Generating “Signalome” cell lines: A novel approach to studying signaling pathways in cancer

Introduction: Signaling pathways control many hallmarks of cancer, including cell growth, survival, and genome maintenance. Adaptive pathway rewiring has an important role in upfront resistance to anti-cancer therapies. Interestingly, all known cancer driver genes are classified into a dozen or so core signaling pathways. Tumor cells heterogeneity adds another layer to the complexity for overcoming drug resistance. For instance, different cancer cells in the same tumor can adopt a different “state” by switching to different survival signaling pathways in response to drugs. Elucidating these adaptive processes across multiple signaling pathways, in a single cell level, is thus paramount to achieve substantial improvements in therapeutic outcomes. A major challenge is the lack of suitable tools to study the dynamics of multiple signaling pathways at the single cell level, and in a high throughput capacity. Current methods profile pathway activity either at the population level (western blots, qPCR), or view cells at the single cell level but rely on low-throughput methods (GFP based reporters, IHC).

Materials and Methods: The “Signalome” cell lines are a tool we developed to allow a high-throughput single cell level live cell imaging of multiple signaling pathways. From each parental original cancer cell lines (A375, SK-Mel-5 and PC9), we generated 12 sub-cell lines, each expressing a combination of one of 12 fluorescent reporters with one of 12 fluorescent barcodes - allowing multiplexing of 12 different reporters. The cells are plated in 384-well plates, enabling the scan of large libraries of drugs, treatments or other conditions of interest.

Results and discussion: Extensive validation studies demonstrated the high accuracy of the barcoding system and the reporters used for the signalome system. By treating the “Signalome” cell lines with 250 drugs with diverse and known mechanisms of action we could detect upregulation of multiple compensatory pathways from hours and up to several days post treatment. Targeting these compensatory pathways might lead to synergistic activity. Integration of the data allowed the construction of new functionally relevant networks that can lead to the identification of Achilles hills - crucial for cells survival.

Conclusion: Our novel system enables a high-throughput, dynamic, single cells level approach for detecting key signaling pathways activity. Using this system, we gain deeper understanding of the complex processes of cancer resistance to improve patient care and response to treatment.