Peritumoural adipose tissue drives immune evasion in colorectal cancer via adipose–mesenchymal transformation

Figures

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  Fig. 1. Single-cell RNA profiling unveils tissue-specific immune landscape of tVAT. a, Study design illustrating the data analysis (left), and representative images of surgical specimens from patients with CRC (Stage, T4a; right). b, Uniform Manifold Approximation and Projection (UMAP) visualization showing major cell clusters from tumour, normal, tVAT and dVAT samples derived from patients with CRC. The cell types shown NK cells, DC, Mono (monocytes), Mφ (macrophages), Neutro (neutrophils), Mast (mast cells), Endo (endothelial cells) and Epi (epithelial cells). c, Heatmap showing the tissue preferences of 13 cell types by the Ratio of observed to expected (Ro/e) index, illustrating preferential cell type enrichment across different tissue regions. d, UMAP visualization of neighbourhoods (Nhoods) identified by Milo, highlighting the differentially abundant neighbourhoods between tVAT and dVAT. Each Nhood is represented as a node, coloured according to log2 fold change (FC) between tVAT (n = 12) and dVAT (n = 12). Non-differentially abundant neighbourhoods (false discovery rate ≥ 0.1) are displayed in white. Node sizes are proportional to the number of cells in each Nhood, with graph…

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  Fig. 2. Characteristic of lymphocytes in tVAT compared with dVAT. a, UMAP embedding showing subsets of CD4+ T cells, cytotoxic lymphocytes and B cells across all tissue samples from patients with CRC. b, Heatmap displaying the abundance of each lymphocyte subset across various tissues, illustrating their distribution patterns in the TME. c, Boxplot comparing the abundance of different subclusters of CD4+ T cells, cytotoxic lymphocytes and B cells between tVAT (n = 12) and dVAT (n = 12), analysed using the two-sided paired Wilcoxon test. d, Heatmap showing the fraction of TCR clonotype overlap among tissue samples and their respective tumours (left). A boxplot comparing TCR overlap between tVAT (n = 3) and dVAT (n = 3), analysed with a paired two-sided Student’s t-test (right). e, UMAP visualization of 13 tumour-specific CD8+ T cell subsets in dVAT and tVAT from patients with CRC (left). Stack plot showing the relative abundance of these 13 subsets in dVAT and tVAT (right). The data are presented as a box-and-whisker graph (bounds of box show the first to third quartile, bottom and top line show the minimum to maximum and central line shows the median) for c,d. Source data

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  Fig. 3. tVAT competes with tumour tissue for the infiltration lymphocytes. a, Experimental design of the PAT immune-competition model using C57BL/6J or BALB/c mice with the removal of either PAT or contralateral inguinal adipose tissue (control). b,c, Tumour weights of MC38-OVA (b) or CT26 (c) tumours at day 16 of the experiment in C57BL/6J or BALB/c mice (n = 5). d,e, Flow cytometry analysis of the infiltration of T cells, CD4+ T cells, CD8+ T cells, and tumour-specific CD8+ T cells in MC38-OVA (d) or CT26 (e) tumours, with and without removal of PAT (n = 5). To identify OVA-specific CD8+ T cells, H-2Kb tetramers were employed in the MC38-OVA tumour model that endogenously expresses ovalbumin. f, Representative images of MC38 tumours (left) and tumour weights (right) in C57BL/6J mice following removal of PAT or control, and treatment with ATS-GNP or saline (n = 5). g, Experimental design of the PAT immune-deficient model (BALB/c-Nude or NSG) with removal of PAT. h,i, Representative images of MC38 tumours (left) and tumour weights (right) at day 16 in C57BL/6 J, BALB/c-Nude (h), or NSG mice (i) (n = 6). j, Schematic representation of the strategy to detect CD45.1+ cells in MC38-OVA…

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  Fig. 4. tVAT recruits CXCR4⁺ immune cells through CXCL12 secretion. a, Cell–cell communication analysis based on ligand–receptor interactions (top six) between stromal cells and lymphocytes in tVAT (left) and a comparison between tVAT, dVAT and tumour (right). b, Marked CXCL12–CXCR4 interactions among CD8+ T cells, CD4+ T cells, B cells, plasma cells and stromal cell populations in tVAT, dVAT and tumour. The width of the lines represents the probability of communication. c, Violin plots showing the expression of CXCL12 (top) and CXCR4 (bottom) across all cell types in patients with CRC. d, Violin plots comparing the expression of CXCL12 in dVAT versus tVAT (top) and tumour versus tVAT (bottom) in patients with CRC, analysed using a two-sided Wilcoxon test. e, Experimental design for the PAT C57BL/6J mouse model treated with IgG or anti-CXCL12 antibody (left), and representative MC38 tumour images at day 16 of the experiment (right) (n = 5). f, Tumour growth (left) and tumour weights (right) of MC38 tumours at day 16 of the experiment in C57BL/6J mice (n = 5). g, Representative MC38 tumour images (left) and tumour growth (right) of experiments in control and Cxcl12fl/fl cKO mice (n = 6).…

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  Fig. 5. Tumours induce adipose mesenchymal transformation in tVAT. a, UMAP of all stromal cells in tVAT, dVAT, tumour and normal from patients with CRC, with ten clusters labelled by inferred cell types. Major lineages included ASCs, pACs, CAFs, pericytes (PCs) and mesothelial cells (Mesos). b, Heatmap displaying the distribution of eight stromal cell subtypes across different tissue types. c, UMAP of eight subsets of VAT-associated stromal cells in tVAT and dVAT from patients with CRC, including ASCs, pACs and adCAFs. d, Beeswarm plot showing the distribution and abundance of VAT-associated stromal cell types in Nhoods between tVAT and dVAT. e, Stack plot displaying the abundance of the eight VAT-associated stromal cell subsets in dVAT and tVAT. f, Heatmap showing the RNA expression of various marker genes in VAT-associated stromal cell types, including ASC/pAC markers, CAF markers, cytokines and stromal markers. g, Representative multiplex immunofluorescence images showing the presence of adCAFs in tVAT samples from patients with CRC. Scale bar, 10 μm. DAPI, 4,6-diamidino-2-phenylindole. h, Relative expression levels of multiple cytokines and protumoural factors in adCAF-enriched…

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  Fig. 6. Tumour-derived factors induce ASC to differentiate into adCAF. a, Cell trajectories (top) and cell abundance (bottom) of ASC-derived pAC and ASC-derived adCAFs inferred by Monocle3, with cell trajectories in dVAT (left) and tVAT (right). The pseudotime colour code is shown in the right box. b, Dynamic changes in the expression of several marker genes over time in dVAT (left) and tVAT (right) by monocle3 pseudotime. c, Pseudotime (top) and cell trajectories (bottom) of ASC-derived pAC and ASC-derived adCAFs inferred by Monocle2. The pseudotime colour code is shown in the right box. d, Cell trajectories in dVAT (top) and tVAT (bottom) of ASC-derived pAC and ASC-derived adCAFs inferred by Monocle2. e, Dynamic changes in the expression of several marker genes over time in pAC markers (left) and adCAF markers (right) by monocle2 pseudotime. f, Dot plot showing the inferred differential transcription factor (TF) activities in ASC, pAC and adCAF. g, Dynamic changes in inferred activities and RNA expression levels of TFs in ASC, pAC, and adCAF. h, Representative images of the morphology of mASCs treated with MC38 tumour-derived CM from MC38-derived tumour tissues for 72 h. Scale bar, 100…

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  Fig. 7. Clinical significance of the tumour-adipose tissue crosstalk. a, Experimental design for constructing Control and MdkDTR cKO mice bearing MC38 tumours near PAT, followed by αPD-1 therapy. b,c, Representative MC38 tumour images (b), tumour weights (c left) and tumour growth (c right) in control and MdkDTR cKO mice treated with IgG or anti-PD-1 (n = 6). d, Flow cytometry analysis of the infiltration of immunocytes, including T cells, CD4+ T cells, CD8+ T cells, and tumour-specific CD8+ T cells, CXCR4+ immunocytes, CXCR4+ T cell, CXCR4+ CD4+ T cell, CXCR4+ CD8+ T cell and CXCR4+ tumour-specific T cell in MC38-OVA tumours from the four treatment groups (n = 6). e,f, Representative MC38 tumour images (e) and tumour weights (f) of the experiment in mice treated with anti-CXCL12 and/or anti-PD-1 (n = 5). g, Representative MRI image of CRC tumour and corresponding tVAT area region of CR and non-CR patients pre- and post-immuno-chemoradiotherapy. The yellow area represents the tVAT area, whereas the red area denotes the tumour region. Note that the mass visible in the intestinal lumen (top right) is faecal material. h, Pre-treatment tVAT area difference based on 3D Slicer between CR (n =…

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  Extended Data Fig. 1. Single-cell RNA profiling unveils tissue-specific immune landscape of tVAT. a. UMAP plots showing the expression patterns of marker genes used to define all cell types within the TME. b. Expression of representative signature genes across major clusters, highlighting key molecular markers for each cell type. c.Enriched pathways based on differentially expressed genes between tVAT and dVAT, providing insight into the functional differences between these tissue types. A two-sided hypergeometric test was used to calculate p values and Benjamini-Hochberg method was used to adjusted the p values. d. Representative images of H&E staining and immunofluorescence (IF) staining for lymphocytes in tVAT and dVAT sections from CRC patients (n = 3 patient samples per group). Scale bar = 200 μm. e. Representative images of multiplex immunohistochemistry (mIHC) staining showing various maturation states of tertiary lymphoid structures (TLSs) in tVAT sections from CRC patients (n = 4 patient samples). Scale bars = 500 μm (overall image) or 200 μm (insets). Source data

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  Extended Data Fig. 2. Characteristic of lymphocytes in tVAT compared with dVAT. a. Dot plot showing RNA expression of marker genes used to define clusters of CD4+ T cells, CD8+ T/NK cells, and B cells. b. Longitudinal tracking of the top 20 most expanded TCR clones in dVAT, Tumour, and tVAT for each patient. Each stratum represents a unique TCR clonotype, highlighted by a different colour. Coloured bands between columns represent shared clones across time points. c. Boxplot comparing TCR clonal diversity between tVAT (n = 3) and dVAT (n = 3), analysed using a two-sided paired Student’s t-test. d. Longitudinal tracking of the top 20 most expanded BCR clones in dVAT, Tumour, and tVAT for each patient. e. Boxplot comparing BCR clonal diversity between tVAT (n = 3) and dVAT (n = 3), analysed using a two-sided paired Student’s t-test. f. Heatmap showing the fraction of BCR clonotype overlap among tissue samples and their respective tumours. g. Boxplot comparing BCR overlap between tVAT (n = 3) and dVAT (n = 3) with their respective tumours, analysed using a two-sided paired Student’s t-test. The data are presented as a box-and-whisker graph (bounds of box: first to third quartile, bottom and top line:…

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  Extended Data Fig. 3. tVAT competes with tumour tissue for the infiltration lymphocytes. a. Representative images of MC38-OVA (left) and tumour growth (right) in C57BL/6J mice (n = 5). b. Representative images of CT26 tumours (left) and tumour growth (right) in BALB/c mice (n = 5). c. Schematic diagram illustrating the working principle of ATS-GNP adipocytolysis. ATS-GNP, containing a CaCO3 core, is receptor-mediated for endocytosis. Upon reaching the acidic environment, ATS-GNP releases CO2 gas, disrupting the adipose cell membrane. d. Tumour growth of MC38 tumours in C57BL/6J, BALB/c-Nude (left), and NSG (right) mice (n = 5). e. Representative images of E0771 tumours at day 16 of the experiment in C57BL/6J mice following removal of PAT (n = 5). f. Tumour weights of E0771 tumours at day 16 in C57BL/6J mice with the removal of PAT (n = 5). g. Representative flow cytometry plots of CD45+ cells gated on live cells in MC38-OVA tumours. h. Violin plots showing the expression of CXCR7 across all cell types in CRC patients, analysed using the Kruskal-Wallis test. i. Editing strategy for constructing Cxcl12fl/fl cKO mouse. j. Experimental design for constructing Control and Cxcl12fl/fl cKO mice bearing…

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  Extended Data Fig. 4. Cross-tissue diversity of stromal cells in VATs, PT and PN. a. Top-ranked markers to define the stromal cell subclusters. b. Cross-tissue diversity (top) and abundance (bottom) of stromal cells in VATs, Tumour and Normal. c. Box plot to compare the abundance of stromal cells in VATs (n = 24), Tumour (n = 70) and Normal (n = 12). P-values were calculated using a two-side Wilcoxon test. The data are presented as a box-and-whisker graph (bounds of box: first to third quartile, bottom and top line: minimum to maximum, central line: median). d. Relative expression levels of CAF-associated markers (FAP and COL1A1) and adipose markers (APOE and APOD) in CAFs versus adCAFs from peritumoral adipose tissue of CRC patients, analysed using the two-sided Wilcoxon test. Source data

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  Extended Data Fig. 5. Tumour induces adipose mesenchymal transformation in tVAT. a. UMAP plot of VAT-associated stromal cells in tVAT and dVAT from CRC patients. The 8 clusters, labelled by inferred cell types, are denoted by colour. b. Dot plot showing RNA expression of marker genes used to define pAC, adCAF, and APC subclusters. Circle size represents the log-normalized P-value, while colour intensity indicates the log-transformed mean expression of marker genes. c. Sorting strategy for isolating adCAFs from mouse PAT by flow cytometry. d. RNA sequencing analysis of adCAF markers in sorted adCAF-enriched stromal cells and non-adCAF stromal cells (n = 4). Statistical significance was assessed using a two-sided, unpaired Student’s t-test. e. RNA sequencing analysis of adipogenesis markers in sorted adCAF-enriched stromal cells and non-adCAF stromal cells (n = 4). Statistical significance was assessed using a two-sided, unpaired Student’s t-test. f. Representative images of the morphology of sorted adCAF-enriched stromal cells and non-adCAF stromal cells. Scale bar = 500 μm. g. Cross-tissue interactions analysis based on ligand-receptor pairs between adCAFs and tumour cells (left) and a comparison…