Spatial immunophenotyping of the tumour microenvironment in non-small cell lung cancer

被引:23
作者
Backman, Max [1 ]
Strell, Carina [1 ,2 ]
Lindberg, Amanda [1 ]
Mattsson, Johanna S. M. [1 ]
Elfving, Hedvig [1 ]
Brunnstrom, Hans [3 ]
O'Reilly, Aine [4 ]
Bosic, Martina [1 ,3 ,5 ]
Gulyas, Miklos [1 ]
Isaksson, Johan [1 ,6 ]
Botling, Johan [1 ]
Karre, Klas [7 ]
Jirstrom, Karin [8 ]
Lamberg, Kristina [9 ]
Ponten, Fredrik [1 ]
Leandersson, Karin [10 ]
Mezheyeuski, Artur [1 ,11 ]
Micke, Patrick [1 ]
机构
[1] Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden
[2] Univ Bergen, Dept Clin Med, Ctr Canc Biomarkers CCBIO, Bergen, Norway
[3] Lund Univ, Dept Clin Sci Lund, Div Pathol, Lund, Sweden
[4] Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden
[5] Univ Belgrade, Fac Med, Belgrade, Serbia
[6] Gavle Cent Hosp, Dept Resp Med, Gavle, Sweden
[7] Karolinska Inst, Dept Microbiol Cell & Tumor Biol, Stockholm, Sweden
[8] Lund Univ, Dept Clin Sci Lund, Div Oncol & Therapeut Pathol, Lund, Sweden
[9] Akadem Sjukhuset, Dept Resp Med, Uppsala, Sweden
[10] Lund Univ, Skanes Univ Hosp, Dept Translat Med, Malmo, Sweden
[11] Vall Hebron Inst Oncol, Mol Oncol Grp, Barcelona, Spain
关键词
Immune cell infiltration; Multiplex imaging; Checkpoint therapy; Tumour microenvironment; Lung cancer; NSCLC; REGULATORY T-CELLS; TISSUE MICROARRAY; PROGNOSTIC IMPACT; PATTERNS; EFFICACY; DENSITY; NSCLC;
D O I
10.1016/j.ejca.2023.02.012
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Introduction: Immune cells in the tumour microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterise the spatial im-mune phenotypes in the mutational and clinicopathological background of non-small cell lung cancer (NSCLC).Methods: 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 thorn myeloid cells (CD163), M2 macrophages (M2), immature dendritic cells (iDCs), mature dendritic cells (mDCs) and plasmacytoid dendritic cells (pDCs).Results: 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.Conclusion: 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. 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页码:40 / 52
页数:13
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