A systematic analysis of signaling reactivation and drug resistance

Kholodenko, Boris N.; Rauch, Nora; Kölch, Walter; Rukhlenko, Oleksii S.

doi:10.1016/j.celrep.2021.109157

Cited by 24 publications

(29 citation statements)

References 119 publications

(201 reference statements)

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“…A combination of types I½ and II RAF inhibitors reduces the dose ranges of paradoxical activation, yielding synergy over a wider dose range than a combination of RAF and MEK inhibitors in RAS-mutant cells. Experiments conducted on RAS-mutant melanoma and acute myeloid leukemia cell lines support these model predictions [ 169 ].…”

Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 82%

“…The model faithfully predicted RAF inhibitor responses in BRAF-mutant, RAS wild-type cells, as well as in RAS-mutant cell lines, confirming the effectiveness of a combination of two structurally different RAF inhibitors, such as vemurafenib plus sorafenib, in inhibiting ERK signaling, cell proliferation and colony formation, even in RAS-mutant cell lines. This paradoxical pathway activation can be facilitated by negative feedback loops, when the alleviation of the feedback induced by a kinase inhibitor leads to further increase in kinase dimerization [ 169 ]. The model allows to estimate the levels of synergy or antagonism between RAF inhibitors and MEK inhibitors, based on the type of RAF inhibitor and the level of RAS activity.…”

Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 99%

“…Negative feedbacks have been held responsible for the development of acquired resistance to many targeted drugs [ 170 , 171 , 172 , 173 , 174 , 175 ]. This hypothesis was addressed by a systematic analysis of network adaptation mechanisms as a cause of drug resistance [ 169 ]. The unbiased analysis and mechanistic modeling demonstrated that feedback loops, by themselves, could not completely reactivate steady state signaling.…”

Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 99%

“…Following drug inhibition, negative feedbacks, mediated by either post-translational modifications or de novo synthesized negative regulators, can lead to a transient reactivation or overshoot, but cannot fully restore output signaling ( Figure 4 A,B). Only partial reactivation, proportional to the strength of the feedback, can be brought about by a negative feedback loop, but a complete signaling reactivation can never occur [ 169 ].…”

Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 99%

“…System analyses of network adaptations highlight three ways in which treatment with a targeted inhibitor can be followed by a complete recovery, or even overshoot, of pathway signaling within a range of inhibitor doses [ 169 ]. First, when there are at least two connection routes, activating and inhibitory, from an inhibited upstream drug target to the downstream output, creating a feedforward loop in addition to the other connection route.…”

Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 99%

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Can Systems Biology Advance Clinical Precision Oncology?

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2021

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Precision oncology is perceived as a way forward to treat individual cancer patients. However, knowing particular cancer mutations is not enough for optimal therapeutic treatment, because cancer genotype-phenotype relationships are nonlinear and dynamic. Systems biology studies the biological processes at the systems’ level, using an array of techniques, ranging from statistical methods to network reconstruction and analysis, to mathematical modeling. Its goal is to reconstruct the complex and often counterintuitive dynamic behavior of biological systems and quantitatively predict their responses to environmental perturbations. In this paper, we review the impact of systems biology on precision oncology. We show examples of how the analysis of signal transduction networks allows to dissect resistance to targeted therapies and inform the choice of combinations of targeted drugs based on tumor molecular alterations. Patient-specific biomarkers based on dynamical models of signaling networks can have a greater prognostic value than conventional biomarkers. These examples support systems biology models as valuable tools to advance clinical and translational oncological research.

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Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 82%

Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 99%

Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 99%

Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 99%

Section: Mechanistic Models Help Us Understand Resistance To Targeted Therapiesmentioning

confidence: 99%

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Can Systems Biology Advance Clinical Precision Oncology?

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Targeting KRAS mutant lung cancer: light at the end of the tunnel

Drosten

Barbacid

2022

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For decades, KRAS mutant lung adenocarcinomas (LUAD) have been refractory to therapeutic strategies based on personalized medicine owing to the complexity of designing inhibitors to selectively target KRAS and downstream targets with acceptable toxicities. The recent development of selective KRAS G12C inhibitors represents a landmark after 40 years of intense research efforts since the identification of KRAS as a human oncogene. Here, we discuss the mechanisms responsible for the rapid development of resistance to these inhibitors, as well as potential strategies to overcome this limitation. Other therapeutic strategies aimed at inhibiting KRAS oncogenic signaling by targeting either upstream activators or downstream effectors are also reviewed. Finally, we discuss the effect of targeting the mitogen-activated protein kinase (MAPK) pathway, both based on the failure of MEK and ERK inhibitors in clinical trials, as well as on the recent identification of RAF1 as a potential target due to its MAPK-independent activity. These new developments, taken together, are likely to open new avenues to effectively treat KRAS mutant LUAD.

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Dose–response analysis after administration of a human platelet‐derived exosome product on neurite outgrowth in vitro

Saffari

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Pulos

et al. 2023

Biotech & Bioengineering

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Modulating the nerve's local microenvironment using exosomes is proposed to enhance nerve regeneration. This study aimed to determine the optimal dose of purified exosome product (PEP) required to exert maximal neurite extension. An in vitro dorsal root ganglion (DRG) neurite outgrowth assay was used to evaluate the effect of treatment with (i) 5% PEP, (ii) 10% PEP, (iii) 15% PEP, or (iv) 20% PEP on neurite extension (N = 9/group), compared to untreated controls. After 72 h, neurite extension was measured to quantify nerve regeneration. Live cell imaging was used to visualize neurite outgrowth during incubation. Treatment with 5% PEP resulted in the longest neurite extension and was superior to the untreated DRG (p = 0.003). Treatment with 10% PEP, 15% PEP, and 20% PEP was found to be comparable to controls (p = 0.12, p = 0.06, and p = 0.41, respectively) and each other. Live cell imaging suggested that PEP migrated towards the DRG neural regeneration site, compared to the persistent homogenous distribution of PEP in culture media alone. 5% PEP was found to be the optimal concentration for nerve regeneration based on this in vitro dose–response analysis.

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A systematic analysis of signaling reactivation and drug resistance

Cited by 24 publications

References 119 publications

Can Systems Biology Advance Clinical Precision Oncology?

Can Systems Biology Advance Clinical Precision Oncology?

Targeting KRAS mutant lung cancer: light at the end of the tunnel

Dose–response analysis after administration of a human platelet‐derived exosome product on neurite outgrowth in vitro

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