Table_4_A Combination of Biomarkers Predict Response to Immune Checkpoint Blockade Therapy in Non-Small Cell Lung Cancer.xlsx
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https://figshare.com/articles/dataset/Table_4_A_Combination_of_Biomarkers_Predict_Response_to_Immune_Checkpoint_Blockade_Therapy_in_Non-Small_Cell_Lung_Cancer_xlsx/17427137
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Immune checkpoint blockade (ICB) therapy has provided clinical benefits for patients with advanced non-small-cell lung cancer (NSCLC), but the majority still do not respond. Although a few biomarkers of ICB treatment response have been developed, the predictive power of these biomarkers showed substantial variation across datasets. Therefore, predicting response to ICB therapy remains a challenge. Here, we provided a concise combinatorial strategy for predicting ICB therapy response and constructed the ICB treatment signature (ITS) in lung cancer. The prediction performance of ITS has been validated in an independent ICB treatment cohort of NSCLC, where patients with higher ITS score were significantly associated with longer progression-free survival and better response. And ITS score was more powerful than traditional biomarkers, such as TMB and PD-L1, in predicting the ICB treatment response in NSCLC. In addition, ITS scores still had predictive effects in other cancer data sets, showing strong scalability and robustness. Further research showed that a high ITS score represented comprehensive immune activation characteristics including activated immune cell infiltration, increased mutation load, and TCR diversity. In conclusion, our practice suggested that the combination of biomarkers will lead to a better prediction of ICB treatment prognosis, and the ITS score will provide NSCLC patients with better ICB treatment decisions.
免疫检查点阻断(Immune checkpoint blockade, ICB)治疗可为晚期非小细胞肺癌(non-small-cell lung cancer, NSCLC)患者带来临床获益,但多数患者仍无法从中获益。尽管已有数种ICB治疗响应相关生物标志物被开发,但这些标志物的预测能力在不同数据集间存在显著差异。因此,预测ICB治疗响应仍是一项挑战。本研究提出了一种简洁的联合策略用于预测ICB治疗响应,并构建了肺癌中的ICB治疗特征(ICB treatment signature, ITS)。ITS的预测性能已在一项独立的NSCLC患者ICB治疗队列中得到验证,其中ITS评分较高的患者无进展生存期更长、治疗响应更佳。在NSCLC的ICB治疗响应预测中,ITS评分的表现优于肿瘤突变负荷(Tumor Mutational Burden, TMB)、程序性死亡配体1(Programmed Death-Ligand 1, PD-L1)等传统生物标志物。此外,ITS评分在其他癌症数据集仍具有预测效能,展现出良好的可推广性与稳健性。进一步研究表明,高ITS评分代表了全面的免疫激活特征,包括活化免疫细胞浸润、突变负荷升高以及T细胞受体(T cell receptor, TCR)多样性增加。综上,本研究表明,联合使用生物标志物可更精准地预测ICB治疗预后,而ITS评分可为NSCLC患者提供更优化的ICB治疗决策依据。
创建时间:
2021-12-23



