Leukocyte DNA as Surrogate for the Evaluation of Imprinted Loci Methylation in Mammary Tissue DNA

There is growing interest in identifying surrogate tissues to identify epimutations in cancer patients since primary target tissues are often difficult to obtain. Methylation patterns at imprinted loci are established during gametogenesis and post fertilization and their alterations have been associated with elevated risk of cancer. Methylation at several imprinted differentially methylated regions (GRB10 ICR, H19 ICR, KvDMR, SNRPN/SNURF ICR, IGF2 DMR0, and IGF2 DMR2) were analyzed in DNA from leukocytes and mammary tissue (normal, benign diseases, or malignant tumors) from 87 women with and without breast cancer (average age of cancer patients: 53; range: 31–77). Correlations between genomic variants and DNA methylation at the studied loci could not be assessed, making it impossible to exclude such effects. Methylation levels observed in leukocyte and mammary tissue DNA were close to the 50% expected for monoallellic methylation. While no correlation was observed between leukocyte and mammary tissue DNA methylation for most of the analyzed imprinted genes, Spearman's correlations were statistically significant for IGF2 DMR0 and IGF2 DMR2, although absolute methylation levels differed. Leukocyte DNA methylation levels of selected imprinted genes may therefore serve as surrogate markers of DNA methylation in cancer tissue

Breast Cancer in the Personal Genomics Era

Breast cancer is a heterogeneous disease with a complex etiology that develops from different cellular lineages, progresses along multiple molecular pathways, and demonstrates wide variability in response to treatment. The “standard of care” approach to breast cancer treatment in which all patients receive similar interventions is rapidly being replaced by personalized medicine, based on molecular characteristics of individual patients. Both inherited and somatic genomic variation is providing useful information for customizing treatment regimens for breast cancer to maximize efficacy and minimize adverse side effects. In this article, we review (1) hereditary breast cancer and current use of inherited susceptibility genes in patient management; (2) the potential of newly-identified breast cancer-susceptibility variants for improving risk assessment; (3) advantages and disadvantages of direct-to-consumer testing; (4) molecular characterization of sporadic breast cancer through immunohistochemistry and gene expression profiling and opportunities for personalized prognostics; and (5) pharmacogenomic influences on the effectiveness of current breast cancer treatments. Molecular genomics has the potential to revolutionize clinical practice and improve the lives of women with breast cancer

Differential Gene Expression in Primary Breast Tumors Associated with Lymph Node Metastasis

Lymph node status remains one of the most useful prognostic indicators in breast cancer; however, current methods to assess nodal status disrupt the lymphatic system and may lead to secondary complications. Identification of molecular signatures discriminating lymph node-positive from lymph node-negative primary tumors would allow for stratification of patients requiring surgical assesment of lymph nodes. Primary breast tumors from women with negative (n = 41) and positive (n = 35) lymph node status matched for possible confounding factors were subjected to laser microdissection and gene expression data generated. Although ANOVA analysis (P < .001, fold-change >1.5) revealed 13 differentially expressed genes, hierarchical clustering classified 90% of node-negative but only 66% of node-positive tumors correctly. The inability to derive molecular profiles of metastasis in primary tumors may reflect tumor heterogeneity, paucity of cells within the primary tumor with metastatic potential, influence of the microenvironment, or inherited host susceptibility to metastasis

PSPHL and breast cancer in African American women: causative gene or population stratification?

Abstract Background Phophoserine phosphatase-like (PSPHL) is expressed at significantly higher levels in breast tumors from African American women (AAW) compared to Caucasian women (CW). How overexpression of PSPHL contributes to outcome disparities is unclear, thus, molecular mechanisms driving expression differences between populations were evaluated. Results PCR was used to detect deletion of 30-Kb of chromosome 7p11 including the first three exons of PSPHL using genomic DNA from AAW (199 with invasive breast cancer, 360 controls) and CW (invasive breast cancer =589, 364 controls). Gene expression levels were evaluated by qRT-PCR using RNA isolated from tumor tissue and blood. Data were analyzed using chi-square analysis and Mann–Whitney U-tests; P &lt; 0.05 was used to define significance. Gene expression levels correlated with deletion status: patients homozygous for the deletion had no detectable expression of PSPHL, while heterozygous had expression levels 2.1-fold lower than those homozygous for retention of PSPHL. Homozygous deletion of PSPHL was detected in 61% of CW compared to 6% of AAW with invasive breast cancer (P &lt; 0.0001); genotype frequencies did not differ significantly between AAW with and without breast cancer (P = 0.211). Conclusions Thus, deletion of 7p11, which prevents expression of PSPHL, is significantly higher in CW compared to AAW, suggesting that this 30-kb deletion and subsequent disruption of PSPHL may be a derived trait in Caucasians. The similar frequency of the deletion allele in AAW with and without invasive breast cancer suggests that this difference represent population stratification, and does not contribute to cancer disparities. </jats:sec

Sequence-based detection of mutations in cadherin 1 to determine the prevalence of germline mutations in patients with invasive lobular carcinoma of the breast

BACKGROUND: Loss of cadherin 1 (CDH1) expression, which is normally involved in cell adhesion and maintenance of tissue architecture, is a hallmark of invasive lobular carcinoma (ILCA). Because hereditary cancers may require different risk reduction, counseling and treatment options than sporadic cancer, it is critical to determine the prevalence of germline CDH1 mutations in patients with ILCA. METHODS: All patients with ILCA (n = 100) previously enrolled in the Clinical Breast Care Project were identified. Genomic DNA was isolated from peripheral blood samples and DNA variants were detected for each exon of CDH1 using high-resolution melting technology followed by direct sequencing. RESULTS: Within the 100 samples screened, four nonsynonymous variants were detected: A592T in one Hispanic patient, A617T in two patients, both African American, P825L in a Causasian patient whose grandmother had stomach cancer, and G879S in a Caucasian patient. Further evaluation of A617T in an additional 165 African American patients found that 11 patients, none with ILCA, carried this variant including one patient who was homozygous for the variant. CONCLUSIONS: CDH1 mutations are infrequent in patients with ILCA, and the variants that were detected have been classified as non-pathogenic. These data suggest that ILCA does not have a significant hereditary component and do not support CDH1 gene mutation testing in patients with ILCA

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Detecting Outlier Microarray Arrays by Correlation and Percentage of Outliers Spots

We developed a quality assurance (QA) tool, namely microarray outlier filter (MOF), and have applied it to our microarray datasets for the identification of problematic arrays. Our approach is based on the comparison of the arrays using the correlation coefficient and the number of outlier spots generated on each array to reveal outlier arrays. For a human universal reference (HUR) dataset, which is used as a technical control in our standard hybridization procedure, 3 outlier arrays were identified out of 35 experiments. For a human blood dataset, 12 outlier arrays were identified from 185 experiments. In general, arrays from human blood samples displayed greater variation in their gene expression profiles than arrays from HUR samples. As a result, MOF identified two distinct patterns in the occurrence of outlier arrays. These results demonstrate that this methodology is a valuable QA practice to identify questionable microarray data prior to downstream analysis