Targeted therapies have made a big splash in the cancer therapeutics field. However, many cancers fail to respond to these treatments, or patients experience the return of their regressed tumors. These problems arise because certain cells within a tumor undergo cell-state changes that promote drug tolerance. To study this process, researchers employ sophisticated multi-omic technologies to identify cells responsible for drug tolerance and to develop strategies for personalized medicine.
Metabolic pathways within cancer cells can change in ways that enhance energy production and cell growth.1 These cell-state changes can be genetic or non-genetic2 and lead to differences in gene expression, protein signaling, and metabolism in certain cells within a population. Cell-state alterations affect the response to cancer therapies, as cells that were once responsive to pharmacological agents adopt drug-resistant states during the course of treatment.
Previous methods for studying drug tolerance relied on bulk analyses of heterogeneous cell samples; however, cell state changes do not occur uniformly within a population. Because uncommon biomarkers are diluted by more prevalent molecules, these experiments insufficiently detected the cellular causes of drug tolerance.
To better identify functional adaptations leading to drug tolerance, researchers now analyze tumor cells at the single-cell level using multi-omic approaches. Single cell multiplexed experiments that identify phosphoproteins and metabolites pin-point cells that have adopted a drug-tolerant state. By tracking cells’ drug response through phenotypic markers and markers of oncogenic signaling, cell proliferation, and metabolic activity, researchers identify small cell subsets that rapidly change their energy state and develop drug tolerance and increased proliferation. By performing metabolomic and functional proteomic analyses, researchers have found that cells within the same population may take independent paths toward cancer drug tolerance.3 It is challenging to develop therapies that target heterogenous cell populations, but understanding how these changes evolve over time will enable researchers to predict which trajectories cells will take to tolerance, which will guide the development of personalized treatments targeting multiple pathways.
Researchers can identify cell states using IsoPlexis’ multi-omic energy state technology with the Single Cell Metabolome solution panel, which simultaneously captures phosphoproteins and metabolites from single cells. Within a chip, the technology captures, images, lyses, and proteomically barcodes single cells in microchambers and measures numerous proteomic and metabolomic biomarkers through an ELISA assay within IsoPlexis’ benchtop functional proteomics system. Using the multiplexed tumor metabolome panel, researchers can capture resistance and activation pathways as cancer drug tolerance develops, identify cell subsets that predict patient outcomes, and develop combination therapies that resolve resistance.
- Q. Wei et al., “Metabolic rewiring in the promotion of cancer metastasis: mechanisms and therapeutic implications,” Oncogene, 39:6139-56, 2020.
- M. Ramirez et al., “Diverse drug-resistance mechanisms can emerge from drug-tolerant cancer persister cells,” Nat Commun, 7:10690, 2016.
- Y. Su et al., “Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line,” Nat Commun, 11:2345, 2020.