Brain metastasis (BM) occurs commonly in patients with lung adenocarcinomas. Limited evidence indicates safety and efficacy of immunotherapy for this metastatic tumor, though immune checkpoint blockade has become the front-line treatment for primary advanced non-small cell lung cancer. We aim to comprehensively compare tumor microenvironments (TME) between primary tumors (PT) and BM at single-cell resolution. Single-cell RNA transcriptomics from tumor samples of PT (N = 23) and BM (N = 16) and bulk sequencing data were analyzed to explore potential differences in immunotherapeutic efficacy between PT and BM of lung adenocarcinomas. Multiple machine learning algorithms were used to develop and validate models that predict responses to immunotherapy using the external cohorts. We found obviously less infiltration of immune cells in BM than PT, characterized specifically by deletion of anti-cancer CD8+ Trm cells and more dysfunctional CD8+ Tem cells in BM tumors. Meanwhile, macrophages and dendritic cells within BM demonstrated more pro-tumoral and anti-inflammatory effects, represented by distinct distribution and function of SPP1+ and C1Qs+ tumor-associated microphages, and inhibited antigen presentation capacity and HLA-I gene expression, respectively. Besides, we also found the lack of inflammatory-like CAFs and enrichment of pericytes within BM tumors, which may be critical factors in shaping inhibitory TME. Cell communication analysis further revealed mechanisms of the immunosuppressive effects associated with the activation of some unfavorable pathways, such as TGFβ signaling, highlighting the important roles of stromal cells in the anti-inflammatory microenvironment, especially specific pericytes. Furthermore, pericyte-related genes were identified to optimally predict immunotherapeutic responses by machine learning models with great predictive performance. Overall, various factors contribute to the immunosuppressive TME within BM tumors, represented by the lack of critical anti-cancer immune cells. Meanwhile, pericytes may help shape the TME and targeting the associated mechanisms may enhance immunotherapy efficacy for BM tumors in patients with lung adenocarcinomas. Keywords: brain metastasis; lung adenocarcinoma; machine learning; single-cell sequencing; tumor microenvironment.

---

 

乐备实（上海优宁维生物科技股份有限公司旗下全资子公司），是国内专注于提供高质量蛋白检测以及组学分析服务的实验服务专家，自2018年成立以来，乐备实不断寻求突破，公司的服务技术平台已扩展到单细胞测序、空间多组学、流式检测、超敏电化学发光、Luminex多因子检测、抗体芯片、PCR Array、ELISA、Elispot、PLA蛋白互作、多色免疫组化、DSP空间多组学等30多个，建立起了一套涵盖基因、蛋白、细胞以及组织水平实验的完整检测体系。

 
我们可提供从样本运输、储存管理、样本制备、样本检测到检测数据分析的全流程服务。凭借严格的实验室管理流程、标准化实验室操作、原始数据储存体系以及实验项目管理系统，已经为超过3000家客户单位提供服务，年检测样本超过100万，受到了广大客户的信任与支持。