背景:肿瘤微环境中的免疫细胞与预后和治疗反应相关。我们旨在全面表征非小细胞肺癌(NSCLC)突变和临床病理背景下的空间免疫表型。
方法:我们建立了多重荧光成像管道,以空间定量359例NSCLC病例中的13个免疫细胞亚群:CD4效应细胞(CD4-Eff),CD4调节性细胞(CD4-Treg),CD8效应细胞(CD8-Eff),CD8调节性细胞(CD8-Treg),B细胞,自然杀伤细胞,自然杀伤T细胞,M1巨噬细胞(M1),CD163+髓样细胞(CD163),M2巨噬细胞(M2),未成熟树突状细胞(iDC),成熟树突状细胞(mDC)和浆细胞样树突状细胞(pDC)。
结果:CD4-Eff细胞,CD8-Eff细胞和M1巨噬细胞是侵入肿瘤细胞区室的最丰富的免疫细胞,在聚类分析中表明患者组预后良好。同样,淋巴细胞亚群的单一密度(CD4-Eff,CD4-Treg,CD8-Treg,B细胞和pDC)与更长的生存期独立相关。然而,当这些免疫细胞位于CD8-Treg细胞附近时,有利的影响减弱。在多变量Cox回归模型中,包括细胞密度和距离,M1和CD163细胞的密度和细胞之间的距离(CD8-Treg-B细胞,CD8-Eff-癌细胞和B细胞-CD4-Treg)显示出积极的预后影响,而短的M2-M1距离在预后上是不利的。
结论:我们提出了NSCLC原位免疫细胞景观的独特空间分布作为公开可用的数据集。细胞密度和细胞距离独立地有助于临床结果的预后信息,这表明空间信息对于诊断用途至关重要。
Immune cells in the tumour microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterise the spatial immune phenotypes in the mutational and clinicopathological background of non-small cell lung cancer (NSCLC).
We established a multiplexed fluorescence imaging pipeline to spatially quantify 13 immune cell subsets in 359 NSCLC cases: CD4 effector cells (CD4-Eff), CD4 regulatory cells (CD4-Treg), CD8 effector cells (CD8-Eff), CD8 regulatory cells (CD8-Treg), B-cells, natural killer cells, natural killer T-cells, M1 macrophages (M1), CD163+ myeloid cells (CD163), M2 macrophages (M2), immature dendritic cells (iDCs), mature dendritic cells (mDCs) and plasmacytoid dendritic cells (pDCs).
CD4-Eff cells, CD8-Eff cells and M1 macrophages were the most abundant immune cells invading the tumour cell compartment and indicated a patient group with a favourable prognosis in the cluster analysis. Likewise, single densities of lymphocytic subsets (CD4-Eff, CD4-Treg, CD8-Treg, B-cells and pDCs) were independently associated with longer survival. However, when these immune cells were located close to CD8-Treg cells, the favourable impact was attenuated. In the multivariable Cox regression model, including cell densities and distances, the densities of M1 and CD163 cells and distances between cells (CD8-Treg-B-cells, CD8-Eff-cancer cells and B-cells-CD4-Treg) demonstrated positive prognostic impact, whereas short M2-M1 distances were prognostically unfavourable.
We present a unique spatial profile of the in situ immune cell landscape in NSCLC as a publicly available data set. Cell densities and cell distances contribute independently to prognostic information on clinical outcomes, suggesting that spatial information is crucial for diagnostic use.