Guy Cavet

Epithelial versus mesenchymal phenotype determines in vitro sensitivity and predicts clinical activity of erlotinib in lung cancer patients.

Significant improvements in the outcome of non–small cell lung carcinoma (NSCLC) have been reported in patients treated with the epidermal growth factor receptor (EGFR) inhibitor, erlotinib. To discover biomarkers for the enrichment of patients who might benefit from treatment, a pharmacogenomic approach was used to identify gene signatures that may predict erlotinib activity using in vitro model systems. Erlotinib sensitivity in a panel of 42 NSCLC cell lines was determined by EGFR-mediated proliferative potential, EGFR mutations, and/or EGFR gene amplification, thus supporting an underlying biological mechanism of receptor activation. A strong multigene signature indicative of an epithelial to mesenchymal transition (EMT) was identified as a determinant of insensitivity to erlotinib through both supervised and unsupervised gene expression approaches. This observation was further supported by expression analysis of classic EMT marker proteins, including E-cadherin and vimentin. To investigate the clinical relevance of these findings, we examined expression of the epithelial marker E-cadherin by immunohistochemistry on primary tumor samples from subjects enrolled in a randomized NSCLC clinical trial in which erlotinib in combination with chemotherapy previously failed to show clinical activity. The majority (75%) of the 87 subjects tested showed strong E-cadherin staining and exhibited a significantly longer time to progression (hazard ratio, 0.37; log rank P = 0.0028) and a nonsignificant trend toward longer survival with erlotinib plus chemotherapy treatment versus chemotherapy alone. These data support a potential role for EMT as a determinant of EGFR activity in NSCLC tumor cells and E-cadherin expression as a novel biomarker predicting clinical activity of the EGFR inhibitor erlotinib in NSCLC patients.

Death-receptor O-glycosylation controls tumor-cell sensitivity to the proapoptotic ligand Apo2L/TRAIL

Apo2L/TRAIL stimulates cancer cell death through the proapoptotic receptors DR4 and DR5, but the determinants of tumor susceptibility to this ligand are not fully defined. mRNA expression of the peptidyl O-glycosyltransferase GALNT14 correlated with Apo2L/TRAIL sensitivity in pancreatic carcinoma, non–small-cell lung carcinoma and melanoma cell lines, and up to 30% of samples from various human malignancies showed GALNT14 overexpression. RNA interference of GALNT14 reduced cellular Apo2L/TRAIL sensitivity, whereas overexpression increased responsiveness. Biochemical analysis of DR5 identified several ectodomain O-(N-acetyl galactosamine–galactose–sialic acid) structures. Sequence comparison predicted conserved extracellular DR4 and DR5 O-glycosylation sites; progressive mutation of the DR5 sites attenuated apoptotic signaling. O-glycosylation promoted ligand-stimulated clustering of DR4 and DR5, which mediated recruitment and activation of the apoptosis-initiating protease caspase-8. These results uncover a new link between death-receptor O-glycosylation and apoptotic signaling, providing potential predictive biomarkers for Apo2L/TRAIL-based cancer therapy.

In vivo Antitumor Activity of MEK and Phosphatidylinositol 3-Kinase Inhibitors in Basal-Like Breast Cancer Models

Purpose: The pathways underlying basal-like breast cancer are poorly understood, and as yet, there is no approved targeted therapy for this disease. We investigated the role of mitogen-activated protein kinase kinase (MEK) and phosphatidylinositol 3-kinase (PI3K) inhibitors as targeted therapies for basal-like breast cancer. Experimental Design: We used pharmacogenomic analysis of a large panel of breast cancer cell lines with detailed accompanying molecular information to identify molecular predictors of response to a potent and selective inhibitor of MEK and also to define molecular mechanisms underlying combined MEK and PI3K targeting in basal-like breast cancer. Hypotheses were confirmed by testing in multiple tumor xenograft models. Results: We found that basal-like breast cancer models have an activated RAS-like transcriptional program and show greater sensitivity to a selective inhibitor of MEK compared with models representative of other breast cancer subtypes. We also showed that loss of PTEN is a negative predictor of response to MEK inhibition, that treatment with a selective MEK inhibitor caused up-regulation of PI3K pathway signaling, and that dual blockade of both PI3K and MEK/extracellular signal–regulated kinase signaling synergized to potently impair the growth of basal-like breast cancer models in vitro and in vivo. Conclusions: Our studies suggest that single-agent MEK inhibition is a promising therapeutic modality for basal-like breast cancers with intact PTEN, and also provide a basis for rational combination of MEK and PI3K inhibitors in basal-like cancers with both intact and deleted PTEN.

Genetic Alterations and Oncogenic Pathways Associated with Breast Cancer Subtypes

Breast cancers can be divided into subtypes with important implications for prognosis and treatment. We set out to characterize the genetic alterations observed in different breast cancer subtypes and to identify specific candidate genes and pathways associated with subtype biology. mRNA expression levels of estrogen receptor, progesterone receptor, and HER2 were shown to predict marker status determined by immunohistochemistry and to be effective at assigning samples to subtypes. HER2+ cancers were shown to have the greatest frequency of high-level amplification (independent of the ERBB2 amplicon itself), but triple-negative cancers had the highest overall frequencies of copy gain. Triple-negative cancers also were shown to have more frequent loss of phosphatase and tensin homologue and mutation of RB1, which may contribute to genomic instability. We identified and validated seven regions of copy number alteration associated with different subtypes, and used integrative bioinformatics analysis to identify candidate oncogenes and tumor suppressors, including ERBB2, GRB7, MYST2, PPM1D, CCND1, HDAC2, FOXA1, and RASA1. We tested the candidate oncogene MYST2 and showed that it enhances the anchorage-independent growth of breast cancer cells. The genome-wide and region-specific differences between subtypes suggest the differential activation of oncogenic pathways. (Mol Cancer Res 2009;7(4):511–22)

High-resolution genomic and expression analyses of copy number alterations in breast tumors

Analysis of recurrent DNA amplification can lead to the identification of cancer driver genes, but this process is often hampered by the low resolution of existing copy number analysis platforms. Fifty‐one breast tumors were profiled for copy number alterations (CNAs) with the high‐resolution Affymetrix 500K SNP array. These tumors were also expression‐profiled and surveyed for mutations in selected genes commonly mutated in breast cancer (TP53, CDKN2A, ERBB2, KRAS, PIK3CA, PTEN). Combined analysis of common CNAs and mutations revealed putative associations between features. Analysis of both the prevalence and amplitude of CNAs defined regions of recurrent alteration. Compared with previous array comparative genomic hybridization studies, our analysis provided boundaries for frequently altered regions that were approximately one‐fourth the size, greatly reducing the number of potential alteration‐driving genes. Expression data from matched tumor samples were used to further interrogate the functional relevance of genes located in recurrent amplicons. Although our data support the importance of some known driver genes such as ERBB2, refined amplicon boundaries at other locations, such as 8p11‐12 and 11q13.5‐q14.2, greatly reduce the number of potential driver genes and indicate alternatives to commonly suggested driver genes in some cases. For example, the previously reported recurrent amplification at 17q23.2 is reduced to a 249 kb minimal region containing the putative driver RPS6KB1 as well as the putative oncogenic microRNA mir‐21. High‐resolution copy number analysis provides refined insight into many breast cancer amplicons and their relationships to gene expression, point mutations and breast cancer subtype classifications. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045‐2257/suppmat.

Functional Genomics Identifies ABCC3 as a Mediator of Taxane Resistance in HER2-Amplified Breast Cancer

Breast cancer is a heterogeneous disease with distinct molecular subtypes characterized by differential response to targeted and chemotherapeutic agents. Enhanced understanding of the genetic alterations characteristic of different subtypes is needed to pave the way for more personalized administration of therapeutic agents. We have taken a functional genomics approach using a well-characterized panel of breast cancer cell lines to identify putative biomarkers of resistance to antimitotic agents such as paclitaxel and monomethyl-auristatin-E (MMAE). In vitro studies revealed a striking difference in sensitivity to these agents between cell lines from different subtypes, with basal-like cell lines being significantly more sensitive to both agents than luminal or HER2-amplified cell lines. Genome-wide association studies using copy number data from Affymetrix single nucleotide polymorphism arrays identified amplification of the chromosome 17q21 region as being highly associated with resistance to both paclitaxel and MMAE. An unbiased approach consisting of RNA interference and high content analysis was used to show that amplification and concomitant overexpression of the gene encoding the ABCC3 drug transporter is responsible for conferring in vitro resistance to paclitaxel and MMAE. We also show that amplification of ABCC3 is present in primary breast tumors and that it occurs predominantly in HER2-amplified and luminal tumors, and we report on development of a specific fluorescence in situ hybridization assay that may have utility as a predictive biomarker of taxane resistance in breast cancer.

Molecular predictors of response to a humanized anti–insulin-like growth factor-I receptor monoclonal antibody in breast and colorectal cancer

The insulin-like growth factor-I receptor (IGF-IR) pathway is required for the maintenance of the transformed phenotype in neoplastic cells and hence has been the subject of intensive drug discovery efforts. A key aspect of successful clinical development of targeted therapies directed against IGF-IR will be identification of responsive patient populations. Toward that end, we have endeavored to identify predictive biomarkers of response to an anti-IGF-IR-targeting monoclonal antibody in preclinical models of breast and colorectal cancer. We find that levels of the IGF-IR itself may have predictive value in these tumor types and identify other gene expression predictors of in vitro response. Studies in breast cancer models suggest that IGF-IR expression is both correlated and functionally linked with estrogen receptor signaling and provide a basis for both patient stratification and rational combination therapy with antiestrogen-targeting agents. In addition, we find that levels of other components of the signaling pathway such as the adaptor proteins IRS1 and IRS2, as well as the ligand IGF-II, have predictive value and report on the development of a pathway-focused panel of diagnostic biomarkers that could be used to test these hypotheses during clinical development of IGF-IR-targeting therapies. [Mol Cancer Ther 2009;8(8):2110–21]

Oncogenic activating mutations are associated with local copy gain.

Although activating mutations and gains in copy number are key mechanisms for oncogene activation, the relationship between the two is not well understood. In this study, we focused on KRAS copy gains and mutations in non–small cell lung cancer. We found that KRAS copy gains occur more frequently in tumors with KRAS activating mutations and are associated with large increases in KRAS expression. These copy gains tend to be more focal in tumors with activating mutations than in those with wild-type KRAS. Fluorescence in situ hybridization analysis revealed that some tumors have homogeneous low-level gains of the KRAS locus, whereas others have high-level amplification of KRAS, often in only a fraction of tumor cells. Associations between activating mutation and copy gains were also observed for other oncogenes (EGFR in non–small cell lung cancer, BRAF and NRAS in melanoma). Activating mutations were associated with copy gains only at the mutated oncogene locus but not other oncogene loci. However, KRAS activating mutations in colorectal cancer were not associated with copy gains. Future work is warranted to clarify the relationship among the different mechanisms of oncogene activation. (Mol Cancer Res 2009;7(8):1244–52)

Inferring the functional effects of mutation through clusters of mutations in homologous proteins.

Inferring functional consequences is a bottleneck in high‐throughput cancer mutation discovery and genetic association studies. Most polymorphisms and germline mutations are unlikely to have functionally significant consequences. Most cancer somatic mutations do not contribute to tumorigenesis and are not under selective pressure. Identifying and understanding functionally important mutations can clarify disease biology and lead to new therapeutic and diagnostic opportunities. We investigated the extent to which protein mutations with functional consequences are enriched in clusters at conserved positions across related proteins. We found that disease‐causing mutations form clusters more than random mutations or single nucleotide polymorphisms, confirming that mutation hotspots occur at the domain level. In addition to helping to identify functionally significant mutations, analysis of clustered mutations can indicate the mechanism and consequences for protein function. Our analysis focused on somatic cancer mutations suggests functional impact for many, including singleton mutations in FGFR1, FGFR3, GFI1B, PIK3CG, RALB, RAP2B, and STK11. This provides evidence and generates mechanistic hypotheses for the contribution of such mutations to cancer. The same approach can be applied to mutations suspected of involvement in other diseases. An interactive Web application for browsing mutation clusters is available at http://www.mcluster.org. Hum Mutat 30:1–9, 2010.