Variability within rare cell states enables multiple paths toward drug resistance

Area of Science:

• Cell Biology
• Cancer Research
• Genomics

Background:

• Cellular heterogeneity influences cancer cell fate upon drug exposure.
• Identifying molecular drivers of rare cell survival is challenging.
• Understanding precursor cell differences is key to predicting drug resistance.

Purpose of the Study:

• To develop a method for capturing and analyzing rare drug-resistant cancer cells.
• To trace drug-resistant cell fates back to specific molecular features in precursor cells.
• To uncover the hidden cellular variability that underlies differential responses to cancer therapy.

Main Methods:

• Developed Rewind, a methodology combining genetic barcoding and RNA fluorescence in situ hybridization.
• Applied Rewind to BRAF V600E melanoma models.
• Analyzed single-cell gene expression and MAP kinase signaling in drug-naive and drug-treated cells.

Main Results:

• Successfully traced drug-resistant cell fates to rare precursor cells (~1:1,000-1:10,000).
• Identified relative persistence of MAP kinase signaling as a key factor in early drug resistance.
• Uncovered a substructure within rare cell populations, where molecular differences predict distinct phenotypic behaviors (e.g., proliferation).

Conclusions:

• Revealed significant, previously hidden, rare-cell variability in cancer.
• Demonstrated that precursor cell molecular states predict latent phenotypic outcomes upon drug exposure.
• Highlighted the importance of studying rare cell populations for understanding and overcoming drug resistance in melanoma.