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Background: Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer (IBC). Studies have indicated differences in DCIS outcome based on race or ethnicity, but molecular differences have not been investigated. Methods: We examined the molecular profile of DCIS by self-reported race (SRR) and outcome groups in Black (n = 99) and White (n = 191) women in a large DCIS case-control cohort study with longitudinal follow up. Results: Gene expression and pathway analyses suggested that different genes and pathways are involved in diagnosis and ipsilateral breast outcome (DCIS or IBC) after DCIS treatment in White versus Black women. We identified differences in ER and HER2 expression, tumor microenvironment composition, and copy number variations by SRR and outcome groups. Conclusions: Our results suggest that different molecular mechanisms drive initiation and subsequent ipsilateral breast events in Black versus White women. [ABSTRACT FROM AUTHOR]

The signaling events that drive familial breast cancer ( FBC) risk remain poorly understood. While the majority of genomic studies have focused on genetic risk variants, known risk variants account for at most 30% of FBC cases. Considering that multiple genes may influence FBC risk, we hypothesized that a pathway-based strategy examining different data types from multiple tissues could elucidate the biological basis for FBC. In this study, we performed integrated analyses of gene expression and exome-sequencing data from peripheral blood mononuclear cells and showed that cell adhesion pathways are significantly and consistently dysregulated in women who develop FBC. The dysregulation of cell adhesion pathways in high-risk women was also identified by pathway-based profiling applied to normal breast tissue data from two independent cohorts. The results of our genomic analyses were validated in normal primary mammary epithelial cells from high-risk and control women, using cell-based functional assays, drug-response assays, fluorescence microscopy, and Western blotting assays. Both genomic and cell-based experiments indicate that cell-cell and cell-extracellular matrix adhesion processes seem to be disrupted in non-malignant cells of women at high risk for FBC and suggest a potential role for these processes in FBC development. [ABSTRACT FROM AUTHOR]

Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P = 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10-7). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r² with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10-7). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10-8). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r 2 = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10-8). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene. [ABSTRACT FROM AUTHOR]

Introduction: Breast cancer heterogeneity occurs as a consequence of the dysregulation of numerous oncogenic pathways as well as many non-genetic factors, including tumor microenvironmental stresses such as hypoxia, lactic acidosis, and glucose deprivation. Although the importance of these non-genetic factors is well recognized, it is not clear how to integrate these factors within the genetic framework of cancer as the next logical step in understanding tumor heterogeneity. Methods: We report here the development of a series of gene expression signatures to measure the influences of microenvironmental stresses. The pathway activities of hypoxia, lactic acidosis, acidosis and glucose deprivation were investigated in a collection of 1,143 breast tumors, which have been separated into 17 breast tumor subgroups defined by their distinct patterns of oncogenic pathways. A validation dataset comprised of 547 breast tumors was also used to confirm the major findings, and representative breast cancer cell lines were utilized to validate in silico results and mechanistic studies. Results: Through the integrative pathway analysis of microenvironmental stresses and oncogenic events in breast tumors, we identified many known and novel correlations between these two sources of tumor heterogeneity. Focusing on differences between two human epidermal growth factor receptor 2 (HER2)-related subgroups, previously identified based on patterns of oncogenic pathway activity, we determined that these subgroups differ with regards to tumor microenvironmental signatures, including hypoxia. We further demonstrate that each of these subgroups have features consistent with basal and luminal breast tumors including patterns of oncogenic signaling pathways, expression of subtype specific genes, and cellular mechanisms that regulate the hypoxia response. Importantly, we also demonstrate that the correlated pattern of hypoxia-related gene expression and basal-associated gene expression are consistent across HER2-related tumors whether we analyze the tumors as a function of our pathway-based classification scheme, using the intrinsic gene list (ERBB2+), or based on HER2 IHC status. Our results demonstrate a cell lineage-specific phenomenon in which basal-like tumors, HER2-related tumors with high hypoxia, as well as normal basal epithelial cells express increased mRNA levels of HIF-1α compared to luminal types and silencing of HIF-1α results in decreased expression of hypoxia-induced genes. Conclusions: This study demonstrates differences in microenvironmental conditions in HER2-related subgroups defined by distinct oncogenic pathway activities, and provides a mechanistic explanation for differences in the observed hypoxia response between these subgroups. Collectively, these data demonstrate the potential of a pathway-based classification strategy as a framework to integrate genetic and non-genetic factors to investigate the basis of tumor heterogeneity. [ABSTRACT FROM AUTHOR]

Background: Mutations in the TP53 gene are extremely common and occur very early in the progression of serous ovarian cancers. Gene expression patterns that relate to mutational status may provide insight into the etiology and biology of the disease. Methods: The TP53 coding region was sequenced in 89 frozen serous ovarian cancers, 40 early stage (I/II) and 49 advanced stage (III/IV). Affymetrix U133A expression data was used to define gene expression patterns by mutation, type of mutation, and cancer stage. Results: Missense or chain terminating (null) mutations in TP53 were found in 59/89 (66%) ovarian cancers. Early stage cancers had a significantly higher rate of null mutations than late stage disease (38% vs. 8%, p < 0.03). In advanced stage cases, mutations were more prevalent in short term survivors than long term survivors (81% vs. 30%, p = 0.0004). Gene expression patterns had a robust ability to predict TP53 status within training data. By using early versus late stage disease for out of sample predictions, the signature derived from early stage cancers could accurately (86%) predict mutation status of late stage cancers. Conclusions: This represents the first attempt to define a genomic signature of TP53 mutation in ovarian cancer. Patterns of gene expression characteristic of TP53 mutation could be discerned and included several genes that are known p53 targets or have been described in the context of expression signatures of TP53 mutation in breast cancer. [ABSTRACT FROM AUTHOR]

Using in vitro drug sensitivity data coupled with Affymetrix microarray data, we developed gene expression signatures that predict sensitivity to individual chemotherapeutic drugs. Each signature was validated with response data from an independent set of cell line studies. We further show that many of these signatures can accurately predict clinical response in individuals treated with these drugs. Notably, signatures developed to predict response to individual agents, when combined, could also predict response to multidrug regimens. Finally, we integrated the chemotherapy response signatures with signatures of oncogenic pathway deregulation to identify new therapeutic strategies that make use of all available drugs. The development of gene expression profiles that can predict response to commonly used cytotoxic agents provides opportunities to better use these drugs, including using them in combination with existing targeted therapies. [ABSTRACT FROM AUTHOR]

The development of an oncogenic state is a complex process involving the accumulation of multiple independent mutations that lead to deregulation of cell signalling pathways central to the control of cell growth and cell fate. The ability to define cancer subtypes, recurrence of disease and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Various studies have also demonstrated the potential for using gene expression profiles for the analysis of oncogenic pathways. Here we show that gene expression signatures can be identified that reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumours and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumour subtypes. Clustering tumours based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Predictions of pathway deregulation in cancer cell lines are also shown to predict the sensitivity to therapeutic agents that target components of the pathway. Linking pathway deregulation with sensitivity to therapeutics that target components of the pathway provides an opportunity to make use of these oncogenic pathway signatures to guide the use of targeted therapeutics. [ABSTRACT FROM AUTHOR]

Treatment of the breast cancer cell line, MDAMB468 with the DNA methylation inhibitor, 5-azacytidine (5-AzaC) results in growth arrest, whereas the growth of the normal breast epithelial line DU99 (telomerase immortalized) is relatively unaffected. Comparing gene expression profiles of these two lines after 5-AzaC treatment, we identified 36 genes that had relatively low basal levels in MDAMB468 cells compared to the DU99 line and were induced in the cancer cell line but not in the normal breast epithelial line. Of these genes, 33 have associated CpG islands greater than 300?bp in length but only three have been previously described as targets for aberrant methylation in human cancer. Northern blotting for five of these genes (a-Catenin, DTR, FYN, GADD45a, and Zyxin) verified the array results. Further analysis of one of these genes, GADD45a, showed that 5-AzaC induced expression in five additional breast cancer cell lines with little or no induction in three additional lines derived from normal breast epithelial cells. The CpG island associated with GADD45a was analysed by bisulfite sequencing, sampling over 100 CpG dinucleotides. We found that four CpG's, located approximately 700?bp upstream of the transcriptional start site are methylated in the majority of breast cancer cell lines and primary tumors but not in DNA from normal breast epithelia or matched lymphocytes from cancer patients. Therefore, this simple method of dynamic transcriptional profiling yielded a series of novel methylation-sensitive genes in breast cancer including the BRCA1 and p53 responsive gene, GADD45a.Oncogene (2005) 24, 2705-2714. doi:10.1038/sj.onc.1208464 Published online 14 February 2005 [ABSTRACT FROM AUTHOR]

The late stages of human breast cancer development are poorly understood complex processes associated with the expression of genes by cancers that promote specific tumorigenic activities, such as angiogenesis. Here, we describe the identification of periostin as a mesenchyme-specific gene whose acquired expression by human breast cancers leads to a significant enhancement in tumor progression and angiogenesis. Undetectable in normal human breast tissues, periostin was found to be overexpressed by the vast majority of human primary breast cancers examined. Tumor cell lines engineered to overexpress periostin showed a phenotype of accelerated growth and angiogenesis as xenografts in immunocompromised animals. The underlying mechanism of periostin-mediated induction of angiogenesis was found to derive in part from the up-regulation of the vascular endothelial growth factor receptor Flk-1/KDR by endothelial cells through au integrin αvβ3-focal adhesion kinase-mediated signaling pathway. These findings demonstrate the presence of a novel mechanism by which tumor angiogenesis is acquired with the expression of a mesenchyme-specific gene as a crucial step in late stages of tumorigenesis. [ABSTRACT FROM AUTHOR]

We have developed a complete statistical model for the analysis of tumor specific gene expression profiles. The approach provides investigators with a global overview on large scale gene expression data, indicating aspects of the data that relate to tumor phenotype, but also summarizing the uncertainties inherent in classification of tumor types. We demonstrate the use of this method in the context of a gene expression profiling study of 27 human breast cancers. The study is aimed at defining molecular characteristics of tumors that reflect estrogen receptor status. In addition to good predictive performance with respect to pure classification of the expression profiles, the model also uncovers conflicts in the data with respect to the classification of some of the tumors, highlighting them as critical cases for which additional investigations are appropriate. [ABSTRACT FROM AUTHOR]

Reports that the expression of the p53 gene protects cells against malignant transformation. How little is known about the factors that regulate p53 synthesis; Display of how p53 messenger RNA levels are low in a large proportion of breast tumors; Consensus HOX binding sites in the p53 promoter; Conclusions that loss of expression of p53 in human breast cancer may be primarily due to lack of expression of HOXA5.

Conventional therapies for breast cancer brain metastases (BCBMs) have been largely ineffective because of chemoresistance and impermeability of the blood-brain barrier. A comprehensive understanding of the underlying mechanism that allows breast cancer cells to infiltrate the brain is necessary to circumvent treatment resistance of BCBMs. Here, we determined that expression of a long noncoding RNA (lncRNA) that we have named lncRNA associated with BCBM (Lnc-BM) is prognostic of the progression of brain metastasis in breast cancer patients. In preclinical murine models, elevated Lnc-BM expression drove BCBM, while depletion of Lnc-BM with nanoparticle-encapsulated siRNAs effectively treated BCBM. Lnc-BM increased JAK2 kinase activity to mediate oncostatin M- and IL-6-triggered STAT3 phosphorylation. In breast cancer cells, Lnc-BM promoted STAT3-dependent expression of ICAM1 and CCL2, which mediated vascular co-option and recruitment of macrophages in the brain, respectively. Recruited macrophages in turn produced oncostatin M and IL-6, thereby further activating the Lnc-BM/JAK2/STAT3 pathway and enhancing BCBM. Collectively, our results show that Lnc-BM and JAK2 promote BCBMs by mediating communication between breast cancer cells and the brain microenvironment. Moreover, these results suggest targeting Lnc-BM as a potential strategy for fighting this difficult disease. [ABSTRACT FROM AUTHOR]

Objectives To identify angiogenic biomarkers associated with tumor angiogenesis and clinical outcome in high-grade serous ovarian cancer (HGSC). Methods 51 HGSC samples were analyzed using Affymetrix HG-U133A microarray. Microvessel density (MVD) counts were determined using CD31 and CD105. Associations between mRNA expression levels and overall survival were assessed using rank score statistic. Effect size was estimated as a hazard ratio (HR) under a proportional hazard model. The Storey q-value method was used to account for multiple testing within the false-discovery rate (FDR) framework. Publicly available databases including TCGA and GSE were used for external confirmation. Results Thirty-one angiogenic-related genes were significantly associated with survival (q ≤ 0.05). Of these 31 genes, 4 were also associated with outcome in the TCGA data: AKT1 (q = 0.02; TCGA p = 0.01, HR = 0.8), CD44 (q = 0.003; TCGA p = 0.05, HR = 0.9), EPHB2 (q = 0.01; TCGA p = 0.05, HR = 1.2), and ERBB2 (q = 0.02; TCGA p = 0.05, HR = 1.2). While 5 were associated with outcome in the GSE database: FLT1 (q = 0.03; GSE26712 p = 0.01, HR = 3.1); PF4 (q = 0.02; GSE26712 p = 0.01, HR = 3.0); NRP1 (q = 0.02; GSE26712 p < 0.04, HR > 1.4); COL4A3 (q = 0.04; GSE26712 p = 0.03, HR = 1.3); and ANGPTL3 (q = 0.02; GSE14764 p = 0.02, HR = 1.5). High AKT1 and CD44 were associated with longer survival. In contrast, high expression of EPHB2 , ERBB2 , FLT1 ; PF4 , NRP1 , COL4A3 , and ANGPTL3 were associated with shorter survival. CD105-MVD and CD31-MVD were not significantly associated with angiogenic gene expression. Conclusions Thirty-one angiogenic-related genes were associated with survival in advanced HGSC and nine of these genes were confirmed in independent publicly available databases. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Gene expression signatures have been identified for epithelial ovarian cancer survival (TCGA) and intrinsic subtypes (Tothill et al.). One obstacle to clinical translation is that these signatures were developed using frozen tissue, whereas usually only formalin-fixed, paraffin embedded (FFPE) tissue is available. The aim of this study was to determine if gene expression signatures can be translated to fixed archival tissues. Methods: RNA extracted from FFPE sections from 240 primary ovarian cancers was analyzed by DASL on Illumina BeadChip arrays. Concordance of expression at the individual gene level was assessed by comparing array data from the same cancers (30 frozen samples analyzed on Affymetrix arrays versus FFPE DASL). Results: The correlation between FFPE and frozen survival signature estimates was 0.774. The TCGA signature using DASL was predictive of survival in 106 advanced stage high grade serous ovarian cancers (median survival 33 versus 60months, estimated hazard ratio for death 2.30, P=0.0007). Similar to Tothill, we found using DASL that most high grade serous ovarian cancers (102/110, 93%) were assigned to subtypes 1, 2, 4 and 5, whereas most endometrioid, clear cell, mucinous and low grade serous cases (39/57, 68%) were assigned to subtypes 3 and 6 (P<10e-15). Conclusions: Although individual probe estimates of microarrays may be weakly correlated between FFPE and frozen samples, combinations of probes have robust ability to predict survival and subtype. This suggests that it may be possible to use these signatures for prognostic and predictive purposes as we seek to individualize the treatment of ovarian cancer. [Copyright &y& Elsevier]

Abstract: Objective.: Epithelial ovarian cancer is the deadliest gynecologic malignancy, yet its molecular etiology remains poorly understood. Evidence is accumulating to support a role for the insulin-like growth factor family in human carcinogenesis, and recently using microarray expression analysis, we demonstrated over-expression of the insulin-like growth factor-2 (IGF-2) gene in advanced stage epithelial ovarian cancers. The purpose of the current study is to further elucidate the role of the IGF-2 gene in ovarian cancer development and progression. Methods.: Relative expression of IGF-2 was measured in 109 epithelial ovarian cancers and eight normal ovarian surface epithelial (NOSE) samples, using quantitative real-time polymerase chain reaction. Associations with clinicopathological parameters were examined. Results.: Expression of the IGF-2 gene was more than 300-fold higher in ovarian cancers compared with normal ovarian surface epithelium samples (P <0.001). High IGF-2 expression was associated with advanced stage disease at diagnosis (P <0.001), high-grade cancers (P <0.05) and sub-optimal surgical cytoreduction (P = 0.08). In multivariate analysis, relative IGF-2 expression was an independent predictor of poor survival. Conclusions.: Expression of the IGF-2 gene is significantly higher in ovarian cancers relative to normal ovarian surface epithelium. Further, high IGF-2 gene expression is associated with high grade, advanced stage disease, and is an independent predictor of poor survival in patients with epithelial ovarian cancer. As such, IGF-2 is a molecular marker and potential therapeutic target for the most aggressive epithelial ovarian cancers. [Copyright &y& Elsevier]

: ObjectiveTo identify gene expression patterns that characterize advanced stage serous ovarian cancers by using microarray expression analysis.: MethodsUsing genome-wide expression analysis, we compared a series of 31 advanced stage (III or IV) serous ovarian cancers from patients who survived either less than 2 years or more than 7 years with three normal ovarian epithelial samples. Array findings were validated by analysis of expression of the insulin-like growth factor binding protein 2 (IGFBP2) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) genes using quantitative real-time polymerase chain reaction (QRT-PCR).: ResultsHierarchical clustering identified patterns of gene expression that distinguished cancer from normal ovarian epithelium. We also identified gene expression patterns that distinguish cancers on the basis of patient survival. These genes include many that are associated with immune function. Expression of IGFBP2 and TRAIL genes measured by array and QRT-PCR analysis demonstrated correlation coefficients of 0.63 and 0.78, respectively.: ConclusionGlobal expression analysis can identify expression patterns and individual genes that contribute to ovarian cancer development and outcome. Many of the genes that determine ovarian cancer survival are associated with the immune response, suggesting that immune function influences ovarian cancer virulence. With the generation of newer arrays with more transcripts, larger studies are possible to fully characterize genetic signatures that predict survival that may ultimately be used to guide therapeutic decision-making. [Copyright &y& Elsevier]