Division of Medical Oncology, Department of Medicine, University of Colorado Cancer Center, Aurora, CO, USA.
Department of Pathology, Aberdeen University Medical School, Aberdeen Royal Infirmary, Aberdeen, UK.
Nat Rev Clin Oncol. 2019 Jun;16(6):341-355. doi: 10.1038/s41571-019-0173-9.
The era of personalized medicine for advanced-stage non-small-cell lung cancer (NSCLC) began when biomarker-based evidence of molecular pathway and/or oncogene addiction of the tumour became mandatory for the allocation of specific targeted therapies. More recently, the immunotherapy revolution, specifically, the development of immune-checkpoint inhibitors (ICIs), has dramatically altered the NSCLC treatment landscape. Herein, we compare and contrast the clinical development of immunotherapy and oncogene-directed therapy for NSCLC, focusing on the role of predictive biomarkers. Immunotherapy biomarkers are fundamentally different from oncogene biomarkers in that they are continuous rather than categorical (binary), spatially and temporally variable and reliant on multiple complex interactions rather than a single, dominant determinant. The performance of predictive biomarkers for ICIs might be improved by combining different markers to reduce the assumptive risks associated with each one. Novel combinations with chemotherapy and ICIs complicate biomarker discovery but do not decrease the value of the markers identified. Perfectly predictive biomarkers of benefit from immunotherapy are unlikely to be identified, although exclusionary biomarkers of minimal benefit or an unacceptable risk of toxicity might be feasible. The clinical adoption and applicability of such biomarkers might vary depending on line of treatment, the available therapeutic alternatives and health economic considerations.
晚期非小细胞肺癌（NSCLC）的个体化医学时代始于肿瘤分子通路和/或致癌基因依赖性的生物标志物证据成为特定靶向治疗分配的强制性要求。最近，免疫治疗革命，特别是免疫检查点抑制剂（ICI）的发展，极大地改变了 NSCLC 的治疗格局。在此，我们比较和对比 NSCLC 的免疫治疗和针对致癌基因的治疗的临床发展，重点关注预测生物标志物的作用。免疫治疗生物标志物与致癌基因生物标志物在根本上不同，因为它们是连续的而不是分类的（二进制），空间和时间上是可变的，并且依赖于多个复杂的相互作用，而不是单一的、占主导地位的决定因素。通过结合不同的标志物来减少每个标志物的假设风险，可以提高预测 ICI 的生物标志物的性能。化疗和 ICI 的新组合使生物标志物的发现变得复杂，但不会降低已确定标志物的价值。不太可能发现完全预测免疫治疗获益的生物标志物，尽管最小获益或不可接受的毒性风险的排他性生物标志物可能是可行的。这些生物标志物的临床采用和适用性可能因治疗线、可用的治疗选择和健康经济考虑因素而异。
