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Updated: Mar 8, 2026
A 3D Organotypic Melanoma Spheroid Skin Model
Published on: May 18, 2018
Cell cycle-tailored targeting of metastatic melanoma: Challenges and opportunities
Nikolas K Haass1,2,3, Brian Gabrielli4
1The University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, Brisbane, Qld, Australia.
Abstract:
The advent of targeted therapies of metastatic melanoma, such as MAPK pathway inhibitors and immune checkpoint antagonists, has turned dermato-oncology from the "bad guy" to the "poster child" in oncology. Current targeted therapies are effective, although here is a clear need to develop combination therapies to delay the onset of resistance. Many antimelanoma drugs impact on the cell cycle but are also dependent on certain cell cycle phases resulting in cell cycle phase-specific drug insensitivity. Here, we raise the question: Have combination trials been abandoned prematurely as ineffective possibly only because drug scheduling was not optimized? Firstly, if both drugs of a combination hit targets in the same melanoma cell, cell cycle-mediated drug insensitivity should be taken into account when planning combination therapies, timing of dosing schedules and choice of drug therapies in solid tumors. Secondly, if the combination is designed to target different tumor cell subpopulations of a heterogeneous tumor, one drug effective in a particular subpopulation should not negatively impact on the other drug targeting another subpopulation. In addition to the role of cell cycle stage and progression on standard chemotherapeutics and targeted drugs, we discuss the utilization of cell cycle checkpoint control defects to enhance chemotherapeutic responses or as targets themselves. We propose that cell cycle-tailored targeting of metastatic melanoma could further improve therapy outcomes and that our real-time cell cycle imaging 3D melanoma spheroid model could be utilized as a tool to measure and design drug scheduling approaches.
Insights
Optimizing drug scheduling in metastatic melanoma combination therapies is crucial. Cell cycle phase-specific drug insensitivity can lead to premature trial abandonment; tailored approaches may improve outcomes.
Area of Science:
- Oncology
- Dermato-oncology
- Cancer Cell Biology
Background:
- Targeted therapies like MAPK pathway inhibitors and immune checkpoint antagonists have advanced metastatic melanoma treatment.
- Despite current successes, developing combination therapies is essential to overcome drug resistance.
- Many antimelanoma drugs exhibit cell cycle phase-specific efficacy and insensitivity, complicating treatment strategies.
Purpose of the Study:
- To investigate whether suboptimal drug scheduling in combination trials has led to premature conclusions of ineffectiveness.
- To highlight the importance of considering cell cycle-mediated drug insensitivity in designing combination therapies for melanoma.
- To explore the potential of cell cycle-tailored targeting and novel imaging models for optimizing melanoma treatment.
Main Methods:
- Reviewing the impact of cell cycle stage on drug sensitivity for targeted therapies and chemotherapeutics.
- Analyzing how drug combinations targeting different melanoma cell subpopulations might be affected by cell cycle dynamics.
- Proposing the use of real-time cell cycle imaging in 3D melanoma spheroid models for drug scheduling optimization.
Main Results:
- Cell cycle phase-specific drug insensitivity can significantly impact the efficacy of combination therapies.
- Suboptimal drug scheduling may lead to the underestimation of combination therapy effectiveness.
- Understanding cell cycle dynamics is critical for both single-agent and combination therapy design.
Conclusions:
- Premature abandonment of combination trials due to perceived ineffectiveness may stem from unoptimized drug scheduling.
- Cell cycle-tailored targeting strategies hold promise for improving therapeutic outcomes in metastatic melanoma.
- Real-time cell cycle imaging models offer a valuable tool for designing and evaluating optimized drug scheduling approaches.
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