Single-cell RNA sequencing reveals distinct tumor microenvironmental patterns in lung adenocarcinoma

生物 癌症研究 癌变 核糖核酸 腺癌 基因 癌症 计算生物学 内科学 遗传学 医学
作者
Philip Bischoff,Alexandra Trinks,Benedikt Obermayer,J. Patrick Pett,Jennifer Wiederspahn,Florian Uhlitz,Xizi Liang,Annika Lehmann,Philipp Jurmeister,Aron Elsner,Tomasz Dziodzio,Jens‐Carsten Rückert,Jens Neudecker,Christine S. Falk,Dieter Beule,Christine Sers,Markus Morkel,David Horst,Nils Blüthgen,Frederick Klauschen
出处
期刊:Oncogene [Springer Nature]
卷期号:40 (50): 6748-6758 被引量:99
标识
DOI:10.1038/s41388-021-02054-3
摘要

Abstract Recent developments in immuno-oncology demonstrate that not only cancer cells, but also the tumor microenvironment can guide precision medicine. A comprehensive and in-depth characterization of the tumor microenvironment is challenging since its cell populations are diverse and can be important even if scarce. To identify clinically relevant microenvironmental and cancer features, we applied single-cell RNA sequencing to ten human lung adenocarcinomas and ten normal control tissues. Our analyses revealed heterogeneous carcinoma cell transcriptomes reflecting histological grade and oncogenic pathway activities, and two distinct microenvironmental patterns. The immune-activated CP²E microenvironment was composed of cancer-associated myofibroblasts, proinflammatory monocyte-derived macrophages, plasmacytoid dendritic cells and exhausted CD8+ T cells, and was prognostically unfavorable. In contrast, the inert N³MC microenvironment was characterized by normal-like myofibroblasts, non-inflammatory monocyte-derived macrophages, NK cells, myeloid dendritic cells and conventional T cells, and was associated with a favorable prognosis. Microenvironmental marker genes and signatures identified in single-cell profiles had progonostic value in bulk tumor profiles. In summary, single-cell RNA profiling of lung adenocarcinoma provides additional prognostic information based on the microenvironment, and may help to predict therapy response and to reveal possible target cell populations for future therapeutic approaches.
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