Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, No. 180, Fenglin Road, Shanghai, 200032, China.
J Transl Med. 2019 Jul 8;17(1):217. doi: 10.1186/s12967-019-1964-6.
Immune infiltration may predict survival and have clinical significance in lung cancer. However, immune signatures derived from immune profiling based on bulk tumor transcriptomes have not been systematically established in lung adenocarcinoma. We aimed to construct an immune cell infiltrating score, using a new algorithm for evaluating immune infiltration, to improve the prognostic model of lung adenocarcinoma.
Public datasets of lung adenocarcinoma from the Gene Expression Omnibus and The Cancer Genome Atlas were adopted as the training and validation cohorts. Fractions of different immune cell subtypes in each sample were estimated using the CIBERSORT algorithm. The immune infiltrating score was further developed by a least absolute shrinkage and selection operator regression model. The prognostic value and clinical relationship of the model was then further explored.
An immune infiltrating score model was established on the basis of the immune cells in the training cohort. A high score was associated with significantly worse survival in patients with lung adenocarcinoma (P < 0.001). The prognostic value of the score was confirmed in the validation cohort. The immune infiltrating score could improve the accuracy of predictions of survival when combined with the staging system. Furthermore, the score was potentially associated with patient smoking status and histologic subtype of lung adenocarcinoma. Its possible association with the efficacy of adjuvant chemotherapy was not statistically significant.
The immune cell infiltrating score has prognostic significance in predicting overall survival in patients with lung adenocarcinoma.
免疫浸润可能预测肺癌的生存情况并具有临床意义。然而，基于肿瘤转录组的免疫分析得出的免疫特征在肺腺癌中尚未得到系统的建立。我们旨在构建一种免疫细胞浸润评分，使用一种新的评估免疫浸润的算法，以改进肺腺癌的预后模型。
采用来自基因表达综合数据库和癌症基因组图谱的公共肺腺癌数据集作为训练和验证队列。使用 CIBERSORT 算法估计每个样本中不同免疫细胞亚群的分数。通过最小绝对收缩和选择算子回归模型进一步开发免疫浸润评分。然后进一步探讨了该模型的预后价值和临床相关性。
基于训练队列中的免疫细胞建立了一个免疫浸润评分模型。高评分与肺腺癌患者的生存显著恶化相关（P<0.001）。该评分的预后价值在验证队列中得到了证实。评分与分期系统相结合可以提高生存预测的准确性。此外，该评分可能与患者的吸烟状况和肺腺癌的组织学亚型有关。其与辅助化疗疗效的可能相关性在统计学上无显著意义。
免疫细胞浸润评分对预测肺腺癌患者的总生存具有预后意义。
