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

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 957

Special Issue Editors


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Guest Editor
Department of Medical, Surgical and Health Sciences, University of Trieste, 34149 Trieste, Italy
Interests: targeted therapies; signal transduction; breast cancer

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Guest Editor
1. Systems Biology Ireland, School of Medicine, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland
2. Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland
3. Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06520, USA
Interests: systems biology; targeted therapies; resistance; structure-based modeling; cell state transitions

Special Issue Information

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

Manuscript Submission Information

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Keywords

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

Published Papers (1 paper)

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Research

16 pages, 6044 KiB  
Article
Reducing State Conflicts between Network Motifs Synergistically Enhances Cancer Drug Effects and Overcomes Adaptive Resistance
by Yunseong Kim, Sea Rom Choi and Kwang-Hyun Cho
Cancers 2024, 16(7), 1337; https://doi.org/10.3390/cancers16071337 - 29 Mar 2024
Viewed by 520
Abstract
Inducing apoptosis in cancer cells is a primary goal in anti-cancer therapy, but curing cancer with a single drug is unattainable due to drug resistance. The complex molecular network in cancer cells causes heterogeneous responses to single-target drugs, thereby inducing an adaptive drug [...] Read more.
Inducing apoptosis in cancer cells is a primary goal in anti-cancer therapy, but curing cancer with a single drug is unattainable due to drug resistance. The complex molecular network in cancer cells causes heterogeneous responses to single-target drugs, thereby inducing an adaptive drug response. Here, we showed that targeted drug perturbations can trigger state conflicts between multi-stable motifs within a molecular regulatory network, resulting in heterogeneous drug responses. However, we revealed that properly regulating an interconnecting molecule between these motifs can synergistically minimize the heterogeneous responses and overcome drug resistance. We extracted the essential cellular response dynamics of the Boolean network driven by the target node perturbation and developed an algorithm to identify a synergistic combinatorial target that can reduce heterogeneous drug responses. We validated the proposed approach using exemplary network models and a gastric cancer model from a previous study by showing that the targets identified with our algorithm can better drive the networks to desired states than those with other control theories. Of note, our approach suggests a new synergistic pair of control targets that can increase cancer drug efficacy to overcome adaptive drug resistance. Full article
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