State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Burning Rock Biotech, Guangzhou, China.
Cancer Cell. 2024 Sep 9;42(9):1598-1613.e4. doi: 10.1016/j.ccell.2024.08.013.
Stratification strategies for chemotherapy plus PD-1 inhibitors in advanced non-small-cell lung cancer (NSCLC) are critically demanded. We performed high-throughput panel-based deep next-generation sequencing and low-pass whole genome sequencing on prospectively collected circulating tumor DNA (ctDNA) specimens from 460 patients in the phase 3 CHOICE-01 study at different time points. We identified predictive markers for chemotherapy plus PD-1 inhibitor, including ctDNA status and genomic features such as blood-based tumor mutational burden, intratumor heterogeneity, and chromosomal instability. Furthermore, we established an integrated ctDNA-based stratification strategy, blood-based genomic immune subtypes (bGIS) scheme, to distinguish patients who benefit from the addition of PD-1 inhibitor to first-line chemotherapy. Moreover, we demonstrated potential applications for the dynamic monitoring of ctDNA. Overall, we proposed a potential therapeutic algorithm based on the ctDNA-based stratification strategy, shedding light on the individualized management of immune-chemotherapies for patients with advanced NSCLC.
在晚期非小细胞肺癌（NSCLC）中，对化疗加 PD-1 抑制剂的分层策略有迫切需求。我们在 3 期 CHOICE-01 研究中对前瞻性收集的 460 名患者的循环肿瘤 DNA（ctDNA）标本进行了高通量基于面板的深度下一代测序和低通量全基因组测序，并在不同时间点进行了分析。我们确定了化疗加 PD-1 抑制剂的预测标志物，包括 ctDNA 状态和基于血液的肿瘤突变负担、肿瘤内异质性和染色体不稳定性等基因组特征。此外，我们建立了一种基于整合 ctDNA 的分层策略，即基于血液的基因组免疫亚型（bGIS）方案，以区分从一线化疗加用 PD-1 抑制剂中获益的患者。此外，我们还展示了 ctDNA 动态监测的潜在应用。总之，我们提出了一种基于 ctDNA 分层策略的潜在治疗算法，为晚期 NSCLC 患者的免疫化疗个体化管理提供了思路。
