CRISPR metabolic screen identifies ATM and KEAP1 as targetable genetic vulnerabilities in solid tumors.
Haojian LiYue LiuYunjie XiaoCrystal N WilsonHui Jen BaiMaxwell D JonesShihchun WangJennie E DeVoreEsther Y MaierStephen T DurantMyriem BoufraqechUrbain WeyemiPublished in: Proceedings of the National Academy of Sciences of the United States of America (2023)
Cancer treatments targeting DNA repair deficiencies often encounter drug resistance, possibly due to alternative metabolic pathways that counteract the most damaging effects. To identify such alternative pathways, we screened for metabolic pathways exhibiting synthetic lethality with inhibition of the DNA damage response kinase Ataxia-telangiectasia-mutated (ATM) using a metabolism-centered Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 library. Our data revealed Kelch-like ECH-associated protein 1 (KEAP1) as a key factor involved in desensitizing cancer cells to ATM inhibition both in vitro and in vivo. Cells depleted of KEAP1 exhibited an aberrant overexpression of the cystine transporter SLC7A11, robustly accumulated cystine inducing disulfide stress, and became hypersensitive to ATM inhibition. These hallmarks were reversed in a reducing cellular environment indicating that disulfide stress was a crucial factor. In The Cancer Genome Atlas (TCGA) pan-cancer datasets, we found that ATM levels negatively correlated with KEAP1 levels across multiple solid malignancies. Together, our results unveil ATM and KEAP1 as new targetable vulnerabilities in solid tumors.
Keyphrases
- dna damage response
- dna repair
- dna damage
- papillary thyroid
- crispr cas
- genome wide
- squamous cell
- genome editing
- protein protein
- single cell
- induced apoptosis
- gene expression
- high throughput
- squamous cell carcinoma
- lymph node metastasis
- stress induced
- early onset
- electronic health record
- cancer therapy
- machine learning
- oxidative stress
- rna seq
- childhood cancer
- cell cycle arrest
- copy number
- data analysis
- endoplasmic reticulum stress
- artificial intelligence