Related Experiment Video
Updated: Oct 20, 2025
An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues
Published on: April 5, 2018
Identifying transcriptional programs underlying cancer drug response with TraCe-seq
Matthew T Chang1,2, Frances Shanahan2, Thi Thu Thao Nguyen1
1Department of Computational Biology and Bioinformatics, Genentech Inc., South San Francisco, CA, USA.
Abstract:
Genetic and non-genetic heterogeneity within cancer cell populations represent major challenges to anticancer therapies. We currently lack robust methods to determine how preexisting and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA sequencing (scRNA-seq), we have developed tracking differential clonal response by scRNA-seq (TraCe-seq). TraCe-seq is a method that captures at clonal resolution the origin, fate and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual epidermal growth factor receptor (EGFR) inhibitor-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. We identified a loss of antigrowth activity associated with targeted degradation of EGFR protein and an essential role of the endoplasmic reticulum (ER) protein processing pathway in anti-EGFR therapeutic efficacy. Our results suggest that targeted degradation is not always superior to enzymatic inhibition and establish TraCe-seq as an approach to study how preexisting transcriptional programs affect treatment responses.
Insights
A new method, TraCe-seq, tracks cancer cell responses to therapy at clonal resolution. Targeted EGFR degradation showed reduced anti-growth activity compared to kinase inhibitors in lung cancer.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- Cancer cell heterogeneity poses challenges for effective anticancer therapies.
- Current methods lack the robustness to assess how pre-existing and adaptive traits influence cellular drug responses.
Purpose of the Study:
- To develop a method for tracking differential clonal responses to cancer therapies at high resolution.
- To compare the efficacy of next-generation EGFR inhibitor-degraders versus standard EGFR kinase inhibitors in EGFR-mutant lung cancer.
Main Methods:
- Developed TraCe-seq (tracking differential clonal response by scRNA-seq), combining clonal fitness mapping and single-cell RNA sequencing (scRNA-seq) with expressed barcodes.
- Utilized TraCe-seq to analyze cellular origins, fates, and early adaptive transcriptional programs under distinct treatments.
- Benchmarked dual EGFR inhibitor-degraders against standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells.
Main Results:
- Identified a loss of anti-growth activity with targeted epidermal growth factor receptor (EGFR) protein degradation.
- Revealed an essential role for the endoplasmic reticulum (ER) protein processing pathway in anti-EGFR therapeutic efficacy.
- Demonstrated that targeted degradation is not consistently superior to enzymatic inhibition.
Conclusions:
- TraCe-seq provides a powerful approach to study how pre-existing transcriptional programs influence treatment responses in cancer.
- Findings suggest a nuanced view on the efficacy of targeted protein degradation versus kinase inhibition for EGFR-mutant lung cancer.
- Highlights the importance of the ER protein processing pathway in mediating anti-EGFR therapy outcomes.
