A Forward Genetic Screen Targeting the Endothelium Reveals a Regulatory Role for the Lipid Kinase Pi4ka in Myelo- and Erythropoiesis

Given its role as the source of definitive hematopoietic cells, we sought to determine whether mutations initiated in the hemogenic endothelium would yield hematopoietic abnormalities or malignancies. Here, we find that endothelium-specific transposon mutagenesis in mice promotes hematopoietic pathologies that are both myeloid and lymphoid in nature. Frequently mutated genes included previously recognized cancer drivers and additional candidates, such as Pi4ka, a lipid kinase whose mutation was found to promote myeloid and erythroid dysfunction. Subsequent validation experiments showed that targeted inactivation of the Pi4ka catalytic domain or reduction in mRNA expression inhibited myeloid and erythroid cell differentiation in vitro and promoted anemia in vivo through a mechanism involving deregulation of AKT, MAPK, SRC, and JAK-STAT signaling. Finally, we provide evidence linking PI4KAP2, previously considered a pseudogene, to human myeloid and erythroid leukemia.

Vav3-induced cytoskeletal dynamics contribute to heterotypic properties of endothelial barriers

Through multiple cell-cell and cell-matrix interactions, epithelial and endothelial sheets form tight barriers. Modulators of the cytoskeleton contribute to barrier stability and act as rheostats of vascular permeability. In this study, we sought to identify cytoskeletal regulators that underlie barrier diversity across vessels. To achieve this, we correlated functional and structural barrier features to gene expression of endothelial cells (ECs) derived from different vascular beds. Within a subset of identified candidates, we found that the guanosine nucleotide exchange factor Vav3 was exclusively expressed by microvascular ECs and was closely associated with a high-resistance barrier phenotype. Ectopic expression of Vav3 in large artery and brain ECs significantly enhanced barrier resistance and cortical rearrangement of the actin cytoskeleton. Mechanistically, we found that the barrier effect of Vav3 is dependent on its Dbl homology domain and downstream activation of Rap1. Importantly, inactivation of Vav3 in vivo resulted in increased vascular leakage, highlighting its function as a key regulator of barrier stability.

Perivascular Macrophages Limit Permeability

OBJECTIVE

Perivascular cells, including pericytes, macrophages, smooth muscle cells, and other specialized cell types, like podocytes, participate in various aspects of vascular function. However, aside from the well-established roles of smooth muscle cells and pericytes, the contributions of other vascular-associated cells are poorly understood. Our goal was to ascertain the function of perivascular macrophages in adult tissues under nonpathological conditions.

APPROACH AND RESULTS

We combined confocal microscopy, in vivo cell depletion, and in vitro assays to investigate the contribution of perivascular macrophages to vascular function. We found that resident perivascular macrophages are associated with capillaries at a frequency similar to that of pericytes. Macrophage depletion using either clodronate liposomes or antibodies unexpectedly resulted in hyperpermeability. This effect could be rescued when M2-like macrophages, but not M1-like macrophages or dendritic cells, were reconstituted in vivo, suggesting subtype-specific roles for macrophages in the regulation of vascular permeability. Furthermore, we found that permeability-promoting agents elicit motility and eventual dissociation of macrophages from the vasculature. Finally, in vitro assays showed that M2-like macrophages attenuate the phosphorylation of VE-cadherin upon exposure to permeability-promoting agents.

CONCLUSIONS

This study points to a direct contribution of macrophages to vessel barrier integrity and provides evidence that heterotypic cell interactions with the endothelium, in addition to those of pericytes, control vascular permeability.

Autocrine VEGF maintains endothelial survival through regulation of metabolism and autophagy

Autocrine VEGF is necessary for endothelial survival, although the cellular mechanisms supporting this function are unknown. Here, we show that--even after full differentiation and maturation--continuous expression of VEGF by endothelial cells is needed to sustain vascular integrity and cellular viability. Depletion of VEGF from the endothelium results in mitochondria fragmentation and suppression of glucose metabolism, leading to increased autophagy that contributes to cell death. Gene-expression profiling showed that endothelial VEGF contributes to the regulation of cell cycle and mitochondrial gene clusters, as well as several--but not all--targets of the transcription factor FOXO1. Indeed, VEGF-deficient endothelium in vitro and in vivo showed increased levels of FOXO1 protein in the nucleus and cytoplasm. Silencing of FOXO1 in VEGF-depleted cells reversed expression profiles of several of the gene clusters that were de-regulated in VEGF knockdown, and rescued both cell death and autophagy phenotypes. Our data suggest that endothelial VEGF maintains vascular homeostasis through regulation of FOXO1 levels, thereby ensuring physiological metabolism and endothelial cell survival.

Canonical and noncanonical vascular endothelial growth factor pathways: new developments in biology and signal transduction

The past 5 years have witnessed a significant expansion in our understanding of vascular endothelial growth factor (VEGF) signaling. In particular, the process of canonical activation of VEGF receptor tyrosine kinases by homodimeric VEGF molecules has now been broadened by the realization that heterodimeric ligands and receptors are also active participants in the signaling process. Although heterodimer receptors were described 2 decades ago, their impact, along with the effect of additional cell surface partners and novel autocrine VEGF signaling pathways, are only now starting to be clarified. Furthermore, ligand-independent signaling (noncanonical) has been identified through galectin and gremlin binding and upon rise of intracellular levels of reactive oxygen species. Activation of the VEGF receptors in the absence of ligand holds immediate implications for therapeutic approaches that exclusively target VEGF. The present review provides a concise summary of the recent developments in both canonical and noncanonical VEGF signaling and places these findings in perspective to their potential clinical and biological ramifications.

A ligand-independent VEGFR2 signaling pathway limits angiogenic responses in diabetes

Although vascular complications are a hallmark of diabetes, the molecular mechanisms that underlie endothelial dysfunction are unclear. We showed that reactive oxygen species generated from hyperglycemia promoted ligand-independent phosphorylation of vascular endothelial growth factor receptor 2 (VEGFR2). This VEGFR2 signaling occurred within the Golgi compartment and resulted in progressively decreased availability of VEGFR2 at the cell surface. Consequently, the responses of endothelial cells to exogenous VEGF in a mouse model of diabetes were impaired because of a specific deficiency of VEGFR2 at the cell surface, despite a lack of change in transcript abundance. Hyperglycemia-induced phosphorylation of VEGFR2 did not require intrinsic receptor kinase activity and was instead mediated by Src family kinases. The reduced cell surface abundance of VEGFR2 in diabetic mice was reversed by treatment with the antioxidant N-acetyl-L-cysteine, suggesting a causative role for oxidative stress. These findings uncover a mode of ligand-independent VEGFR2 signaling that can progressively lead to continuously muted responses to exogenous VEGF and limit angiogenic events.

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

Background

An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data.

Results

We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information.

Conclusions

The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge.

Molecular mechanisms of tumor angiogenesis

Tumors have been recently recognized as aberrant organs composed of a complex mixture of highly interactive cells that in addition to the cancer cell include stroma (fibroblasts, adipocytes, and myofibroblasts), inflammatory (innate and adaptive immune cells), and vascular cells (endothelial and mural cells). While initially cancer cells co-opt tissue-resident vessels, the tumor eventually recruits its own vascular supply. The process of tumor neovascularization proceeds through the combined output of inductive signals from the entire cellular constituency of the tumor. During the last two decades, the identification and mechanistic outcome of signaling pathways that mediate tumor angiogenesis have been elucidated. Interestingly, many of the genes and signaling pathways activated in tumor angiogenesis are identical to those operational during developmental vascular growth, but they lack feedback regulatory control and are highly affected by inflammatory cells and hypoxia. Consequently, tumor vessels are abnormal, fragile, and hyperpermeable. The lack of hierarchy and inconsistent investment of mural cells dampen the ability of the vessels to effectively perfuse the tumor, and the resulting hypoxia installs a vicious cycle that continuously perpetuates a state of vascular inefficiency. Pharmacological targeting of blood vessels, mainly through the VEGF signaling pathway, has proven effective in normalizing tumor vessels. This normalization improves perfusion and distribution of chemotherapeutic drugs with resulting tumor suppression and moderate increase in overall survival. However, resistance to antiangiogenic therapy occurs frequently and constitutes a critical barrier in the inhibition of tumor growth. A concrete understanding of the chief signaling pathways that stimulate vascular growth in tumors and their cross-talk will continue to be essential to further refine and effectively abort the angiogenic response in cancer.

Abstract 1979: Algebraic factorization of gene expression profiles reveals subtype-specific drug sensitivities among 54 breast cancer cell lines

Breast cancer is a heterogeneous disease, with reproducible and prognostically important subclasses. Breast cancer cell lines are widely used to study preclinical investigational agents, but the relationships, if any, between breast cancer subclass and drug response are not well understood. To help bridge this gap, we have profiled drug responses across a large panel of well-annotated breast cancer cell lines. In order to translate in vitro drug responses into clinically useful predictions, it is important that the cell line panel be organized into subtypes representative of the cancer subtype diversity found in the clinic. Recent studies have demonstrated that an algebraic clustering method known as “non-negative matrix factorization” (NMF) can be applied to gene expression profiles to resolve clinically meaningful cancer subtypes in greater detail than achievable using other clustering methods. To test whether NMF improves our ability to resolve drug sensitivities in breast cancer cell lines, we clustered pretreatment gene expression profiles of 54 breast cancer cell lines using two different methods: (1) NMF-based consensus clustering and (2) hierarchical consensus clustering. Using NMF-based consensus, we identified five robust subtypes (two Basal-A, one Basal-B and two Luminal classes). In contrast, using hierarchical consensus clustering, we could identify only three robust subtypes (one Basal-A, one Basal-B and one Luminal class). The drug response profiles were then segregated by subtype to determine whether either of the two clustering methods improves our ability to resolve drug sensitivities. Of the 67 drug compounds included in our study, the 5-subtype NMF-based classification scheme revealed three compounds (AG1024, CPT-11 and topotecan) exhibiting subtype-specific drug effects (p<0.1) that are undetectable using the 3-subtype hierarchical clustering. The statistical significance of drug sensitivity was gauged using the Kruskal-Wallis rank sum test, adjusted for false discovery rate Q=0.05. In conclusion, NMF consensus clustering can be used to detect drug response patterns that would otherwise go undetected.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1979.

Activity of the kinesin spindle protein inhibitor ispinesib (SB-715992) in models of breast cancer

PURPOSE

Ispinesib (SB-715992) is a potent inhibitor of kinesin spindle protein, a kinesin motor protein essential for the formation of a bipolar mitotic spindle and cell cycle progression through mitosis. Clinical studies of ispinesib have shown a 9% response rate in patients with locally advanced or metastatic breast cancer and a favorable safety profile without significant neurotoxicities, gastrointestinal toxicities, or hair loss. To better understand the potential of ispinesib in the treatment of breast cancer, we explored the activity of ispinesib alone and in combination with several therapies approved for the treatment of breast cancer.

EXPERIMENTAL DESIGN

We measured the ispinesib sensitivity and pharmacodynamic response of breast cancer cell lines representative of various subtypes in vitro and as xenografts in vivo and tested the ability of ispinesib to enhance the antitumor activity of approved therapies.

RESULTS

In vitro, ispinesib displayed broad antiproliferative activity against a panel of 53 breast cell lines. In vivo, ispinesib produced regressions in each of five breast cancer models and tumor-free survivors in three of these models. The effects of ispinesib treatment on pharmacodynamic markers of mitosis and apoptosis were examined in vitro and in vivo, revealing a greater increase in both mitotic and apoptotic markers in the MDA-MB-468 model than in the less sensitive BT-474 model. In vivo, ispinesib enhanced the antitumor activity of trastuzumab, lapatinib, doxorubicin, and capecitabine and exhibited activity comparable with paclitaxel and ixabepilone.

CONCLUSIONS

These findings support further clinical exploration of kinesin spindle protein inhibitors for the treatment of breast cancer.

A Systems Analysis of Mitotic Apparatus Inhibitors Defines a Response Network for Breast Cancer

Deregulation of aspects of the mitotic apparatus leads to increased genome instability, carcinogenesis and aggressive tumor behavior in human and rodent model systems1. This knowledge has stimulated development of inhibitors of elements of the mitotic apparatus as anticancer agents including PLK1, CENPE, and AURKB and several are now being tested for efficacy clincially2-6. These trials and eventual clinical use will benefit from molecular markers that predict response. In order to identify such markers, we assessed quantitative responses to the agents GSK461364, GSK923295 and GSK1070916 that target PLK1, CENPE and AURKB; respectively, in a panel of 50 breast cancer cell lines. This analysis showed that basal subtype cell lines were preferentially sensitive to all three agents and that responses among the lines to the three agents were strongly correlated. This may be explained by our discovery that components of the mitotic apparatus including PLK1, CENPE and AURKB form a transcriptionally co-regulated network comprised of more than 50 genes that is preferentially active in basal subtype of breast cell lines and primary tumors. Remarkably, this network also is activate in subsets of cancers of the lung, ovarian, prostate and brain, Wilms tumor, human blood malignancies and selected normal tissues. We then defined a mitotic apparatus network index (MANI) and showed that high MANI was associated with poor outcome clinically and with preferential responsive to GSK461364, GSK923295 and GSK1070916 in preclinical models. This suggests that measures of the MANI will identify poor outcome tumors that will likely respond well to mitotic apparatus network gene inhibitors as well as potential dose limiting normal tissues.Reference1. Quigley, D.A. et al. Nature 458, 505-8 (2009).2. Strebhardt, K. & Ullrich, A. Nat. Rev. Cancer 6, 321-330 (2006).3. Toyoshima-Morimoto, F., Taniguchi, E., Shinya, N., Iwamatsu, A. & Nishida, E. Nature 410, 215-20 (2001).4. Barr, F.A., Sillje, H.H. & Nigg, E.A. Nat. Rev. Mol. Cell. Biol. 5, 429–440 (2004).5. McInnes, C. et al. Nat. Chem. Biol. 2, 608–617 (2006).6. Yamada, S. et al. Oncogene 23, 5901-5911(2004).

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 2020.

A systems analysis of the chemosensitivity of breast cancer cells to the polyamine analogue PG-11047

BACKGROUND

Polyamines regulate important cellular functions and polyamine dysregulation frequently occurs in cancer. The objective of this study was to use a systems approach to study the relative effects of PG-11047, a polyamine analogue, across breast cancer cells derived from different patients and to identify genetic markers associated with differential cytotoxicity.

METHODS

A panel of 48 breast cell lines that mirror many transcriptional and genomic features present in primary human breast tumours were used to study the antiproliferative activity of PG-11047. Sensitive cell lines were further examined for cell cycle distribution and apoptotic response. Cell line responses, quantified by the GI50 (dose required for 50% relative growth inhibition) were correlated with the omic profiles of the cell lines to identify markers that predict response and cellular functions associated with drug sensitivity.

RESULTS

The concentrations of PG-11047 needed to inhibit growth of members of the panel of breast cell lines varied over a wide range, with basal-like cell lines being inhibited at lower concentrations than the luminal cell lines. Sensitive cell lines showed a significant decrease in S phase fraction at doses that produced little apoptosis. Correlation of the GI50 values with the omic profiles of the cell lines identified genomic, transcriptional and proteomic variables associated with response.

CONCLUSIONS

A 13-gene transcriptional marker set was developed as a predictor of response to PG-11047 that warrants clinical evaluation. Analyses of the pathways, networks and genes associated with response to PG-11047 suggest that response may be influenced by interferon signalling and differential inhibition of aspects of motility and epithelial to mesenchymal transition.

Integrated analysis of breast cancer cell lines reveals unique signaling pathways

Mapping of sub-networks in the EGFR-MAPK pathway in different breast cancer cell lines reveals that PAK1 may be a marker for sensitivity to MEK inhibitors.

Background

Cancer is a heterogeneous disease resulting from the accumulation of genetic defects that negatively impact control of cell division, motility, adhesion and apoptosis. Deregulation in signaling along the EgfR-MAPK pathway is common in breast cancer, though the manner in which deregulation occurs varies between both individuals and cancer subtypes.

Results

We were interested in identifying subnetworks within the EgfR-MAPK pathway that are similarly deregulated across subsets of breast cancers. To that end, we mapped genomic, transcriptional and proteomic profiles for 30 breast cancer cell lines onto a curated Pathway Logic symbolic systems model of EgfR-MAPK signaling. This model was composed of 539 molecular states and 396 rules governing signaling between active states. We analyzed these models and identified several subtype-specific subnetworks, including one that suggested Pak1 is particularly important in regulating the MAPK cascade when it is over-expressed. We hypothesized that Pak1 over-expressing cell lines would have increased sensitivity to Mek inhibitors. We tested this experimentally by measuring quantitative responses of 20 breast cancer cell lines to three Mek inhibitors. We found that Pak1 over-expressing luminal breast cancer cell lines are significantly more sensitive to Mek inhibition compared to those that express Pak1 at low levels. This indicates that Pak1 over-expression may be a useful clinical marker to identify patient populations that may be sensitive to Mek inhibitors.

Conclusions

All together, our results support the utility of symbolic system biology models for identification of therapeutic approaches that will be effective against breast cancer subsets.

Sparse combinatorial inference with an application in cancer biology

MOTIVATION

Combinatorial effects, in which several variables jointly influence an output or response, play an important role in biological systems. In many settings, Boolean functions provide a natural way to describe such influences. However, biochemical data using which we may wish to characterize such influences are usually subject to much variability. Furthermore, in high-throughput biological settings Boolean relationships of interest are very often sparse, in the sense of being embedded in an overall dataset of higher dimensionality. This motivates a need for statistical methods capable of making inferences regarding Boolean functions under conditions of noise and sparsity.

RESULTS

We put forward a statistical model for sparse, noisy Boolean functions and methods for inference under the model. We focus on the case in which the form of the underlying Boolean function, as well as the number and identity of its inputs are all unknown. We present results on synthetic data and on a study of signalling proteins in cancer biology.