Andrew J. Shih

A Multiscale Computational Approach to Dissect Early Events in the Erb Family Receptor Mediated Activation, Differential Signaling, and Relevance to Oncogenic Transformations

We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy-based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the prior modeling of EGF-mediated signal transduction by considering specific EGFR tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and phosphorylation of different C-terminal peptide tyrosines on the RTK tail. By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our molecular dynamics simulations show that the drug sensitizing mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for wildtype vs. mutant receptors) in inhibitor binding as well as preferential enhancement of phosphorylation of particular substrate tyrosines over others. We find that in comparison to the wildtype system, the L834R mutant RTK preferentially binds the inhibitor erlotinib, as well as preferentially phosphorylates the substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential activation of the Akt signaling pathway in comparison to the Erk signaling pathway for cells with normal EGFR expression. For cells with EGFR over expression, the mutant over activates both Erk and Akt pathways, in comparison to wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (mutant) cell lines are shaped differently in relationship to native cell lines.

Molecular Dynamics Analysis of Conserved Hydrophobic and Hydrophilic Bond Interaction Networks in ErbB Family Kinases

The EGFR (epidermal growth factor receptor)/ErbB/HER (human EGFR) family of kinases contains four homologous receptor tyrosine kinases that are important regulatory elements in key signalling pathways. To elucidate the atomistic mechanisms of dimerization-dependent activation in the ErbB family, we have performed molecular dynamics simulations of the intracellular kinase domains of three members of the ErbB family (those with known kinase activity), namely EGFR, ErbB2 (HER2) and ErbB4 (HER4), in different molecular contexts: monomer against dimer and wild-type against mutant. Using bioinformatics and fluctuation analyses of the molecular dynamics trajectories, we relate sequence similarities to correspondence of specific bond-interaction networks and collective dynamical modes. We find that in the active conformation of the ErbB kinases, key subdomain motions are co-ordinated through conserved hydrophilic interactions: activating bond-networks consisting of hydrogen bonds and salt bridges. The inactive conformations also demonstrate conserved bonding patterns (albeit less extensive) that sequester key residues and disrupt the activating bond network. Both conformational states have distinct hydrophobic advantages through context-specific hydrophobic interactions. We show that the functional (activating) asymmetric kinase dimer interface forces a corresponding change in the hydrophobic and hydrophilic interactions that characterize the inactivating bond network, resulting in motion of the αC-helix through allostery. Several of the clinically identified activating kinase mutations of EGFR act in a similar fashion to disrupt the inactivating bond network. The present molecular dynamics study reveals a fundamental difference in the sequence of events in EGFR activation compared with that described for the Src kinase Hck.

Molecular systems biology of ErbB1 signaling: bridging the gap through multiscale modeling and high-performance computing

The complexity in intracellular signaling mechanisms relevant for the conquest of many diseases resides at different levels of organization with scales ranging from the subatomic realm relevant to catalytic functions of enzymes to the mesoscopic realm relevant to the cooperative association of molecular assemblies and membrane processes. Consequently, the challenge of representing and quantifying functional or dysfunctional modules within the networks remains due to the current limitations in our understanding of mesoscopic biology, i.e., how the components assemble into functional molecular ensembles. A multiscale approach is necessary to treat a hierarchy of interactions ranging from molecular (nm, ns) to signaling (microm, ms) length and time scales, which necessitates the development and application of specialized modeling tools. Complementary to multiscale experimentation (encompassing structural biology, mechanistic enzymology, cell biology, and single molecule studies) multiscale modeling offers a powerful and quantitative alternative for the study of functional intracellular signaling modules. Here, we describe the application of a multiscale approach to signaling mediated by the ErbB1 receptor which constitutes a network hub for the cells proliferative, migratory, and survival programs. Through our multiscale model, we mechanistically describe how point-mutations in the ErbB1 receptor can profoundly alter signaling characteristics leading to the onset of oncogenic transformations. Specifically, we describe how the point mutations induce cascading fragility mechanisms at the molecular scale as well as at the scale of the signaling network to preferentially activate the survival factor Akt. We provide a quantitative explanation for how the hallmark of preferential Akt activation in cell-lines harboring the constitutively active mutant ErbB1 receptors causes these cell-lines to be addicted to ErbB1-mediated generation of survival signals. Consequently, inhibition of ErbB1 activity leads to a remarkable therapeutic response in the addicted cell lines.

Analysis of Somatic Mutations in Cancer: Molecular Mechanisms of Activation in the ErbB Family of Receptor Tyrosine Kinases

The ErbB/EGFR/HER family of kinases consists of four homologous receptor tyrosine kinases which are important regulatory elements in many cellular processes, including cell proliferation, differentiation, and migration. Somatic mutations in, or over-expression of, the ErbB family is found in many cancers and is correlated with a poor prognosis; particularly, clinically identified mutations found in non-small-cell lung cancer (NSCLC) of ErbB1 have been shown to increase its basal kinase activity and patients carrying these mutations respond remarkably to the small tyrosine kinase inhibitor gefitinib. Here, we analyze the potential effects of the currently catalogued clinically identified mutations in the ErbB family kinase domains on the molecular mechanisms of kinase activation. Recently, we identified conserved networks of hydrophilic and hydrophobic interactions characteristic to the active and inactive conformation, respectively. Here, we show that the clinically identified mutants influence the kinase activity in distinctive fashion by affecting the characteristic interaction networks.

3.310 – Computational Methods Related to Reaction Chemistry

In this chapter, we discuss the implementation of several computational techniques that are commonly employed to simulate interactions between biomaterials and cellular systems. These methods include molecular dynamics and homology modeling, which focus on the atomic structure of biomaterials, electronic structure methods, and free-energy simulations. Challenges involved in applying these techniques and connections to cellular experiments are also addressed. These computational methods are important tools in delineating the molecular mechanisms involved in the interactions between biomaterials and tissue, which govern biocompatibility. They have also been applied in the rational design of biomaterials, as molecular-based models predict likely recognition sequences and the corresponding conformations at the interface between material surface and extracellular matrix and cell membrane. Focusing on these molecular mechanisms will lead to new insights into the bioactivity of existing biomaterials and to the development of improved biomaterials for use in bone tissue repair therapies. The chapter concludes with a discussion of recent applications of computational methods to the rational design of biomaterials, including the creation of surfaces with tailored functionality and computational modeling of the attachment function of fibronectin.

Paraneoplastic Syndrome Secondary to Treatment Emergent Neuroendocrine Tumor in Metastatic Castration-resistant Prostate Cancer: A Unique Case

Treatment-emergent neuroendocrine prostate cancer has become increasingly more common owing to the development of second-generation anti-hormonal therapy. It is characterized by a morphology similar to small-cell carcinoma, a low prostate-specific antigen, and visceral metastasis. This case features a paraneoplastic Cushing syndrome, initial resistance to androgen receptortargeted therapy, a continuously rising prostatespecific antigen, and a lack of disease spread to visceral organs. RNA sequencing revealed a gene expression profile consistent with a neuroendocrine tumor and identified the potential therapeutic targets such as Aurora kinase A and EZH2. Regardless of PSA levels and the extent of metastatic disease, patients with initial resistance to androgen receptor-directed and new-onset paraneoplastic syndrome should raise a high suspicion of neuroendocrine prostate cancer.

Abstract P2-07-09: Integrative analysis of miRNA and mRNA expression in metastatic versus non-metastatic triple negative breast cancer

Background: Triple Negative Breast Cancer (TNBC) is a subset of breast cancer that is difficult to treat clinically and is characterized by being estrogen receptor (ER) negative, progesterone receptor (PR) negative, and does not overexpress human epidermal growth factor receptor 2 (HER2). Patients with TNBC tend to have a worse prognosis than other breast cancer subtypes. Methods: We obtained fifteen TNBC sample FFPE tissue blocks with corresponding plasma samples. All samples were from primary tumors; seven samples having metastasized, four samples that had not metastasized and four samples with unknown metastatic status. The total RNA was isolated from FFPE blocks using the RecoverAll Total Nucleic Acid Isolation Protocol. miRNA from plasma was isolated using Ambion9s mirVANA kit. The plasma and tissue miRNAs were evaluated using the QuantStudio qPCR platform, capturing ˜750 miRNAs. The mRNA was processed using the TruSeq RNA Access kit and sequenced on the Illumina NextSeq platform. Analysis of the miRNA and mRNA individually was performed using limma and DESeq2 packages, respectively. Gene enrichment analysis of the mRNA expression was done using the GAGE package on KEGG pathways while the integrative analysis was done with sparse Canonical Correlation Analysis (sCCA) using the PMA pacakge. Results: Analysis of plasma miRNA had four miRNAs with a significant difference in raw p-value (p Conclusions: One of the circulating plasma miRNAs, miR483-3p, has been found to promote tumorigenesis, while miR581f and miR766 have not been reported in cancer to date. Further investigation into these miRNA could provide a feasible biomarker. The downregulation of immune pathways observed within the metastatic TNBC subjects implies immune evasion is of particular importance for metastasis and a targeted immunotherapy may be a viable treatment option. The integrative analysis of the miRNA and mRNA showed an enrichment in pathways previously linked to increased proliferation and chemoresistance, with an increased signal compared to either miRNA or mRNA alone. Citation Format: Shih AJ, Korsunsky I, Guttadauria B, Bhuiya T, Liew A, Khalili H, Gregersen PK, Lee AT. Integrative analysis of miRNA and mRNA expression in metastatic versus non-metastatic triple negative breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-07-09.