It is crucial to unravel molecular determinants of responses to immune checkpoint blockade (ICB) therapy, because only a small subset of advanced non-small cell lung cancer (NSCLC) patients responds to ICB therapy. Previous studies were concentrated on genomic and transcriptomic markers (e.g. mutation burden and immune gene expression). However, these markers are not sufficient to accurately predict a response to ICB therapy. Here, we analysed DNA methylomes of 141 advanced NSCLC samples subjected to ICB therapy (i.e., Anti-programmed death-1) from two independent cohorts (60 and 81 patients from our and IDIBELL cohorts). Integrative analysis of patients with matched transcriptome data in our cohort (n=28) at pathway level revealed significant overlaps between promoter hypermethylation and transcriptional repression in nonrespondersrelative to responders. Fifteen immune-related pathways, including interferon signaling, were identified to be enriched for both hypermethylation and repression. Global methylation loss correlated with immune evasion signatures independently of mutation burden and aneuploidy. Higher predictive power was observed for methylation loss than mutation burden. Hence, DNA methylation alterations implicate epigenetic modulation in precision immunotherapy. Next, we built a reliable prognostic risk model based on eight genes using LASSO model and successfully validated the model in an independent cohort. Furthermore, we found 30 survival-associated molecular interaction networks, in which two or three hypermethylated genes showed significant mutual exclusion across nonresponders. Our study demonstrates that methylation patterns can provide insight into molecular determinants underlying the clinical benefit of ICB therapy.
폐암 환자들의 면역항암치료의 예후 예측을 하기 위해 분자적 특성을 이해하는 것이 중요하다. 과거에 마커로 제시되었던 유전적 그리고 전사적 요인들은 정확한 예측이 불가하기 때문에 새로운 마커의 필요성이 대두되고 있다. 이 연구에서는 면역항암치료의 예후 예측을 위해 메틸화를 제시하고, 치료에 반응이 있는 환자와 그렇지 않은 환자간의 차이를 분석하였다. 면역항암치료를 받은 두 폐암 코호트 141 명의 환자들(각 60 명, 81 명)의 특성을 살펴보니 프로모터 메틸화와 전사의 억제가 면역 관련된 것을 확인했다. 다음으로, 치료 예후 예측을 위한 LASSO 선형 회귀 모델을 수립하고 별도의 코호트들에서 성능을 확인했다. 마지막으로, 상호 배타적인 유전자 쌍들을 찾아 생존에 영향을 끼침을 보여줌으로써 메틸화가 생존에 끼치는 영향에 대해 보고했다. 이 연구는 메틸화의 패턴이 면역항암치료의 예후 예측 및 설명을 할 수 있음을 보여준다.
