Integrative analysis of imaging and transcriptomic data of the immune landscape associated with tumor metabolism in lung adenocarcinoma: Clinical and prognostic implications.
Integrative analysis of imaging and transcriptomic data of the immune landscape associated with tumor metabolism in lung adenocarcinoma: Clinical and prognostic implications.
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作者：
Choi H;Na KJ
尽管肿瘤微环境（TME）中的代谢调节是癌症免疫逃逸的关键机制之一，但基于临床证据，人们对TME的综合免疫景观及其与肿瘤代谢的关系缺乏了解。我们的目的是研究 TME 中的免疫景观与肺腺癌中肿瘤葡萄糖代谢之间的关系。方法：利用RNA测序和图像数据，我们开发了基于转录组的肿瘤代谢估计模型。估计了综合 TME 细胞类型富集评分和总体免疫细胞富集 (ImmuneScore)。受试者根据 TME 中的细胞异质性进行聚类，聚类的特征是肿瘤葡萄糖代谢和免疫细胞组成。此外，还评估了免疫评分、肿瘤代谢和基于细胞类型的簇的预后价值。结果：根据 TME 中的细胞异质性鉴定出四个簇。它们表现出不同的免疫细胞组成、不同的肿瘤代谢以及与总生存期的密切关系。具有高调节性 T 细胞的簇表现出相对代谢亢进和不良预后。另一个具有高肥大细胞和 CD4+ 中央记忆 T 细胞的簇表现出相对低代谢和良好的预后。具有高免疫分数的簇显示出良好的预后。多变量 Cox 分析表明，ImmuneScore 是独立于其他临床特征的预测预后因素。结论：我们的结果显示了 TME 中预测的肿瘤代谢与免疫细胞组成之间的关联。我们的研究还表明，TME 中的肿瘤葡萄糖代谢和免疫细胞浸润可在临床上适用于开发预后分层模型。
Although metabolic modulation in the tumor microenvironment (TME) is one of the key mechanisms of cancer immune escape, there is a lack of understanding of the comprehensive immune landscape of the TME and its association with tumor metabolism based on clinical evidence. We aimed to investigate the relationship between the immune landscape in the TME and tumor glucose metabolism in lung adenocarcinoma. Methods: Using RNA sequencing and image data, we developed a transcriptome-based tumor metabolism estimation model. The comprehensive TME cell types enrichment scores and overall immune cell enrichment (ImmuneScore) were estimated. Subjects were clustered by cellular heterogeneity in the TME and the clusters were characterized by tumor glucose metabolism and immune cell composition. Moreover, the prognostic value of ImmuneScore, tumor metabolism and the cell type-based clusters was also evaluated. Results: Four clusters were identified based on the cellular heterogeneity in the TME. They showed distinct immune cell composition, different tumor metabolism, and close relationship with overall survival. A cluster with high regulatory T cells showed relative hypermetabolism and poor prognosis. Another cluster with high mast cells and CD4+ central memory T cells showed relative hypometabolism and favorable prognosis. A cluster with high ImmuneScore showed favorable prognosis. Multivariate Cox analysis demonstrated that ImmuneScore was a predictive prognostic factor independent of other clinical features. Conclusions: Our results showed the association between predicted tumor metabolism and immune cell composition in the TME. Our studies also suggest that tumor glucose metabolism and immune cell infiltration in the TME can be clinically applicable for developing a prognostic stratification model.
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