Prediction of immunotherapy response using mutations to cancer protein assemblies.
JungHo KongXiaoyu ZhaoAkshat SinghalSungjoon ParkRobin BachelderJeanne ShenHaiyu ZhangJimin MoonChang Ho AhnChan-Young OckHannah CarterTrey IdekerPublished in: Science advances (2024)
While immune checkpoint inhibitors have revolutionized cancer therapy, many patients exhibit poor outcomes. Here, we show immunotherapy responses in bladder and non-small cell lung cancers are effectively predicted by factoring tumor mutation burden (TMB) into burdens on specific protein assemblies. This approach identifies 13 protein assemblies for which the assembly-level mutation burden (AMB) predicts treatment outcomes, which can be combined to powerfully separate responders from nonresponders in multiple cohorts (e.g., 76% versus 37% bladder cancer 1-year survival). These results are corroborated by (i) engineered disruptions in the predictive assemblies, which modulate immunotherapy response in mice, and (ii) histochemistry showing that predicted responders have elevated inflammation. The 13 assemblies have diverse roles in DNA damage checkpoints, oxidative stress, or Janus kinase/signal transducers and activators of transcription signaling and include unexpected genes (e.g., PIK3CG and FOXP1) for which mutation affects treatment response. This study provides a roadmap for using tumor cell biology to factor mutational effects on immune response.
Keyphrases
- oxidative stress
- dna damage
- immune response
- cancer therapy
- single cell
- protein protein
- cell therapy
- genome wide
- end stage renal disease
- ejection fraction
- newly diagnosed
- regulatory t cells
- spinal cord injury
- squamous cell carcinoma
- drug delivery
- dendritic cells
- prognostic factors
- metabolic syndrome
- ischemia reperfusion injury
- dna repair
- squamous cell
- stem cells
- papillary thyroid
- diabetic rats
- small molecule
- young adults
- mesenchymal stem cells
- tyrosine kinase
- bone marrow
- heat shock protein