Accelerated aging in normal breast tissue of women with breast cancer.

BACKGROUND: DNA methylation alterations have similar patterns in normal aging tissue and in cancer. In this study, we investigated breast tissue-specific age-related DNA methylation alterations and used those methylation sites to identify individuals with outlier phenotypes. Outlier phenotype is identified by unsupervised anomaly detection algorithms and is defined by individuals who have normal tissue age-dependent DNA methylation levels that vary dramatically from the population mean. METHODS: We generated whole-genome DNA methylation profiles (GSE160233) on purified epithelial cells and used publicly available Infinium HumanMethylation 450K array datasets (TCGA, GSE88883, GSE69914, GSE101961, and GSE74214) for discovery and validation. RESULTS: We found that hypermethylation in normal breast tissue is the best predictor of hypermethylation in cancer. Using unsupervised anomaly detection approaches, we found that about 10% of the individuals (39/427) were outliers for DNA methylation from 6 DNA methylation datasets. We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) than in normal samples (15/228, 5.2%). Additionally, we found significant differences between the predicted ages based on DNA methylation and the chronological ages among outliers and not-outliers. Additionally, we found that accelerated outliers (older predicted age) were more frequent in normal-adjacent to cancer (14/17, 82%) compared to normal samples from individuals without cancer (3/17, 18%). Furthermore, in matched samples, we found that the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer. CONCLUSIONS: A subset of patients with breast cancer has severely altered epigenomes which are characterized by accelerated aging in their normal-appearing tissue. In the future, these DNA methylation sites should be studied further such as in cell-free DNA to determine their potential use as biomarkers for early detection of malignant transformation and preventive intervention in breast cancer.

The Protein Encoded by the CCDC170 Breast Cancer Gene Functions to Organize the Golgi-Microtubule Network.

Genome-Wide Association Studies (GWAS) and subsequent fine-mapping studies (>50) have implicated single nucleotide polymorphisms (SNPs) located at the CCDC170/C6ORF97-ESR1 locus (6q25.1) as being associated with the risk of breast cancer. Surprisingly, our analysis using genome-wide differential allele-specific expression (DASE), an indicator for breast cancer susceptibility, suggested that the genetic alterations of CCDC170, but not ESR1, account for GWAS-associated breast cancer risk at this locus. Breast cancer-associated CCDC170 nonsense mutations and rearrangements have also been detected, with the latter being specifically implicated in driving breast cancer. Here we report that the wild type CCDC170 protein localizes to the region of the Golgi apparatus and binds Golgi-associated microtubules (MTs), and that breast cancer-linked truncations of CCDC170 result in loss of Golgi localization. Overexpression of wild type CCDC170 triggers Golgi reorganization, and enhances Golgi-associated MT stabilization and acetyltransferase ATAT1-dependent α-tubulin acetylation. Golgi-derived MTs regulate cellular polarity and motility, and we provide evidence that dysregulation of CCDC170 affects polarized cell migration. Taken together, our findings demonstrate that CCDC170 plays an essential role in Golgi-associated MT organization and stabilization, and implicate a mechanism for how perturbations in the CCDC170 gene may contribute to the hallmark changes in cell polarity and motility seen in breast cancer.

LincIN, a novel NF90-binding long non-coding RNA, is overexpressed in advanced breast tumors and involved in metastasis.

BACKGROUND: Recent genome-wide profiling by sequencing and distinctive chromatin signatures has identified thousands of long non-coding RNA (lncRNA) species (>200 nt). LncRNAs have emerged as important regulators of gene expression, involving in both developmental and pathological processes. While altered expression of lncRNAs has been observed in breast cancer development, their roles in breast cancer progression and metastasis are still poorly understood. METHODS: To identify novel breast cancer-associated lncRNA candidates, we employed a high-density SNP array-based approach to uncover intergenic lncRNA genes that are aberrantly expressed in breast cancer. We first evaluated the potential value as a breast cancer prognostic biomarker for one breast cancer-associated lncRNA, LincIN, using a breast cancer cohort retrieved from The Cancer Genome Atlas (TCGA) Data Portal. Then we characterized the role of LincIN in breast cancer progression and metastasis by in vitro invasion assay and a mouse tail vein injection metastasis model. To study the action of LincIN, we identified LincIN-interacting protein partner(s) by RNA pull-down experiments followed with protein identification by mass spectrometry. RESULTS: High levels of LincIN expression are frequently observed in tumors compared to adjacent normal tissues, and are strongly associated with aggressive breast cancer. Importantly, analysis of TCGA data further suggest that high expression of LincIN is associated with poor overall survival in patients with breast cancer (P = 0.044 and P = 0.011 after adjustment for age). The functional experiments demonstrate that knockdown of LincIN inhibits tumor cell migration and invasion in vitro, which is supported by the results of transcriptome analysis in the LincIN-knockdown cells. Furthermore, knockdown of LincIN diminishes lung metastasis in a mouse tail vein injection model. We also identified a LincIN-binding protein, NF90, through which overexpression of LincIN may repress p21 protein expression by inhibiting its translation, and upregulation of p21 by LincIN knockdown may be associated with less aggressive metastasis phenotypes. CONCLUSIONS: Our studies provide clear evidence to support LincIN as a new regulator of tumor progression-metastasis at both transcriptional and translational levels and as a promising prognostic biomarker for breast cancer.

Identifying a highly-aggressive DCIS subgroup by studying intra-individual DCIS heterogeneity among invasive breast cancer patients.

The heterogeneity among multiple ductal carcinoma in situ (DCIS) lesions within the same patient also diagnosed with invasive ductal carcinoma (IDC) has not been well evaluated, leaving research implications of intra-individual DCIS heterogeneity yet to be explored. In this study formalin-fixed paraffin embedded sections from 36 patients concurrently diagnosed with DCIS and IDC were evaluated by immunohistochemistry. Ten DCIS lesions from each patient were then randomly selected and scored. Our results showed that expression of PR, HER2, Ki-67, and p16 varied significantly within DCIS lesions from a single patient (P<0.05 for PR; P<1×10(-8) for HER2, Ki-67 and p16). In addition, seventy-two percent of the individuals had heterogeneous expression of at least 2/6 markers. Importantly, by evaluating the expression of promising DCIS risk biomarkers (Ki-67, p53 and p16) among different DCIS subgroups classified by comparing DCIS molecular subtypes with those of adjacent normal terminal duct lobular units (TDLU) and IDC, our results suggest the existence of a highly-aggressive DCIS subgroup, which had the same molecular subtype as the adjacent IDC but not the same subtype as the adjacent normal TDLU. By using a systematic approach, our results clearly demonstrate that intra-individual heterogeneity in DCIS is very common in patients concurrently diagnosed with IDC. Our novel findings of a DCIS subpopulation with aggressive characteristics will provide a new paradigm for mechanistic studies of breast tumor progression and also have broad implications for prevention research as heterogeneous pre-invasive lesions are present in many other cancer types.

Identifying putative breast cancer-associated long intergenic non-coding RNA loci by high density SNP array analysis.

Recent high-throughput transcript discoveries have yielded a growing recognition of long intergenic non-coding RNAs (lincRNAs), a class of arbitrarily defined transcripts (>200 nt) that are primarily produced from the intergenic space. lincRNAs have been increasingly acknowledged for their expressional dynamics and likely functional associations with cancers. However, differential gene dosage of lincRNA genes between cancer genomes is less studied. By using the high-density Human Omni5-Quad BeadChips (Illumina), we investigated genomic copy number aberrations in a set of seven tumor-normal paired primary human mammary epithelial cells (HMECs) established from patients with invasive ductal carcinoma. This Beadchip platform includes a total of 2,435,915 SNP loci dispersed at an average interval of ~700 nt throughout the intergenic region of the human genome. We mapped annotated or putative lincRNA genes to a subset of 332,539 SNP loci, which were included in our analysis for lincRNA-associated copy number variations (CNV). We have identified 122 lincRNAs, which were affected by somatic CNV with overlapped aberrations ranging from 0.14% to 100% in length. lincRNA-associated aberrations were detected predominantly with copy number losses and preferential clustering to the ends of chromosomes. Interestingly, lincRNA genes appear to be less susceptible to CNV in comparison to both protein-coding and intergenic regions (CNV affected segments in percentage: 1.8%, 37.5%, and 60.6%, respectively). In summary, our study established a novel approach utilizing high-resolution SNP array to identify lincRNA candidates, which could functionally link to tumorigenesis, and provide new strategies for the diagnosis and treatment of breast cancer.

Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome.

BACKGROUND: The significant mortality associated with breast cancer (BCa) suggests a need to improve current research strategies to identify new genes that predispose women to breast cancer. Differential allele-specific expression (DASE) has been shown to contribute to phenotypic variables in humans and recently to the pathogenesis of cancer. We previously reported that nonsense-mediated mRNA decay (NMD) could lead to DASE of BRCA1/2, which is associated with elevated susceptibility to breast cancer. In addition to truncation mutations, multiple genetic and epigenetic factors can contribute to DASE, and we propose that DASE is a functional index for cis-acting regulatory variants and pathogenic mutations, and that global analysis of DASE in breast cancer precursor tissues can be used to identify novel causative alleles for breast cancer susceptibility. RESULTS: To test our hypothesis, we employed the Illumina(®) Omni1-Quad BeadChip in paired genomic DNA (gDNA) and double-stranded cDNA (ds-cDNA) samples prepared from eight BCa patient-derived normal mammary epithelial lines (HMEC). We filtered original array data according to heterozygous genotype calls and calculated DASE values using the Log ratio of cDNA allele intensity, which was normalized to the corresponding gDNA. We developed two statistical methods, SNP- and gene-based approaches, which allowed us to identify a list of 60 candidate DASE loci (DASE ≥ 2.00, P ≤ 0.01, FDR ≤ 0.05) by both methods. Ingenuity Pathway Analysis of DASE loci revealed one major breast cancer-relevant interaction network, which includes two known cancer causative genes, ZNF331 (DASE = 2.31, P = 0.0018, FDR = 0.040) and USP6 (DASE = 4.80, P = 0.0013, FDR = 0.013), and a breast cancer causative gene, DMBT1 (DASE=2.03, P = 0.0017, FDR = 0.014). Sequence analysis of a 5' RACE product of DMBT1 demonstrated that rs2981745, a putative breast cancer risk locus, appears to be one of the causal variants leading to DASE in DMBT1. CONCLUSIONS: Our study demonstrated for the first time that global DASE analysis is a powerful new approach to identify breast cancer risk allele(s).

Chromosome 17p13.2 transfer reverts transformation phenotypes and Fas-mediated apoptosis in breast epithelial cells.

Transformation of the human breast epithelial cells (HBEC) MCF-10F with the carcinogen benz(a)pyrene (BP) into BP1-E cells resulted in the loss of the chromosome 17 p13.2 locus (D17S796 marker) and formation of colonies in agar-methocel (colony efficiency (CE)), loss of ductulogenic capacity in collagen matrix, and resistance to anti-Fas monoclonal antibody (Mab)-induced apoptosis. For testing the role of that specific region of chromosome 17 in the expression of transformation phenotypes, we transferred chromosome 17 from mouse fibroblast donors to BP1-E cells. Chromosome 11 was used as negative control. After G418 selection, nine clones each were randomly selected from BP1-E-11neo and BP1-E-17neo hybrids, respectively, and tested for the presence of the donor chromosomes by fluorescent in situ hybridization and polymerase chain reaction-based restriction fragment length polymorphism (PCR-RFLP) analyses. Sensitivity to Fas Mab-induced apoptosis and evaluation of transformation phenotype expression were tested in MCF-10F, BP1-E, and nine BP1-E-11neo and BP1-E-17neo clones each. Six BP1-E-17neo clones exhibited a reversion of transformation phenotypes and a dose dependent sensitivity to Fas Mab-induced apoptosis, behaving similarly to MCF-10F cells. All BP1-E-11neo, and three BP1-E-17neo cell clones, like BP1-E cells, retained a high CE, loss of ductulogenic capacity, and were resistant to all Fas Mab doses tested. Genomic analysis revealed that those six BP1-E-17neo clones that were Fas-sensitive and reverted their transformed phenotypes had retained the 17p13.2 (D17S796 marker) region, whereas it was absent in all resistant clones, indicating that the expression of transformation phenotypes and the sensitivity of the cells to Fas-mediated apoptosis were under the control of genes located in this region.