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Spherical Manifolds Capture Drug-Induced Changes in Tumor Cell Cycle Behavior
Olivia Wen1, Samuel C Wolff2, Wayne Stallaert3
1Department of Biology, University of North Carolina at Chapel Hill, NC, United States.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|December 13, 2024
Summary
CDK4/6 inhibitors show promise in ER+/HER2- breast cancer, but resistance is common. New computational methods reveal cell cycle shifts and potential resistance mechanisms, aiding precision medicine development.
Area of Science:
- Oncology
- Computational Biology
- Cell Biology
Background:
- CDK4/6 inhibitors like palbociclib are effective against ER+/HER2- breast cancer.
- Tumor cell heterogeneity contributes to primary and acquired resistance to these therapies.
- Understanding resistance mechanisms is crucial for developing more effective treatments.
Purpose of the Study:
- To investigate cell cycle protein profiles in ER+ breast cancer cells under palbociclib treatment.
- To identify mechanisms of resistance to CDK4/6 inhibitors using advanced computational analysis.
- To explore the utility of spherical principal component analysis (SPCA) for interpreting high-dimensional biological data.
Main Methods:
- Multiplex single-cell imaging was employed to profile cell cycle proteins.
- Increasing concentrations of palbociclib were used to induce varying levels of drug response.
- Spherical principal component analysis (SPCA) was applied to analyze high-dimensional cell cycle data.
Main Results:
- SPCA visualized shifts in cell cycle states and population heterogeneity.
- The analysis confirmed expected reductions in proliferation markers (Ki67, pRB).
- Potential resistance mechanisms, including increased cyclin D1 and CDK2 expression, were identified.
Conclusions:
- SPCA is a valuable tool for analyzing cell cycle dynamics and identifying resistance mechanisms in cancer.
- Understanding these resistance pathways can inform the development of novel therapeutic strategies.
- SPCA holds potential as a precision medicine tool for tailoring cancer treatments.
