Tracing back primed resistance in cancer via sister cells

Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. We developed ReSisTrace that uses shared transcriptomic features of synchronized sister cells to predict the states that prime treatment resistance. We applied ReSisTrace in ovarian cancer cells to dissect primed resistance against olaparib, carboplatin or natural killer (NK) cells, and discovered a novel connection between DNA repair deficiency and susceptibility to NK cells. Furthermore, we identified small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification for personalized treatments and discovery of synergistic pre-sensitizing therapies. Overall design: We developed ReSisTrace to reveal the cell states that are primed to treatment resistance. We allowed uniquely labeled, synchronized cells to divide once, after which half of the cells (pre-treatment samples) were analyzed by scRNA-seq, while the other half underwent the treatment. Surviving cells were allowed to recover, and then analyzed by scRNA-seq to identify resistant lineages and their expression profiles (post-treatment samples). We applied ReSisTrace in HGSOC cell line Kuramochi to address primed resistance against carboplatin chemotherapy, the PARP inhibitor olaparib, and anti-tumor immunity represented by natural killer (NK) cells. We also included a non-treatment control that mimicked the splitting, re-plating, and growth conditions of the drug treatment experiments. All the assays are performed in two replicates.