NIH Reporter #5R35CA197745-12

Predicting Cancer Cell Response to Endogenous and Exogenous Perturbations at the Single Cell Level

This award funds research to develop predictive models of cancer cell responses to genetic and molecular perturbations at the single-cell level, using advanced CRISPRi and RNA sequencing technologies to understand cancer cell plasticity and resistance mechanisms.

Description

The study aims to understand the dysregulated signaling and regulatory logic of cancer cells caused by mutations, which leads to a highly plastic and dynamic landscape. The project proposes leveraging advanced technology to silence thousands of genes in millions of cells, followed by RNA sequencing, to develop genome- and proteome-wide network models. These models will predict the probabilistic, time-dependent responses of mammalian cells to small molecules and genetic perturbations, and their ability to reprogram across various molecular states. The research will generate large-scale single-cell profiles using CRISPRi-mediated silencing, enabling causal network learning and dynamic modeling of cell regulation in normal and cancerous states, as well as interactions within the tumor microenvironment.

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