A Novel Network Profiling Analysis Reveals System Changes in Epithelial-Mesenchymal Transition

Patient-specific analysis of molecular networks is a promising strategy for making individual risk predictions and treatment decisions in cancer therapy. Although systems biology allows the gene network of a cell to be reconstructed from clinical gene expression data, traditional methods, such as Bayesian networks, only provide an averaged network for all samples. Therefore, these methods cannot reveal patient-specific differences in molecular networks during cancer progression. In this study, we developed a novel statistical method called NetworkProfiler, which infers patient-specific gene regulatory networks for a specific clinical characteristic, such as cancer progression, from gene expression data of cancer patients. We applied NetworkProfiler to microarray gene expression data from 762 cancer cell lines and extracted the system changes that were related to the epithelial-mesenchymal transition (EMT). Out of 1732 possible regulators of E-cadherin, a cell adhesion molecule that modulates the EMT, NetworkProfiler, identified 25 candidate regulators, of which about half have been experimentally verified in the literature. In addition, we used NetworkProfiler to predict EMT-dependent master regulators that enhanced cell adhesion, migration, invasion, and metastasis. In order to further evaluate the performance of NetworkProfiler, we selected Krueppel-like factor 5 (KLF5) from a list of the remaining candidate regulators of E-cadherin and conducted in vitro validation experiments. As a result, we found that knockdown of KLF5 by siRNA significantly decreased E-cadherin expression and induced morphological changes characteristic of EMT. In addition, in vitro experiments of a novel candidate EMT-related microRNA, miR-100, confirmed the involvement of miR-100 in several EMT-related aspects, which was consistent with the predictions obtained by NetworkProfiler

Identifying the Rules of Engagement Enabling Leukocyte Rolling, Activation, and Adhesion

The LFA-1 integrin plays a pivotal role in sustained leukocyte adhesion to the endothelial surface, which is a precondition for leukocyte recruitment into inflammation sites. Strong correlative evidence implicates LFA-1 clustering as being essential for sustained adhesion, and it may also facilitate rebinding events with its ligand ICAM-1. We cannot challenge those hypotheses directly because it is infeasible to measure either process during leukocyte adhesion following rolling. The alternative approach undertaken was to challenge the hypothesized mechanisms by experimenting on validated, working counterparts: simulations in which diffusible, LFA1 objects on the surfaces of quasi-autonomous leukocytes interact with simulated, diffusible, ICAM1 objects on endothelial surfaces during simulated adhesion following rolling. We used object-oriented, agent-based methods to build and execute multi-level, multi-attribute analogues of leukocytes and endothelial surfaces. Validation was achieved across different experimental conditions, in vitro, ex vivo, and in vivo, at both the individual cell and population levels. Because those mechanisms exhibit all of the characteristics of biological mechanisms, they can stand as a concrete, working theory about detailed events occurring at the leukocyte–surface interface during leukocyte rolling and adhesion experiments. We challenged mechanistic hypotheses by conducting experiments in which the consequences of multiple mechanistic events were tracked. We quantified rebinding events between individual components under different conditions, and the role of LFA1 clustering in sustaining leukocyte–surface adhesion and in improving adhesion efficiency. Early during simulations ICAM1 rebinding (to LFA1) but not LFA1 rebinding (to ICAM1) was enhanced by clustering. Later, clustering caused both types of rebinding events to increase. We discovered that clustering was not necessary to achieve adhesion as long as LFA1 and ICAM1 object densities were above a critical level. Importantly, at low densities LFA1 clustering enabled improved efficiency: adhesion exhibited measurable, cell level positive cooperativity

Signaling Mechanisms of Vav3, a Guanine Nucleotide Exchange Factor and Androgen Receptor Coactivator, in Physiology and Prostate Cancer Progression

The Rho GTPase guanine nucleotide exchange factor (GEF) Vav3 is the third member of the Vavfamily of GEFS and is activated by tyrosine phosphorylation. Through stimulation of Rho GTPaseactivity, Vav3 promotes cell migration, invasion, and other cellular processes. Work from our laboratory first established that Vav3 is upregulated in models of castration-resistant prostate cancer progression and enhances androgen receptor as well as androgen receptor splice variant activity. Recent analysis of clinical specimens supports Vav3 as a potential biomarker of aggressive prostate cancer. Consistent with a role in promoting castration-­resistant disease, Vav3 is a versatile enhancer of androgen receptor by both ligand-dependent and ligand-independent mechanisms and as such impacts established pathways of androgen receptor reactivation in advanced prostate cancer. Distinct Vav3 domains and mechanisms participate in ligand-dependent and -independent androgen receptor coactivation. To provide a physiologic context, we review Vav3 actions elucidated by gene knockout studies. This chapter describes the pervasive role of Vav3 in progression of prostate cancer to castration resistance. We discuss the mechanisms by which prostate cancer cells exploit Vav3 signaling to promote androgen receptor activity under different hormonal milieus, which are relevant to clinical prostate cancer. Lastly, we review the data on the emerging role for Vav3 in other cancers ranging from leukemias to gliomas.https://nsuworks.nova.edu/hpd_medsci_faculty_books/1002/thumbnail.jp