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High-content microscopy reveals a morphological signature of bortezomib resistance
Megan E Kelley1, Adi Y Berman1, David R Stirling2
1Laboratory of Chemistry and Cell Biology, The Rockefeller University, New York City, United States.
Abstract:
Drug resistance is a challenge in anticancer therapy. In many cases, cancers can be resistant to the drug prior to exposure, that is, possess intrinsic drug resistance. However, we lack target-independent methods to anticipate resistance in cancer cell lines or characterize intrinsic drug resistance without a priori knowledge of its cause. We hypothesized that cell morphology could provide an unbiased readout of drug resistance. To test this hypothesis, we used HCT116 cells, a mismatch repair-deficient cancer cell line, to isolate clones that were resistant or sensitive to bortezomib, a well-characterized proteasome inhibitor and anticancer drug to which many cancer cells possess intrinsic resistance. We then expanded these clones and measured high-dimensional single-cell morphology profiles using Cell Painting, a high-content microscopy assay. Our imaging- and computation-based profiling pipeline identified morphological features that differed between resistant and sensitive cells. We used these features to generate a morphological signature of bortezomib resistance. We then employed this morphological signature to analyze a set of HCT116 clones (five resistant and five sensitive) that had not been included in the signature training dataset, and correctly predicted sensitivity to bortezomib in seven cases, in the absence of drug treatment. This signature predicted bortezomib resistance better than resistance to other drugs targeting the ubiquitin-proteasome system, indicating specificity for mechanisms of resistance to bortezomib. Our results establish a proof-of-concept framework for the unbiased analysis of drug resistance using high-content microscopy of cancer cells, in the absence of drug treatment.
Insights
Cell morphology can predict anticancer drug resistance. Researchers developed a method using Cell Painting to identify morphological signatures, successfully predicting bortezomib resistance in cancer cells without drug exposure.
Area of Science:
- Oncology
- Cell Biology
- Drug Discovery
Background:
- Drug resistance, particularly intrinsic resistance, poses a significant challenge in anticancer therapy.
- Current methods for predicting drug resistance often require prior knowledge of resistance mechanisms or drug exposure.
- There is a need for target-independent approaches to characterize and anticipate cancer cell line drug resistance.
Purpose of the Study:
- To investigate if cell morphology can serve as an unbiased indicator of intrinsic drug resistance in cancer cells.
- To develop and validate a morphological signature for predicting resistance to bortezomib, a proteasome inhibitor.
- To establish a proof-of-concept for using high-content microscopy to analyze drug resistance without drug treatment.
Main Methods:
- Isolation of bortezomib-resistant and -sensitive HCT116 cancer cell clones.
- High-dimensional single-cell morphology profiling using the Cell Painting assay.
- Development of an imaging- and computation-based pipeline to identify morphological features associated with resistance.
- Generation and validation of a morphological signature for bortezomib resistance.
Main Results:
- Distinct morphological features were identified between bortezomib-resistant and -sensitive HCT116 cells.
- A morphological signature was generated and successfully predicted bortezomib sensitivity in a validation set of clones with 70% accuracy, without drug treatment.
- The developed signature demonstrated specificity for bortezomib resistance compared to resistance against other drugs targeting the ubiquitin-proteasome system.
Conclusions:
- Cell morphology provides an unbiased readout for predicting intrinsic drug resistance in cancer.
- High-content microscopy and morphological profiling offer a novel framework for analyzing drug resistance.
- This approach enables the characterization of drug resistance mechanisms independent of drug exposure or prior knowledge.
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