Specimens for Septin 9 Performance
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer,Colorectal Neoplasms
PROVIDER: 2104850 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
Similar Datasets
Project description:Background: Colorectal cancer (CRC) remains a major concern with high morbidity and mortality worldwide. DNA methylation alteration plays a pivotal role in cancer development. We aimed to screen novel biomarkers for CRC diagnosis and chemotherapy-related adverse event (CRAE) prediction using the advanced Illumina Infinium MethylationEPIC (850K) BeadChip. Methods: We analyzed the methylation profiles of paired tumor and normal tissues from 21 Chinese CRC patients. After normalization by potential confounders, three types of methylation profiles (differentially methylated probes, differentially methylated regions, and gene-function-differentially methylated regions) were further studied by functional annotation and pathway enrichment analysis. At last, integrated-methylation-marker systems for CRC diagnosis and CRAE prediction were developed based on genes within the mostly related pathways and LASSO regression. Findings: Tumor-related methylation was characterized with hypermethylated promoter islands and hypomethylated intragenic openseas. CRAE-related methylation was characterized with hyper- (or hypo-) methylated intragenic (or intergenic) regions. The two most important susceptible factors for various types of CARE were inactive regeneration functions and active immune response. Differentially methylated genes were significantly enriched in neuronal system, metabolism of RNA, and extracellular matrix organization. All of the integrated-methylation-marker systems demonstrated high discriminative accuracy in both CRC diagnosis (AUROC = 1) and CRAE prediction (AUROC = 0.817-1). Interpretation: In this study, we provided new insights on the formation of CRC diagnosis and CRAE based on three types of methylation profile. The integrated-methylation-marker systems combining multiple DMPs were found to have potentially diagnostic and predictive values. Hence, our findings have important clinical implications, and further validation is warranted.
2021-08-01 | GSE159898 | GEO
Project description:Colorectal polyp is known a precursor of colorectal cancer (CRC) that holds an increased risk for progression to CRC. Circulating cell-free DNA(cfDNA) methylation has shown favorable performance in the detection and monitoring the malignant progression in a variety of cancers. Here, we conducted a study to discovery cfDNA methylation markers for the diagnosis of CRC. We first performed a genome-wide analysis using the Infinium HumanMethylationEPIC BeadChip array to identify differentially methylated CpGs (DMCs) between 8 CRC and 8 polyp tissues. Then, we validated DMCs in a larger tissue cohort and four methylation markers (cg04486886, cg06712559, cg13539460 and cg27541454) were selected as the methylation markers in tissue by LASSO and random forest models. A diagnosis prediction model was bulit based on the four markers and the methylaion diagnosis score (md-score) can effectively discriminate patients with CRC from polyp tissues. Finally, a single cfDNA methylation marker, cg27541454, was confirmed hypermethylated in CRC in the plasma validation cohort. Together, our findings suggested that the md-score derived from tissue could robustly detect CRC from polpy patients, and cg27541454 may be a promising candidate non-invasive biomarker for CRC early diagnosis.
2024-01-01 | GSE220160 | GEO
Project description:Determination of the profile of genes commonly aberrantly methylated in colorectal cancer (CRC) has substantial potential value for diagnostic and therapeutic application. However, our knowledge of the DNA methylation pattern in CRC is currently limited. Therefore, we analyzed the methylation profile of 27,578 CpG sites spanning more than 14,000 genes in CRC and in adjacent normal mucosa using beadchip array-based technology. We identified 621 CpG sites located in promoter region and CpG islands that were significantly hypermethylated in CRC compared to normal mucosa. Genes on chromosome 18 showed promoter hypermethylation most frequently. According to gene ontology analysis, the most common biologically relevant class of genes affected by methylation was the class associated with the cadherin signaling pathway. In comparison with genome-wide expression array, mRNA expression was more like to be down-regulated in the genes demonstrating promoter hypermethylation, although this was not statistically significant. We validated 10 CpG sites that were shown to be hypermethylated in the array studies (ADHFE1, BOLL, SLC6A15, ADAMTS5, TFPI2, EYA4, NPY, TWIST1, LAMA1, GAS7) and 2 CpG sites showing hypomethylaion (MAEL, SFT2D3) in CRC compared to normal mucosa using pyrosequencing. The methylation status measured by pyrosequencing was consistent with the methylation array data. In conclusion, we have shown that methylation profiling based on beadchip arrays is an effective method for screening for aberrantly methylated genes in CRC. In addition, we identified novel methylated genes that are candidate diagnostic or prognostic markers for CRC. We measured the methylation status of the 27,578 CpG sites (Human Methylation27 DNA Analysis BeadChip) in 22 pairs of CRC tissue and adjacent normal mucosa to identify genes that are commonly aberrantly methylated in CRC.
2010-06-24 | E-GEOD-17648 | biostudies-arrayexpress
Project description:Colorectal tumorigenesis proceedes through well defined clinical stages assoicated with charateristic mutations. Besides genetic alterations, epi-driver genes that are aberrantly expressed in cancers in a fashion that confers a seletive growth advantage can also contribute to tumor evolution. To gain a global view of methylation patterns in normal and maliganant colorectal epithelia, we performed genome-wide DNA methylation analysis on DNAs from 48 fresh frozen CRC samples at different stages of CRC progression. We used IlluminaHumanMethylation450 Beadchip to get a broad view of genome-wide DNA methylationdata during CRC progression and identified significantly differentially methylated genes during CRC progression
2016-05-13 | GSE77954 | GEO
Project description:Colorectal tumorigenesis proceedes through well defined clinical stages assoicated with charateristic mutations. Besides genetic alterations, epi-driver genes that are aberrantly expressed in cancers in a fashion that confers a seletive growth advantage can also contribute to tumor evolution. To gain a global view of methylation patterns in normal and maliganant colorectal epithelia, we performed genome-wide DNA methylation analysis on DNAs from 48 fresh frozen CRC samples at different stages of CRC progression. We used IlluminaHumanMethylation450 Beadchip to get a broad view of genome-wide DNA methylationdata during CRC progression and identified significantly differentially methylated genes during CRC progression A total of 48 macro-dissected tissues including normal colon tissue, adenomas, carcinomas and metastases were collected by the Department of Pathology at the University of Virginia under the supervision of an experienced pathologist. DNA was extracted and run on IlluminaHumanMethylation450 Beadchip by Expression Analyisis.
2016-05-13 | E-GEOD-77954 | biostudies-arrayexpress
Project description:Post-translational arginine methylation is responsible for regulation of a variety of biological processes. The protein arginine methyltransferase 5 (PRMT5) is the major enzyme responsible for generating monomethyl- and symmetric dimethyl arginine (MMA and SDMA, respectively) in proteins. PRMT5 is essential for viability and normal development, and overexpressed in a wide variety of cancer types. In the present study, we found that the levels of PRMT5 and symmetric dimethylation in proteins from colorectal cancer (CRC) tissues are more highly maintained relative to adjacent normal tissues from patients. Using immunoaffinity enrichment of methylated peptides combined with high resolution mass spectrometry, a total of 147 SDMA sites from 94 proteins were identified. Most abundant methylated proteins identified from normal and CRC tissues are RNA processing proteins, transcriptional and translational regulators. Furthermore, when quantitative analysis of the two tissue types of samples was carried out, 77 SDMA sites exhibited statistically significant changes (>2.0-fold, p-value <0.05) between normal and CRC tissues. We confirmed KSRP, G3BP2 and TRIP6 which are more highly maintained in cancer tissues relative to adjacent normal tissues from same patients as well as the expression levels of the proteins. This study is the first comprehensive analysis of symmetric arginine dimethylation using clinical samples and suggests that the modification can be used in clinical application.
2020-06-01 | PXD015653 | Pride
Project description:Purpose: To comprehensively profile the landscape of the mRNA N6-methyladenosine (m6A) modification in human colorectal cancer (CRC). Methylated RNA immunoprecipitation sequencing (MeRIP-seq) was explored to compare the difference in mRNA N6-methyladenosine (m6A) methylation between CRC tissues and adjacent normal control (NC) tissue. RNA-sequencing (RNA-seq) was performed to transcribe differentially expressed mRNAs. Conjoint analysis of MeRIP-seq and RNA-seq data was conducted to predict RNA-binding proteins (RBPs). Results: MeRIP-seq identified 1110 differentially m6A methylated sites (DMMSs) and 980 differentially m6A methylated genes (DMMGs) in CRC, with 50.13% of all modified genes showing unique m6A-modified peaks in CRC. RNA-seq showed 915 upregulated genes and 1463 downregulated genes in CRC. QRT-PCR verified the RNA-seq results by detecting the expression of some mRNAs. Conjoint analysis of MeRIP-seq and RNA-seq identified 400 differentially m6A methylated and expressed genes (DEGs), and pathway analysis detected that DMMGs and DEGs were closely related to cancer. After analyzing these DMMGs and DEGs through the GEPIA database, we found that the expression of B3GNT6, DKC1, SRPK1 and RIMKLB were associated with prognosis, and the expression of B3GNT6 and RIMKLB were associated with clinical stage. 17 RBPs were identified based on the DMMGs and DEGs, among which FXR1, FXR2, FMR1, IGF2BP2, IGF2BP3 and SRSF1 were obviously highly expressed in CRC, and FMR1, IGF2BP2 and IGF2BP3 were closely related to methylation, and might be involved in the development of CRC. Conclusions: This study comprehensively profiled m6A modification of mRNAs in CRC, which revealed possible mechanisms of m6A-mediated gene expression regulation.
2022-02-02 | GSE190388 | GEO
Project description:The methylome of open chromatins was investigated in colorectal cancer (CRC) to explore cancer-specific methylation and potential biomarkers. Epigenome-wide methylome of open chromatins was studied in colorectal cancer tissues using Infinium DNA MethylationEPIC assay. Differentially methylated regions were identified using the ChAMP Bioconductor. Our stringent analysis led to the discovery of 2187 significant differentially methylated open chromatins in CRCs. More hypomethylated probes were observed and the trend was similar across all chromosomes. Majority of hyper- and hypomethylated probes in open chromatin were in chromosome 1. Our unsupervised hierarchical clustering analysis showed that 40 significant differentially methylated open chromatins were able to segregate CRC from normal colonic tissues. Receiver operating characteristic analyses from the top 40 probes revealed several significant, highly discriminative, specific and sensitive probes such as OPLAH cg26256223, EYA4 cg01328892, and CCNA1 cg11513637, among others. OPLAH cg26256223 hypermethylation is associated with reduced gene expression in the CRC. This study reports many open chromatin loci with novel differential methylation statuses, some of which with the potential as candidate markers for diagnostic purposes.
2020-04-25 | GSE149282 | GEO
Project description:Pancreatic ductal adenocarcinoma (PDAC) suffers from lack of an effective diagnostic method, limiting improvement in patient survival. Although the FDA-approved biomarker CA19-9 has been used for detection and surveillance of PDAC, its clinical utility is generally regarded to be limited due to its suboptimal diagnostic performance. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a burgeoning technology in clinical proteomics, and identified a plethora of protein biomarker candidates for PDAC. Yet few if any has successfully transitioned into clinical practice. This translational standstill is owed partly to the limited considerations of practical needs and perspectives of clinical implementation in the course of a biomarker pipeline, such as demonstrating analytical validity of proposed biomarkers, which is critical to turning research-grade assays to clinical-grade tests. Here, we developed a fit-for-purpose multi-marker panel for PDAC diagnosis by consolidating analytically robust biomarkers as well as employing a relatively simple LC-MS method. In the discovery phase, we systematically collected putative biomarkers from both in-house proteomics data and the large volume of literature documenting PDAC biomarkers. In the verification phase, we developed a multiple-reaction monitoring (MRM)-MS-based proteomic assay using surrogate peptides that passed stringent analytical validation criteria. Given the intended use of our panel (i.e., primary screening), we adopted a high-throughput protocol including short gradient (<10 min) and simple sample preparation (no depletion or enrichment steps). To further facilitate clinical implementation, we performed verification of our panel on serum samples, which are usually the preferred biospecimen available in clinical settings. We developed a stacking ensemble model based on our final panel of 12 protein biomarkers combined with CA19-9, which showed improved diagnostic performance compared to using CA19-9 alone (AUC 0.919 and 0.830, respectively). A large-scale clinical validation study is underway to demonstrate the clinical validity of our panel.
2024-08-12 | PXD048034 | Pride
Project description:Aberrant DNA methylation, one of the major epigenetic alterations in cancer, has been reported to accumulate in a subset of colorectal cancer (CRC), so-called CpG island methylator phenotype (CIMP), which was known to correlate with microsatellite instability (MSI)-high CRC. To select new methylation markers genome-widely and epigenotype CRC by DNA methylation comprehensively, we performed methylated DNA immunoprecipitation-on-chip analysis using MSI-high CRC cell line HCT116 and microsatellite-stable SW480, and re-expression array analysis by 5-aza-2-deoxycytidine/Trichostatin A. Methylation levels of 44 new markers selected and 16 previously reported markers were analyzed quantitatively in 149 clinical CRC samples using MALDI-TOF mass spectrometry. By unsupervised two-way hierarchical clustering, CRC was clustered into high-, intermediate-, and low-methylation epigenotypes. Methylation markers were clustered into two groups: Group-1 showing methylation in high-methylation epigenotype and including all the 11 CIMP-related markers except NEUROG1, and Group-2 showing methylation in high- and intermediate-methylation epigenotypes. Marker panel deciding methylation epigenotypes with the highest accuracy was developed: 1st-Panel consisting of Group-1 genes (CACNA1G, LOX, SLC30A10) to extract high-methylation epigenotype, and 2nd-Panel consisting of Group-2 genes (ELMO1, FBN2, THBD, HAND1) and SLC30A10 again to divide the remains into intermediate- and low-methylation epigenotypes. High-methylation epigenotype correlated significantly with BRAF mutation, MSI, proximal tumor location, and mucinous component, in concordance with reported CIMP. Intermediate- and low-methylation epigenotypes significantly correlated with KRAS-mutation(+) and KRAS-mutation(-), respectively. KRAS-mutation(+) intermediate-methylation epigenotype showed worse prognosis than KRAS-mutation(-) low-methylation epigenotype (p=0.030). These three epigenotypes with different genetic characteristics suggested different molecular CRC genesis, and the markers might be useful to predict prognosis.
2010-01-05 | GSE14526 | GEO