Drug Sensitivity Screening and Targeted Pathway Analysis Reveal a Multi-Driver Proliferative Mechanism and Suggest a Strategy of Combination Targeted Therapy for Colorectal Cancer Cells

Challenges and Opportunities in Developing Targeted Therapies for Triple Negative Breast Cancer

Triple negative breast cancer (TNBC) is a heterogeneous group of breast cancers characterized by their lack of estrogen receptors, progesterone receptors, and the HER2 receptor. They are more aggressive than other breast cancer subtypes, with a higher mean tumor size, higher tumor grade, the worst five-year overall survival, and the highest rates of recurrence and metastasis. Developing targeted therapies for TNBC has been a major challenge due to its heterogeneity, and its treatment still largely relies on surgery, radiation therapy, and chemotherapy. In this review article, we review the efforts in developing targeted therapies for TNBC, discuss insights gained from these efforts, and highlight potential opportunities going forward. Accumulating evidence supports TNBCs as multi-driver cancers, in which multiple oncogenic drivers promote cell proliferation and survival. In such multi-driver cancers, targeted therapies would require drug combinations that simultaneously block multiple oncogenic drivers. A strategy designed to generate mechanism-based combination targeted therapies for TNBC is discussed.

Dasatinib in combination with BMS-754807 induce synergistic cytotoxicity in lung cancer cells through inhibiting lung cancer cell growth, and inducing autophagy as well as cell cycle arrest at the G1 phase

Lung cancer is the leading cause of cancer-related deaths worldwide. Combination of drugs targeting independent signaling pathways would effectively block the proliferation of cancer cells with lower concentrations and stronger synergy effects. Dasatinib, a multi-targeted protein tyrosine kinase inhibitor targeting BCR-ABL and kinases of SRC family, has been successfully applied in the treatment of chronic myeloid leukemia (CML). BMS-754807, an inhibitor targeting the insulin-like growth factor 1 receptor (IGF-IR) and insulin receptor (IR) family kinases, has been in phase I development for the treatment of a variety of human cancers. Herein, we demonstrated that dasatinib in combination with BMS-754807 inhibited lung cancer cell growth, while induced autophagy as well as cell cycle arrest at the G1 phase. Dasatinib in combination with BMS-754807 suppressed the expression of cell cycle marker proteins, Rb, p-Rb, CDK4, CDK6 and Cyclin D1, and the PI3K/Akt/mTOR signaling pathway. Dasatinib in combination with BMS-754807 induced autophagy in lung cancer cells, evidenced by the upregulation of LC3B II and beclin-1, the downregulation of LC3B I and SQSTM1/p62, and the autophagic flux observed with a confocal fluorescence microscopy. Furthermore, dasatinib (18 mg/kg) in combination with BMS-754807 (18 mg/kg) inhibited the growth of tumors in NCI-H3255 xenografts without changing the bodyweight. Overall, our results suggest that dasatinib in combination with BMS-754807 inhibits the lung cancer cell proliferation in vitro and tumor growth in vitro, which indicates promising evidence for the application of the drug combination in lung cancer therapy.

A combinatorial strategy for overcoming primary and acquired resistance of MEK inhibition in colorectal cancer

Compared with traditional chemotherapeutic drugs, targeted therapeutic medicine has the advantages of high efficacy and less toxic side effects. However, in clinical practice for treatment of colorectal cancer, the primary and acquired resistance of these medicines limits their effectiveness in targeted therapy, therefore impedes the development of precision medicine and personalized therapy. Currently, there are limited number of drugs for targeted therapy of colorectal cancer, mainly monoclonal antibodies against EGFR or VEGFR inhibitors. Trametinib, a MEK inhibitor, has been applied in melanoma patient successfully, but not been used in clinical treatment of colorectal cancer because of its drug resistance. To identify the resistance mechanism of colorectal cancer cells to trametinib and find useful chemical combination to overcome the resistance, we screened primary and acquired cell line first and then tested multiple synergistic drug combinations by using the Chou-Talalay method. We obtained the primary resistant cell lines SW480, CW-2 and the acquired drug-resistant cell line RKO-R as well as a synergistic combination of trametinib and GSK2126458. This combination inhibits the colony formation of colorectal cancer cells and the growth of xenograft tumors in nude mice. Mechanistic analysis showed that trametinib can activate the alternative PI3K-AKT signaling pathway while inhibiting the MAPK pathway, which may be one of the molecular mechanisms of primary and acquired trametinib tolerance in colorectal cancer cells. Importantly, this bypass activation can be blocked by GSK2126458. These results suggest that a combination of trametinib and GSK2126458 is an effective approach for treating colorectal cancer resistance to trametinib.

Application of a Biphasic Mathematical Model of Cancer Cell Drug Response for Formulating Potent and Synergistic Targeted Drug Combinations to Triple Negative Breast Cancer Cells

Triple negative breast cancer is a collection of heterogeneous breast cancers that are immunohistochemically negative for estrogen receptor, progesterone receptor, and ErbB2 (due to deletion or lack of amplification). No dominant proliferative driver has been identified for this type of cancer, and effective targeted therapy is lacking. In this study, we hypothesized that triple negative breast cancer cells are multi-driver cancer cells, and evaluated a biphasic mathematical model for identifying potent and synergistic drug combinations for multi-driver cancer cells. The responses of two triple negative breast cancer cell lines, MDA-MB-231 and MDA-MB-468, to a panel of targeted therapy drugs were determined over a broad range of concentrations. The analyses of the drug responses by the biphasic mathematical model revealed that both cell lines were indeed dependent on multiple drivers, and inhibitors of individual drivers caused a biphasic response: a target-specific partial inhibition at low nM concentrations, and an off-target toxicity at μM concentrations. We further demonstrated that combinations of drugs, targeting each driver, cause potent, synergistic, and cell-specific cell killing. Immunoblotting analysis of the effects of the individual drugs and drug combinations on the signaling pathways supports the above conclusion. These results support a multi-driver proliferation hypothesis for these triple negative breast cancer cells, and demonstrate the applicability of the biphasic mathematical model for identifying effective and synergistic targeted drug combinations for triple negative breast cancer cells.

Biphasic Mathematical Model of Cell-Drug Interaction That Separates Target-Specific and Off-Target Inhibition and Suggests Potent Targeted Drug Combinations for Multi-Driver Colorectal Cancer Cells

Quantifying the response of cancer cells to a drug, and understanding the mechanistic basis of the response, are the cornerstones for anti-cancer drug discovery. Classical single target-based IC₅₀ measurements are inadequate at describing cancer cell responses to targeted drugs. In this study, based on an analysis of targeted inhibition of colorectal cancer cell lines, we develop a new biphasic mathematical model that accurately describes the cell–drug response. The model describes the drug response using three kinetic parameters: ratio of target-specific inhibition, F₁, potency of target-specific inhibition, K_d1, and potency of off-target toxicity, K_d2. Determination of these kinetic parameters also provides a mechanistic basis for predicting effective combination targeted therapy for multi-driver cancer cells. The experiments confirmed that a combination of inhibitors, each blocking a driver pathway and having a distinct target-specific effect, resulted in a potent and synergistic blockade of cell viability, improving potency over mono-agent treatment by one to two orders of magnitude. We further demonstrate that mono-driver cancer cells represent a special scenario in which F₁ becomes nearly 100%, and the drug response becomes monophasic. Application of this model to the responses of >400 cell lines to kinase inhibitor dasatinib revealed that the ratio of biphasic versus monophasic responses is about 4:1. This study develops a new mathematical model of quantifying cancer cell response to targeted therapy, and suggests a new framework for developing rational combination targeted therapy for colorectal and other multi-driver cancers.