Project description:Triple negative breast cancers (TNBCs) comprise a heterogeneous group of cancers with varying prognoses, presenting a challenge for effective clinical management. Epigenetic alterations in the cancer methylome are common in breast cancer and provide novel options for tumor stratification on the basis of prognosis. Advances in genome-wide DNA methylation technology have enabled more comprehensive identification of potential epigenetic diagnostic and prognostic cancer biomarkers. Here, we use MBDCap-Seq to perform genome-wide DNA methylation profiling from archival TNBC and matched normal DNA samples. We identified 822 differentially methylated regions (DMRs) comprising 308 genes affected by cancer-specific promoter hypermethylation. Notably, 51 of these genes are also recurrently mutated in breast cancer, seven of which include members of the axon guidance pathway recently implicated in tumor initiation and progression. Using TCGA methylation data as an independent validation cohort for TNBCs (n= 73), we showed that 36 genomic regions were specific for TNBCs, including both promoter and gene body hypermethyled loci. Importantly, we stratified TNBCs into three distinct methylation clusters associated with better or worse prognosis. Furthermore, we identified a “survival” methylation signature consisting of 17 DMRs that show strong regional association with overall survival, 16 of which overlap DNase1 hypersensitive sites. Notably three of these “survival” DMRs are located in the bi-directional promoter and gene bodies of WT1 gene and its anti-sense counter-part WT1-AS. Together, our data identifies for the first time a cancer DNA methylation diagnostic and prognostic signature that promises to stratify TNBCs for more personalized management.
Project description:Triple negative breast cancer (TNBC) accounts for 15-20% of all breast carcinomas and it is clinically characterized by an aggressive phenotype and bad prognosis. TNBC does not benefit from any targeted therapy, so further characterization is needed to define subgroups with potential therapeutic value. In this work, the proteomes of one hundred twenty-five formalin-fixed paraffin-embedded samples from patients diagnosed with triple negative breast cancer were analyzed by mass spectrometry using data-independent acquisition. Hierarchical clustering, probabilistic graphical models and Significance Analysis of Microarrays were used to characterize molecular groups. Additionally, a predictive signature related with relapse was defined. Two molecular groups with differences in several biological processes as glycolysis, translation and immune response, were defined in this cohort, and a prognostic signature based on the abundance of proteins RBM3 and NIPSNAP1 was defined. This predictor split the population into low-risk and high-risk groups. The differential processes identified between the two molecular groups may serve to design new therapeutic strategies in the future and the prognostic signature could be useful to identify a population at high-risk of relapse that could be directed to clinical trials.
Project description:Epigenetic deregulation is a critical event in human malignancies. A number of DNA methylation markers are currently under evaluation as diagnostic and prognostic biomarkers for many cancers. However, its potential role in hepatocellular carcinoma (HCC) is under-explored. Aims: To develop a DNA methylation-based prognostic signature in surgically resected HCC Tumors from 224 HCC resected patients, 10 normal Liver individuals and 9 Cirrhotic patients were analyzed. Methylome profiling was done with Illumina HumanMethylation450 (485,000 CpG, 96% of known CpG islands). We selected probes in CpG islands located in promoters, hypermethylated (B value higher than 50%) in at least 5% of the tumors and hypomethylated (B value lower than 33%) in more than 90% of normal liver.
Project description:Methylome analysis of different histological thyroid lesions and clinical features, aiming to better understand the DNA methylation deregulation of TC and to identify a prognostic epigenetic signature in well differentiated thyroid carcinomas.