Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

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

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE197861 | GEO | 2022/03/05

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Integrative Analysis of DNA Methylation and Gene Expression Identified Follicular Thyroid Cancer-Specific Diagnostic Biomarkers.

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 array 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.

| S-EPMC8964406 | biostudies-literature

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.

2022-03-05 | GSE197860 | GEO

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

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.

2022-03-05 | GSE197852 | GEO

Integrative analysis of DNA methylation and gene expression identified cervical cancer-specific diagnostic biomarkers.

Project description:Cervical cancer is the leading cause of death among women with cancer worldwide. Here, we performed an integrative analysis of Illumina HumanMethylation450K and RNA-seq data from TCGA to identify cervical cancer-specific DNA methylation markers. We first identified differentially methylated and expressed genes and examined the correlation between DNA methylation and gene expression. The DNA methylation profiles of 12 types of cancers, including cervical cancer, were used to generate a candidate set, and machine-learning techniques were adopted to define the final cervical cancer-specific markers in the candidate set. Then, we assessed the protein levels of marker genes by immunohistochemistry by using tissue arrays containing 93 human cervical squamous cell carcinoma samples and cancer-adjacent normal tissues. Promoter methylation was negatively correlated with the local regulation of gene expression. In the distant regulation of gene expression, the methylation of hypermethylated genes was more likely to be negatively correlated with gene expression, while the methylation of hypomethylated genes was more likely to be positively correlated with gene expression. Moreover, we identified four cervical cancer-specific methylation markers, cg07211381 (RAB3C), cg12205729 (GABRA2), cg20708961 (ZNF257), and cg26490054 (SLC5A8), with 96.2% sensitivity and 95.2% specificity by using the tenfold cross-validation of TCGA data. The four markers could distinguish tumors from normal tissues with a 94.2, 100, 100, and 100% AUC in four independent validation sets from the GEO database. Overall, our study demonstrates the potential use of methylation markers in cervical cancer diagnosis and may boost the development of new epigenetic therapies.

| S-EPMC6908647 | biostudies-literature

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

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

| PRJNA812524 | ENA

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

Project description:Integrative analysis of DNA methylation and gene expression identified follicular thyroid cancer-specific diagnostic biomarkers

| PRJNA812519 | ENA

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

Project description:Integrative analysis of DNA methylation and gene expression identified follicular thyroid cancer-specific diagnostic biomarkers [Expression]

| PRJNA812512 | ENA

Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers.

Project description:Breast cancer is a common malignant tumor among women whose prognosis is largely determined by the period and accuracy of diagnosis. We here propose to identify a robust DNA methylation-based breast cancer-specific diagnostic signature. Genome-wide DNA methylation and gene expression profiles of breast cancer patients along with their adjacent normal tissues from the Cancer Genome Atlas (TCGA) were obtained as the training set. CpGs that with significantly elevated methylation level in breast cancer than not only their adjacent normal tissues and the other ten common cancers from TCGA but also the healthy breast tissues from the Gene Expression Omnibus (GEO) were finally remained for logistic regression analysis. Another independent breast cancer DNA methylation dataset from GEO was used as the testing set. Lots of CpGs were hyper-methylated in breast cancer samples compared with adjacent normal tissues, which tend to be negatively correlated with gene expressions. Eight CpGs located at RIIAD1, ENPP2, ESPN, and ETS1, were finally retained. The diagnostic model was reliable in separating BRCA from normal samples. Besides, chromatin accessibility status of RIIAD1, ENPP2, ESPN and ETS1 showed great differences between MCF-7 and MDA-MB-231 cell lines. In conclusion, the present study should be helpful for breast cancer early and accurate diagnosis.

| S-EPMC7263199 | biostudies-literature

Integrative analysis of DNA methylation and gene expression reveals hepatocellular carcinoma-specific diagnostic biomarkers.

Project description:BACKGROUND:Hepatocellular carcinoma (HCC) is the one of the most common cancers and lethal diseases in the world. DNA methylation alteration is frequently observed in HCC and may play important roles in carcinogenesis and diagnosis. METHODS:Using the TCGA HCC dataset, we classified HCC patients into different methylation subtypes, identified differentially methylated and expressed genes, and analyzed cis- and trans-regulation of DNA methylation and gene expression. To find potential diagnostic biomarkers for HCC, we screened HCC-specific CpGs by comparing the methylation profiles of 375 samples from HCC patients, 50 normal liver samples, 184 normal blood samples, and 3780 samples from patients with other cancers. A logistic regression model was constructed to distinguish HCC patients from normal controls. Model performance was evaluated using three independent datasets (including 327 HCC samples and 122 normal samples) and ten newly collected biopsies. RESULTS:We identified a group of patients with a CpG island methylator phenotype (CIMP) and found that the overall survival of CIMP patients was poorer than that of non-CIMP patients. Our analyses showed that the cis-regulation of DNA methylation and gene expression was dominated by the negative correlation, while the trans-regulation was more complex. More importantly, we identified six HCC-specific hypermethylated sites as potential diagnostic biomarkers. The combination of six sites achieved ~?92% sensitivity in predicting HCC, ~?98% specificity in excluding normal livers, and ~?98% specificity in excluding other cancers. Compared with previously published methylation markers, our markers are the only ones that can distinguish HCC from other cancers. CONCLUSIONS:Overall, our study systematically describes the DNA methylation characteristics of HCC and provides promising biomarkers for the diagnosis of HCC.

| S-EPMC5977535 | biostudies-literature

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

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