Adaptive Resistance to Targeted Cancer Therapies and Rational Development of Combination Therapies

Dear Colleagues,

Although genetic events are important determinants of resistance to molecularly targeted therapies, the sensitivity of tumors to drugs is also substantially shaped by the plasticity of tumor cells, which, through epigenetic mechanisms and remodulation of gene expression and through the complex dynamics of intracellular signaling networks, underlies adaptation to drug-induced perturbations. Drug resistance can be deciphered as an adaptation of a complex system to a perturbation affecting one or a few of its elements.

Adaptive resistance has been defined as a form of nongenomic resistance that intervenes rapidly and is potentially reversible and targetable. A thorough understanding of this form of resistance would facilitate the development of more effective therapies. Phenomena such as paradoxical activation of the ERK pathway by BRAF inhibitors, the rapid onset of BRAF inhibitor resistance in melanoma patients, the compensatory activation of one pathway following inhibition of a parallel pathway (e.g., PI3K/AKT and RAS/ERK), and the variable effects of targeted therapies on apoptosis and cellular senescence, underscore the importance of a thorough understanding of cancer cell responses to drugs. This underlies the rational development of effective drug combinations specific to any single tumor, aiming to avoid or delay the development of resistance.

This Special Issue will explore the phenomena of adaptive resistance to molecularly targeted therapies, with a systems perspective, to stimulate research in the area of rational drug combinations.

Dr. Andrea Rocca
Prof. Dr. Boris Kholodenko
Guest Editors

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• targeted therapies
• cancer drug resistance
• adaptive resistance
• signal transduction networks
• network adaptation
• cell state transitions

Title: Model-based analysis reveals different dosing strategies for beneficial combination of pan-RAF and MEK inhibitors in BRAF vs NRAS mutant melanomas
Authors: Gerosa, Luca
Affiliation: Harvard Medical School., Boston, United States

Title: Cell state transition models enable engineering breast cancer cell phenotypes
Authors: Oleksii S. Rukhlenko; Hiroaki Imoto; Ayush Tambde; Amy McGillycuddy; Philipp Junk; Anna Tuliakova; Walter Kolch; Boris N. Kholodenko
Affiliation: 1 Systems Biology Ireland, School of Medicine, University College Dublin, Dublin, Ireland; 2 Stratford college, Dublin, Ireland; 3 Technological University Dublin, Ireland; 4 Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland; 5 Department of Pharmacology, Yale University School of Medicine, New Haven, USA.
Abstract: Understanding signalling patterns of transformation and controlling cell phenotypes is a challenge of current biology. Here we applied a cell State Transition Assessment and Regulation (cSTAR) approach to a publicly available perturbation dataset of single cell phosphoproteomic patterns of multiple breast cancer (BC) and normal breast tissue-derived cell lines. Following a separation of luminal, basal, and normal cell states, we determined signalling nodes and causal connections of core controlling network, and main drivers of oncogenic transformation and transitions between different BC subtypes. Whereas cell lines within the same BC subtype have different mutational and expression profiles, the architecture of core network was similar for all luminal BC cells, and mTOR was a main oncogenic driver. In contrast, core networks of basal BC were heterogeneous and segregated into two major subclasses that featured distinct main oncogenic and phenotype drivers. Likewise, normal breast tissue cells separated into two different subclasses. Based on the data and quantified network topologies we derived mechanistic cSTAR models that serve as digital cell twins and allow to deliberately control cells’ movements in a Waddington landscape of different cell states. These cSTAR models suggested strategies of normalizing phosphorylation networks of BC cell lines using small molecule inhibitors.