CD163+ TAMs are associated with lymphogenesis. A, LVD and LVI were assessed in the stroma using D2-40–stained lymphatic endothelium. Intratumoral and stromal CD163 immunoreactivity was recorded as in Fig. 1B; data are presented as mean immunoreactivity normalized to tissue compartments in percent. CD163+ TAMs were categorized on the basis of high/low LVD and the presence/absence of LVI. Individual datapoints, shown as dots, overlap summary statistics boxplots with medians represented by horizontal center lines. Significance analysis by two-sided Mann–Whitney U test with Benjamini–Hochberg procedure. B, BVD and BVI were assessed in the stroma using CD31-stained vessels. Intratumoral and stromal CD163 immunoreactivity was recorded as in Fig. 1B; data are presented as mean immunoreactivity normalized to tissue compartments in percent. CD163+ TAMs were categorized on the basis of high/low BVD and the presence/absence of BVI. Individual datapoints, shown as dots, overlap summary statistics boxplots with medians represented by horizontal center lines. Significance analysis by two-sided Mann–Whitney U test with Benjamini–Hochberg procedure.

Supplementary Table 3 summarizes clinicopathological characteristics of the discovery cohort.

Abstract The incidence rates of vulvar squamous cell cancer (VSCC) have increased over the past decades, requiring personalized oncologic approaches. Currently, lymph node involvement is a key factor in determining prognosis and treatment options. However, there is a need for additional immune-related biomarkers to provide more precise treatment and prognostic information. Here, we used IHC and expression data to characterize immune cells and their spatial distribution in VSCC. Hierarchical clustering analysis identified distinct immune subtypes, of which the macrophage-rich subtype was associated with adverse outcome. This is consistent with our findings of increased lymphogenesis, lymphatic invasion, and lymph node involvement associated with high macrophage infiltration. Further in vitro studies showed that VSCC-associated macrophages expressed VEGF-A and subsequently induced VEGF-A in the VSCC cell line A-431, providing experimental support for a pro-lymphangiogenic role of macrophages in VSCC. Taken together, immune profiling in VSCC revealed tumor processes, identified a subset of patients with adverse outcome, and provided a valuable biomarker for risk stratification and therapeutic decision making for anti-VEGF treatment, ultimately contributing to the advancement of precision medicine in VSCC. Significance: Immunoprofiling in VSCC reveals subtypes with distinct clinical and biological behavior. Of these, the macrophage-rich VSCC subtype is characterized by poor clinical outcome and increased VEGF-A expression, providing a biomarker for risk stratification and therapeutic sensitivity.

Supplementary Figure 3 shows expression of VEGF proteins.

Density of stromal TAMs affect outcome. Survival analysis of intratumoral and stromal immune cell counts

VEGF-A expression by in vitro polarized TAMs. A, Healthy donor monocytes were differentiated into macrophages using GMCSF and exposed to different culture conditions: medium alone (monocyte-derived macrophage) or A-431 supernatant (in vitro polarized TAM). Immunofluorescent staining was performed on day 5 and compared with A-431 cells. Cells were stained with anti-VEGF-A (clone VG-1; cytoplasma, green), PKH26 (cell membrane, red), and Hoechst 34580 (cell nucleus, blue). Representative overlay figures are depicted (32x magnification); white scale bar length 200 µm. B, Macrophages were generated as in A and intracellular VEGF-A expression was determined by flow cytometry (anti-VEGF-A clone 23410) on day 5. Data combine results from two independently analyzed individuals. Data are given as d-gMFIs. Individual datapoints, shown as dots, overlap summary statistics barplots (mean ± SEM). Significance analysis by two-sided Student t test. C, Macrophages were generated as in A, and in vitro polarized TAMs and A-431 cells were cultured alone (monoculture) or together (coculture with 2:1 ratio) in the presence of LPS. Intracellular VEGF-A expression was determined by flow cytometry using two anti-VEGF-A antibody clones as indicated after 24 hours of coculture following a 4-hour restimulation with Brefeldin A. For comparison between different cell types, specific cell populations of interest were identified on the basis of their expression of phenotypic markers (EpCAM for cancer cells, CD14 for macrophages), a negative control was included, and cocultured cells were normalized to VEGF expression of blood lymphocytes. Data combine results from three individuals and are given as d-gMFIs. Individual datapoints, shown as dots, overlap summary statistics boxplots with medians represented by horizontal center lines. Significance analysis by two-sided Student t test.

Supplementary Figure 2 shows analysis in independent validation cohorts.

The TAMhigh immune cell cluster is associated with poor outcome. A, Heat map shows the distribution of immune cells (intratumoral and stromal combined). Immunoreactivity was recorded as in Fig. 1B. Unsupervised clustering of log2-transformed cell count data from 41 samples was performed using Euclidean distance. B, Kaplan–Meier plots depict OS and RFS of patients stratified by TAM clusters from A; significance analysis by log-rank test.

CD163+ TAMs are abundant in VSCC. A, Representative images show high CD163 expression in TAMs (brown cytoplasm/cell membrane) in tumor and stroma as visualized by IHC; hematoxylin (blue) was used for nuclear staining (bright field, 400 × magnification; scale bar length 50 µm). B, CD163 immunoreactivity was digitally recorded and analyzed separately in tumor and stroma using three HPFs; results are shown as mean immunoreactivity per tissue compartment in percent. CD68+, CD3+, Foxp3+, and CD20+ immune cell counts were determined in relation to stroma and tumor, respectively. Individual datapoints, shown as dots, overlap summary statistics boxplots with medians represented by horizontal center lines; a split axis is used for CD68 immunoreactivity. Significance analysis by two-sided Mann–Whitney U test with Benjamini–Hochberg procedure. C, Representative images of D2-40–stained lymphatic and CD31-stained vascular endothelium in the peritumoral stroma (brown; bright field, 400 × magnification; scale bar length 50 µm).

Supplementary Table 1 summarizes immunohistochemical antibodies.

High numbers of stromal CD163+ TAMs are associated with adverse outcome. A, CD163 immunoreactivity was recorded intratumorally as in Fig. 1B; data are presented as mean immunoreactivity normalized to tissue compartments in percent. Cutoff values were determined using median CD163 expression to classify low-risk and high-risk groups; Kaplan–Meier curves are shown for each risk tier; log-rank test results are reported. B, CD163 immunoreactivity was recorded in the stroma as in A; Kaplan–Meier curves are shown for each risk tier; log-rank test results are reported.

Supplementary Table 4 summarizes immunohistochemical characteristics of the discovery cohort.

Supplementary Figure 1 shows T cell-based immune phenotypes and spatial analysis of immune cell populations

Supplementary Table 2 summarizes fluorescently labeled antibodies.

Supplementary Table 5 shows the correlation between immune cells and HPV.

Supplementary Methods, Tables 1-4, Figure Legends 1-9 from Targeted Activation of RNA Helicase Retinoic Acid–Inducible Gene-I Induces Proimmunogenic Apoptosis of Human Ovarian Cancer Cells

Supplementary Figure 1 from Targeted Activation of RNA Helicase Retinoic Acid–Inducible Gene-I Induces Proimmunogenic Apoptosis of Human Ovarian Cancer Cells

Supplementary Figures 8-9 from Targeted Activation of RNA Helicase Retinoic Acid–Inducible Gene-I Induces Proimmunogenic Apoptosis of Human Ovarian Cancer Cells

Tissue resident memory T cells (TRM cells) can provide effective tissue surveillance and can respond rapidly to infection. Vaccination strategies aimed at generating TRM cells have shown promise against a range of pathogens. We have previously shown that the choice of adjuvant critically influences CD8+ TRM cell formation in the liver. However, the range of adjuvants tested was limited. Here, we assessed the ability of a broad range of adjuvants stimulating membrane (TLR4), endosomal (TLR3, TLR7 and TLR9) and cytosolic (cGAS, RIG-I) pathogen recognition receptors for their capacity to induce CD8+ TRM formation in a subunit vaccination model. We show that CpG oligodeoxynucleotides (ODN) remain the most efficient inducers of liver TRM cells among all adjuvants tested. Moreover, their combination with the cationic liposome DOTAP further enhances the potency, particularly of the class B ODN CpG 1668 and the human TLR9 ligand CpG 2006 (CpG 7909). This study informs the design of efficient liver TRM-based vaccines for their potential translation.

Supplementary Figures 2-3 from Targeted Activation of RNA Helicase Retinoic Acid–Inducible Gene-I Induces Proimmunogenic Apoptosis of Human Ovarian Cancer Cells