An EV-Associated Gene Signature Correlates with Hypoxic Microenvironment and Predicts Recurrence in Lung Adenocarcinoma
An EV-Associated Gene Signature Correlates with Hypoxic Microenvironment and Predicts Recurrence in Lung Adenocarcinoma
复制标题
EV 相关基因特征与缺氧微环境相关并预测肺腺癌复发
DOI：
10.1016/j.omtn.2019.07.021
复制
发表时间：
2019-09-06
影响因子：
8.8
通讯作者：
Lang, Jinyi
中科院分区：
文献类型：
--
作者：
Cao, Bangrong;Dai, Wei;Lang, Jinyi
细胞外囊泡（EV）介导肿瘤微环境中的细胞间通讯，并有助于癌症的侵袭现象。虽然体液中的EV被认为是癌症诊断和预后的理想生物标志物，但仍然难以区分肿瘤来源的EV与其他组织释放的EV。我们假设，分析肿瘤组织中的EV相关分子将有助于估计肿瘤特异性EV的预后价值。在这里，我们调查的小EVs（sEVs）携带的蛋白质编码基因在原发性肺腺癌的表达。基于蛋白质-蛋白质相互作用网络，我们确定了三个网络模块（3-PPI-Mod）作为可以预测复发的签名。该特征在三个独立的数据集中得到验证，并显示出比单独从基因表达产生的特征更好的预后价值。同时，由签名分配的高危亚组可以从辅助化疗中获益，尽管在NSCLC患者中没有获益。三个模块中的两个通过在来自非小细胞肺癌细胞的sEV中鉴定的蛋白质富集。此外，这两个模块与肿瘤内缺氧评分显著相关。这些结果表明，3-PPI-Mod特征在肿瘤来源的sEV中富集，并且可以作为肺腺癌的预后和预测生物标志物。
Extracellular vesicles (EVs) mediate intercellular communications in the tumor microenvironment and contribute to the aggressive phenomenon of cancers. Although EVs in body fluids are supposed to be ideal biomarkers for cancer diagnosis and prognosis, it remains difficult to distinguish the tumor-derived EVs from those released by other tissues. We hypothe-sized that analyzing the EV-related molecules in tumor tissues would help to estimate the prognostic value of tumor-specific EVs. Here, we investigate the expression of coding genes of proteins carried by small EVs (sEVs) in primary lung adenocarcinoma. Based on the protein-protein interaction network, we identified three network modules (3-PPI-Mod) as a signature that could predict recurrence. This signature was validated in three independent datasets and demonstrated better prognostic value than signature generated from gene expression alone. Meanwhile, the high-risk subgroup assigned by the signature could benefit from adjuvant chemotherapy, although it was not beneficial in unselected patients. Two out of three modules were enriched by proteins identified in sEVs from non-small-cell lung cancer cells. Furthermore, the two modules were remarkably correlated with intratumoral hypoxia score. These results suggest that the 3-PPI-Mod signature was enriched in tumor-derived sEVs and could serve as a prognostic and predictive biomarker for lung adenocarcinoma.