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Combinatorial genetic strategy accelerates the discovery of cancer genotype-phenotype associations

Li, S.; Wong, A.; Sun, H.; Bhatia, V.; Javier, G.; Jana, S.; Mongomery, R. B.; Wright, J. L.; Lam, H.-M.; Hsieh, A. C.; Faltas, B. M.; Haffner, M. C.; Lee, J. K.

2023-04-14 cancer biology
10.1101/2023.04.12.536652 bioRxiv
Show abstract

Available genetically-defined cancer models are limited in genotypic and phenotypic complexity and underrepresent the heterogeneity of human cancer. Herein, we describe a combinatorial genetic strategy applied to an organoid transformation assay to rapidly generate diverse, clinically relevant bladder and prostate cancer models. Importantly, the clonal architecture of the resultant tumors can be resolved using single-cell or spatially resolved next-generation sequencing to uncover polygenic drivers of cancer phenotypes.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.