Defining the genetic landscape of cancer drug resistance mechanisms

Good news! Cancer is history (soon)!

"... The team used CRISPR gene editing and other genomic techniques to create a map of drug resistance mutations in colon, lung, and Ewing sarcoma cancers, which are prone to developing drug resistance and have limited available second line treatments. ...

“Our study details how mutations fall into four different groups, which might need different treatment plans,” ...

These categories include:

• Canonical drug resistance mutations, which lead to the drug being less effective.
• Drug addiction mutations, in which cancer cells use the drug to help them grow, instead of destroying them.
• Driver mutations, which allow cancer cells to use a different pathway to grow, avoiding the pathway the drug may have blocked.
• And drug sensitising variants, which make the cancer more sensitive to certain treatments and may indicate a patient would benefit from particular drugs.

..."

From the abstract:

"Drug resistance is a principal limitation to the long-term efficacy of cancer therapies. Cancer genome sequencing can retrospectively delineate the genetic basis of drug resistance, but this requires large numbers of post-treatment samples to nominate causal variants. Here we prospectively identify genetic mechanisms of resistance to ten oncology drugs from CRISPR base editing mutagenesis screens in four cancer cell lines using a guide RNA library predicted to install 32,476 variants in 11 cancer genes. We identify four functional classes of protein variants modulating drug sensitivity and use single-cell transcriptomics to reveal how these variants operate through distinct mechanisms, including eliciting a drug-addicted cell state. We identify variants that can be targeted with alternative inhibitors to overcome resistance and functionally validate an epidermal growth factor receptor (EGFR) variant that sensitizes lung cancer cells to EGFR inhibitors. Our variant-to-function map has implications for patient stratification, therapy combinations and drug scheduling in cancer treatment."

New step towards personalised cancer therapies

Base editing screens define the genetic landscape of cancer drug resistance mechanisms (open access)

Fig. 1: Base editing screens map functional domains in oncogenes.

Fig. 2: Variants modulating drug sensitivity cluster into four functional classes.