Metabolism archetype cancer cells induce protumor TREM2+ macrophages via oxLDL-mediated metabolic interplay in hepatocellular carcinoma

Abstract

The functional programs adopted by cancer cells and their impact on the tumor microenvironment are complex and remain unclear. Here, we identify three distinct single-cell archetypes (i.e. metabolism, stemness and inflammation) in hepatocellular carcinoma (HCC) cells, each exhibiting unique spatial distribution. Further analysis shows an immune-suppressive niche populated by metabolism archetype cancer cells and TREM2-positive tumor-associated macrophages (TREM2⁺ TAMs), which exacerbates immune exclusion and compromises patient outcomes. Mechanistically, we demonstrate that the upregulated squalene epoxidase (SQLE) expression in metabolism archetype cancer cells facilitates the generation of oxidized LDL (oxLDL). OxLDL induces TREM2⁺ TAM polarization through the TREM2-SYK-CEBPα axis, enabling these TAMs to promote cancer cell invasion, resistance to effector cytokines and CD8⁺ T cell dysfunction. Importantly, cancer cell-intrinsic SQLE and TREM2⁺ TAMs are associated with inferior immunotherapy response in human and mouse HCC. Our results highlight an oxLDL-mediated metabolic interplay between cancer cells and TREM2⁺ TAMs, offering a promising therapeutic avenue for HCC immunotherapies.

Fig. 1. Three functional archetypes of HCC cancer cells.

A Schematic diagram of this study design. B UMAP (uniform manifold approximation and projection) of main cell types in human primary HCC sc & snRNA-seq dataset (left) and mouse HCC scRNA-seq dataset (right). C Hierarchical clustering of pairwise similarities between NMF programs identified across all cancer cells from snRNA-seq samples. D Heatmap displays the Pearson correlation coefficients calculated between the single-cell gene signature scores of NMF metaprograms. E Heatmap showing the expression of NMF metaprograms. Cells were ordered by the P2 score. F PCA of 1000 random-sampled cancer cells colored by functional archetypes (left). The normalized, scaled expression of indicated marker genes for each functional archetype (right). G, J HE staining and predicted abundance of indicated cancer cell archetypes in spatial sections of HCC-2 (G) and HCC-3 (J). Data are representative of n = 4 spatial transcriptomic slides. Scale bar, 1 mm. H, K Volcano plot displays the DEGs between indicated spatial regions in HCC-2 (H) and HCC-3 (K). I, L GO analysis of the DEGs of indicated spatial regions in HCC-2 (I) and HCC-3 (L). M Immunofluorescence staining of CD44, APOE, SAA1/2, and PanCK on HCC sections. For each field, representative cells are indicated by arrows, including CD44⁺PanCK⁺ cells (red), APOE⁺PanCK⁺ cells (yellow), and SAA1/2⁺PanCK⁺ cells (green). Scale bar, 50 μm. Images are representative of n = 3 HCC samples. Schematic in A was created in BioRender. Chu, T. (2025) https://BioRender.com/r2v4jgs.

Fig. 2. Identification of an immuno-inhibitory niche supported by metabolism archetype cancer cells and TREM2⁺TAMs.

A UMAP of main cell types and their subtypes recovered from the human sc & snRNA-seq dataset. B, C Seurat-predicted cell abundance of indicated cell subtypes on spatial sections of HCC-2 (B, left) and HCC-3 (C, left). Visualization of cell type co-localization by Pearson correlations in HCC-2 (B, right) and HCC-3 (C, right). Positive correlation values indicate spatial co-localization, while negative values represent spatial segregation. Scale bar, 1 mm. D Dotplot displays the mean estimated cell abundance (x-axis) and spatial correlation coefficients with metabolism archetype cancer cells (y-axis) of indicated cell clusters across the tumor region of four spatial transcriptomic slices in this study (HCC-1, HCC-2, HCC-3, and HCC-4). Positive correlation values indicate spatial co-localization, while negative values represent spatial segregation. E Cell2location-predicted cell abundance of indicated cell subtypes on spatial sections of HCC-2 (upper) and HCC-3 (lower). Scale bar, 1 mm. F Cell abundance for CD8⁺Tem, TREM2⁺TAM, and metabolism archetype cancer cells in HCC-2 (upper) and HCC-3 (lower), shown as overlaid color intensity over the hematoxylin and eosin (H&E) images. White dotted lines indicated the niche formed by metabolism archetype cancer cells and TREM2⁺TAMs that restricted CD8⁺Tem infiltration. Data are representative of n = 4 spatial transcriptomic slides. Scale bar, 1 mm. G Immunofluorescence staining of PanCK, APOE, CD68, and TREM2 on HCC tissue sections. Two images represented the colocalization region and non-colocalization region of metabolism archetype cancer cells and TREM2⁺TAMs, respectively. White arrows indicated the close proximity between metabolism archetype cancer cells (APOE⁺PanCK⁺) and TREM2⁺TAMs (CD68⁺TREM2⁺). Scale bar, 100 μm. Images are representative of n = 3 HCC samples.

Fig. 3. TREM2⁺TAM drives HCC progression and immunotherapy resistance via SPP1-mediated dual action on CD8⁺T cells and cancer cells.

A UMAP of the Scissor-selected cells (left). Barplot shows the distribution of Scissor⁺ cells across different myeloid populations and conditions (right). B Forestplot shows the hazard ratios and 95% confidence intervals for different myeloid cluster signatures and clinical information according to a multivariable Cox model in the TCGA-LIHC cohort (n = 353 patients). Squares represent the hazard ratios, and the horizontal bars extend from the lower limits to the upper limits of the 95% confidence intervals of the estimates of the hazard ratios. C Dotplot displays the DEGs between Scissor⁺ cells and all other cells. D Dotplot displays the expression correlation of SPP1 with other genes in myeloid cells (left). Heatmap shows the expression correlation of indicated genes with SPP1 in myeloid cells from adjacent non-tumor (ANT) and tumor samples (right). E Representative images and quantification of TREM2, SPP1, and CD68 immunofluorescence staining on human HCC sections. Representative cells that denote the co-upregulation of TREM2 and SPP1 in CD68⁺ TAMs are circled by a dotted line. Scale bar, 50 μm. F Kaplan–Meier survival analysis of HCC patients from the TCGA-LIHC cohort categorized into groups based on normalized TREM2 and SPP1 expression. The cutpoints for patient grouping were calculated by the surv_cutpoint function from the survminer R package. G Barplot shows the mean expression of SPP1 across different myeloid cell populations (upper) and in TAMs from ICB-R and ICB-NR HCC samples (lower). H Dotplot shows the expression of SPP1 ligands in CD8⁺T cells (above) or cancer cells (below) from pre-ICB, ICB-NR, and ICB-R HCC scRNA-seq samples. I Schematic of the interaction between TREM2⁺TAMs and CD8⁺T cells or cancer cells in immunotherapy-resistant HCC. J Heatmap shows the relative expression of indicated genes in isolated TREM2⁺/TREM2⁻ TAMs. K Flow cytometry of IFNγ expression in CD8⁺T cells co-cultured with human HCC-isolated TREM2^-TAMs or TREM2⁺TAMs ± SPP1 antibody (1 μg/mL). CD8⁺T cells were isolated from human PBMC and then activated with anti-CD3/CD28 + IL-2 (50 U/mL) before co-culture assays. L Violin plots display the expression of IFNG and TNF in CD8⁺T cells from ICB-NR or ICB-R scRNA-seq samples, with two-tailed Wilcoxon-test statistics. M Dotplot shows the relative expression of IFNG and TNF in CD8⁺T cell clusters. N Tissue preference of CD8⁺T cell clusters, revealed by odds ratio (OR) value. O Relative cell viability (mean of n = 3 biological replicates) for Hep3B cells treated with a half-log dilution series of TNF (2.5–250 ng/mL) and IFNγ (1–100 ng/mL), cocultured with human HCC-isolated TREM2^-TAMs or TREM2⁺TAMs ± SPP1 antibody (1 μg/mL). P Relative cell viability of Hep3B cells treated with mock, SPP1 (50 ng/mL), integrin inhibitor TFA (100 μM), TNF (250 ng/mL) plus IFNγ (100 ng/mL) (TNF/IFNγ), TNF/IFNγ plus SPP1, or TNF/IFNγ plus SPP1 plus TFA (100 μM) for 24 h. Q Relative cell viability for patient-derived HCC organoid with indicated treatment. Data represent the mean ± SD, n = 5 biological replicates in (P), n = 6 biological replicates in (K, Q). Statistical significance was determined by two-tailed Wald test (B), two-tailed unpaired t test (K, P, Q), two-tailed Wilcoxon signed rank test (L), and log rank test (F). Schematic in I was created in BioRender. Chu, T. (2025) https://BioRender.com/r2v4jgs. Source data are provided as a Source Data file.

Fig. 4. TREM2 + TAMs exhibit elevated lipid metabolism and are induced by oxLDL produced from metabolism archetype cancer cells.

A Gene set enrichment analysis (GSEA) on genes ranked by log2 fold change between TREM2⁺TAMs and other TAM clusters. B Dotplot shows the expression of selected genes belonging to the indicated biological process in TAM subsets. C Flow cytometry of TREM2 and SPP1 expression in macrophages treated with TIF ± Na₂CO₃ or lipid removal reagent (Cleanascite). D Bodipy, TREM2, and SPP1 staining on HCC frozen sections. Scale bar, 500 μm (left), 100 μm (right). Images are representative of n = 2 HCC samples. E Heatmap summarizing TREM2, SPP1 expression (mean of n = 3 biological replicates, upper) and supernatant SPP1 concentrations (lower) in BMDMs or TAMs treated with indicated lipids. F Relative TREM2, SPP1 mRNA (left), protein expression (middle), and supernatant SPP1 concentration (right) in BMDM or TAM treated with vehicle or oxLDL (25 or 50 μg/mL). G Transwell migration and evasion assays of Hepa1–6 co-cultured with BMDM or TAM treated with vehicle, LDL (50 μg/mL) or oxLDL (50 μg/mL) ± SPP1 antibody (1 μg/mL). Scale bar, 100 μm. Quantification was performed with n = 5 random fields. H Flow cytometry of IFNγ expression in CD8⁺T cells co-cultured with BMDM or TAM treated with vehicle, LDL, or oxLDL ± SPP1 antibody. I, K Concentrations of indicated lipoproteins in human plasma (n = 16 patients) or human TIF (n = 12 patients) (I), and in mouse plasma or mouse TIF (n = 12 mice) (K). J, L Correlation between TIF oxLDL level and TREM2⁺SPP1⁺TAM proportion in human HCC tumors (n = 12) (J) and mouse HCC tumors (n = 12) (L). M PCA of the transcriptome of BMDM (n = 3 biological replicates) or TAM treated with vehicle (n = 3 biological replicates), LDL (n = 2 biological replicates), or oxLDL (n = 3 biological replicates). N GSEA of genes upregulated by oxLDL (log2 fold change > 1), on genes ranked by log2 fold change between TAM subsets versus other TAMs. Statistical P value was determined from 10,000 permutations. O Schematic of co-injection experiments. P Tumor volume of mock/oxLDL-treated TAM co-injection tumors (n = 6 mice). Q, R Flow cytometry of TREM2, SPP1 expression in TAMs (Q) and IFNγ expression in tumor-infiltrating CD8⁺T cells (R) (n = 6 mice). S Schematic of the sample collection and analysis workflow. T Heatmap depicts the BayesPrism-inferred fractions of indicated cancer cell subpopulations in 13 HCC samples. Hierarchical clustering shows that these 13 HCC samples can be classified into metabolism (8 samples) and stemness (5 samples) subtypes. U OxLDL concentrations (mean of n = 3 experimental replicates) in the TIF isolated from metabolism (n = 8) and stemness (n = 5) subtype HCC samples. V Flow cytometry of TREM2 and SPP1 expression in macrophages (mean of n = 3 biological replicates) treated with TIF (1:10) isolated from metabolism (n = 8) and stemness subtype (n = 5) HCC samples. Data represent the mean ± SD, n = 3 biological replicates in (C, E, F, H). Statistical significance was determined by a two-tailed unpaired t-test (C, E–I, K, P–R, U, V) and a two-tailed one-sample t-test (J, L). Schematics in O and S were created in BioRender. Chu, T. (2025) https://BioRender.com/r2v4jgs. Source data are provided as a Source Data file.

Fig. 5. OxLDL induces TREM2 and SPP1 expression via the TREM2/SYK/CEBPα axis in TAMs.

A UMAP projection (upper) and barplot (lower) show Spp1 expression in TAMs from Trem2-wildtype or Trem2-KO tumors, with two-tailed Wilcoxon-test statistics. B Relative SPP1 protein (left, representative of n = 3 biological replicates), mRNA (middle), and supernatant (right) expression in wildtype or Trem2^−/− TAMs treated with oxLDL (50 μg/mL). C Flow cytometry of IFNγ in CD8⁺T cells co-cultured with wildtype or Trem2^−/− TAMs treated with oxLDL. D Transwell migration and evasion assays of Hepa1–6 co-cultured with wildtype or Trem2^−/− TAMs treated with oxLDL. Scale bar, 100 μm. Quantification was performed with n = 5 random fields. E–G Western blot (WB) and flow cytometry of pSYK expression in BMDM or TAM treated with vehicle, LDL (50 μg/mL) or oxLDL (E), in wildtype or Trem2^−/− TAMs treated with oxLDL (F), and in TAMs isolated from wildtype or Trem2^−/− tumors (G). H Protein (left, representative of n = 3 biological replicates) and supernatant (right) expression of SPP1 in TAMs treated with oxLDL ± R406 (5 μM) or Piceatannol (40 μM). I Venn diagram shows the overlapping activated TFs in human and mouse TREM2⁺TAM (left). Regulon ranks of top enriched TFs in human and mouse TREM2⁺TAM (right). J Heatmap summarizing the qPCR results in TAMs treated with vehicle or oxLDL with indicated TF KD (mean of n = 3 biological replicates). K, L WB of CEBPα levels in BMDM or TAM treated with vehicle, LDL or oxLDL (K), in wildtype or Trem2^−/− TAMs treated with oxLDL (L, left), and in TAMs isolated from wildtype or Trem2^−/− tumors (L, right). M ChIP-qPCR assays of CEBPα binding at the Trem2 or Spp1 promoter (n = 3 experimental replicates). N Co-immunoprecipitation assays of DNMT3A and CEBPα interaction in TAMs treated with vehicle or oxLDL. O 5mC levels at the CpG-rich promoter regions of Trem2 and Spp1 were determined by BS-PCR in wildtype or Trem2^−/− TAMs treated with vehicle or oxLDL ± siCebpa. P Schematic of the co-injection experiments. Q Tumor volume of Hepa1-6 cells co-injected with shNC/shCebpa TAMs (n = 6 mice). R, S Flow cytometry of TREM2, SPP1 expression in TAMs (R) and IFNγ expression in tumor-infiltrating CD8⁺T cells (S) (n = 6 mice). T Schematic summarizing the mechanism of oxLDL inducing TREM2 and SPP1 expression in TAMs. WB results shown were representative of three independent experiments in (E–G, K, L, N). Data represent the mean ± SD, n = 3 biological replicates in (B, C, E–H). Statistical significance was determined by the Wilcoxon signed rank test (A) and two-tailed unpaired t test (B–H, M, Q–S). Schematics in P and T were created in BioRender. Chu, T. (2025) https://BioRender.com/r2v4jgs. Source data is provided as a Source Data file.

Fig. 6. Targeting SQLE enzyme enhances anti-tumor immunity by acting on the oxLDL-TREM2⁺TAM axis.

A Venn diagram shows the overlapping metabolism genes that are upregulated in the tumor and the metabolism archetype (left). Heatmap depicts prognostic significance of top genes in five primary HCC cohorts using an univariate Cox regression model (right). B Correlation between cancer cell SQLE expression and TREM2⁺TAM signatures of TAMs in snRNA-seq (n = 12, left) and public scRNA-seq dataset (n = 10, right). C Representative images showing the expression of SQLE, oxLDL, TREM2, SPP1, and CD68 in SQLE-positive and SQLE-negative tissue spots from HCC TMA. Representative cells that denote the presence of TREM2⁺SPP1⁺TAMs are indicated by arrowheads. Scale bar, 50 μm (left). Composition of oxLDL-high or oxLDL-low spots in SQLE-positive (n = 110) and SQLE-negative (n = 126) spots. Quantification of TREM2⁺SPP1⁺TAMs in SQLE-positive and SQLE-negative spots (right). D Violinplot shows SQLE expression in normal/malignant hepatocytes from indicated groups, with two-tailed Wilcoxon-test statistics. E Representative images showing SQLE expression in ICB-NR and ICB-R tumors. Scale bar, 100 μm (left). Quantification of SQLE fluorescence in the tumor region of ICB-NR (n = 6) and ICB-R (n = 4) tumors (right). F, G NADP⁺/NADPH ratio, ROS (F), lipid peroxidation levels (G) of shNC or shSqle cancer cells. H Supernatant oxLDL levels of shNC or shSqle cancer cells cultured with DMEM plus 10% mouse serum for 48 h. I Flow cytometry shows Dil-oxLDL uptake in shNC or shSqle cancer cells ± SSO (100 μM). J Schematic of the orthotopic models. K Tumor volume of shNC or shSqle tumors (n = 6 mice). L Concentration of oxLDL in TIF isolated from shNC or shSqle tumors (n = 6 mice). M, N Flow cytometry of TREM2, SPP1 expression in TAMs (M) and IFNγ expression in tumor-infiltrating CD8⁺T cells (N) (n = 6 mice). O Schematic of the orthotopic models and treatment. P Tumor volume of shNC or shSqle tumors treated with isotype or anti-PD1 (n = 6 mice). Q, R Flow cytometry of TREM2, SPP1 expression in TAMs (Q) and GZMB, IFNγ expression in tumor-infiltrating CD8⁺T cells (R) (n = 6 mice). S Schematic of experimental treatment in spontaneous HCC model. T Tumor burden in mice treated with isotype or anti-PD-1 and Terbinafine or DMSO (n = 6 mice). U, V Flow cytometry of TREM2, SPP1 expression in TAMs (U) and GZMB expression in tumor-infiltrating CD8⁺T cells (V) (n = 6 mice). Data represent the mean ± SD, n = 3 biological replicates in (F right), H, I, n = 5 biological replicates in (F left), n = 6 biological replicates in (G). Statistical significance was determined by two-tailed Wald test (A), two-tailed Wilcoxon signed rank test (D), two-tailed Fisher’s exact test (C middle), two-tailed unpaired t test (C right, E–I, K–N, P–R, T–V), and two-tailed one-sample t test (B). Schematics in J, O, and S were created in BioRender. Chu, T. (2025) https://BioRender.com/r2v4jgs. Source data is provided as a Source Data file.