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肺癌治疗中TREM2+巨噬细胞如何助肿瘤免疫逃逸

Genelibs文献解读 2026-10-23 01:43 36 次阅读

原文：TREM2+ macrophages mediate anticancer therapy-induced immune evasion in lung adenocarcinoma via the CCL5/CCL22-Treg axis.
期刊：Frontiers in immunology（影响因子 7.0） | PubMed | PMC 全文（含 PDF）

在非小细胞肺癌（NSCLC）的临床治疗中，奥希替尼（osimertinib，第三代EGFR-TKI）和顺铂（cisplatin）分别是携带EGFR突变患者和无驱动基因突变患者的标准疗法。然而，医生们在现实中常常面对一个难题：这些药物在杀伤肿瘤细胞的同时，也会“重塑”肿瘤微环境（TME），有时反而让肿瘤获得免疫逃逸能力，导致耐药或复发。近期，一项发表在《Frontiers in Immunology》（影响因子7.0）上的研究，揭开了这一过程中的一条关键通路——TREM2阳性肿瘤相关巨噬细胞（TREM2+ TAMs）通过CCL5/CCL22–Treg轴，在抗癌治疗压力下帮助肺腺癌“策反”免疫系统。

研究背景：当化疗/靶向药遇上“免疫抑制型”微环境

肺腺癌是NSCLC中最常见的亚型。对于晚期患者，若没有可靶向的驱动突变，以顺铂为基础的双药化疗仍是主力方案；而对于EGFR突变患者，奥希替尼是一线标准治疗，FLAURA2试验也显示奥希替尼联合铂类化疗优于单药。但肿瘤微环境并不是静态的“旁观者”——它由肿瘤细胞、免疫细胞、成纤维细胞、血管和细胞外基质组成，并通过动态相互作用影响治疗响应。

在NSCLC的TME中，肿瘤相关巨噬细胞（TAMs）高度异质，且多呈现M2样免疫抑制表型，促进进展、转移和耐药。其中，表达髓系细胞触发受体2（TREM2）的巨噬细胞（即TREM2+ TAMs，本质为CD68+ TAMs）是免疫抑制微环境的核心组分：它们能压制CD8+效应T细胞增殖与杀伤功能，并上调CTLA4、TIM3等共抑制受体；还与PD-1抑制剂耐药有关。另一方面，调节性T细胞（Tregs，标志为FOXP3+）会被TAM来源的CCL22等趋化因子招募，削弱抗肿瘤免疫。

此前研究已发现：顺铂处理会增加肺癌组织中TREM2+ TAMs；用顺铂或奥希替尼处理THP-1单核细胞，会提升TREM2表达、推动M2极化。但“治疗后的TREM2+ TAMs如何具体改变T细胞格局、通过什么介质招募Treg”仍不清楚。这正是本研究的出发点。

核心发现：TREM2+ TAMs与Treg“并肩增多”，由CCL5/CCL22牵线

研究团队首先利用已发表的NSCLC患者来源单细胞RNA测序（scRNA-seq）数据集，对配对癌旁正常肺组织（NL）和肿瘤组织（Tu）进行无监督聚类，解析出T/NK细胞与髓系细胞图谱。在T/NK区室中，他们注释出10个亚群，包括初始T细胞、Tregs、CD4+组织驻留T细胞（CD4_Trm）、CD8+效应T细胞、CD8_Trm、γδ T细胞和NK细胞等。比较发现：肿瘤中初始T细胞、Tregs、CD4_Trm、CD8_Teff_1和CD8_Trm显著增多，而CD8_Teff_3、γδT_1和NK细胞减少。

在髓系区室中，TREM2高表达细胞（TREM2>2.5）被单独提取为一个亚群，主要映射至CD163/LGMN巨噬细胞状态，共表达CD68、CD163、SPP1、LGMN、APOE、GPNMB，而不表达肺泡巨噬细胞标志，符合M2样TAM特征。关键的是，TREM2+ TAMs的数量与Tregs呈正相关、与NK细胞呈负相关；在汇总单细胞水平上，TREM2+细胞与FOXP3+细胞的丰度相关性达到Spearman rho = 0.7323（P < 0.001）。TCGA-LUAD队列分析也显示TREM2与FOXP3 mRNA表达显著正相关（r = 0.370，P < 0.001）。

**Figure 1** Distribution of TREM2+ TAMs and T/NK subclusters in scRNA-seq data from lung cancer (Tu) and adjacent normal-like lung (NL). (A) UMAP of T/NK and myeloid cell clusters derived from unsupervised clustering of the scRNA-seq dataset. (B) Dot plot showing the expression of representative marker genes used for cell-type annotation. (C) Alluvial plot showing the distribution of T/NK subclusters between Tu and NL. (D) Box plot comparing the proportion of the Treg subcluster between Tu and NL (P value calculated by Wilcoxon signed-rank test). (E) Dot correlation plot showing correlations in cell abundance between TREM2+ TAMs and the T/NK subclusters. (F) Scatter plot showing the association between TREM2 and FOXP3 expression in the LUAD cohort from cBioPortal (P value calculated by Spearman’s correlation test; r, Spearman’s rho).

为了在真实人类组织中验证，研究者构建了116例未经治疗的肺腺癌组织芯片（TMA），进行TREM2和FOXP3免疫组化（IHC）染色与定量。结果显示，TREM2+ TAM计数与FOXP3+细胞计数呈轻度但显著的正相关（r = 0.199，P = 0.033）。在LSL-Kras-G12D小鼠肺癌模型中，顺铂治疗相比对照同时增加了Trem2+和Foxp3+细胞，且两者再次正相关（r = 0.249，P = 0.026）。尽管在异质性TME中相关系数不算高，但方向在人类组织、独立小鼠模型和汇总单细胞数据中一致，说明TREM2+ TAM富集确实伴随FOXP3+细胞增多。

**Figure 2** Quantitative association between TREM2+ TAMs and FOXP3+ cells. (A) Representative images and analysis workflow of immunohistochemistry (IHC) for TREM2 and FOXP3 in a tissue microarray (TMA) of 116 human lung adenocarcinomas. (B) Representative images and analysis workflow of IHC for Trem2 and Foxp3 in lung tissues from the LSL-Kras G12D mouse lung cancer model treated with vehicle or cisplatin. (C) Correlation plots showing the relationship between the numbers of TREM2+ and FOXP3+ cells in the human lung adenocarcinoma TMA (left) and in the LSL-Kras G12D mouse lung cancer model (right). (D) Caterpillar plots showing the weight of interaction (left) and the number of interactions (right) between TREM2+ TAMs and T/NK subclusters as inferred by CellChat analysis. (E) Dot plot showing candidate interacting molecules between TREM2+ TAMs and T/NK subclusters predicted by CellChat.

那么，是谁把TREM2+ TAMs和Tregs“连”在一起？研究者用CellChat进行细胞间通讯分析，发现TREM2+ TAMs与Treg、NK亚群之间存在显著相互作用权重。进一步结合药物处理后的基因表达谱，他们锁定两个关键趋化因子：CCL5和CCL22。对M0极化的THP-1巨噬细胞分别用顺铂（500 nM）或奥希替尼（100 nM）处理16小时后进行微阵列分析，两种药物诱导了重叠的差异表达基因集，富集于“白细胞趋化”和“CCR相关通路”；CCL5和CCL22均位列上调最显著的趋化因子之中。

**Figure 3** Microarray analysis of M0-polarized THP-1 cells treated with cisplatin or osimertinib. (A) Heatmap with hierarchical clustering of upregulated and downregulated genes obtained from microarray data of THP-1 cells differentiated to an M0 state by treatment with 150 nM PMA for 72 h and subsequently exposed to 500 nM cisplatin or 100 nM osimertinib for 16 h. (B) Venn diagram showing the overlap between the sets of upregulated and downregulated genes. (C) Dot plot of Gene Ontology molecular function terms identified by gene enrichment and functional annotation analysis using g:Profiler. (D) Enrichment map of KEGG pathways derived from the microarray data. (E) Schematic diagram depicting the predicted molecular interactions within the “cytokine–cytokine receptor interaction” pathway identified in (D). (F) Volcano plots (left) showing upregulated genes in THP-1 cells treated with 500 nM cisplatin (top) or 100 nM osimertinib (bottom) for 16 h, and corresponding tables (right) listing the top five upregulated genes for each treatment condition.

接下来验证“是否依赖TREM2”。团队用两条独立策略：一是shRNA敲低TREM2（shTREM2），二是使用合成9肽IA9（阻断TREM2与适配蛋白DAP12/TYROBP相互作用）进行药理抑制。在对照细胞中，顺铂或奥希替尼显著上调CCL5和CCL22；而在TREM2被沉默或IA9预处理的细胞中，这种药物诱导的上调被消除。相反，过表达TREM2则进一步增强其诱导。机制上，CCL22的诱导广泛依赖SYK、Src、AKT、NF-κB或STAT3信号；而CCL5上调依赖Src、NF-κB和STAT3，SYK的参与因细胞类型而异。

**Figure 4** Effects of TREM2 inhibition (shRNA, IA9) and overexpression on CCL22 and CCL5 expression. (A) THP-1 cells transduced with a human TREM2–targeting shRNA (shTREM2) or control shRNA (shCTL) were polarized to M0/M1/M2 and analyzed. Representative immunoblots for TREM2 and β-actin. (B) shCTL and shTREM2 M0 cells were treated with cisplatin (500 nM) or osimertinib (100 nM) for 16 h, followed by immunoblotting (TREM2, CCL22, β-actin; representative). (C) RT-qPCR under the same conditions as in (B) for CCL5 (top) and CCL22 (bottom). Data are expressed as 2-ΔΔCt, normalized to GAPDH, and plotted relative to vehicle (veh). Within each cell line, Veh vs. Cis and Veh vs. Osi were compared using two-sided Welch’s t test. (D) M0 THP-1 cells were pretreated with TREM2 inhibitor, IA9 (1 µM for 1 h), and then exposed to cisplatin (500 nM) or osimertinib (100 nM) for 16 h. RT-qPCR quantification of CCL5 and CCL22 (normalization and statistics as in (C)). (E) THP-1 cells were transduced with control or TREM2-expressing lentivirus and examined by fluorescence microscopy (upper; scale bar, 200 µm) and immunoblotting (lower). (F) Baseline RT-qPCR in control vs. TREM2-overexpressing cells for CCL5 (top) and CCL22 (bottom). Analyses used two-sided Welch’s t test. Bar graphs show mean ± s.e.m. with biological replicates n = 3. Significance: *p < 0.05, **p < 0.01, ***p < 0.001. veh, vehicle; cis, cisplatin; osi, osimertinib; IA9, TREM2-inhibitory peptide; shCTL, control shRNA; shTREM2, TREM2 shRNA.

**Figure 5** Signaling pathways regulating CCL5 and CCL22 expression. (A) RT-qPCR analysis of CCL5 (left) and CCL22 (right) mRNA expression in M0-polarized THP-1 cells pretreated for 1 h with (1) the SYK inhibitor BAY 61-3606 (100 nM), (2) the Src inhibitor dasatinib (30 nM), (3) the MEK inhibitor AZD6244 (500 nM), (4) the PI3K/Akt inhibitor LY294002 (10 μM), (5) the JAK inhibitor ruxolitinib (100 nM), (6) the STAT3 inhibitor STX-0119 (10 μM), or (7) the NF-κB inhibitor TPCA1 (2.5 μM), followed by stimulation with 500 nM cisplatin or 100 nM osimertinib for 16 h. Differences between vehicle and cisplatin or osimertinib within each pretreatment condition were evaluated using Welch’s t test. (B) RT-qPCR analysis of Ccl5 (left) and Ccl22 (right) mRNA expression in M0-polarized bone marrow–derived macrophages (BMDMs) treated with the same panel of inhibitors and cisplatin or osimertinib as in (A). Differences between vehicle and cisplatin or osimertinib were evaluated using Welch’s t test. (C) Immunoblot analysis of M0-polarized THP-1 cells (left) and BMDMs (right) treated with 500 nM cisplatin, 100 nM osimertinib, or 2 nM PV (positive control) for 30 min. In (A, B) bar graphs show mean ± s.e.m. with biological replicates n = 3. Significance: *p < 0.05, **p < 0.01, ***p < 0.001. Abbreviations: Veh, vehicle; Cis, cisplatin; Osi, osimertinib; BMDM, bone marrow–derived macrophage; PV, pervanadate.

最后，在原位Lewis肺癌（LLC）小鼠模型中，化疗期间抑制Trem2可减少Treg浸润，缓解化疗相关的免疫逃逸。这提示：标准治疗“逼出”了TREM2+ TAMs的促免疫抑制功能，而阻断TREM2能打断这条轴。

**Figure 6** Trem2 inhibition attenuates cisplatin-driven Foxp3+ enrichment in an orthotopic lung cancer model. (A) Representative hematoxylin and eosin (H&E) staining and Foxp3 immunohistochemistry (IHC) of orthotopic Lewis lung carcinoma (LLC) tumors from C57BL/6 mice treated with vehicle (Veh), cisplatin (Cis), IA9, or Cis + IA9. Representative images are shown; n = 4 mice per group. Scale bar, 20 µm. (B) Box-and-whisker plot denoting the fraction of Foxp3+ cells among total mononuclear cells, quantified using QuPath. Statistical significance was determined by one-way ANOVA followed by Tukey’s HSD post-hoc test; full pairwise comparisons are provided in Supplementary Table 20. (C) Representative immunofluorescence (IF) staining for Foxp3 (white), CD3 (green), and DAPI (blue) in orthotopic LLC tumors from the indicated treatment groups (Veh, Cis, IA9, Cis + IA9), confirming that Foxp3+ cells represent a CD3+ T-cell subset. Images are representative of n = 4 mice per group. Scale bar, 20 µm. (D) Representative IF staining for Ccl22 (green), Ccl5 (red), Trem2 (white), and DAPI (blue) in orthotopic LLC tumors from the indicated treatment groups, showing co-localization of Ccl22/Ccl5 signals with Trem2+ cells. Images are representative of n = 4 mice per group. Scale bar, 20 µm.

方法亮点：多组学+空间定量+体内外闭环验证

这项研究的证据链较为完整。在数据层面，它整合了：

公共scRNA-seq数据集（10x Chromium，来自既往两项NSCLC研究），经质控、整合、去恶性上皮细胞（inferCNV）后，用Seurat分群并重新注释T/NK与髓系亚群；
人类肺腺癌组织芯片（116例，2014–2018年手术切除、未接受新辅助/辅助化疗），以3 mm核心构建TMA，并用QuPath机器学习分类器自动识别核FOXP3+与胞质TREM2+细胞；
基因表达微阵列（Affymetrix Human Gene 2.0 ST Array，GEO编号GSE309879）筛选药物处理后的差异基因；
CellChat细胞通讯推断与TCGA/cBioPortal相关性分析。

在实验层面，研究者使用THP-1来源巨噬细胞（PMA诱导M0，再极化为M1/M2）以及小鼠原代骨髓来源巨噬细胞（BMDMs）进行体外机制研究；通过慢病毒/shRNA调控TREM2，并用IA9肽进行药理干预；以RT-qPCR、免疫印迹、IHC/免疫荧光定量。动物实验采用C57BL/6小鼠左肺原位注射LLC细胞建立模型，顺铂处理后8天取肺，评估Trem2抑制对Foxp3+细胞的影响，并遵循ARRIVE指南与IACUC协议。

一个值得注意的细节是：在未治疗的scRNA-seq数据中，CellChat并未把CCL5-CCR5、CCL22-CCR4对返回为显著互作，因为TREM2+簇本身低表达这些配体。作者据此指出，这条轴是“治疗诱导”而非组成型存在的——也就是说，是顺铂/奥希替尼“唤醒”了TREM2+ TAMs分泌CCL5/CCL22的能力。

应用意义：把TREM2变成增敏标准治疗的靶点

该研究的结论可以概括为：在肺腺癌中，TREM2+ TAMs在奥希替尼或顺铂治疗下被诱导或活化，通过Src/NF-κB/STAT3（及部分SYK/AKT）信号上调CCL5与CCL22；这些趋化因子分别作用于Treg上的CCR5和CCR4，将FOXP3+ Tregs招募至肿瘤微环境，从而抑制抗肿瘤免疫、造成治疗诱导的免疫逃逸。而在小鼠模型中抑制Trem2，可降低Treg浸润、减轻这种逃逸。

对科研而言，它细化了“TAM–Treg”互作在治疗压力下的分子图谱，明确了CCL22-CCR4是髓系→Treg的方向性信号，而CCL5-CCR5是多功能轴。对临床转化而言，结果支持一种组合策略：在奥希替尼或顺铂标准治疗基础上，联合TREM2靶向干预（如抑制性肽或抗体），有望削弱Treg介导的免疫抑制，提高疗效。此前已有研究显示TREM2抗体联合PD-1抑制剂可增强T细胞浸润；本研究则把这一逻辑扩展到了化疗和EGFR-TKI场景。

当然，作者也谨慎指出：人类TMA和小鼠模型中的相关性系数较温和（r约0.2–0.25），反映了TME的高度异质性；CCL5/CCL22轴是治疗诱导的，并非基线主要通路。未来仍需在更大队列、尤其是接受奥希替尼或化疗后的患者样本中验证，并探索TREM2抑制剂与现有方案联用的最佳时机与安全性。

论文信息：TREM2+ macrophages mediate anticancer therapy-induced immune evasion in lung adenocarcinoma via the CCL5/CCL22-Treg axis. Frontiers in Immunology (IF 7.0).

本文图片转载自 PMC 开放获取全文，仅供学习参考，请以原文为准。

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