Targeting IDH1/2 mutant cancers with combinations of ATR and PARP inhibitors.
Amrita SuleJinny Van DoornRanjini K SundaramSachita GanesaJuan C VasquezRanjit S BindraPublished in: NAR cancer (2021)
Mutations in the isocitrate dehydrogenase-1 and -2 (IDH1/2) genes were first identified in glioma and acute myeloid leukemia (AML), and subsequently found in multiple other tumor types. These neomorphic mutations convert the normal product of enzyme, α-ketoglutarate (αKG), to the oncometabolite 2-hydroxyglutarate (2HG). Our group recently demonstrated that 2HG suppresses the high-fidelity homologous recombination (HR) DNA repair pathway, resulting in a state referred to as 'BRCAness', which confers exquisite sensitivity to poly(ADP-ribose) polymerase (PARP) inhibitors. In this study, we sought to elucidate sensitivity of IDH1/2-mutant cells to DNA damage response (DDR) inhibitors and, whether combination therapies could enhance described synthetic lethal interactions. Here, we report that ATR (ataxia telangiectasia and Rad3-related protein kinase) inhibitors are active against IDH1/2-mutant cells, and that this activity is further potentiated in combination with PARP inhibitors. We demonstrate this interaction across multiple cell line models with engineered and endogenous IDH1/2 mutations, with robust anti-tumor activity in vitro and in vivo. Mechanistically, we found ATR and PARP inhibitor treatment induces premature mitotic entry, which is significantly elevated in the setting of IDH1/2-mutations. These data highlight the potential efficacy of targeting HR defects in IDH1/2-mutant cancers and support the development of this combination in future clinical trials.
Keyphrases
- dna repair
- dna damage response
- wild type
- dna damage
- low grade
- acute myeloid leukemia
- induced apoptosis
- clinical trial
- oxidative stress
- cancer therapy
- signaling pathway
- allogeneic hematopoietic stem cell transplantation
- risk assessment
- machine learning
- early onset
- gene expression
- endoplasmic reticulum stress
- open label
- big data
- randomized controlled trial
- acute lymphoblastic leukemia
- cell cycle
- transcription factor
- combination therapy