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DNA defects, epigenetics, and gene expression in cancer-adjacent breast: a study from The Cancer Genome Atlas.

ABSTRACT: Recurrence rates after breast-conserving therapy may depend on genomic characteristics of cancer-adjacent, benign-appearing tissue. Studies have not evaluated recurrence in association with multiple genomic characteristics of cancer-adjacent breast tissue. To estimate the prevalence of DNA defects and RNA expression subtypes in cancer-adjacent, benign-appearing breast tissue at least 2?cm from the tumor margin, cancer-adjacent, pathologically well-characterized, benign-appearing breast tissue specimens from The Cancer Genome Atlas project were analyzed for DNA sequence, copy-number variation, DNA methylation, messenger RNA (mRNA) sequence, and mRNA/microRNA expression. Additional samples were also analyzed by at least one of these genomic data types and associations between genomic characteristics of normal tissue and overall survival were assessed. Approximately 40% of cancer-adjacent, benign-appearing tissues harbored genomic defects in DNA copy number, sequence, methylation, or in RNA sequence, although these defects did not significantly predict 10-year overall survival. Two mRNA/microRNA expression phenotypes were observed, including an active mRNA subtype that was identified in 40% of samples. Controlling for tumor characteristics and the presence of genomic defects, this active subtype was associated with significantly worse 10-year survival among estrogen receptor (ER)-positive cases. This multi-platform analysis of breast cancer-adjacent samples produced genomic findings consistent with current surgical margin guidelines, and provides evidence that extratumoral RNA expression patterns in cancer-adjacent tissue predict overall survival among patients with ER-positive disease.

SUBMITTER: Troester MA

PROVIDER: S-EPMC5515343 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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DNA defects, epigenetics, and gene expression in cancer-adjacent breast: a study from The Cancer Genome Atlas.

Troester Melissa A MA Hoadley Katherine A KA D'Arcy Monica M Cherniack Andrew D AD Stewart Chip C Koboldt Daniel C DC Robertson A Gordon AG Mahurkar Swapna S Shen Hui H Wilkerson Matthew D MD Sandhu Rupninder R Johnson Nicole B NB Allison Kimberly H KH Beck Andrew H AH Yau Christina C Bowen Jay J Sheth Margi M Hwang E Shelley ES Perou Charles M CM Laird Peter W PW Ding Li L Benz Christopher C CC

NPJ breast cancer 20160504

Recurrence rates after breast-conserving therapy may depend on genomic characteristics of cancer-adjacent, benign-appearing tissue. Studies have not evaluated recurrence in association with multiple genomic characteristics of cancer-adjacent breast tissue. To estimate the prevalence of DNA defects and RNA expression subtypes in cancer-adjacent, benign-appearing breast tissue at least 2 cm from the tumor margin, cancer-adjacent, pathologically well-characterized, benign-appearing breast tissue sp ...[more]

PMID: 28721375

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Project description:BackgroundDNA methylation is a form of epigenetic modification that has been shown to play a significant role in gene regulation. In cancer, DNA methylation plays an important role by regulating the expression of oncogenes. The role of DNA methylation in the onset and progression of various cancer types is now being elucidated as more large-scale data become available. The Cancer Genome Atlas (TCGA) provides a wealth of information for the analysis of various molecular aspects of cancer genetics. Gene expression data and DNA methylation data from TCGA have been used for a variety of studies. A traditional understanding of the effects of DNA methylation on gene expression has linked methylation of CpG sites in the gene promoter region with the decrease in gene expression. Recent studies have begun to expand this traditional role of DNA methylation.ResultsHere we present a pan-cancer analysis of correlation patterns between CpG methylation and gene expression. Using matching patient data from TCGA, 33 cancer-specific correlations were calculated for each CpG site and the expression level of its corresponding gene. These correlations were used to identify patterns on a per-site basis as well as patterns of methylation across the gene body. Using these identified patterns, we found genes that contain conflicting methylation signals beyond the commonly accepted association between the promoter region methylation and silencing of gene expression. Beyond gene body methylation in whole, we examined individual CpG sites and show that, even in the same gene body, some sites can have a contradictory effect on gene expression in cancers.ConclusionsWe observed that within promoter regions there was a substantial amount of positive correlation between methylation and gene expression, which contradicts the commonly accepted association. We observed that the correlation between CpG methylation and gene expression does not exhibit in a tissue-specific manner, suggesting that the effects of methylation on gene expression are largely tissue independent. The analysis of correlation associated with the location of the CpG site in the gene body has led to the identification of several different methylation patterns that affect gene expression, and several examples of methylation activating gene expression were observed. Distinctly opposing or conflicting effects were seen in close proximity on the gene body, where negative and positive correlations were seen at the neighboring CpG sites.

Project description:BackgroundThe Cancer Genome Atlas (TCGA) has generated comprehensive molecular profiles. We aim to identify a set of genes whose expression patterns can distinguish diverse tumor types. Those features may serve as biomarkers for tumor diagnosis and drug development.MethodsUsing RNA-seq expression data, we undertook a pan-cancer classification of 9,096 TCGA tumor samples representing 31 tumor types. We randomly assigned 75% of samples into training and 25% into testing, proportionally allocating samples from each tumor type.ResultsWe could correctly classify more than 90% of the test set samples. Accuracies were high for all but three of the 31 tumor types, in particular, for READ (rectum adenocarcinoma) which was largely indistinguishable from COAD (colon adenocarcinoma). We also carried out pan-cancer classification, separately for males and females, on 23 sex non-specific tumor types (those unrelated to reproductive organs). Results from these gender-specific analyses largely recapitulated results when gender was ignored. Remarkably, more than 80% of the 100 most discriminative genes selected from each gender separately overlapped. Genes that were differentially expressed between genders included BNC1, FAT2, FOXA1, and HOXA11. FOXA1 has been shown to play a role for sexual dimorphism in liver cancer. The differentially discriminative genes we identified might be important for the gender differences in tumor incidence and survival.ConclusionsWe were able to identify many sets of 20 genes that could correctly classify more than 90% of the samples from 31 different tumor types using TCGA RNA-seq data. This accuracy is remarkable given the number of the tumor types and the total number of samples involved. We achieved similar results when we analyzed 23 non-sex-specific tumor types separately for males and females. We regard the frequency with which a gene appeared in those sets as measuring its importance for tumor classification. One third of the 50 most frequently appearing genes were pseudogenes; the degree of enrichment may be indicative of their importance in tumor classification. Lastly, we identified a few genes that might play a role in sexual dimorphism in certain cancers.

Project description:Our previously published data link P-selectin-reactive chondroitin sulfate structures on the surface of breast cancer cells to metastatic behavior of cells. We have shown that a particular sulfation pattern mediated by the expression of carbohydrate (chondroitin 4) sulfotransferase-11 (CHST11) correlates with P-selectin binding and aggressiveness of human breast cancer cell lines. The present study was performed to evaluate the prognostic value of CHST11 expression and determine whether aberrant DNA methylation controls CHST11 expression in breast cancer. Publicly available datasets were used to examine the association of CHST11 expression to aggressiveness and progression of breast cancer. Methylation status was analyzed using bisulfite genomic sequencing. 5-aza-2'-deoxycytidine (5AzadC) was used for DNA demethylation. Reduced representation bisulfite sequencing was performed in the CpG island of CHST11 with a minimum coverage of 10. Quantitative real-time RT-PCR was employed to confirm the expression profile of CHST11 in breast cancer cell lines. Flow cytometry was also used to confirm the expression of the CHST11 product, chondroitin sulfate A (CS-A). The expression of CHST11 was significantly higher in basal-like and Her2-amplified cell lines compared to luminal cell lines. CHST11 was also highly expressed in cancer tissues compared to normal tissues and the expression levels were significantly associated with tumor progression. We observed very low levels of DNA methylation in a CpG island of CHST11 in basal-like cells but very high levels in the same region in luminal cells. Treatment of MCF7 cells, a luminal cell line with very low expression of CHST11, with 5AzadC increased the expression of CHST11 and its immediate product, CS-A, in a dose-dependent manner. These results suggest that CHST11 may play a direct role in progression of breast cancer and that its expression is controlled by DNA methylation. Therefore, in addition to CHST11 mRNA levels, the methylation status of this gene also has potential as a prognostic biomarker.

Dataset Information

DNA defects, epigenetics, and gene expression in cancer-adjacent breast: a study from The Cancer Genome Atlas.

Publications

DNA defects, epigenetics, and gene expression in cancer-adjacent breast: a study from The Cancer Genome Atlas.

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