Project description:Using genome-wide approaches, we have identified groups of genes modulated by CAF-secreted factors from human breast cancer cell lines grown in different CAF-conditioned medium. The genes modulated by CAF secreted factors were characterized by a specific DNA methylation pattern: hypermethylation at transcription start site (TSS) and shore regions. Approximately 60% of them exhibited a methylation-dependent expression level and 20% of them were also dependent on the methyl-CpG-binding protein domain 2. Thus, these specific DNA methylation patterns were linked to an epigenetic control of their expression, upon CAF-secreted factors. We have therefore identified some molecular events defining the responsiveness of groups of genes to stromal cell contents in human breast tumors.
Project description:Using genome-wide approaches we have identified groups of genes modulated by CAF-secreted factors from human breast cancer cell lines grown in different CAF-conditioned medium. The genes modulated by CAF secreted factors were characterized by a specific DNA methylation pattern: hypermethylation at transcription start site (TSS) and shore regions. Approximately 60% of them exhibited a methylation-dependent expression level and 20% of them were also dependent on the methyl-CpG-binding protein domain 2. Thus, these specific DNA methylation patterns were linked to an epigenetic control of their expression, upon CAF-secreted factors. We have therefore identified some molecular events defining the responsiveness of groups of genes to stromal cell contents in human breast tumors.
Project description:We focused on studying the methylation signature of the spectrum of PNSTs to develop a methylome-based classification of these common tumors. We studied the genome-wide DNA methylation patterns using the Illumina MethylationEPIC array
Project description:We focused on studying the methylation signature of the spectrum of PNSTs to develop a methylome-based classification of these common tumors. We studied the genome-wide DNA methylation patterns using the Illumina MethylationEPIC array and classified the samples into 5 subgroups. Gene Expression comparing the subgroups were performed using bulk RNA Seq
Project description:We focused on studying the methylation signature of the spectrum of PNSTs to develop a methylome-based classification of these common tumors. We studied the genome-wide DNA methylation patterns using the Illumina MethylationEPIC array and classified the samples into 5 subgroups. Gene Expression comparing the subgroups were performed using single nuclear RNA Seq
Project description:Purpose: Multiple studies from last decades have shown that the microenvironment of carcinomas plays an important role in the initiation, progression and metastasis of cancer. Our group has previously identified novel cancer stroma gene expression signatures associated with outcome differences in breast cancer by gene expression profiling of two tumors of fibroblasts as surrogates for physiologic stromal expression patterns. The aim of this study is to find additional new types of tumor stroma gene expression patterns. Results: 53 tumors were sequenced by 3SEQ with an average of 29 million reads per sample. Both the elastofibroma (EF) and fibroma of tendon sheath (FOTS) gene signatures demonstrated robust outcome results for survival in the four breast cancer datasets. The EF signature positive breast cancers (20-33% of the cohort) demonstrated significantly better outcome for survival. In contrast, the FOTS signature positive breast cancers (11-35% of the cohort) had a worse outcome. The combined stromal signatures of EF, FOTS, and our previously identified DTF, and CSF1 signatures characterize, in part, the stromal expression profile for the tumor microenvironment for between 74%-90% of all breast cancers. Conclusions: We defined and validated two new stromal signatures in breast cancer (EF and FOTS), which are significantly associated with prognosis. Gene expression profiling by 3SEQ was performed on 8 additional types of fibrous tumors, to identify different fibrous tumor specific gene expression signatures. We then determined the significance of the fibrous tumor gene signatures in four publically available breast cancer datasets (GSE1456, GSE4922, GSE3494, NKI Dataset).
Project description:To better understand the biology of hormone receptor-positive and negative breast cancer and to identify methylated gene markers of disease progression, we performed a genome-wide methylation array analysis on 103 primary invasive breast cancers and 21 normal breast samples using the Illumina Infinium HumanMethylation27 array that queried 27,578 CpG loci. Estrogen and/or progesterone receptor-positive tumors displayed more hypermethylated loci than ER-negative tumors. However, the hypermethylated loci in ER-negative tumors were clustered closer to the transcriptional start site compared to ER-positive tumors. An ER-classifier set of CpG loci was identified, which independently partitioned primary tumors into ER-subtypes. Forty (32 novel, 8 previously known) CpG loci showed differential methylation specific to either ER-positive or ER-negative tumors. Each of the 40 ER-subtype-specific loci was validated in silico using an independent, publicly available methylome dataset from The Cancer Genome Atlas (TCGA). In addition, we identified 100 methylated CpG loci that were significantly associated with disease progression; the majority of these loci were informative particularly in ER-negative breast cancer. Overall, the set was highly enriched in homeobox containing genes. This pilot study demonstrates the robustness of the breast cancer methylome and illustrates its potential to stratify and reveal biological differences between ER-subtypes of breast cancer. Further, it defines candidate ER-specific markers and identifies potential markers predictive of outcome within ER subgroups. Frozen breast cancer tissues that were excised from patients with Stage 1-3 disease prior to treatment (n=103) were retrieved from Surgical Pathology at Johns Hopkins Hospital (Baltimore, Maryland) and confirmed to contain > 50% epithelial cells. Normal breast organoids were prepared by enzymatic digestion of reduction mammoplasty specimens (n=15; median patient age = 52 years, range 47 to 71). Normal ducts from breast tissue > 2 cm away from the tumor (n=6) were isolated from cryosections using laser-capture micro-dissection (PALM MicroBeam, Carl Zeiss Microimaging, North America). To determine the differences in breast cancer biology/behavior between ER subtypes, we characterized methylation patterns at 8376 selected CpG loci according to ER status. These loci met two criteria: 1) showed the most variation across primary tumors (SD >0.100) and 2) had probe detection p-values <0.0001. To develop an epigenomic signature that predicts outcome in patients with breast cancer, we conducted differential methylation analysis on primary tumors from recurrent versus non-recurrent breast cancers. We used a subgroup of 82 well-annotated, invasive breast tumors derived from the discovery set of 103 tumors that included 44 ER-positive (7 recurrences) and 38 ER-negative (11 recurrences) breast cancers and independently queried the ER-positive and ER-negative tumor groups
Project description:Genome-wide DNA methylation profiling of non-small cell lung cancer (NSCLC) cell line A549 and breast cancer cell line MDA-MB-231 stably expressing hSTELLA and mSTELLA, as well as the HCT116 xenograft tumor tissues from the mice treated by the indicated LNP formulations. The Infinium MethylationEPIC v2.0 array was used to obtain DNA methylation profiles across more than 935,000 CpGs in 15 samples. Samples included 3 stable NSCLC cells and 3 stable breast cancer cells expressing the STELLA orthologs, and 9 xenograft tumors from the mice with the indicated treatments.
