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Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer 

Running Title: Distinct microenvironments co-evolve with lung tumours

Katey S. S. Enfield1,*, Emma Colliver1,*, Claudia Lee1,*, Alastair Magness1,*, David A. Moore1,2,3, Monica Sivakumar3, Kristiana Grigoriadis1,2,4, Oriol Pich1, Takahiro Karasaki1,2,5, Philip S. Hobson6, Dina Levi6, Selvaraju Veeriah2, Clare Puttick1,2,4, Emma L. Nye7, Mary Green7, Krijn K. Dijkstra1,8,9, Masako Shimato1, Ayse U. Akarca3, Teresa Marafioti3, Roberto Salgado10,11, Allan Hackshaw12, TRACERx consortium, Mariam Jamal-Hanjani2,5,13, Febe van Maldegem14,15,16,17, Nicholas McGranahan2,4, Benjamin Glass18, Hanna Pulaski18, Eric Walk18, James L. Reading2,19,20, Sergio A. Quezada2,20, Crispin T. Hiley1,2, Julian Downward14,#, Erik Sahai21,#,†, Charles Swanton1,2,13,#,†, Mihaela Angelova1,† 

Cancer Discovery APRIL 06 2024

Abstract: Understanding the role of the tumour microenvironment (TME) in lung cancer is critical to improving patient outcome. We identified four histology-independent archetype TMEs in treatment-naive early-stage lung cancer using imaging mass cytometry in the TRACERx study (n=81 patients/198 samples/2.3million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterised by sparse lymphocytes and high tumour-associated neutrophil (TAN) infiltration, had tumour cells spatially separated from vasculature and exhibited low spatial intratumour heterogeneity. TAN-High LUSC had frequent PIK3CA mutations. TAN-High tumours harboured recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis.

摘要：了解肿瘤微环境(TME)在肺癌中的作用是改善患者预后的关键。在TRACERx研究中，使用成像质谱流式术(n=81名患者/198个样本/230万个细胞)，在初治早期肺癌中确定了四个独立于组织学的TME。在免疫热型肺腺癌中，T细胞和巨噬细胞的空间生态位随着克隆性新抗原负荷的增加而增加，而在免疫排除型鳞癌(LUSC)中则观察到血浆和B细胞的空间生态位的增加。低免疫型的TMEs与成纤维细胞对免疫渗透的屏障有关。第四中亚型，以稀疏淋巴细胞和高肿瘤相关中性粒细胞(TAN)浸润为特征，肿瘤细胞与脉管系统在空间上分离，肿瘤内空间异质性较低。TAN-High LUSC有频繁的PIK3CA突变。TAN-High肿瘤包含最近扩大和转移播种的亚克隆，并且无病生存时间较短，与分期无关。本研究描绘了免疫监测的基因组、免疫和物理障碍，并提示富含中性粒细胞的TMEs参与了转移。

Statement of significance: This study provides novel insights into the spatial organisation of the lung cancer TME in the context of tumour immunogenicity, tumour heterogeneity and cancer evolution. Pairing the tumour evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumour progression and metastasis with implications for patient outcome and treatment.

方法：这项研究在肿瘤免疫原性、肿瘤异质性和癌症进化的背景下为肺癌TME的空间组织提供了新的见解。将肿瘤进化史与空间分辨的TME联合分析，促使本研究提出了对患者预后和治疗有启示意义的肿瘤进展和转移的机械性假说。

目录

1. INTRODUCTION

2. Materials and Methods 

    2.1 Clinical samples

    2.2 Clinical data

    2.3 Imaging mass cytometry panel development 

    2.4 Tissue processing for immunofluorescence 

    2.5 Tissue processing for imaging mass cytometry

    2.6 TRACERx imaging mass cytometry data acquisition

    2.7 Spillover compensation

    2.8 Cell segmentation

    2.9 Cell phenotyping

    2.10 Cell subtype definitions

    2.11 Tissue segmentation of tumour nest and stroma 

    2.12 Pathology review and feature mask generation

    2.13 Identification of spatial cellular communities

    2.14 Spatial clustering

    2.15 Barrier score definition

    2.16 TME classes definition

    2.17 Spatial heterogeneity of TME classes and TAN-High tumours 

    2.18 Spatial heterogeneity of cell types and communities

    2.19 PD-L1 Immunohistochemistry of regional tumour blocks

    2.20 Immunohistochemistry validation of checkpoint molecule expression

    2.21  Tumour-Associated Neutrophil (TAN) scoring from H&E images in TRACERx

    2.22 RNAscope

    2.23 Neighbourhood analysis

    2.24 TRACERx 100 whole exome sequencing 

    2.25 TRACERx 100 RNA-sequencing

    2.26 Tumour mutational burden calculation 

    2.27 Driver mutation analyses

    2.28 Copy Number Analysis

    2.29 Class I/Antigen Presentation Machinery (APM) disruption 

    2.30 Whole genome doubling

    2.31 Neoantigen analysis 

    2.32 Differential gene expression, Gene Set Enrichment and GO analyses

    2.33 Recent subclonal expansion score

    2.34 Phylogenetic tree and clone map visualisation

    2.35 Survival analysis

    2.36 Granulocyte scoring from H&E images and survival analysis in TCGA

    2.37 Statistical analysis

    2.38 Code and Data Availability

3. Results

    3.1 Building an atlas of the early-stage non-small cell lung cancer microenvironment (Figure 1)

    3.2 Immune composition in tumour nests and surrounding stroma reveals four TME classes in NSCLC (Figure 2)

    3.3 Multicellular communities associate with neoantigen burden and intrinsic immune evasion (Figure 3)

    3.4 Peritumoral ɑSMA+ fibroblasts spatially separate CD8 T cells and tumour cells in immune low TMEs (Figure 3. f-g)

    3.5 Tumours infiltrated with neutrophils and sparse T cells are metabolically rewired and distant from vasculature (Figure 4)

    3.6 Gain-of-function mutations in phosphoinositide 3-kinase (PI3K) signalling implicated in neutrophil recruitment in LUSC tumours (Figure 5)

    3.7 Tumour-associated neutrophils infiltrate regions with expanded tumour subclones and predict poor clinical outcome in NSCLC (Figure 6)

4. DISCUSSION

— 图表汇总—

Figure 1. IMC workflow defines the single cell spatial landscape of the NSCLC tumour microenvironment. 

a, TRACERx 100 imaging mass cytometry (IMC) cohort. We developed and applied two IMC antibody panels, Pan-Immune and T cells & Stroma, to tissue microarrays (TMAs) from clinical samples collected at surgical resection (created with BioRender.com). 

b, Targets of antibodies described in this study. Bold text indicates targets detected in both IMC panels. 

c, IMC data was acquired from stained TMAs and processed to identify single cells and their phenotypes. 

d, 40,000um2 crops of IMC images representing the markers from (b) with corresponding cell types from the Pan-Immune panel, unless annotated with an asterisk for the T cells & Stroma panel only. 

e, A heatmap of the z-score normalised median intensities  of markers from the Pan-Immune panel across the identified cell subtypes. 

f, Proportion of major immune cell types identified in the Pan-Immune IMC dataset per TMA core, calculated over the total tissue area (illustrated as blue and gold domains), tumour/epithelial compartment (gold domain), or the stromal compartment (blue domain). In two normal cores, the epithelial cell signal reflected very thin cells, which were not resolved into an epithelial compartment. All data from these cores is represented by the stroma compartment. Cell types colour legend applies to panels d and f, where asterisks denote cell types identified in T cells & Stroma panel only. 

LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; NSCLC, non-small cell lung cancer; Other, other non-small cell lung cancer histologies; IMC, imaging mass cytometry. 

Figure 2. Four TME classes in NSCLC defined by immune composition in tumour nests and surrounding stroma. 

a, Tumour cores were classified into four TME classes, derived by clustering immune cell densities in the tumour nest and stroma. Only LUAD (n=65 cores, 35 tumours) and LUSC (n=48, 23 tumours) tumour cores are featured, and corresponding clinical annotations are displayed. Regional growth patterns are shown for LUAD: lepidic (low grade), acinar and papillary (mid grade), solid and cribriform (high grade). 

b, TME classifications displayed separately for LUAD and LUSC. Numbers indicate the number of cores with a given TME class for each histology subtype. The barplot shows the total expressed neoantigen count for all predicted HLA alleles in the range 0-269 for LUAD and 23-160 for LUSC, coloured by their clonal and subclonal status. Horizontal lines connect tumour cores from the same multi-region tumour (n=33 tumours). The annotation bars display tumour genomic features and PD-L1 tumour cell (TC) staining (SP142 immunohistochemistry (IHC)) for the corresponding tumour cores. 

c, Composite images and cell type maps of representative examples for each TME class. Crop insets are 82μm in diameter. 

d, A heatmap of T values derived from an LMEM of the major cell type density across TME classes, adjusted for histology subtype as a fixed effect and patient as a random effect. Significant relationships are indicated with an asterisk for p-values≤0.05. 

TIL, tumour-infiltrating lymphocyte; MΦ, macrophage; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; NSCLC, non-small cell lung cancer; TME, tumour microenvironment; TMB, tumour mutation burden; muts/Mb, mutations per megabase; panCK, pancytokeratin; LMEM, linear mixed effects model. 

Figure 3. Spatial features associated with neoantigen burden and immune low TMEs. 

a, Correlation of densities of spatial cellular communities and the burden of expressed clonal, subclonal and total neoantigens predicted to bind intact HLA alleles, after accounting for HLA LOH, in LUAD (n=31, 51 tumour cores) and LUSC (n=17, 37 tumour cores). Bar plot shows the median neoantigen burden with whiskers extending to the 75th percentile. 

b, Comparison of the densities of spatial cellular communities in a given TME class compared to all other TME classes combined. LUAD: n=21 TS:TIL+MΦ High cores, n=20 T:TIL+MΦ Excluded cores, n=13 TS:Immune Low cores, n=11 TS:Neutrophil High cores. LUSC: n=13 TS:TIL+MΦ High cores, n=12 T:TIL+MΦ Excluded cores, n=8 TS:Immune Low cores, n=15 TS:Neutrophil High cores. Box sizes in a, b correspond to T values. 

c, Community and cell subtype maps from a LUAD tumour core with a high burden of expressed clonal neoantigens and high densities of C2:T cell enriched and C6:Macrophage & T cells communities. 

d, Community and cell subtype maps from a LUSC tumour core with a high burden of expressed clonal neoantigens and high densities of community C9:B cells & plasma cells. Single cells in c, d are coloured by community according to the colour legend below panel d or cell subtype as indicated. Scale bars represent 200μm. The middle panel is an enlargement of the area highlighted with a white box in the left panel with matched cell subtypes shown in the right panel. 

e, Schematic of ɑSMA+ fibroblast barrier score calculation. The barrier score measures the degree of spatial interpositioning of tumour cell- adjacent ɑSMA+ fibroblasts between CD8 T cells and their nearest tumour cell(s) in a tissue core. In the lower half of the schematic, three nearest tumour cells are defined for the green CD8 T cell, all six hops away. Tumour cell-adjacent ɑSMA+ fibroblasts are found on two of these three paths from CD8 T cell to tumour cell, resulting in a barrier score of ⅔. 

f, Boxplot comparing the ɑSMA+ fibroblast barrier scores in a given TME class compared to all other TME classes combined in LUAD (n=36, 57 tumour cores) and LUSC (n=22, 45 tumour cores). Boxplots show median and lower and upper quartile values, and whiskers extend up to 1.5*IQR above and below the quartiles.

g, Representative IMC images and cell type maps from LUAD and LUSC tumour cores classified as TS:Immune Low with a high barrier score. Scale bars represent 200μm. 

P-values in a, b, f and T values in a, b were calculated in a linear mixed effects model with patient as a random effect, using smoking status as a fixed effect in a with a p-value<0.05 considered significant. LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; panCK, pancytokeratin; TS, Tumour/Stroma; T, Tumour; TIL, tumour-infiltrating lymphocytes; MФ, macrophage; *:p<0.05, **:p<0.01.

Figure 4. Neutrophil infiltration in LUSC is associated with distinct metabolic and immunosuppressive phenotypes. 

a, Gene Ontology (GO) biological processes enriched among up-regulated genes in the TS:Neutrophil High TME class (n=10 cores) compared to other TME classes combined (n=28 cores) in LUSC (FDR<0.01, gene ratio>0.05). 

b, Gene-set enrichment analysis (GSEA) of hallmark gene sets compared between tumour cores from the Tumour/Stroma:Neutrophil High TME class and other TME classes combined, using the t- statistic derived from the limma-voom model on TMM-normalised gene expression.Significantly enriched pathways were coloured by type of pathway (FDR<0.05). 

c, Normalised enrichment score derived from single-sample GSEA visualised for TS:Neutrophil High and cores from other TME classes. The p-value is derived from GSEA analysis of LUSC as shown in a and adjusted for other hallmark pathways using the Benjamini- Hochberg method. 

d, Proportion of tumour cells assigned MCT4+ in TS:Neutrophil High tumour cores compared to tumour cores from other TME classes combined in LUSC. 

e, Spearman correlation coefficient and p-value comparing the proportion of MCT4+ and CAIX+ tumour cells in TS:Neutrophil High LUSC TMEs. 

f, Median distance between LUSC tumour cells to their nearest endothelial cell per core in TS:Neutrophil High TME class compared to all other TME classes combined. 

g, Single channel images and composite image alongside cell type map displaying tumour cells , neutrophils (MPO, yellow), endothelial cells (CD31, magenta) and regions of hypoxia (CAIX, cyan) and MCT4 (green) expression. 

Boxplots show median and lower and upper quartile values, and whiskers extend up to 1.5*IQR above and below the quartiles. P-values for d, f were calculated in a linear mixed effects model with patient as the random-effect covariate. 

LUSC, lung squamous cell carcinoma; TS, Tumour/Stroma; FDR, false discovery rate; TMM, trimmed mean of M-values; panCK, pancytokeratin; *:p<0.05; **:p<0.01; ***:p<0.001. 

Figure 5. Neutrophil-rich TMEs are associated with activating mutations in PI3K and tumour-intrinsic CXCL8 upregulation. 

a, Representative crops of tumour-level H&E images with low TAN scores in the tumour nest and stroma (left) and high TAN scores in the tumour nest and stroma (right), inferred as the proportion of the neutrophil area in tumour/stroma from the total tumour/stroma tissue area. Scale bar length 50µm, 400x magnification. 

b, Neutrophil cell density as defined by IMC compared between region-level TAN-Low versus TAN-High tumour cores based on H&E scores in LUAD and LUSC. 

c-d, Proportion of tumour cores with (mut) and without (wt) PIK3CA driver mutations compared between TS:Neutrophil High versus other TME classes combined (c) and region-level TAN-High versus TAN-Low cores (d) in LUSC. P-values were derived from a Chi-square test. 

e, Neutrophil cell density by PIK3CA mutation status, points coloured by TME class assignment. 

f, g, TMM expression values for CXCL8 compared by PIK3CA mutation status (f) and between TME classes (g) in LUSC. 

h, Immunofluorescence images of CXCL8 RNAscope multiplexed with antibody staining of pancytokeratin (panCK) or MPO in a LUSC tumour region with a TS:Neutrophil High TME and subclonal PIK3CA mutation, and a LUSC patient with multiple TAN-High tumour regions and a clonal PIK3CA mutation. panCK and MPO examples for CRUK0075:R2 illustrate the same region of interest, while different regions of interest are shown for CRUK0468:R6. Scale bar represents 100µm. 

P-values for b, e were calculated in a linear mixed effects model with patient as the random-effect covariate. P-values in f,g were derived from a limma-voom differential expression analysis correcting for multiple regions per tumour. ·:p<0.1, *:p<0.05, **:p<0.01, ***:p<0.001; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; TMM, trimmed mean of M-values; TS, Tumour/Stroma; TIL, tumour-infiltrating lymphocyte; MΦ, macrophage; TAN, tumour-associated neutrophils; H&E, haematoxylin and eosin; mt, mutant; wt, wild type. 

Figure 6. Neutrophil infiltration is associated with recent subclonal expansion and poorer disease-free survival. 

a, Comparison of neutrophil cell density in primary tumours with metastasis-seeding clones detectable at time of surgery or during follow up (metastasising tumours) to tumours from patients that were metastasis-free and recurrence-free for more than 3 years of follow-up time (control) in LUAD (n=28) and LUSC (n=15) within the TRACERx discovery cohort. Maximum neutrophil density taken for tumours with multiple tumour cores. P-values derived from one-tailed Wilcoxon test. 

b, Kaplan-Meier curves for disease-free survival (DFS) according to tumour-level tumour-associated neutrophil (TAN) score in the validation cohort (n=332 patients). P-value derived from univariate Cox model adjusted for histology. 

c, Multivariable Cox proportional hazard regression analysis of DFS using tumour-level TAN score and tumour-level necrosis evaluation from hematoxylin and eosin (H&E) images of diagnostic tumour blocks. 

d, Recent subclonal expansion score, measured as the maximum cancer cell fraction of subclones at the terminus of the phylogenetic tree, compared between TAN-High and TAN-Low tumour regions in LUAD and LUSC patients from the TRACERx 421 cohort. P-values were derived from a linear mixed effects model with patient as random effect.

e, Spatial ITH score of cell types and communities and ITH probabilities of TME classes in multi-region analysis (Pan-Immune n=41 tumours, 112 cores). ITH score was calculated as the average standard deviation of the cell/community density in multiple regions per tumour and z-score transformed. ITH score of ɑSMA+ cells was derived from T cells & Stroma panel (n=39 tumours, 105 cores). ITH probability was calculated as 1-probability of all regions having the same indicated TME class. 

f, Example phylogenetic tree depicting a Stage IIIA LUSC case with a clonal PIK3CA mutation, high TAN scores, and recent subclonal expansion, including in a region (R5) that seeded a lymph node (LN) metastasis (FLN, FFPE LN). The metastasis-seeding lineage is highlighted in orange. Tumour-level TAN scores and regional subclonal expansion (SubExp) scores are reported for primary tumour regions. The reported TAN score represents the maximum of the tumour nest and stroma scores. Each cluster in the phylogenetic tree is assigned a colour that is also represented in the region clone maps. The clone maps illustrate the prevalence of each clone within a region. 

g, IMC images shown for R5 and the LN metastasis. Scale bar represents 200µm.

h, Summary schematic of the link between tumours with a neutrophil enriched microenvironment with tumour progression. 

·:p<0.1, *:p<0.05; **:p<0.01; ***:p<0.001; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; ITH, intratumour heterogeneity. 

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