Comprehensive Profiling Reveals Distinct Microenvironment and Metabolism Characterization of Lung Adenocarcinoma.
Comprehensive Profiling Reveals Distinct Microenvironment and Metabolism Characterization of Lung Adenocarcinoma.
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综合分析揭示肺腺癌独特的微环境和代谢特征
DOI：
10.3389/fgene.2021.619821
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发表时间：
2021
影响因子：
3.7
通讯作者：
Liu L
中科院分区：
文献类型：
--
作者：
Li C;Tian C;Liu Y;Liang J;Zeng Y;Yang Q;Liu Y;Wu D;Wu J;Wang J;Zhang K;Gu F;Hu Y;Liu L
随着免疫检查点抑制剂（ICI）的发展，肺腺癌进入了免疫治疗时代。免疫亚型的鉴定对于延长患者的生存至关重要。肿瘤微环境（TME）和代谢对预后和治疗有着深远的影响。以往的研究大多集中在一个方面，而这两个方面对于理解肿瘤的发生和发展至关重要。我们假设肺腺癌可以根据TME浸润的改变分为免疫亚组。我们的目的是探索每个亚型的“TME-代谢-风险”模式及其背后的机制。基于研究的前半部分，选择糖酵解和胆固醇用于代谢状态分析。进行生物信息学分析以研究由三个肺腺癌队列（GSE 30219、GSE 31210、GSE 37745，N = 415）整合的转录组学和临床数据。结果在一个独立队列（GSE 50081，N = 127）中得到验证。总共对415份肺腺癌样本进行了整合和分析。利用生物信息学分析鉴定了四种主要的免疫亚型。亚型NC 1，特征为高水平的糖酵解，具有极低的微环境细胞浸润。NC 2亚型，以“沉默”和“胆固醇生物合成主导”代谢状态为特征，具有中等程度的微环境细胞浸润。NC 3亚型，以缺乏“胆固醇生物合成主导”代谢状态为特征，具有丰富的微环境细胞浸润。NC 4亚型，以“混合”代谢状态为特征，具有相对低的微环境细胞浸润。采用最小绝对收缩和选择算子（LASSO）回归和多因素分析计算每个样本的风险，并试图找出不同亚型的潜在免疫逃逸机制。结果表明，NC 1和NC 4亚型的免疫逃逸可能与免疫细胞浸润不足有关。NC 3的特征在于免疫检查点分子和成纤维细胞的高表达。NC 2在天然免疫细胞的激活方面存在缺陷。NC 2亚型存在明显的生存优势。基因集富集分析（GSEA）和基因本体论（Gene Ontology）分析表明，PI 3 K-AKT-mTOR、TGF-β、MYC等相关通路可能与该现象相关。此外，在NC 3亚型中发现了一些差异表达基因，这些基因可能是转化存活表型的潜在靶基因。
Lung adenocarcinoma has entered into an era of immunotherapy with the development of immune checkpoint inhibitors (ICIs). The identification of immune subtype is crucial to prolonging survival in patients. The tumor microenvironment (TME) and metabolism have a profound impact on prognosis and therapy. The majority of previous studies focused on only one aspect, while both of them are essential to the understanding of tumorigenesis and development. We hypothesized that lung adenocarcinoma can be stratified into immune subgroups with alterations in the TME infiltration. We aimed to explore the “TME-Metabolism-Risk” patterns in each subtypes and the mechanism behind. Glycolysis and cholesterol were selected for the analysis of metabolic states based on the first half of the study. Bioinformatic analysis was performed to investigate the transcriptomic and clinical data integrated by three lung adenocarcinoma cohorts (GSE30219, GSE31210, GSE37745, N = 415). The results were validated in an independent cohort (GSE50081, N = 127). In total, 415 lung adenocarcinoma samples were integrated and analyzed. Four major immune subtypes were indentified using bioinformatic analysis. Subtype NC1, characterized by a high level of glycolysis, with extremely low microenvironment cell infiltration. Subtype NC2, characterized by the “Silence” and “Cholesterol biosynthesis Predominant” metabolic states, with a middle degree infiltration of microenvironment cell. Subtype NC3, characterized by the lack of “Cholesterol biosynthesis Predominant” metabolic state, with abundant microenvironment cell infiltration. Subtype NC4, characterized by “Mixed” metabolic state, with a relatively low microenvironment cell infiltration. Least absolute shrinkage and selection operator (LASSO) regression and multivariate analyses were performed to calculate the risk of each sample, and we attempted to find out the potential immune escape mechanism in different subtypes. The result revealed that the lack of immune cells infiltration might contribute to the immune escape in subtypes NC1 and NC4. NC3 was characterized by the high expression of immune checkpoint molecules and fibroblasts. NC2 had defects in activation of innate immune cells. There existed an obviously survival advantage in subtype NC2. Gene set enrichment analysis (GSEA) and Gene Ontology analysis indicated that the PI3K-AKT-mTOR, TGF-β, MYC-related pathways might be correlated with this phenomenon. In addition, some differentially expressed genes (DEGs) were indentified in subtype NC3, which might be potential targets for survival phenotype transformation.
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影响因子：
11.5
作者：
Karasinska, Joanna M.;Topham, James T.;Schaeffer, David F.
通讯作者：
Schaeffer, David F.
影响因子：
5.8
作者：
Liberzon, Arthur;Subramanian, Aravind;Mesirov, Jill P.
通讯作者：
Mesirov, Jill P.
影响因子：
64.5
作者：
David CJ;Huang YH;Chen M;Su J;Zou Y;Bardeesy N;Iacobuzio-Donahue CA;Massagué J
通讯作者：
Massagué J
影响因子：
3.7
作者：
Li, Jie;Liu, Cun;Sun, Changgang
通讯作者：
Sun, Changgang
影响因子：
4.8
作者：
Le Stunff, H;Peterson, C;Spiegel, S
通讯作者：
Spiegel, S