TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma

Abstract

Novel individual biomarkers are needed to guide therapeutic decisions for patients with head and neck cancer. We report for the first time, granulomas of TREM2-expressing multinucleated giant macrophages in keratin-rich tumor niches, as a biomarker of favorable prognosis and developed a deep-learning model to automate its quantification on routinely stained pathological slides.

Figure 1.

MGC density is a biomarker of prognosis in patients with HNSCC. A, Therapeutic sequence of the treatment-naive cohorts of patients with HNSCC from TCGA and GR. B, Flow chart of TCGA and GR cohorts of treatment-naive patients with HNSCC. Among the 946 patients (527 from TCGA and 419 from GR), 394 were included (110 from TCGA and 284 from GR). C, Non-keratinizing HNSCC (left) and keratinizing HNSCC (right), stained by H&E. WSI from TCGA (scale bar, 250 μm). D, Histograms showing the number of K^Low and K^High patients from TCGA and GR. E, Keratinizing SCC of the oral cavity of a patient from GR, with MGC-rich granulomas surrounding keratin debris. Left, low magnification of the carcinoma (scale bar, 2 mm). Middle, high magnification of a granuloma containing MGC and keratin (scale bar, 50 μm). Right, MGC are highlighted in yellow and keratin in red. F, Histograms showing the proportion of MGC^high patients (TCGA and GR cohorts) among the keratinization groups (no, low, moderate, and high). G, OS curve of 110 TCGA patients stratified according to MGC density in their tumors. The vertical tick mark on the curves means that a patient was censored at this time. H, OS curve of 284 GR patients stratified according to MGC density in their tumors. I, OS curve of all patients (TCGA and GR) stratified according to MGC density in their tumors. J, PFI curve of all patients (TCGA and GR) stratified according to MGC density in their tumors. K, Therapeutic sequence of the induction chemotherapy (ICT)-treated cohort of patients with HNSCC from GR. L, Flow chart of the ICT-treated cohort of patients with HNSCC from GR. M, Keratinizing oral SCC from a patient treated at GR whose tumor responded well to ICT, showing areas of keratin surrounded by numerous MGC. Left, low magnification of the carcinoma (scale bar, 2 mm). Middle, high magnification of a granuloma containing MGC and keratin (scale bar, 50 μm). Right, MGC are highlighted in yellow and keratin in red. N, Histograms showing the percentage of patients with no residual tumor, and the percentage of patients with residual tumor being MGC^High or MGC^Low/Int, in treatment-naive (TCGA and GR) and ICT patients (GR). O, OS curve of 52 patients treated by ICT at GR, stratified by their tumor content and MGC density on surgical resection. The vertical tick mark on the curves means that a patient was censored at this time. P, Histograms showing the proportion of MGC^High and MGC^Low/Int patients according to the pathological response status of their tumors (poor vs. good/partial).

Figure 2.

Automatic detection of MGC and tumor cells on H&E/HES whole slide images by deep learning. A, Overview of the methodology. Manual annotations of MGC and tumor cells were used to train two cell detection models to identify and count MGC and carcinomatous cells in SCC. An automatic score was computed as the ratio of MGC to tumor cells. The score was applied first to TCGA and GR oral cavity cohorts and second to TCGA Uterine cervix and Larynx cohorts. B, Keratinizing oral SCC with granulomas, from the TCGA cohort. Left, low magnification of the carcinoma (scale bar, 2 mm). Middle, high magnification of the carcinoma where automatically detected carcinomatous cells are highlighted in red (scale bar, 50 μm). Right, high magnification of the carcinoma where automatically detected MGC are highlighted in yellow (scale bar, 50 μm). C, Correlation between the number of MGC per patient quantified manually by a pathologist and automatically detected by the model. Patients were from the oral cavity TCGA cohort (n = 110 patients). D, Bland-Altman plots for TCGA oral cavity data shown in C. E, Correlation between the number of MGC per patient quantified manually by a pathologist and automatically detected by the model. Patients are from the oral cavity GR cohort (n = 231 patients). F, Bland–Altman plots for the GR oral cavity data shown in E. G, OS curve of oral cavity TCGA and GR patients (n = 341 patients) stratified according to MGC density computed by the cell detection model. The vertical tick mark on the curves means that a patient was censored at this time. H, PFI curve of oral cavity TCGA and GR patients (n = 341 patients) stratified according to MGC density computed by the cell detection model. I, OS curve of Uterine cervix SCC TCGA patients (n = 189 patients) stratified according to MGC density computed by the cell detection model. J, OS curve of Larynx TCGA patients (n = 100 patients) stratified according to MGC density computed by the cell detection model.

Figure 3.

Spatial transcriptomics reveals a unique MGC signature. A, Low magnification of a representative HES section of a carcinoma selected for spatial transcriptomic analysis. Inset, high magnification of an MGC. B, Same HES section with the overlay of the spots analyzed by Visium technology. One spot is covering a single MGC. C, Low magnification of a representative HES of an MGC^High carcinoma from a patient in the GR cohort. D, Overlay of the seven cell populations analyzed by unsupervised clustering. E, Same HES section showing pathologist annotations of the tumor area (blue) and the MGC (yellow). F, Low magnification of a representative HES of an MGC^Low carcinoma from a patient in the GR cohort. G, Overlay of the seven cell populations analyzed by unsupervised clustering. H, Same HES section showing pathologist annotations of the tumor area (blue). I, Projection of the Visium spots onto a UMAP space; spots from nine different patients. J, Histograms showing the number of spots capturing the different cell types in MGC^High and MGC^Low carcinomas. K, Volcano plot showing MGC RNA signature extracted from the DEG analysis between supervised MGC spots and all the other non-MGC spots. L, Volcano plot showing the DEG between MGC^High and MGC^Low tumors from patients in TCGA cohort (n = 108 patients). M, GSEA plot showing the enrichment of the Visium MGC signature in MGC^High vs. MGC^Low patients classified from TCGA. The green line represents the running enrichment score for the MGC signature, with the peak indicating maximum enrichment. The normalized enrichment score (NES) is 3.24, and the P value is 0.000522, demonstrating significant enrichment of the MGC signature in MGC^High patients. The barcode plot shows the positions of the MGC signature genes within the ranked list of genes from the bulk RNA sequencing data, with a higher density of genes towards the left, indicating higher enrichment.

Figure 4.

MGC-related tumor microenvironment is enriched in CD4 TCM T cells and TREM2-expressing mononuclear macrophages. A, Low magnification of a representative HES section MGC^High carcinoma selected for CosMx 64-plex protein panel analysis. Scale bar, 500 μm. Inset, high magnification of an area annotated by a pathologist, enriched in TILs (green) close to tumor cells (blue) and a granuloma with MGC (yellow). Scale bar, 50 μm. B, Low magnification of the same tumor section, stained by the CosMx protein panel, with the overlay of 20 cell populations (non-immune and immune). Scale bar, 500 μm. Inset, high magnification of the same area, with the annotation overlay of tumor cells, MGC (yellow), TCM CD4 T cells (red), B cells (light gray) and plasma cells (dark gray). C, Projection of the CosMx cell population onto a UMAP space. D, Heat maps showing the expression of immune markers across the 14 immune cell types. Red indicates a higher expression and blue a bottom expression. E, Box-plot showing the TCM CD4 T cells ratio between MGC^Low (n = 4) and MGC^High patients (n = 4). F, Box-plot showing TCM CD4 T cells degree centrality (left) and average clustering (right) between MGC^Low (n = 4) and MGC^High patients (n = 4). G, Heat maps of neighborhood enrichment scores showing the spatial colocalization of the 22 cell types across four MGC^High patients. Yellow indicates a high enrichment and purple a low enrichment. White boxes are highlighting the proximity between (i) TCM CD4 T cells and B cells and (ii) MGC and MGC-MNP. H, Box plots showing B cells (left) and plasma cells ratio (right) between MGC^Low (n = 4) and MGC^High patients (n = 4). I, Box plots showing B cells (left) and plasma cells average clustering between MGC^Low (n = 4) and MGC^High patients (n = 4). J, Low magnification of a representative section stained by the CosMx protein panel, of two granulomas, with the annotation overlay of tumor cells (blue), stromal cells (green), MGC and MGC-MNP (yellow). Insets: high magnification showing MGC surrounded by numerous MGC-MNP. Scale bar, 800 μm. K, Box-plot showing the MGC-MNP ratio between MGC^Low (n = 4) and MGC^High patients (n = 4). L, Representative image of a single MGC stained by CD68 (pink), TREM2 (orange), and Hoechst (cyan). The merge image is shown (scale bar, 50 μm). M, Representative high magnification image of a small granuloma. The arrow indicates mononuclear macrophages (scale bar, 20 μm). N, Histograms showing the distance of TREM2^High MGC from keratin (left) and histograms showing the distance of TREM2^High mononuclear macrophages from keratin (right).