文献检索，用中文搜 PubMed

BACKGROUND

Immune checkpoint inhibitors (ICIs) treatment have shown high efficacy for about 15 cancer types. However, this therapy is only effective in 20-30% of cancer patients. Thus, the precise biomarkers of ICI response are an urgent need.

METHODS

We conducted a prospective observational study of the prognostic potential ofseveral existing and putative biomarkers of response to immunotherapy in acohort of 85 patients with lung cancer (LC) receiving PD-1 or PD-L1 targeted ICIs. Tumor biosamples were obtained prior to ICI treatment and profiled by whole exome and RNA sequencing. The entire 403 putative biomarkers were screened, including tumor mutation burden (TMB) and number of cancer neoantigens, 131 specific HLA alleles, homozygous state of 11 HLA alleles and their superfamilies; four gene mutation biomarkers, expression of 45 immune checkpoint genes and closely related genes, and three previously published diagnostic gene signatures; for the first time, activation levels of 188 molecular pathways containing immune checkpoint genes and activation levels of 19 pathways algorithmically generated using a human interactome model centered around immune checkpoint genes. Treatment outcomes and/or progression-free survival (PFS) times were available for 61 of 85 patients with LC, including 24 patients with adenocarcinoma and 27 patients with squamous cell LC, whose samples were further analyzed. For the rest 24 patients, both treatment outcomes and PFS data could not be collected. Of these, 54 patients were treated with PD1-specific and 7 patients with PD-L1-specific ICIs. We evaluated the potential of biomarkers based on PFS and RECIST treatment response data.

RESULTS

In our sample, 45 biomarkers were statistically significantly associated with PFS and 44 with response to treatment, of which eight were shared. Five of these (CD3G and NCAM1 gene expression levels, and levels of activation of Adrenergic signaling in cardiomyocytes, Growth hormone signaling, and Endothelin molecular pathways) were used in our signature that showed an AUC of 0.73 and HR of 0.27 (p=0.00034) on the experimental dataset. This signature was also reliable (AUC 0.76, 0.87) for the independent publicly available LC datasets GSE207422, GSE126044 annotated with ICI response data and demonstrated same survival trends on independent dataset GSE135222 annotated with PFS data. In both experimental and one independent datasets annotated with samples' histotypes, the signature worked better for lung adenocarcinoma than for squamous cell LC.

CONCLUSION

The high reliability of our signature to predict response and PFS after ICI treatment was demonstrated using experimental and 3 independent datasets. Additionally, annotated molecular profiles obtained in this study were made publicly accessible.

背景

免疫检查点抑制剂（ICI）治疗已在约15种癌症类型中显示出高效性。然而，这种疗法仅对20%-30%的癌症患者有效。因此，急需ICI反应的精确生物标志物。

方法

我们对85例接受PD-1或PD-L1靶向ICI治疗的肺癌（LC）患者队列中几种现有和假定的免疫治疗反应生物标志物的预后潜力进行了一项前瞻性观察研究。在ICI治疗前获取肿瘤生物样本，并通过全外显子组和RNA测序进行分析。筛选了总共403个假定的生物标志物，包括肿瘤突变负荷（TMB）和癌症新抗原数量、131个特定的HLA等位基因、11个HLA等位基因及其超家族的纯合状态；四个基因突变生物标志物、45个免疫检查点基因和密切相关基因的表达，以及三个先前发表的诊断基因特征；首次检测了188条包含免疫检查点基因的分子通路的激活水平，以及使用以免疫检查点基因为中心的人类相互作用组模型算法生成的19条通路的激活水平。85例LC患者中有61例可获得治疗结果和/或无进展生存期（PFS）数据，其中包括24例腺癌患者和27例鳞状细胞LC患者，对其样本进行了进一步分析。其余24例患者无法收集治疗结果和PFS数据。其中，54例患者接受了PD-1特异性ICI治疗，7例患者接受了PD-L1特异性ICI治疗。我们基于PFS和RECIST治疗反应数据评估了生物标志物的潜力。

结果

在我们的样本中，45个生物标志物与PFS在统计学上显著相关，44个与治疗反应相关，其中8个是共同的。其中5个（CD3G和NCAM1基因表达水平，以及心肌细胞中肾上腺素能信号通路、生长激素信号通路和内皮素分子通路的激活水平）被用于我们的特征分析，在实验数据集上显示AUC为0.73，HR为0.27（p=0.00034）。对于标注有ICI反应数据的独立公开可用LC数据集GSE207422、GSE126044，该特征分析也具有可靠性（AUC分别为0.76、0.87），并且在标注有PFS数据的独立数据集GSE135222上显示出相同的生存趋势。在实验数据集和一个标注有样本组织类型的独立数据集中，该特征分析对肺腺癌的效果比对鳞状细胞LC更好。