Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

DNA Methylation-based Stratification of Pediatric Thyroid Carcinoma Invasiveness [2nd batch]

ABSTRACT: Accurate triage of pediatric thyroid carcinomas requires reliable biomarkers of tumor invasiveness. DNA methylation, a proven molecular analyte for cancer classification, offers potential for stratifying thyroid carcinoma behavior. In a cohort of 88 patients, we identified distinct methylation profiles associated with both tumor invasiveness and driver mutations, such as BRAF p.V600E, Ras-like, kinase fusions, and DICER1 mutations. Differentially methylated regions implicate immune infiltration and disrupted thyroid tissue development and function, implicating nuclear receptor, Hippo, and AP1 signaling pathways. Using these features, we developed accurate classifiers for tumor invasiveness and driver mutation groups. Our findings highlight the clinical utility of DNA methylation profiling for risk stratification and prognostic assessment in pediatric thyroid cancers.

ORGANISM(S): Homo sapiens

PROVIDER: GSE312587 | GEO | 2026/02/04

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

DNA Methylation-based Stratification of Pediatric Thyroid Carcinoma Invasiveness [1st batch]

Project description:Accurate triage of pediatric thyroid carcinomas requires reliable biomarkers of tumor invasiveness. DNA methylation, a proven molecular analyte for cancer classification, offers potential for stratifying thyroid carcinoma behavior. In a cohort of 88 patients, we identified distinct methylation profiles associated with both tumor invasiveness and driver mutations, such as BRAF p.V600E, Ras-like, kinase fusions, and DICER1 mutations. Differentially methylated regions implicate immune infiltration and disrupted thyroid tissue development and function, implicating nuclear receptor, Hippo, and AP1 signaling pathways. Using these features, we developed accurate classifiers for tumor invasiveness and driver mutation groups. Our findings highlight the clinical utility of DNA methylation profiling for risk stratification and prognostic assessment in pediatric thyroid cancers.

2026-02-04 | GSE296440 | GEO

DNA Methylation-based Stratification of Pediatric Thyroid Carcinoma Invasiveness [2nd batch]

Project description:DNA Methylation-based Stratification of Pediatric Thyroid Carcinoma Invasiveness [2nd batch]

| PRJNA1374272 | ENA

DNA Methylation-based Stratification of Pediatric Thyroid Carcinoma Invasiveness

Project description:DNA Methylation-based Stratification of Pediatric Thyroid Carcinoma Invasiveness

| PRJNA1377594 | ENA

DNA Methylation-based Stratification of Pediatric Thyroid Carcinoma Invasiveness [1st batch]

Project description:DNA Methylation-based Stratification of Pediatric Thyroid Carcinoma Invasiveness [1st batch]

| PRJNA1259388 | ENA

Novel kinase fusion oncogenes in post-Chernobyl radiation-induced pediatric thyroid cancers

Project description:Exposure to ionizing radiation during childhood markedly increases the risk of developing papillary thyroid cancer. We identified non-overlapping somatic driver mutations in all 26 cases of post-Chernobyl thyroid cancers we studied through candidate gene assays and next generation RNA-sequencing. We found that 22/26 harbored fusion oncogenes arising primarily through intrachromosomal rearrangements. Altogether 23/26 of the oncogenic drivers identified in this cohort aberrantly activate MAPK signaling, including the two novel somatic rearrangements ETV6-NTRK3 and AGK-BRAF. Two other tumors harbored distinct fusions leading to overexpression of the nuclear receptor PPARγ. A lower prevalence of fusion oncogenes was found in a cohort of pediatric thyroid cancers from children from the same geographical regions that were not exposed to radiation. Radiation-induced thyroid cancers are a paradigm of tumorigenesis driven by fusion oncogenes that activate MAPK signaling or, less frequently, a PPARγ-driven transcriptional program. Examination of transcriptome profiles and genetic somatic changes in thyroid cancer.

2013-10-25 | E-GEOD-48850 | biostudies-arrayexpress

RNA-Sequencing of human papillary thyroid carcinomas

Project description:RNA-Sequencing analysis of 18 papillary thyroid carcinoma biopsies and of 4 healthy donors' thyroids. In this analysis we assessed differential gene expression and investigated the mutational landscape in this tumor type. Analysis of gene fusion was also performed, leading to the identification of a novel chimeric transcript, potential driver in tumor initiation. Total RNA isolated from 18 papillary thyroid carcinoma biopsies and 4 healthy donors' thyroids.

2015-05-01 | E-GEOD-64912 | biostudies-arrayexpress

Comprehensive DNA methylation profiling identifies novel diagnostic biomarkers for thyroid cancer

Project description:DNA methylation markers in thyroid tumor We used Illumina HumanMethylation EPIC bead array containing over the 850,000 CpG sites in 34 thyroid normal and tumor samples to identify thyroid subtype-specfic DNA methylation markers.

2020-01-01 | GSE121377 | GEO

Mitochondrial SHMT2 is a crucial therapeutic target in dedifferentiated thyroid cancer (2nd study)

Project description:The roles of the serine/glycine metabolic pathway (SGP) have recently been evident in certain types of tumor physiology; however, the pathological relevance of SGP in undifferentiated thyroid cancer remains unexplored. Herein, we employed a comparative transcriptome analysis of bulk RNA sequencing coupled with single-cell RNA sequencing, showing that the high expression of SHMT2 and MTHFD2 is tightly associated with a low thyroid differentiation score (TDS) and poor clinical features in thyroid cancer. In addition, unique metabolic reprogramming of SGP-relevant pathways in dedifferentiated cancer cells, and a distinct trajectory of a subpopulation of tumor cells with a high mitochondrial one-carbon pathway was observed. More importantly, such dramatic changes are functionally relevant, as inhibition of SHMT2 significantly compromises mitochondrial respiration and decreases tumor size by upregulating TDS markers. Taken together, our results highlight the importance of the mitochondrial one-carbon pathway, including SGP, in undifferentiated thyroid cancer and suggest that SHMT2 is a novel therapeutic target. RNA-seq data of 65 fresh frozen normal tissues were generated. Total RNA was isolated by RNeasy Mini Kit (Qiagen, CA, USA), according to the manufacturer's protocol. The quality and integrity of the RNA were confirmed by agarose gel electrophoresis and ethidium bromide staining, followed by visual examination under ultraviolet light. Sequencing library was prepared using TruSeq RNA Sample Preparation kit v2 (Illumina, CA, USA) according to the manufacturer’s protocols. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads, fragmented, and converted into cDNAs. Then, adapters were ligated and the fragments were amplified on a PCR. Sequencing was performed in paired end reads (2x75 bp) using NextSeq 500 platform (Illumina).

2024-07-01 | GSE223765 | GEO

RNA-seq of tumor cells sorted from YAPS127A and BrafV600E/YAPS127A mouse thyroid tumors

Project description:We performed high-throughput RNA sequencing of tumor cells sorted from YAPS127A and BrafV600E/YAPS127A to investigate YAP dependency and driver cooperativity in thyroid tumor progression.

2023-03-09 | GSE198381 | GEO

Classification of pediatric soft and bone sarcomas using DNA methylation-based profiling

Project description:Pediatric sarcomas present heterogeneous morphology, genetics and clinical behavior posing a challenge for an accurate diagnosis. DNA methylation is an epigenetic modification that coordinates chromatin structure and regulates gene expression, determining cell type and function. DNA methylation-based tumor profiling classifier for sarcomas (known as sarcoma classifier) from the German Cancer Research Center (Deutsches Krebsforschungszentrum) was applied to 122 pediatric sarcomas referred to a reference pediatric oncology hospital. The classifiers reported 88.5% of agreement between histopathological and molecular classification confirming the initial diagnosis of all osteosarcomas and Ewing sarcomas. Transcriptome raw data quality was verified with FASTQC. We used STAR-fusion to identify and annotate fusion transcripts based on discordant read alignments with default configurations. ChimeraViz was used to plot fusion-genes.

2024-11-05 | GSE275159 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data