Resources: Publications
Leveraging a novel, multi-modal platform to identify drug resistant clones with distinct mechanisms of resistance to EGFR inhibitors
November 25, 2025
Journal for Immunotherapy of Cancer (JITC)
Authors
Yunmin Li, Shan Sabri, Teresa Ai, Pier Federico Gherardini, Annarita Scaramozza, Gary Schroth, Mostafa Ronaghi, Tarun Khurana
Scientific Summary
This conference abstract presents preliminary research that was later expanded in related publications.
Drug resistance remains one of the greatest challenges in cancer research, as individual cells within the same tumor can respond differently to therapeutic treatment. While single-cell transcriptomics has advanced our understanding of tumor heterogeneity, many important aspects of drug response—including changes in cell behavior over time—cannot be fully captured from a single molecular measurement alone.
In this conference presentation, researchers applied Cellanome’s R3200 platform to study how individual lung cancer cells responded to EGFR inhibitor treatment through paired longitudinal live-cell imaging and transcriptomic analysis. By tracking thousands of individual cells over several days before measuring gene expression from the same cells, the study identified multiple distinct behavioral responses among drug-resistant cell populations.
These imaging-derived phenotypes were linked with transcriptomic measurements, revealing both shared molecular programs associated with drug resistance and distinct functional behaviors across resistant clones. The findings demonstrate how combining longitudinal phenotypic measurements with transcriptomic analysis can help distinguish heterogeneous cellular responses that may not be apparent from endpoint molecular measurements alone.
As an early conference presentation, this work highlights the value of integrating cellular behavior with molecular state to investigate mechanisms of therapeutic response and resistance, providing a foundation for subsequent studies exploring longitudinal multimodal single-cell analysis.
Key Highlights
- Demonstrated paired longitudinal live-cell imaging and transcriptomic analysis of individual lung cancer cells following EGFR inhibitor treatment.
- Identified multiple distinct behavioral phenotypes among drug-resistant cell populations, including proliferative, arrested, and apoptotic response patterns.
- Connected longitudinal imaging observations with transcriptomic measurements from the same cells to investigate molecular programs associated with drug resistance.
- Revealed that cells sharing common drug-resistance pathways could exhibit different functional behaviors over time.
- Illustrated how longitudinal phenotypic measurements can provide biological context beyond endpoint molecular measurements when studying therapeutic response.
- Presented an early application of Cellanome’s multimodal workflow for investigating mechanisms of treatment resistance and identifying potential biomarkers of therapeutic response.
Explore Related Topics
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Technology
CellCage™ Technology
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Publications
Scalable Longitudinal Imaging and Transcriptomics of Cells in Dynamic Enclosures
Explore the full technology preprint expanding on the multimodal workflow introduced in this conference abstract.
Scientific Perspectives
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If You Care About Function, Make Function the Response Variable
A perspective on why directly measuring cellular behavior can change the biological questions researchers ask.
Scientific Posters & Presentations
Explore additional conference presentations highlighting applications of paired longitudinal imaging and transcriptomics across cancer biology, immunology, and drug discovery.