Dual Inhibition of IGF-1R and ErbB3 Enhances the Activity of Gemcitabine and Nab-Paclitaxel in Preclinical Models of Pancreatic Cancer.

Purpose: Insulin-like growth factor receptor 1 (IGF-1R) is critically involved in pancreatic cancer pathophysiology, promoting cancer cell survival and therapeutic resistance. Assessment of IGF-1R inhibitors in combination with standard-of-care chemotherapy, however, failed to demonstrate significant clinical benefit. The aim of this work is to unravel mechanisms of resistance to IGF-1R inhibition in pancreatic cancer and develop novel strategies to improve the activity of standard-of-care therapies.Experimental Design: Growth factor screening in pancreatic cancer cell lines was performed to identify activators of prosurvival PI3K/AKT signaling. The prevalence of activating growth factors and their receptors was assessed in pancreatic cancer patient samples. Effects of a bispecific IGF-1R and ErbB3 targeting antibody on receptor expression, signaling, cancer cell viability and apoptosis, spheroid growth, and in vivo chemotherapy activity in pancreatic cancer xenograft models were determined.Results: Growth factor screening in pancreatic cancer cells revealed insulin-like growth factor 1 (IGF-1) and heregulin (HRG) as the most potent AKT activators. Both growth factors reduced pancreatic cancer cell sensitivity to gemcitabine or paclitaxel in spheroid growth assays. Istiratumab (MM-141), a novel bispecific antibody that blocks IGF-1R and ErbB3, restored the activity of paclitaxel and gemcitabine in the presence of IGF-1 and HRG in vitro Dual IGF-1R/ErbB3 blocking enhanced chemosensitivity through inhibition of AKT phosphorylation and promotion of IGF-1R and ErbB3 degradation. Addition of istiratumab to gemcitabine and nab-paclitaxel improved chemotherapy activity in vivoConclusions: Our findings suggest a critical role for the HRG/ErbB3 axis and support the clinical exploration of dual IGF-1R/ErbB3 blocking in pancreatic cancer. Clin Cancer Res; 24(12); 2873-85. ©2018 AACR.

Analysis of growth factor signaling in genetically diverse breast cancer lines.

BACKGROUND: Soluble growth factors present in the microenvironment play a major role in tumor development, invasion, metastasis, and responsiveness to targeted therapies. While the biochemistry of growth factor-dependent signal transduction has been studied extensively in individual cell types, relatively little systematic data are available across genetically diverse cell lines. RESULTS: We describe a quantitative and comparative dataset focused on immediate-early signaling that regulates the AKT (AKT1/2/3) and ERK (MAPK1/3) pathways in a canonical panel of well-characterized breast cancer lines. We also provide interactive web-based tools to facilitate follow-on analysis of the data. Our findings show that breast cancers are diverse with respect to ligand sensitivity and signaling biochemistry. Surprisingly, triple negative breast cancers (TNBCs; which express low levels of ErbB2, progesterone and estrogen receptors) are the most broadly responsive to growth factors and HER2amp cancers (which overexpress ErbB2) the least. The ratio of ERK to AKT activation varies with ligand and subtype, with a systematic bias in favor of ERK in hormone receptor positive (HR+) cells. The factors that correlate with growth factor responsiveness depend on whether fold-change or absolute activity is considered the key biological variable, and they differ between ERK and AKT pathways. CONCLUSIONS: Responses to growth factors are highly diverse across breast cancer cell lines, even within the same subtype. A simple four-part heuristic suggests that diversity arises from variation in receptor abundance, an ERK/AKT bias that depends on ligand identity, a set of factors common to all receptors that varies in abundance or activity with cell line, and an "indirect negative regulation" by ErbB2. This analysis sets the stage for the development of a mechanistic and predictive model of growth factor signaling in diverse cancer lines. Interactive tools for looking up these results and downloading raw data are available at http://lincs.hms.harvard.edu/niepel-bmcbiol-2014/.

Profiles of Basal and stimulated receptor signaling networks predict drug response in breast cancer lines.

Identifying factors responsible for variation in drug response is essential for the effective use of targeted therapeutics. We profiled signaling pathway activity in a collection of breast cancer cell lines before and after stimulation with physiologically relevant ligands, which revealed the variability in network activity among cells of known genotype and molecular subtype. Despite the receptor-based classification of breast cancer subtypes, we found that the abundance and activity of signaling proteins in unstimulated cells (basal profile), as well as the activity of proteins in stimulated cells (signaling profile), varied within each subtype. Using a partial least-squares regression approach, we constructed models that significantly predicted sensitivity to 23 targeted therapeutics. For example, one model showed that the response to the growth factor receptor ligand heregulin effectively predicted the sensitivity of cells to drugs targeting the cell survival pathway mediated by PI3K (phosphoinositide 3-kinase) and Akt, whereas the abundance of Akt or the mutational status of the enzymes in the pathway did not. Thus, basal and signaling protein profiles may yield new biomarkers of drug sensitivity and enable the identification of appropriate therapies in cancers characterized by similar functional dysregulation of signaling networks.

Therapeutically targeting ErbB3: a key node in ligand-induced activation of the ErbB receptor-PI3K axis.

The signaling network downstream of the ErbB family of receptors has been extensively targeted by cancer therapeutics; however, understanding the relative importance of the different components of the ErbB network is nontrivial. To explore the optimal way to therapeutically inhibit combinatorial, ligand-induced activation of the ErbB-phosphatidylinositol 3-kinase (PI3K) axis, we built a computational model of the ErbB signaling network that describes the most effective ErbB ligands, as well as known and previously unidentified ErbB inhibitors. Sensitivity analysis identified ErbB3 as the key node in response to ligands that can bind either ErbB3 or EGFR (epidermal growth factor receptor). We describe MM-121, a human monoclonal antibody that halts the growth of tumor xenografts in mice and, consistent with model-simulated inhibitor data, potently inhibits ErbB3 phosphorylation in a manner distinct from that of other ErbB-targeted therapies. MM-121, a previously unidentified anticancer therapeutic designed using a systems approach, promises to benefit patients with combinatorial, ligand-induced activation of the ErbB signaling network that are not effectively treated by current therapies targeting overexpressed or mutated oncogenes.

Inhibition of transcription factor NF-kappaB signaling proteins IKKbeta and p65 through specific cysteine residues by epoxyquinone A monomer: correlation with its anti-cancer cell growth activity.

Transcription factor NF-kappaB is constitutively active in many human chronic inflammatory diseases and cancers. Epoxyquinone A monomer (EqM), a synthetic derivative of the natural product epoxyquinol A, has previously been shown to be a potent inhibitor of tumor necrosis factor-alpha (TNF-alpha)-induced activation of NF-kappaB, but the mechanism by which EqM inhibits NF-kappaB activation was not known. In this report, we show that EqM blocks activation of NF-kappaB by inhibiting two molecular targets: IkappaB kinase IKKbeta and NF-kappaB subunit p65. EqM inhibits TNF-alpha-induced IkappaBalpha phosphorylation and degradation by targeting IKKbeta, and an alanine substitution for Cys179 in the activation loop of IKKbeta makes it resistant to EqM-mediated inhibition. EqM also directly inhibits DNA binding by p65, but not p50; moreover, replacement of Cys38 in p65 with Ser abolishes EqM-mediated inhibition of DNA binding. Pretreatment of cells with reducing agent dithiothreitol dose-dependently reduces EqM-mediated inhibition of NF-kappaB, further suggesting that EqM directly modifies the thiol group of Cys residues in protein targets. Modifications of the exocyclic alkene of EqM substantially reduce EqM's ability to inhibit NF-kappaB activation. In the human SUDHL-4 lymphoma cell line, EqM inhibits both proliferation and NF-kappaB DNA binding, and activates caspase-3 activity. EqM also effectively inhibits the growth of human leukemia, kidney, and colon cancer cell lines in the NCI's tumor cell panel. Among six colon cancer cell lines, those with low amounts of constitutive NF-kappaB DNA-binding activity are generally more sensitive to growth inhibition by EqM. Taken together, these results suggest that EqM inhibits growth and induces cell death in tumor cells through a mechanism that involves inhibition of NF-kappaB activity at multiple steps in the signaling pathway.

A compendium of signals and responses triggered by prodeath and prosurvival cytokines.

Cell-signaling networks consist of proteins with a variety of functions (receptors, adaptor proteins, GTPases, kinases, proteases, and transcription factors) working together to control cell fate. Although much is known about the identities and biochemical activities of these signaling proteins, the ways in which they are combined into networks to process and transduce signals are poorly understood. Network-level understanding of signaling requires data on a wide variety of biochemical processes such as posttranslational modification, assembly of macromolecular complexes, enzymatic activity, and localization. No single method can gather such heterogeneous data in high throughput, and most studies of signal transduction therefore rely on series of small, discrete experiments. Inspired by the power of systematic datasets in genomics, we set out to build a systematic signaling dataset that would enable the construction of predictive models of cell-signaling networks. Here we describe the compilation and fusion of approximately 10,000 signal and response measurements acquired from HT-29 cells treated with tumor necrosis factor-alpha, a proapoptotic cytokine, in combination with epidermal growth factor or insulin, two prosurvival growth factors. Nineteen protein signals were measured over a 24-h period using kinase activity assays, quantitative immunoblotting, and antibody microarrays. Four different measurements of apoptotic response were also collected by flow cytometry for each time course. Partial least squares regression models that relate signaling data to apoptotic response data reveal which aspects of compendium construction and analysis were important for the reproducibility, internal consistency, and accuracy of the fused set of signaling measurements. We conclude that it is possible to build self-consistent compendia of cell-signaling data that can be mined computationally to yield important insights into the control of mammalian cell responses.

Jesterone dimer, a synthetic derivative of the fungal metabolite jesterone, blocks activation of transcription factor nuclear factor kappaB by inhibiting the inhibitor of kappaB kinase.

Rel/nuclear factor-kappaB (NF-kappaB) transcription factors control a variety of cellular processes, such as cell growth and apoptosis, and are continually activated in many human diseases, including chronic inflammatory diseases and cancer. Jesterone dimer (JD) is a synthetic derivative of the natural fungal metabolite jesterone, and JD has previously been shown to be cytotoxic in select tumor cell lines. In this report, we demonstrate that JD is a potent inhibitor of the activation of transcription factor NF-kappaB. Namely, JD inhibits tumor necrosis factor-alpha-induced activation of NF-kappaB in mouse 3T3 and human HeLa cells. JD seems to block the induction of the NF-kappaB pathway by inhibiting the inhibitor of kappaB kinase (IKK); that is, treatment of cells with JD blocks phosphorylation of IkappaBalpha, inhibits the activity of a constitutively active form of the IKKbetacatalytic subunit, and converts IKKbetato stable high molecular mass forms. Like JD, a JD-related epoxyquinoid (isotorreyanic acid) inhibits activation of NF-kappaB at 20 microM, whereas several other epoxyquinoids that are related to JD, including its parent compound jesterone, do not block activation of NF-kappaB at this concentration. Finally, JD inhibits both proliferation and DNA binding by REL-containing complexes in the human lymphoma SUDHL-4 cell line, and JD activates caspase-3 activity in these cells. In summary, these results suggest that JD induces apoptosis in tumor cells through a mechanism that involves the inhibition of Rel/NF-kappaB activity and demonstrate the usefulness of assessing the bioactivity of synthetic derivatives of natural products.

Angiogenesis inhibitor epoxyquinol a: total synthesis and inhibition of transcription factor NF-kappaB.

[reaction: see text] The asymmetric synthesis of the natural product (+)-epoxyquinol A (1) and related epoxyquinoid dimers, employing a cascade oxidation/electrocyclization/Diels-Alder dimerization sequence, is reported. In addition, we show that 1 and related molecules inhibit activation of the transcription factor NF-kappaB.