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早期肺腺癌中新型复发相关免疫特征的临床意义及炎症图谱。

Clinical significance and inflammatory landscapes of a novel recurrence-associated immune signature in early-stage lung adenocarcinoma.

机构信息

Department of Thoracic Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.

出版信息

Cancer Lett. 2020 Jun 1;479:31-41. doi: 10.1016/j.canlet.2020.03.016. Epub 2020 Mar 19.

Abstract

The prevalence of early-stage lung adenocarcinoma (LUAD) has increased alongside increased implementation of lung cancer screenings. Robust discrimination criteria are urgently needed to identify those patients who might benefit from additional systemic therapy. Here, to develop a reliable, individualized immune gene-set-based signature to predict recurrence in early-stage LUAD, a novel recurrence-associated immune signature was identified using a least absolute shrinkage and selection operator model, and a stepwise Cox proportional hazards regression model with a training set comprised of 338 early-stage LUAD samples form TCGA, which was subsequently validated in 226 cases from GSE31210 and an independent set of 68 frozen tumor samples with qRT-PCR data. This new classification system remained strongly predictive of prognoses across clinical subgroups and mutation status. Further analysis revealed that samples from high-risk cases were characterized by active interferon signal transduction, distinctive immune cell proportions and immune checkpoint profiles. Moreover, the signature was identified as an independent prognostic factor. In conclusion, the signature is highly predictive of recurrence in patients with early-stage LUAD, which may serve as a powerful prognostic tool to further optimize immunotherapies for cancer.

摘要

早期肺腺癌 (LUAD) 的患病率随着肺癌筛查的广泛实施而增加。迫切需要建立稳健的判别标准,以确定那些可能受益于额外系统治疗的患者。在这里,为了开发一种可靠的、个体化的免疫基因集为基础的签名来预测早期 LUAD 的复发,使用最小绝对收缩和选择算子模型,以及一个逐步的 Cox 比例风险回归模型,从 TCGA 中的 338 个早期 LUAD 样本中识别出一个新的与复发相关的免疫签名,该模型随后在 GSE31210 中的 226 个病例和带有 qRT-PCR 数据的 68 个冷冻肿瘤样本的独立集中进行了验证。该新的分类系统在临床亚组和突变状态方面仍然具有很强的预后预测能力。进一步的分析表明,高危病例的样本表现出活跃的干扰素信号转导、独特的免疫细胞比例和免疫检查点特征。此外,该签名被确定为一个独立的预后因素。总之,该签名高度预测了早期 LUAD 患者的复发情况,这可能成为一个强大的预后工具,以进一步优化癌症的免疫治疗。

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