Tumour heterogeneity is an obstacle to effective breast cancer diagnosis and therapy. DNA methylation is an important regulator of gene expression, thus characterizing tumour heterogeneity by epigenetic features can be clinically informative. In this study, we explored specific prognosis‐subtypes based on DNA methylation status using 669 breast cancers from the TCGA database. Nine subgroups were distinguished by consensus clustering using 3869 CpGs that significantly influenced survival. The specific DNA methylation patterns were reflected by different races, ages, tumour stages, receptor status, histological types, metastasis status and prognosis. Compared with the PAM50 subtypes, which use gene expression clustering, DNA methylation subtypes were more elaborate and classified the Basal‐like subtype into two different prognosis‐subgroups. Additionally, 1252 CpGs (corresponding to 888 genes) were identified as specific hyper/hypomethylation sites for each specific subgroup. Finally, a prognosis model based on Bayesian network classification was constructed and used to classify the test set into DNA methylation subgroups, which corresponded to the classification results of the train set. These specific classifications by DNA methylation can explain the heterogeneity of previous molecular subgroups in breast cancer and will help in the development of personalized treatments for the new specific subtypes.

Although systematic studies have identified a host of long non-coding RNAs (lncRNAs) which are involved in breast cancer, the knowledge about the methyla-tion-mediated dysregulation of those lncRNAs remains limited. Here, we integrated multi-omics data to analyze the methylated alteration of lncRNAs in breast invasive carcinoma (BRCA). We found that lncRNAs showed diverse methylation patterns on promoter regions in BRCA. LncRNAs were divided into two categories and four subcategories based on their promoter methylation patterns and expression levels be-tween tumor and normal samples. Through cis-regulatory analysis and gene ontology network, abnormally methylated lncRNAs were identified to be associated with can-cer regulation, proliferation or expression of transcription factors. Competing endog-enous RNA network and functional enrichment analysis of abnormally methylated lncRNAs showed that lncRNAs with different methylation patterns were involved in several hallmarks and KEGG pathways of cancers significantly. Finally, survival analysis based on mRNA modules in networks revealed that lncRNAs silenced by high methylation were associated with prognosis significantly in BRCA. This study enhances the understanding of aberrantly methylated patterns of lncRNAs and pro-vides a novel insight for identifying cancer biomarkers and potential therapeutic tar-gets in breast cancer.

Several studies have found that DNA methylation is associated with transcriptional regulation and affect sponge regulation of non-coding RNAs in cancer. The integration of circRNA, miRNA, DNA methylation and gene expression data to identify sponge circRNAs is important for revealing the role of DNA methylation-mediated regulation of sponge circRNAs in cancer progression. We established a DNA methylation-mediated circRNA crosstalk network by integrating gene expression, DNA methylation and non-coding RNA data of breast cancer in TCGA. Four modules (26 candidate circRNAs) were mined. Next, 10 DNA methylation-mediated sponge circRNAs (sp_circRNAs) and five sponge driver genes (sp_driver genes) in breast cancer were identified in the CMD network using a computational process. Among the identified genes, ERBB2 was associated with six sponge circRNAs, which illustrates its better sponge regulatory function. Survival analysis showed that DNA methylations of 10 sponge circRNA host genes are potential prognostic biomarkers in the TCGA dataset (p = 0.0239) and GSE78754 dataset (p = 0.0377). In addition, the DNA methylation of two sponge circRNA host genes showed a significant negative correlation with their driver gene expressions. We developed a strategy to predict sponge circRNAs by DNA methylation mediated with playing the role of regulating breast cancer sponge driver genes.

One hundred and thirty-six copy number gain and 142 copy number loss cell lines were classified into CIMP-high and CIMP-low groups, meanwhile 9 and 24 CIMP-associated drugs were identified, respectively. Specially, breast invasive carcinoma samples primarily composed by HCC1419 were predicted to be sensitive to GSK690693. The study provides guidance for drug response in cancer therapy through genome-wide DNA methylation.

IntroductionThe coal-manufacturing districts in the Eastern Yunnan province of Southwest China are the utmost occurrence and death of lung tumors. As previously reported on unique clinical characteristics of non-small cell lung cancer (NSCLC) in patients from these regions without a clear understanding of the aetiology and molecular characteristics. We aim to identify the unique driver gene mutations spectrum.Material and methodsSamples from 1120 NSCLC patients from Eastern Yunnan were gathered for next-generation sequencing. Seventeen gene targets were sequenced. We have compared individuals' medical and genetic features from the coal- and non-coal-manufacturing zones.ResultsThe mutation rates of EGFR (L858R, 19-Del, G719X+L861X, L858R+EGFR amplification) and ERBB2 (20ins) were low in patients from coal-manufacturing regions. Interestingly, EGFR (G719X, S768I, G719X+S768I), KRAS (G12C), TP53 (R158L) and NTRK3 demonstrated a much higher mutation frequency. Furthermore, EGFR compound mutations were linked with the patient's job and TNM staging IIIb-IV. The OncodriverCLUST algorithm authenticated 6 genes (KRAS, EGFR, ROS1, NRAS, BRAF, and ERBB2) as driver genes in patients from coal manufacturing. EGFR with KRAS, BRAF, RET, and TP53 with ALK and KRAS were mutually exclusive. Mutations in the TP53 signaling pathway were the most common in NSCLC patients from the coal-fabricating districts.ConclusionsOur analyses confirmed the unique spectrum of driver genetic mutations and emphasized the potential of future targeted therapy in NSCLC patients from the coal-manufacturing districts of Eastern Yunnan. Our data broaden the view of NSCLC pathogenesis and its relationship with the environmental conditions in coal-producing regions.