Heregulin-ErbB3-Driven Tumor Growth Persists in PI3 Kinase Mutant Cancer Cells

Dietary intake of iodine-enriched eggs decreases the incidence of mouse mammary tumors caused by the activated ErbB2 oncogene

Human epigenetic studies suggest that consumption of seaweed prevents mammary cancer, which possibly is explained by iodine daily intake. In this study, we evaluated the efficacy of dietary intake of iodine-enriched eggs on mammary tumor incidence caused by the expression of activated type ErbB2. Female transgenic mice were divided into three groups, and fed a basic diet, a diet supplemented with ordinary eggs, or with iodine-enriched eggs. The number of mammary tumors greater than 5 mm in diameter was recorded in mice at 6 months of age. We report that the average number of mammary tumors per mouse was significantly lower in the iodine-enriched egg-added diet group than in either the basic diet or ordinary egg diet groups. These results indicate that iodine intake through livestock-derived products can reduce the incidence of mammary cancers caused by the expression of activated type ErbB2.

EGFR-TKIs resistance via EGFR-independent signaling pathways

Tyrosine kinase inhibitors (TKIs)-treatments bring significant benefit for patients harboring epidermal growth factor receptor (EGFR) mutations, especially for those with lung cancer. Unfortunately, the majority of these patients ultimately develop to the acquired resistance after a period of treatment. Two central mechanisms are involved in the resistant process: EGFR secondary mutations and bypass signaling activations. In an EGFR-dependent manner, acquired mutations, such as T790 M, interferes the interaction between TKIs and the kinase domain of EGFR. While in an EGFR-independent manner, dysregulation of other receptor tyrosine kinases (RTKs) or abnormal activation of downstream compounds both have compensatory functions against the inhibition of EGFR through triggering phosphatidylinositol 3-kinase (PI3K)/Akt and mitogen-activated protein kinase (MAPK) signaling axes. Nowadays, many clinical trials aiming to overcome and prevent TKIs resistance in various cancers are ongoing or completed. EGFR-TKIs in accompany with the targeted agents for resistance-related factors afford a promising first-line strategy to further clinical application.

Predicting ligand-dependent tumors from multi-dimensional signaling features

Targeted therapies have shown significant patient benefit in about 5-10% of solid tumors that are addicted to a single oncogene. Here, we explore the idea of ligand addiction as a driver of tumor growth. High ligand levels in tumors have been shown to be associated with impaired patient survival, but targeted therapies have not yet shown great benefit in unselected patient populations. Using an approach of applying Bagged Decision Trees (BDT) to high-dimensional signaling features derived from a computational model, we can predict ligand dependent proliferation across a set of 58 cell lines. This mechanistic, multi-pathway model that features receptor heterodimerization, was trained on seven cancer cell lines and can predict signaling across two independent cell lines by adjusting only the receptor expression levels for each cell line. Interestingly, for patient samples the predicted tumor growth response correlates with high growth factor expression in the tumor microenvironment, which argues for a co-evolution of both factors in vivo.

Systems biology driving drug development: from design to the clinical testing of the anti-ErbB3 antibody seribantumab (MM-121)

The ErbB family of receptor tyrosine kinases comprises four members: epidermal growth factor receptor (EGFR/ErbB1), human EGFR 2 (HER2/ErbB2), ErbB3/HER3, and ErbB4/HER4. The first two members of this family, EGFR and HER2, have been implicated in tumorigenesis and cancer progression for several decades, and numerous drugs have now been approved that target these two proteins. Less attention, however, has been paid to the role of this family in mediating cancer cell survival and drug tolerance. To better understand the complex signal transduction network triggered by the ErbB receptor family, we built a computational model that quantitatively captures the dynamics of ErbB signaling. Sensitivity analysis identified ErbB3 as the most critical activator of phosphoinositide 3-kinase (PI3K) and Akt signaling, a key pro-survival pathway in cancer cells. Based on this insight, we designed a fully human monoclonal antibody, seribantumab (MM-121), that binds to ErbB3 and blocks signaling induced by the extracellular growth factors heregulin (HRG) and betacellulin (BTC). In this article, we present some of the key preclinical simulations and experimental data that formed the scientific foundation for three Phase 2 clinical trials in metastatic cancer. These trials were designed to determine if patients with advanced malignancies would derive benefit from the addition of seribantumab to standard-of-care drugs in platinum-resistant/refractory ovarian cancer, hormone receptor-positive HER2-negative breast cancer, and EGFR wild-type non-small cell lung cancer (NSCLC). From preclinical studies we learned that basal levels of ErbB3 phosphorylation correlate with response to seribantumab monotherapy in mouse xenograft models. As ErbB3 is rapidly dephosphorylated and hence difficult to measure clinically, we used the computational model to identify a set of five surrogate biomarkers that most directly affect the levels of p-ErbB3: HRG, BTC, EGFR, HER2, and ErbB3. Preclinically, the combined information from these five markers was sufficient to accurately predict which xenograft models would respond to seribantumab, and the single-most accurate predictor was HRG. When tested clinically in ovarian, breast and lung cancer, HRG mRNA expression was found to be both potentially prognostic of insensitivity to standard therapy and potentially predictive of benefit from the addition of seribantumab to standard of care therapy in all three indications. In addition, it was found that seribantumab was most active in cancers with low levels of HER2, consistent with preclinical predictions. Overall, our clinical studies and studies of others suggest that HRG expression defines a drug-tolerant cancer cell phenotype that persists in most solid tumor indications and may contribute to rapid clinical progression. To our knowledge, this is the first example of a drug designed and clinically tested using the principles of Systems Biology.