Michael Morrissey

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens.

Interfering with Resistance to Smoothened Antagonists by Inhibition of the PI3K Pathway in Medulloblastoma

Resistance of medulloblastoma to Smo antagonists can be delayed or prevented by specific drug combinations. An End Run Against Tumor Resistance Cancer cells are as clever as microbes. Mustering their considerable abilities to rapidly replicate and evolve, both cancer cells and bacteria quickly develop resistance to the drugs we use to fight them. Modern medicine confronts a growing population of pathogens that cannot be treated by our usual antibiotics, and oncologists must be prepared with second- and third-line therapies, because tumors that retreat from initial drug treatments often return with renewed vigor. Buonamici et al. confront this problem in their study of a new class of cancer therapeutic agents now in clinical trials—antagonists of a membrane protein called Smoothened (Smo). The Smo receptor normally regulates a developmental pathway but is abnormally activated in medulloblastoma (a malignant brain tumor) and basal cell carcinoma of the skin. Medulloblastomas in mice respond well to these Smo antagonists but soon become resistant, these authors find. If, however, an inhibitor of the phosphatidylinositol 3-kinase (PI3K) signaling pathway is added to the initial drug cocktail, resistance is delayed or even prevented. In some cancers, the Smo receptor is active even when its ligand is absent, conferring dependence of the tumor on the downstream Hedgehog signaling pathway, which ultimately regulates gene expression through the Gli transcription factors. Treatment of Smo-addicted tumors in mice with Smo antagonists ultimately leads to development of resistance, although tumor growth is inhibited for a while. The authors found that the tumors eluded the drug in several ways: The genes for the Gli transcription factors were sometimes amplified, compensating for loss of pathway stimulation. In other resistant tumors, there were point mutations in the Smo receptor itself that allowed reactivation of the pathway. In yet another group of tumors, by examining which genes were up-regulated, the authors found activation of a completely different signaling pathway—the PI3K pathway. Further experiments in medulloblastoma-bearing mice revealed that resistance could be delayed or even prevented by including a PI3K inhibitor along with the Smo antagonist in the initial treatment that tumor-bearing animals received. The PI3K inhibitor alone had no effect. By looking at resistance mechanisms to Smo antagonists before the drug is used in the clinic, the results of this study will better arm oncologists against the molecular defenses that cancers may commandeer to evade this drug. And by identifying a drug combination that delays or even combats development of resistance when used as a first-line treatment in clinical trials, these results could ultimately improve the lives of patients with medulloblastoma or other cancers that depend on Smo for their survival. The malignant brain cancer medulloblastoma is characterized by mutations in Hedgehog (Hh) signaling pathway genes, which lead to constitutive activation of the G protein (heterotrimeric guanosine triphosphate–binding protein)–coupled receptor Smoothened (Smo). The Smo antagonist NVP-LDE225 inhibits Hh signaling and induces tumor regression in animal models of medulloblastoma. However, evidence of resistance was observed during the course of treatment. Molecular analysis of resistant tumors revealed several resistance mechanisms. We noted chromosomal amplification of Gli2, a downstream effector of Hh signaling, and, more rarely, point mutations in Smo that led to reactivated Hh signaling and restored tumor growth. Analysis of pathway gene expression signatures also, unexpectedly, identified up-regulation of phosphatidylinositol 3-kinase (PI3K) signaling in resistant tumors as another potential mechanism of resistance. Probing the relevance of increased PI3K signaling, we demonstrated that addition of the PI3K inhibitor NVP-BKM120 or the dual PI3K-mTOR (mammalian target of rapamycin) inhibitor NVP-BEZ235 to the initial treatment with the Smo antagonist markedly delayed the development of resistance. Our findings may be useful in informing treatment strategies for medulloblastoma.

Pharmacological and genomic profiling identifies NF-κB–targeted treatment strategies for mantle cell lymphoma

Mantle cell lymphoma (MCL) is an aggressive malignancy that is characterized by poor prognosis. Large-scale pharmacological profiling across more than 100 hematological cell line models identified a subset of MCL cell lines that are highly sensitive to the B cell receptor (BCR) signaling inhibitors ibrutinib and sotrastaurin. Sensitive MCL models exhibited chronic activation of the BCR-driven classical nuclear factor-κB (NF-κB) pathway, whereas insensitive cell lines displayed activation of the alternative NF-κB pathway. Transcriptome sequencing revealed genetic lesions in alternative NF-κB pathway signaling components in ibrutinib-insensitive cell lines, and sequencing of 165 samples from patients with MCL identified recurrent mutations in TRAF2 or BIRC3 in 15% of these individuals. Although they are associated with insensitivity to ibrutinib, lesions in the alternative NF-κB pathway conferred dependence on the protein kinase NIK (also called mitogen-activated protein 3 kinase 14 or MAP3K14) both in vitro and in vivo. Thus, NIK is a new therapeutic target for MCL treatment, particularly for lymphomas that are refractory to BCR pathway inhibitors. Our findings reveal a pattern of mutually exclusive activation of the BCR–NF-κB or NIK–NF-κB pathways in MCL and provide critical insights into patient stratification strategies for NF-κB pathway–targeted agents.

Contribution of Polycomb Homologues Bmi-1 and Mel-18 to Medulloblastoma Pathogenesis

ABSTRACT Bmi-1 and Mel-18 are structural homologues that belong to the Polycomb group of transcriptional regulators and are believed to stably maintain repression of gene expression by altering the state of chromatin at specific promoters. While a number of clinical and experimental observations have implicated Bmi-1 in human tumorigenesis, the role of Mel-18 in cancer cell growth has not been investigated. We report here that short hairpin RNA-mediated knockdown of either Bmi-1 or Mel-18 in human medulloblastoma DAOY cells results in the inhibition of proliferation, loss of clonogenic survival, anchorage-independent growth, and suppression of tumor formation in nude mice. Furthermore, overexpression of both Bmi-1 and Mel-18 significantly increases the clonogenic survival of Rat1 fibroblasts. In contrast, stable downregulation of Bmi-1 or Mel-18 alone does not affect the growth of normal human WI38 fibroblasts. Proteomics-based characterization of Bmi-1 and Mel-18 protein complexes isolated from cancer cells revealed substantial similarities in their respective compositions. Finally, gene expression analysis identified a number of cancer-relevant pathways that may be controlled by Bmi-1 and Mel-18 and also showed that these Polycomb proteins regulate a set of common gene targets. Taken together, these results suggest that Bmi-1 and Mel-18 may have overlapping functions in cancer cell growth.

Association of MTOR Mutations With Developmental Brain Disorders, Including Megalencephaly, Focal Cortical Dysplasia, and Pigmentary Mosaicism

IMPORTANCE Focal cortical dysplasia (FCD), hemimegalencephaly, and megalencephaly constitute a spectrum of malformations of cortical development with shared neuropathologic features. These disorders are associated with significant childhood morbidity and mortality. OBJECTIVE To identify the underlying molecular cause of FCD, hemimegalencephaly, and diffuse megalencephaly. DESIGN, SETTING, AND PARTICIPANTS Patients with FCD, hemimegalencephaly, or megalencephaly (mean age, 11.7 years; range, 2-32 years) were recruited from Pediatric Hospital A. Meyer, the University of Hong Kong, and Seattle Childrens Research Institute from June 2012 to June 2014. Whole-exome sequencing (WES) was performed on 8 children with FCD or hemimegalencephaly using standard-depth (50-60X) sequencing in peripheral samples (blood, saliva, or skin) from the affected child and their parents and deep (150-180X) sequencing in affected brain tissue. Targeted sequencing and WES were used to screen 93 children with molecularly unexplained diffuse or focal brain overgrowth. Histopathologic and functional assays of phosphatidylinositol 3-kinase-AKT (serine/threonine kinase)-mammalian target of rapamycin (mTOR) pathway activity in resected brain tissue and cultured neurons were performed to validate mutations. MAIN OUTCOMES AND MEASURES Whole-exome sequencing and targeted sequencing identified variants associated with this spectrum of developmental brain disorders. RESULTS Low-level mosaic mutations of MTOR were identified in brain tissue in 4 children with FCD type 2a with alternative allele fractions ranging from 0.012 to 0.086. Intermediate-level mosaic mutation of MTOR (p.Thr1977Ile) was also identified in 3 unrelated children with diffuse megalencephaly and pigmentary mosaicism in skin. Finally, a constitutional de novo mutation of MTOR (p.Glu1799Lys) was identified in 3 unrelated children with diffuse megalencephaly and intellectual disability. Molecular and functional analysis in 2 children with FCD2a from whom multiple affected brain tissue samples were available revealed a mutation gradient with an epicenter in the most epileptogenic area. When expressed in cultured neurons, all MTOR mutations identified here drive constitutive activation of mTOR complex 1 and enlarged neuronal size. CONCLUSIONS AND RELEVANCE In this study, mutations of MTOR were associated with a spectrum of brain overgrowth phenotypes extending from FCD type 2a to diffuse megalencephaly, distinguished by different mutations and levels of mosaicism. These mutations may be sufficient to cause cellular hypertrophy in cultured neurons and may provide a demonstration of the pattern of mosaicism in brain and substantiate the link between mosaic mutations of MTOR and pigmentary mosaicism in skin.

The Polycomb Group Protein Bmi-1 Is Essential for the Growth of Multiple Myeloma Cells

Bmi-1 is a member of the Polycomb group family of proteins that function in the epigenetic silencing of genes governing self-renewal, differentiation, and proliferation. Bmi-1 was first identified through its ability to accelerate c-Myc-induced lymphomagenesis. Subsequent studies have further supported an oncogenic role for Bmi-1 in several cancers including those of the breast, lung, prostate, and brain. Using a stable and inducible shRNA system to silence Bmi-1 gene expression, we show a novel role for Bmi-1 in regulating the growth and clonogenic capacity of multiple myeloma cells both in vitro and in vivo. Moreover, to elucidate novel gene targets controlled by Bmi-1, global transcriptional profiling studies were performed in the setting of induced loss of Bmi-1 function. We found that the expression of the proapoptotic gene Bim is negatively regulated by Bmi-1 and that Bim knockdown functionally rescues the apoptotic phenotype induced upon loss of Bmi-1. Therefore, these studies not only highlight Bmi-1 as a cancer-dependent factor in multiple myeloma, but also elucidate a novel antiapoptotic mechanism for Bmi-1 function involving the suppression of Bim.

PureCN: copy number calling and SNV classification using targeted short read sequencing

BackgroundMatched sequencing of both tumor and normal tissue is routinely used to classify variants of uncertain significance (VUS) into somatic vs. germline. However, assays used in molecular diagnostics focus on known somatic alterations in cancer genes and often only sequence tumors. Therefore, an algorithm that reliably classifies variants would be helpful for retrospective exploratory analyses. Contamination of tumor samples with normal cells results in differences in expected allelic fractions of germline and somatic variants, which can be exploited to accurately infer genotypes after adjusting for local copy number. However, existing algorithms for determining tumor purity, ploidy and copy number are not designed for unmatched short read sequencing data.ResultsWe describe a methodology and corresponding open source software for estimating tumor purity, copy number, loss of heterozygosity (LOH), and contamination, and for classification of single nucleotide variants (SNVs) by somatic status and clonality. This R package, PureCN, is optimized for targeted short read sequencing data, integrates well with standard somatic variant detection pipelines, and has support for matched and unmatched tumor samples. Accuracy is demonstrated on simulated data and on real whole exome sequencing data.ConclusionsOur algorithm provides accurate estimates of tumor purity and ploidy, even if matched normal samples are not available. This in turn allows accurate classification of SNVs. The software is provided as open source (Artistic License 2.0) R/Bioconductor package PureCN (http://bioconductor.org/packages/PureCN/).

Abstract B27: Correlation between TNFα and LCL161 anti‐tumor activity in patient derived xenograft models of human cancer

LCL161, a small molecule antagonist of inhibitor of apoptosis proteins (IAPs), induces TNF ‐mediated apoptosis in a subset of tumor cell lines including the MDA‐MB‐231 breast cancer line. To investigate the in vivo activity of LCL161, MDA‐MB‐231 tumor bearing mice were treated with a once weekly oral dose. We observed anti‐tumor activity that was associated with pharmacodynamic responses including degradation of CIAP1 and induction of cleaved caspase 3. The loss of CIAP1, specifically the E3 ligase activity of this protein, has been shown to directly impact the stability of a number of client proteins including NIK (NF‐κB inducing kinase), Mad1 (MAX‐binding protein), and others. Gene expression analysis on LCL161 treated MDA‐MB‐231 tumors revealed a striking upregulation of NF‐κB regulated target genes. These data were further supported by the observation that TNFα, a direct target of NF‐κB, was induced in LCL161 treated MDAMB‐231 tumor lysates. To explore whether TNFα expression levels could be used to predict single agent efficacy in a more clinically relevant context, a series of human primary tumor xenografts were profiled for baseline TNFα mRNA levels and evaluated for response to LCL161 in vivo. We observed that tumors with the highest TNFα expression levels showed the greatest sensitivity to LCL161. These studies demonstrate an essential role of the NF‐κB pathway in IAP antagonist anti‐tumor activity. Ongoing efforts focus on delineating the contribution of the canonical and non‐canonical NF‐κB pathways to efficacy and on leveraging this mechanism for LCL161 patient selection. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):B27.

Molecular analysis of a male breast cancer patient with prolonged stable disease under mTOR/PI3K inhibitors BEZ235/everolimus

The mTORC1 inhibitor everolimus (Afinitor/RAD001) has been approved for multiple cancer indications, including ER+/HER2− metastatic breast cancer. However, the combination of everolimus with the dual PI3K/mTOR inhibitor BEZ235 was shown to be more efficacious than either everolimus or BEZ235 alone in preclinical models. Herein, we describe a male breast cancer (MBC) patient who was diagnosed with hormone receptor-positive (HR+)/HER2− stage IIIA invasive ductal carcinoma and sequentially treated with chemoradiotherapy and hormonal therapy. Upon the development of metastases, the patient began a 200 mg twice-daily BEZ235 and 2.5 mg weekly everolimus combination regimen. The patient sustained a prolonged stable disease of 18 mo while undergoing the therapy, before his tumor progressed again. Therefore, we sought to both better understand MBC and investigate the underlying molecular mechanisms of the patients sensitivity and subsequent resistance to the BEZ235/everolimus combination therapy. Genomic and immunohistochemical analyses were performed on samples collected from the initial invasive ductal carcinoma pretreatment and a metastasis postprogression on the BEZ235/everolimus combination treatment. Both tumors were relatively quiet genomically with no overlap to recurrent MBC alterations in the literature. Markers of PI3K/mTOR pathway hyperactivation were not identified in the pretreatment sample, which complements previous reports of HR+ female breast cancers being responsive to mTOR inhibition without this activation. The postprogression sample, however, demonstrated greater than fivefold increased estrogen receptor and pathogenesis-related protein expression, which could have constrained the PI3K/mTOR pathway inhibition by BEZ235/everolimus. Overall, these analyses have augmented the limited episteme on MBC genetics and treatment.

Prediction of drug response using genomic signatures from the Cancer Cell Line Encyclopedia

Accurate prediction of patient drug response is required for successful personalized medicine. Cancer is a disease resulting from myriad genetic alterations. Accordingly, it should be possible to predict drug response of specific cancers using genetic and molecular signatures. To aid this effort, an ongoing collaboration established between Novartis and the Broad Institute called the Cancer Cell Line Encyclopedia (CCLE) has (i) comprehensively characterized genome-scale mRNA expression, copy number alteration and mutation profiles for nearly 1000 cancer cell line models spanning many tumor types and (ii) profiled ~500 of these cell lines against ~1000 anticancer compounds. Using these data, we are developing a scalable, extensible predictive modeling framework based on various supervised learning methods that include both categorical classification and linear regression approaches to predict compound sensitivity. By cross-validation of the generated models against test data sets, we quantitatively estimated model performance. Our initial results validate several preexisting genetic predictors of sensitivity. In addition, our models reported 70% or higher sensitivity and specificity for a number of compounds and yielded interesting potentially novel predictive features that, in some cases, outperform previously existing genetic predictors of sensitivity. Our integrative approach demonstrates that pharmacological profiling of large, genomically annotated cancer model systems, coupled with systematic predictive modeling, can uncover novel predictors of drug response and may ultimately aid patient stratification. This talk is also presented as Poster A4.