지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2022.4
- 수록면
- 424 - 433 (10page)
- DOI
- 10.4143/crt.2021.583
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초록· 키워드
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Purpose Since tumor mutational burden (TMB) and gene expression profiling (GEP) have complementary effects, they may have improved predictive power when used in combination. Here, we investigated the ability of TMB and GEP to predict the immunotherapy response in patients with non–small cell lung cancer (NSCLC) and assessed if this combination can improve predictive power compared to that when used individually.Materials and Methods This retrospective cohort study included 30 patients with NSCLC who received immune checkpoint inhibitors (ICI) therapy at the Seoul National University Bundang Hospital. programmed cell death-ligand-1 (PD-L1) protein expression was assessed using immunohistochemistry, and TMB was measured by targeted deep sequencing. Gene expression was determined using NanoString nCounter analysis for the PanCancer IO360 panel, and enrichment analysis were performed.Results Eleven patients (36.7%) showed a durable clinical benefit (DCB), whereas 19 (63.3%) showed no durable benefit (NDB). TMB and enrichment scores (ES) showed significant differences between the DCB and NDB groups (p=0.044 and p=0.017, respectively); however, no significant correlations were observed among TMB, ES, and PD-L1. ES was the best single biomarker for predicting DCB (area under the curve [AUC], 0.794), followed by TMB (AUC, 0.679) and PD-L1 (AUC, 0.622). TMB and ES showed the highest AUC (0.837) among other combinations (AUC [TMB and PD-L1], 0.777; AUC [PD-L1 and ES], 0.763) and was similar to that of all biomarkers used together (0.832).Conclusion The combination of TMB and ES may be an effective predictive tool to identify patients with NSCLC patients who would possibly benefit from ICI therapies.
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