Jennifer A. Rohrs

Co-Eradication of Breast Cancer Cells and Cancer Stem Cells by Cross-Linked Multilamellar Liposomes Enhances Tumor Treatment.

The therapeutic limitations of conventional chemotherapeutic drugs have emerged as a challenge for breast cancer therapy; these shortcomings are likely due, at least in part, to the presence of the cancer stem cells (CSCs). Salinomycin, a polyether antibiotic isolated from Streptomyces albus, has been shown to selectively inhibit cancer stem cells; however, its clinical application has been hindered by the drugs hydrophobility, which limits the available administration routes. In this paper, a novel drug delivery system, cross-linked multilamellar liposomal vesicles (cMLVs), was optimized to allow for the codelivery of salinomycin (Sal) and doxorubicin (Dox), targeting both CSCs and breast cancer cells. The results show that the cMLV particles encapsulating different drugs have similar sizes with high encapsulation efficiencies (>80%) for both Dox and Sal. Dox and Sal were released from the particles in a sustained manner, indicating the stability of the cMLVs. Moreover, the inhibition of cMLV(Dox+Sal) against breast cancer cells was stronger than either single-drug treatment. The efficient targeting of cMLV(Dox+Sal) to CSCs was validated through in vitro experiments using breast cancer stem cell markers. In accordance with the in vitro combination treatment, in vivo breast tumor suppression by cMLV(Dox+Sal) was 2-fold more effective than single-drug cMLV treatment or treatment with the combination of cMLV(Dox) and cMLV(Sal). Thus, this study demonstrates that cMLVs represent a novel drug delivery system that can serve as a potential platform for combination therapy, allowing codelivery of an anticancer agent and a CSC inhibitor for the elimination of both breast cancer cells and cancer stem cells.

Development and Challenges of Nanovectors in Gene Therapy

In recent years, hundreds of genes have been linked to a variety of human diseases, and the field of gene therapy has emerged as a way to treat this wide range of diseases. The main goal of gene therapy is to find a gene delivery vehicle that can successfully target diseased cells and deliver therapeutic genes directly to their cellular compartment. The two main types of gene delivery vectors currently being investigated in clinical trials are recombinant viral vectors and synthetic nonviral vectors. Recombinant viral vectors take advantage of the evolutionarily optimized viral mechanisms to deliver genes, but they can be hard to specifically target in vivo and are also associated with serious side effects. Synthetic nonviral vectors are made out of highly biocompatible lipids or polymers, but they are much less efficient at delivering their genetic payload due to the lack of any active delivery mechanism. This mini review will introduce the current state of gene delivery in clinical trials, and discuss t...

Predictive model of thrombospondin-1 and vascular endothelial growth factor in breast tumor tissue

Angiogenesis, the formation of new blood capillaries from pre-existing vessels, is a hallmark of cancer. Thus far, strategies for reducing tumor angiogenesis have focused on inhibiting pro-angiogenic factors, and less is known about the therapeutic effects of mimicking the actions of angiogenesis inhibitors. Thrombospondin-1 (TSP1) is an important endogenous inhibitor of angiogenesis that has been investigated as an anti-angiogenic agent. TSP1 impedes the growth of new blood vessels in many ways, including crosstalk with pro-angiogenic factors. Owing to the complexity of TSP1 signaling, a predictive systems biology model would provide quantitative understanding of the angiogenic balance in tumor tissue. Therefore, we have developed a molecular-detailed, mechanistic model of TSP1 and vascular endothelial growth factor (VEGF), a promoter of angiogenesis, in breast tumor tissue. The model predicts the distribution of the angiogenic factors in tumor tissue, revealing that TSP1 is primarily in an inactive, cleaved form owing to the action of proteases, rather than bound to its cellular receptors or to VEGF. The model also predicts the effects of enhancing TSP1’s interactions with its receptors and with VEGF. To provide additional predictions that can guide the development of new anti-angiogenic drugs, we simulate administration of exogenous TSP1 mimetics that bind specific targets. The model predicts that the CD47-binding TSP1 mimetic markedly decreases the ratio of receptor-bound VEGF to receptor-bound TSP1, in favor of anti-angiogenesis. Thus, we have established a model that provides a quantitative framework to study the response to TSP1 mimetics.

Advances and Challenges in the Use of Nanoparticles to Optimize PK/PD Interactions of Combined Anti-Cancer Therapies

Combination chemotherapy has become the primary strategy for treating cancer; however, the clinical success of combination treatments is limited by the distinct pharmacokinetics (PK) of different drugs, which lead to nonuniform distribution and an inability to coordinate dosing regimes at the site of the tumor. In the first half of this review, we will discuss the recent development of nanoparticlebased combination strategies to overcome these limitations. Nanoparticles are able to co-encapsulate and carry multiple drugs with different hydrophobicities while maintaining precise ratiometric loading and delivery. They can also temporally sequence the release of multiple drugs and reduce undesirable PK interactions. In the second half of this review, we will touch on the key factors that affect nanoparticle stability and distribution. Nanoparticles provide a promising strategy to improve combinatorial cancer treatments by better controlling PK and metabolic differences between drugs.

Predictive Model of Lymphocyte-Specific Protein Tyrosine Kinase (LCK) Autoregulation

Lymphocyte-specific protein tyrosine kinase (LCK) is a key activator of T cells; however, little is known about the specific autoregulatory mechanisms that control its activity. We have constructed a model of LCK autophosphorylation and phosphorylation by the regulating kinase CSK. The model was fit to existing experimental data in the literature that presents an in vitro reconstituted membrane system, which provides more physiologically relevant kinetic measurements than traditional solution-based systems. The model is able to predict a robust mechanism of LCK autoregulation. It provides insights into the molecular causes of key site-specific phosphorylation differences between distinct experimental conditions. Probing the model also provides new hypotheses regarding the influence of individual binding and catalytic rates, which can be tested experimentally. This minimal model is required to elucidate the mechanistic interactions of LCK and CSK and can be further expanded to better understand T cell activation from a systems perspective. Our computational model enables the evaluation of LCK protein interactions that mediate T cell activation on a more quantitative level, providing new insights and testable hypotheses.

CAR-T Cells Surface-Engineered with Drug-Encapsulated Nanoparticles Can Ameliorate Intratumoral T-Cell Hypofunction

CAR-T cells were conjugated to A2aR antagonist-loaded nanoparticles to overcome an immunosuppressive, adenosine-rich TME. Treating tumor-bearing mice with drug-conjugated CAR-T cells enhanced tumor control and survival, as well as improved antitumor efficacy of the CAR T-cell treatment. One limiting factor of CAR T-cell therapy for treatment of solid cancers is the suppressive tumor microenvironment (TME), which inactivates the function of tumor-infiltrating lymphocytes (TIL) through the production of immunosuppressive molecules, such as adenosine. Adenosine inhibits the function of CD4+ and CD8+ T cells by binding to and activating the A2a adenosine receptor (A2aR) expressed on their surface. This suppression pathway can be blocked using the A2aR-specific small molecule antagonist SCH-58261 (SCH), but its applications have been limited owing to difficulties delivering this drug to immune cells within the TME. To overcome this limitation, we used CAR-engineered T cells as active chaperones to deliver SCH-loaded cross-linked, multilamellar liposomal vesicles (cMLV) to tumor-infiltrating T cells deep within the immune suppressive TME. Through in vitro and in vivo studies, we have demonstrated that this system can be used to effectively deliver SCH to the TME. This treatment may prevent or rescue the emergence of hypofunctional CAR-T cells within the TME. Cancer Immunol Res; 6(7); 812–24. ©2018 AACR.

Combination drug delivery via multilamellar vesicles enables targeting of tumor cells and tumor vasculature

Blood vessel development is critical for the continued growth and progression of solid tumors and, therefore, makes an attractive target for improving cancer therapy. Indeed, vascular‐targeted therapies have been extensively explored but they have shown minimal efficacy as monotherapies. Combretastatin A4 (CA‐4) is a tubulin‐binding vascular disrupting agent that selectively targets the established tumor endothelium, causing rapid vascular beak down. Despite its potent anticancer potential, the drug has dose‐limiting side effects, particularly in the form of cardiovascular toxicity. Furthermore, its poor aqueous solubility and the resulting limited bioavailability hinder its antitumor activity in the clinic. To improve the therapeutic efficacy of CA‐4, we investigated its application as a combination therapy with doxorubicin (Dox) in a tumor vasculature targeted delivery vehicle: peptide‐modified cross‐linked multilamellar liposomal vesicles (cMLVs). In vitro cell culture studies showed that a tumor vasculature‐targeting peptide, RIF7, could facilitate higher cellular uptake of drug‐loaded cMLVs, and consequently enhance the antitumor efficacy in both drug resistant B16 mouse melanoma and human MDA‐MB‐231 breast cancer cells. In vivo, upon intravenous injection, targeted cMLVs could efficiently deliver both Dox and CA‐4 to significantly slow tumor growth through the specific interaction of the targeting peptide with its receptor on the surface of tumor vasculature. This study demonstrates the potential of our novel targeted combination therapy delivery vehicle to improve the outcome of cancer treatment.

Constructing predictive cancer systems biology models

Systems biology combines computational modeling with quantitative experimental measurements to study complex biological processes. Here, we outline an approach for parameterizing and validating a systems biology model to yield predictive tool that can generate testable hypotheses and expand biological understanding.

Abstract NG01: Effects of altering receptor structure in CAR T cells: Predictions from an experimentally-validated systems biology model

Background and motivation. As T cell immunotherapy applications have expanded, it has become increasingly important to better understand the signaling events that lead to T cell activation. We are particularly interested in chimeric antigen receptor- (CAR-) engineered T cells (CAR-T cells). CAR-T cells have emerged as a promising treatment for B cell lymphoma, but their success has not transferred to other cancer types. This is, in part, due to a fundamental lack of understanding of the mechanistic signaling events initiated by the CAR intracellular domains, which prevents us from being able to engineer an optimal CAR. Traditional CARs consist of intracellular signaling domains derived from CD3ζ, the main activating domain in the endogenous T cell receptor (TCR), and a co-stimulatory domain, such as CD28. The immuno-tyrosine activating motifs (ITAMs) on CD3ζ are able to induce T cell cytotoxicity on their own, while CD28 and other co-stimulatory signaling domains augment particular aspects of the response. It is known that phosphorylation of the six tyrosine sites on CD3ζ and four on CD28 by lymphocyte-specific protein tyrosine kinase (LCK) results in downstream signaling that leads to T cell activation. However, the specific mechanisms that control LCK9s binding and catalytic activity are not well defined. These ten phosphorylation sites on the CAR contribute to different signaling events in the T cells, so understanding the mechanisms through which these sites are activated can inform the best strategies for engineering the next generations of CARs. To date, development of CAR constructs is largely achieved using a trial-and-error experimental approach, which has several disadvantages: it does not uncover why a particular CAR construct works; it does not necessarily identify the optimal design, just a particular design that works; and it does not generate insight that can be generalized to different cancer types. Additionally, this trial-and-error approach does not consider the intracellular signaling induced by the CAR, which ultimately governs T cell function and promotes cell killing. Our proposed research uses computational modeling to address these limitations. In this study, I describe our work to develop a predictive mechanistic computational model that describes the signaling events that occur upon CAR activation. This work builds on our published model of LCK autoregulation [1]. Here, we use quantitative phospho-proteomic mass spectroscopy and computational modeling to quantify the site-specific kinetics of CD3ζ and CD28 phosphorylation. We apply the model to improve our understanding of how CAR structure influences activation and to develop new hypotheses for the optimal design of CAR-engineered T cell systems. Citation Format: Jennifer A. Rohrs, Dongqing Zheng, Nicholas A. Graham, Pin Wang, Stacey D. Finley. Effects of altering receptor structure in CAR T cells: Predictions from an experimentally-validated systems biology model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr NG01.

Computational Model of Chimeric Antigen Receptors Explains Site-Specific Phosphorylation Kinetics

Chimeric antigen receptors (CARs) have recently been approved for the treatment of hematological malignancies, but our lack of understanding of the basic mechanisms that activate these proteins has made it difficult to optimize and control CAR-based therapies. In this study, we use phosphoproteomic mass spectrometry and mechanistic computational modeling to quantify the in vitro kinetics of individual tyrosine phosphorylation on a variety of CARs. We show that each of the 10 tyrosine sites on the CD28-CD3ζ CAR is phosphorylated by lymphocyte-specific protein-tyrosine kinase (LCK) with distinct kinetics. The addition of CD28 at the N-terminal of CD3ζ increases the overall rate of CD3ζ phosphorylation. Our computational model identifies that LCK phosphorylates CD3ζ through a mechanism of competitive inhibition. This model agrees with previously published data in the literature and predicts that phosphatases in this system interact with CD3ζ through a similar mechanism of competitive inhibition. This quantitative modeling framework can be used to better understand CAR signaling and T cell activation.