and non medullary basal-like breast carcinoma (non-MBC BLC).
Project description:Thyroid tumors represent 1-3% of canine cancers with most tumors classified as follicular carcinomas and less frequently as medullary carcinomas. A cohort of canine thyroid carcinomas underwent RNASeq exploration (n=30). Clustering of tumor transcriptomes produced 2 groups; T1 and T2 clusters comprised of follicular thyroid carcinomas (FTC) and medullary thyroid carcinomas (MTC), respectively. Tumors were histologically typed as follicular, compact, and follicular-compact on blinded review, with most MTC classified as compact with rare follicular-compact appearance, while FTC displayed all 3 patterns. FTC samples had significantly elevated levels of ERBB2 and HER2 protein and RET signaling was up-regulated in MTC. Elevated HER2 protein staining was associated with shorter progression free survival (PFI). Additional studies are warranted to explore the utility of these biomarkers to improve diagnosis and treatment of thyroid carcinoma in dogs.
2025-11-06 | GSE289443 | GEO
Project description:Genomic Profiling of Anaplastic/Undifferentiated Thyroid Carcinoma
| PRJNA1072836 | ENA
Project description:Genomic profiling of Poorly Differentiated Thyroid Carcinoma
Project description:Medullary thyroid carcinoma (MTC) is a rare and aggressive neuroendocrine tumor. Our study involves 482 retrospective MTC formalin-fixed, paraffin-embedded (FFPE) samples from 452 patients, collected from 10 Chinese clinical centers. Quantification of 10,092 proteins were achieved via diaPASEF, and 87.8% patients were found to harbor at least one mutation. International MTC grading system, concurrent papillary thyroid carcinoma (PTC), and lymph node metastasis were identified as significant risk factors. Notably, RET mutations M918T and S891A were associated with high recurrence risk in sporadic and hereditary MTC, respectively. Pathway analyses highlighted enhanced collagen biosynthesis linked to poor prognosis. Ubiquitinomics showed downregulated E3 ligases CUL4B and TRIM32 linked to structural recurrence. Unsupervised clustering identified three molecular subtypes with distinct clinical outcomes and characteristics. To address the need for precise risk stratification, we developed a machine learning model using clinical, genomic, and proteomic data to predict individualized recurrence risk. Our integrated model, comprising 20 features (2 clinical factors and 18 proteins), achieved 84.8% accuracy and an AUC of 0.87 in the independent test dataset. As a comprehensive multi-center, multi-omics study of MTC, our work provides critical insights into MTC heterogeneity and aggressiveness while offering a robust framework for personalized patient management and follow-up strategies.
Project description:We report gene expression profiling in a series of 17 human medullary thyroid cancer (MTC) tissues, including 8 primary tumors and 9 patient paired neck nodes metastases, in comparison with 3 non-neoplastic thyroid tissues. For the same series we have previously reported miRNA expression profiles (GSE97070 series).