An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer

INTRODUCTION. Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation. METHODS. We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies. RESULTS. We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient. CONCLUSIONS. Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.V Foundation for Cancer Research (Partners in Excellence grant

Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy

Reactivation of epigenetically silenced HER4/ERBB4 results in apoptosis of breast tumor cells

Experimental and clinical data support a growth inhibitory role for HER4 in breast cancer. Clinically HER4 expression is extinguished during breast tumorigenesis supporting a tumor suppressor function for HER4, however, a molecular mechanism to explain the selective loss of HER4 expression has remained elusive. Epigenetic mechanisms, for example, aberrant gene promoter hypermethylation, have been shown to ablate tumor suppressor gene expression in breast carcinomas. We identified a CpG island within the HER4 promoter and show by pyrosequencing of bisulfite-treated DNA an inverse correlation between HER4 expression and the extent of promoter methylation. Treatment of the HER4-negative BT20 cell line with the DNA demethylating agent 5-aza-2′-deoxycytidine (DAC)-enhanced HER4 expression, confirming a role for DNA methylation in suppressed HER4 expression. DAC treatment to reactive HER4 expression in combination with the HER4 ligand heregulin-β1 (HRG) resulted in apoptosis of BT20 cells providing a novel therapeutic strategy for triple-negative tumors. The BT20 cells were rescued from apoptosis when preincubated with HER4 small interfering RNA, thereby confirming a role for HER4 in DAC/HRG-induced apoptosis. We verified HER4 promoter methylation in primary breast carcinomas and detected a significant increase in HER4 promoter methylation in HER4-negative breast tumors (P<0.001). Furthermore, increased levels of HER4 promoter methylation were significantly associated with worse patient prognosis (P=0.0234). Taken together, our data support a tumor suppressor function for HER4, which is epigenetically suppressed in breast tumors through promoter hypermethylation

A strategy to incorporate prior knowledge into correlation network cutoff selection

Correlation networks are frequently used to statistically extract biological interactions between omics markers. Network edge selection is typically based on the statistical significance of the correlation coefficients. This procedure, however, is not guaranteed to capture biological mechanisms. We here propose an alternative approach for network reconstruction: a cutoff selection algorithm that maximizes the overlap of the inferred network with available prior knowledge. We first evaluate the approach on IgG glycomics data, for which the biochemical pathway is known and well-characterized. Importantly, even in the case of incomplete or incorrect prior knowledge, the optimal network is close to the true optimum. We then demonstrate the generalizability of the approach with applications to untargeted metabolomics and transcriptomics data. For the transcriptomics case, we demonstrate that the optimized network is superior to statistical networks in systematically retrieving interactions that were not included in the biological reference used for optimization

Identification of Trypanosoma brucei RMI1/BLAP75 Homologue and Its Roles in Antigenic Variation

At any time, each cell of the protozoan parasite Trypanosoma brucei expresses a single species of its major antigenic protein, the variant surface glycoprotein (VSG), from a repertoire of >2,000 VSG genes and pseudogenes. The potential to express different VSGs by transcription and recombination allows the parasite to escape the antibody-mediated host immune response, a mechanism known as antigenic variation. The active VSG is transcribed from a sub-telomeric polycistronic unit called the expression site (ES), whose promoter is 40–60 kb upstream of the VSG. While the mechanisms that initiate recombination remain unclear, the resolution phase of these reactions results in the recombinational replacement of the expressed VSG with a donor from one of three distinct chromosomal locations; sub-telomeric loci on the 11 essential chromosomes, on minichromosomes, or at telomere-distal loci. Depending on the type of recombinational replacement (single or double crossover, duplicative gene conversion, etc), several DNA-repair pathways have been thought to play a role. Here we show that VSG recombination relies on at least two distinct DNA-repair pathways, one of which requires RMI1-TOPO3α to suppress recombination and one that is dependent on RAD51 and RMI1. These genetic interactions suggest that both RAD51-dependent and RAD51-independent recombination pathways operate in antigenic switching and that trypanosomes differentially utilize recombination factors for VSG switching, depending on currently unknown parameters within the ES

Lack of evidence for KRAS oncogenic mutations in triple-negative breast cancer

<p>Abstract</p> <p>Background</p> <p>Mutational analysis of the <it>KRAS </it>gene has recently been established as a complementary <it>in vitro </it>diagnostic tool for the identification of patients with colorectal cancer who will not benefit from anti-epidermal growth factor receptor (EGFR) therapies. Assessment of the mutation status of <it>KRAS </it>might also be of potential relevance in other EGFR-overexpressing tumors, such as those occurring in breast cancer. Although <it>KRAS </it>is mutated in only a minor fraction of breast tumors (5%), about 60% of the basal-like subtype express EGFR and, therefore could be targeted by EGFR inhibitors. We aimed to study the mutation frequency of <it>KRAS </it>in that subtype of breast tumors to provide a molecular basis for the evaluation of anti-EGFR therapies.</p> <p>Methods</p> <p>Total, genomic DNA was obtained from a group of 35 formalin-fixed paraffin-embedded, triple-negative breast tumor samples. Among these, 77.1% (27/35) were defined as basal-like by immunostaining specific for the established surrogate markers cytokeratin (CK) 5/6 and/or EGFR. <it>KRAS </it>mutational status was determined in the purified DNA samples by Real Time (RT)-PCR using primers specific for the detection of wild-type <it>KRAS </it>or the following seven oncogenic somatic mutations: Gly12Ala, Gly12Asp, Gly12Arg, Gly12Cys, Gly12Ser, Gly12Val and Gly13Asp.</p> <p>Results</p> <p>We found no evidence of <it>KRAS </it>oncogenic mutations in all analyzed tumors.</p> <p>Conclusions</p> <p>This study indicates that <it>KRAS </it>mutations are very infrequent in triple-negative breast tumors and that EGFR inhibitors may be of potential benefit in the treatment of basal-like breast tumors, which overexpress EGFR in about 60% of all cases.</p

Copy number signatures and mutational processes in ovarian carcinoma.

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.NIHR, Ovarian Cancer Action, Cancer Research UK Cambridge Centre, Cambridge Experimental Cancer Medicine Centr

ErbB2, EphrinB1, Src Kinase and PTPN13 Signaling Complex Regulates MAP Kinase Signaling in Human Cancers

In non-cancerous cells, phosphorylated proteins exist transiently, becoming de-phosphorylated by specific phosphatases that terminate propagation of signaling pathways. In cancers, compromised phosphatase activity and/or expression occur and contribute to tumor phenotype. The non-receptor phosphatase, PTPN13, has recently been dubbed a putative tumor suppressor. It decreased expression in breast cancer correlates with decreased overall survival. Here we show that PTPN13 regulates a new signaling complex in breast cancer consisting of ErbB2, Src, and EphrinB1. To our knowledge, this signaling complex has not been previously described. Co-immunoprecipitation and localization studies demonstrate that EphrinB1, a PTPN13 substrate, interacts with ErbB2. In addition, the oncogenic V660E ErbB2 mutation enhances this interaction, while Src kinase mediates EphrinB1 phosphorylation and subsequent MAP Kinase signaling. Decreased PTPN13 function further enhances signaling. The association of oncogene kinases (ErbB2, Src), a signaling transmembrane ligand (EphrinB1) and a phosphatase tumor suppressor (PTPN13) suggest that EphrinB1 may be a relevant therapeutic target in breast cancers harboring ErbB2-activating mutations and decreased PTPN13 expression