Victor J. Weigman

Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors

BackgroundAlthough numerous mouse models of breast carcinomas have been developed, we do not know the extent to which any faithfully represent clinically significant human phenotypes. To address this need, we characterized mammary tumor gene expression profiles from 13 different murine models using DNA microarrays and compared the resulting data to those from human breast tumors.ResultsUnsupervised hierarchical clustering analysis showed that six models (TgWAP-Myc, TgMMTV-Neu, TgMMTV-PyMT, TgWAP-Int3, TgWAP-Tag, and TgC3(1)-Tag) yielded tumors with distinctive and homogeneous expression patterns within each strain. However, in each of four other models (TgWAP-T121, TgMMTV-Wnt1, Brca1Co/Co;TgMMTV-Cre;p53+/- and DMBA-induced), tumors with a variety of histologies and expression profiles developed. In many models, similarities to human breast tumors were recognized, including proliferation and human breast tumor subtype signatures. Significantly, tumors of several models displayed characteristics of human basal-like breast tumors, including two models with induced Brca1 deficiencies. Tumors of other murine models shared features and trended towards significance of gene enrichment with human luminal tumors; however, these murine tumors lacked expression of estrogen receptor (ER) and ER-regulated genes. TgMMTV-Neu tumors did not have a significant gene overlap with the human HER2+/ER- subtype and were more similar to human luminal tumors.ConclusionMany of the defining characteristics of human subtypes were conserved among the mouse models. Although no single mouse model recapitulated all the expression features of a given human subtype, these shared expression features provide a common framework for an improved integration of murine mammary tumor models with human breast tumors.

Allele-specific copy number analysis of tumors

We present an allele-specific copy number analysis of the in vivo breast cancer genome. We describe a unique bioinformatics approach, ASCAT (allele-specific copy number analysis of tumors), to accurately dissect the allele-specific copy number of solid tumors, simultaneously estimating and adjusting for both tumor ploidy and nonaberrant cell admixture. This allows calculation of “ASCAT profiles” (genome-wide allele-specific copy-number profiles) from which gains, losses, copy number-neutral events, and loss of heterozygosity (LOH) can accurately be determined. In an early-stage breast carcinoma series, we observe aneuploidy (>2.7n) in 45% of the cases and an average nonaberrant cell admixture of 49%. By aggregation of ASCAT profiles across our series, we obtain genomic frequency distributions of gains and losses, as well as genome-wide views of LOH and copy number-neutral events in breast cancer. In addition, the ASCAT profiles reveal differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH, and copy number-neutral events between the five previously identified molecular breast cancer subtypes. Basal-like breast carcinomas have a significantly higher frequency of LOH compared with other subtypes, and their ASCAT profiles show large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. Finally, from the ASCAT profiles, we construct a genome-wide map of allelic skewness in breast cancer, indicating loci where one allele is preferentially lost, whereas the other allele is preferentially gained. We hypothesize that these alternative alleles have a different influence on breast carcinoma development.

EGFR associated expression profiles vary with breast tumor subtype

BackgroundThe epidermal growth factor receptor (EGFR/HER1) and its downstream signaling events are important for regulating cell growth and behavior in many epithelial tumors types. In breast cancer, the role of EGFR is complex and appears to vary relative to important clinical features including estrogen receptor (ER) status. To investigate EGFR-signaling using a genomics approach, several breast basal-like and luminal epithelial cell lines were examined for sensitivity to EGFR inhibitors. An EGFR-associated gene expression signature was identified in the basal-like SUM102 cell line and was used to classify a diverse set of sporadic breast tumors.ResultsIn vitro, breast basal-like cell lines were more sensitive to EGFR inhibitors compared to luminal cell lines. The basal-like tumor derived lines were also the most sensitive to carboplatin, which acted synergistically with cetuximab. An EGFR-associated signature was developed in vitro, evaluated on 241 primary breast tumors; three distinct clusters of genes were evident in vivo, two of which were predictive of poor patient outcomes. These EGFR-associated poor prognostic signatures were highly expressed in almost all basal-like tumors and many of the HER2+/ER- and Luminal B tumors.ConclusionThese results suggest that breast basal-like cell lines are sensitive to EGFR inhibitors and carboplatin, and this combination may also be synergistic. In vivo, the EGFR-signatures were of prognostic value, were associated with tumor subtype, and were uniquely associated with the high expression of distinct EGFR-RAS-MEK pathway genes.

Gene Expression Signatures from Three Genetically Separable Resistance Gene Signaling Pathways for Downy Mildew Resistance

Resistance gene-dependent disease resistance to pathogenic microorganisms is mediated by genetically separable regulatory pathways. Using the GeneChip Arabidopsis genome array, we compared the expression profiles of approximately 8,000 Arabidopsis genes following activation of three RPP genes directed against the pathogenic oomycete Peronospora parasitica. Judicious choice of P. parasitica isolates and loss of resistance plant mutants allowed us to compare the responses controlled by three genetically distinct resistance gene-mediated signaling pathways. We found that all three pathways can converge, leading to up-regulation of common sets of target genes. At least two temporal patterns of gene activation are triggered by two of the pathways examined. Many genes defined by their early and transient increases in expression encode proteins that execute defense biochemistry, while genes exhibiting a sustained or delayed expression increase predominantly encode putative signaling proteins. Previously defined and novel sequence motifs were found to be enriched in the promoters of genes coregulated by the local defense-signaling network. These putative promoter elements may operate downstream from signal convergence points.

HIF2α cooperates with RAS to promote lung tumorigenesis in mice

Members of the hypoxia-inducible factor (HIF) family of transcription factors regulate the cellular response to hypoxia. In non–small cell lung cancer (NSCLC), high HIF2α levels correlate with decreased overall survival, and inhibition of either the protein encoded by the canonical HIF target gene VEGF or VEGFR2 improves clinical outcomes. However, whether HIF2α is causal in imparting this poor prognosis is unknown. Here, we generated mice that conditionally express both a nondegradable variant of HIF2α and a mutant form of Kras (KrasG12D) that induces lung tumors. Mice expressing both Hif2a and KrasG12D in the lungs developed larger tumors and had an increased tumor burden and decreased survival compared with mice expressing only KrasG12D. Additionally, tumors expressing both KrasG12D and Hif2a were more invasive, demonstrated features of epithelial-mesenchymal transition (EMT), and exhibited increased angiogenesis associated with mobilization of circulating endothelial progenitor cells. These results implicate HIF2α causally in the pathogenesis of lung cancer in mice, demonstrate in vivo that HIF2α can promote expression of markers of EMT, and define HIF2α as a promoter of tumor growth and progression in a solid tumor other than renal cell carcinoma. They further suggest a possible causal relationship between HIF2α and prognosis in patients with NSCLC.

Rb deletion in mouse mammary progenitors induces luminal-B or basal-like/EMT tumor subtypes depending on p53 status

Breast cancer is a highly heterogeneous disease, with several different subtypes being characterized by distinct histology, gene expression patterns, and genetic alterations. The tumor suppressor gene retinoblastoma 1 (RB1) is frequently lost in both luminal-B and triple-negative tumor (TNT; i.e., estrogen receptor-, progesterone receptor-, and human epidermal growth factor receptor 2-negative) breast cancer subtypes. However, a causal role for RB1 loss in different subtypes remains undefined. Here we report that deletion of Rb alone or together with its relative p107 in mouse mammary stem/bipotent progenitor cells induced focal acinar hyperplasia with squamous metaplasia. These lesions progressed into histologically diverse, transplantable mammary tumors with features of either luminal-B or TNT subtypes. The TNTs included basal-like tumors as well as tumors that exhibited epithelial-to-mesenchymal transition (EMT). The EMT-type tumors and a subset of the basal-like tumors, but not luminal-B-like tumors, expressed mutant forms of the tumor suppressor p53. Accordingly, targeted deletion of both Rb and p53 in stem/bipotent progenitors led to histologically uniform, aggressive, EMT-type tumors. Reintroduction of Rb into these tumor cells suppressed growth in vitro and tumor formation in vivo. These results establish a causal role for Rb loss in breast cancer in mice and demonstrate that cooperating oncogenic events, such as mutations in p53, dictate tumor subtype after Rb inactivation.

FINDING LARGE AVERAGE SUBMATRICES IN HIGH DIMENSIONAL DATA

The search for sample-variable associations is an important problem in the exploratory analysis of high dimensional data. Biclustering methods search for sample-variable associations in the form of distinguished submatrices of the data matrix. (The rows and columns of a submatrix need not be contiguous.) In this paper we propose and evaluate a statistically motivated biclustering procedure (LAS) that finds large average submatrices within a given real-valued data matrix. The procedure operates in an iterative-residual fashion, and is driven by a Bonferroni-based significance score that effectively trades off between submatrix size and average value. We examine the performance and potential utility of LAS, and compare it with a number of existing methods, through an extensive three-part validation study using two gene expression datasets. The validation study examines quantitative properties of biclusters, biological and clinical assessments using auxiliary information, and classification of disease subtypes using bicluster membership. In addition, we carry out a simulation study to assess the effectiveness and noise sensitivity of the LAS search procedure. These results suggest that LAS is an effective exploratory tool for the discovery of biologically relevant structures in high dimensional data. Software is available at https://genome.unc.edu/las/.

Basal-like Breast cancer DNA copy number losses identify genes involved in genomic instability, response to therapy, and patient survival

Breast cancer is a heterogeneous disease with known expression-defined tumor subtypes. DNA copy number studies have suggested that tumors within gene expression subtypes share similar DNA Copy number aberrations (CNA) and that CNA can be used to further sub-divide expression classes. To gain further insights into the etiologies of the intrinsic subtypes, we classified tumors according to gene expression subtype and next identified subtype-associated CNA using a novel method called SWITCHdna, using a training set of 180 tumors and a validation set of 359 tumors. Fisher’s exact tests, Chi-square approximations, and Wilcoxon rank-sum tests were performed to evaluate differences in CNA by subtype. To assess the functional significance of loss of a specific chromosomal region, individual genes were knocked down by shRNA and drug sensitivity, and DNA repair foci assays performed. Most tumor subtypes exhibited specific CNA. The Basal-like subtype was the most distinct with common losses of the regions containing RB1, BRCA1, INPP4B, and the greatest overall genomic instability. One Basal-like subtype-associated CNA was loss of 5q11–35, which contains at least three genes important for BRCA1-dependent DNA repair (RAD17, RAD50, and RAP80); these genes were predominantly lost as a pair, or all three simultaneously. Loss of two or three of these genes was associated with significantly increased genomic instability and poor patient survival. RNAi knockdown of RAD17, or RAD17/RAD50, in immortalized human mammary epithelial cell lines caused increased sensitivity to a PARP inhibitor and carboplatin, and inhibited BRCA1 foci formation in response to DNA damage. These data suggest a possible genetic cause for genomic instability in Basal-like breast cancers and a biological rationale for the use of DNA repair inhibitor related therapeutics in this breast cancer subtype.

Deep sequencing of gastric carcinoma reveals somatic mutations relevant to personalized medicine

BackgroundGlobally, gastric cancer is the second most common cause of cancer-related death, with the majority of the health burden borne by economically less-developed countries.MethodsHere, we report a genetic characterization of 50 gastric adenocarcinoma samples, using affymetrix SNP arrays and Illumina mRNA expression arrays as well as Illumina sequencing of the coding regions of 384 genes belonging to various pathways known to be altered in other cancers.ResultsGenetic alterations were observed in the WNT, Hedgehog, cell cycle, DNA damage and epithelial-to-mesenchymal-transition pathways.ConclusionsThe data suggests targeted therapies approved or in clinical development for gastric carcinoma would be of benefit to ~22% of the patients studied. In addition, the novel mutations detected here, are likely to influence clinical response and suggest new targets for drug discovery.

HIF2α cooperates with RAS to promote lung tumorigenesis in mice (Journal of Clinical Investigation (2009) 119, (2160-2170) doi: 101172/JCI38443)

1Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA. 2Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA. 3Ludwig Center at Dana-Farber/Harvard Cancer Center, Boston, Massachusetts, USA. 4Department of Surgery, University of North Carolina, Chapel Hill, North Carolina, USA. 5Department of Thoracic/Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA. 6Department of Pediatric Oncology, Dana-Farber Cancer Institute and Children’s Hospital Boston, Boston, Massachusetts, USA. 7Department of Surgery, Children’s Hospital Boston, Boston, Massachusetts, USA. 8Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts, USA. 9Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA. 10Howard Hughes Medical Institute, Boston, Massachusetts, USA.