Association between high immune activity and poor overall survival in patients with UVM and LGG

To evaluate immune activity status in the TME, we assessed the CTL levels in all TCGA samples and performed a survival analysis between the high and low CTL groups for each cancer type (Materials and Methods; Fig. S1a, b and c). In most cancers, including SKCM, the patient’s overall survival was significantly better in the high CTL group than in the low CTL group. However, in patients with UVM and low-grade glioma (LGG), the low CTL group had a significantly better overall survival than the high CTL group (Figs. 1a and S1c). Moreover, the survival did not differ between high and low CTL groups in patients with glioblastoma (GBM), which is a high-grade glioma. The CTL level was higher in patients with GBM than in those with LGG (Fig. S1a). To validate these findings, we performed the same analysis for gliomas in the CGGA dataset and found that a high CTL level was associated with a worse overall survival in LGG. Moreover, the immune activity of GBM was higher than that of LGG (Fig. S1b). The high CTL group had higher PD-L1 (CD274) expression than the low CTL group, which was common in all cancer types (Fig. S1d).

Fig. 1
figure 1

High immune activity was associated with poor overall survival in patients with UVM and LGG. a Kaplan-Meier curves of overall survival classified according to CTL levels (red: high CTL level, blue: low CTL level). The number samples are indicated in the legend. b tSNE plot based on the activity of well-defined biological states and processes calculated for all samples and color-coded according to cancer type. The names of the cancer types follow TCGA Study Abbreviations. EMT, epithelial mesenchymal transition

Next, we assessed well-known biological states and processes in the Hallmark gene sets registered in MSigDB by calculating the activities of these states and processes in all TCGA samples via ssGSEA. A dimensional compression analysis using tSNE showed clustering according to cancer type and organs with similar functions were plotted adjacent to each other (Fig. 1b). Interestingly, UVM and SKCM were almost in the same position (Fig. 1b). Melanocyte-derived cancers had similar biological states and processes compared with other types of cancers. The relationships between immune activity and prognosis were completely reversed between UVM and SKCM. Similarly, LGG and GBM clustered tightly with each other. Therefore, in the succeeding analysis, we focused on the differences between UVM and SKCM as well as LGG and GBM to assess the prognostic factors of UVM and LGG.

Hazard ratios of inflammation and EMT in UVM and LGG

To examine which biological states and processes in ssGSEA that were strongly associated with worse overall survival in UVM and LGG, we calculated their hazard ratios (HRs). Results showed that epithelial mesenchymal transition (EMT) had the highest HR for worse survival in LGG (Fig. 2a). On the other hand, the HR of EMT in GBM was close to 1 (Fig. 2a; Table S1). In LGG, the activity score of EMT was positively correlated with the CTL level and was significantly enhanced in the high CTL group compared with the low CTL group (Figs. 2b and S2c; Table S2). Moreover, these results were confirmed via an analysis using the CGGA dataset (Fig. S2a and b). To investigate the cause of the enhanced EMT and immune activation, we focused on the upstream signaling pathways associated with the former. In gliomas, EMT is promoted by the TGF-beta, Wnt-beta catenin, Notch, and Hedgehog signaling pathways [9,10,11]. The TGF-beta pathway alone was found to be minimally activated in the high CTL group, as assessed using the TCGA dataset (Fig. 2b). However, this result could not be validated using the CGGA dataset (Fig. S2b). The activity of the Notch and Hedgehog signaling pathways was not correlated with the differences in immune activation status, and there was greater Wnt-beta activation in the low CTL group than in the high CTL group (Figs. 2b, S2b, c and d). By contrast, inflammation and hypoxia are also known to enhance EMT in several brain diseases [9, 11], and these scores were significantly increased in the high CTL group in our results (Fig. 2b). The activities of the inflammatory signaling pathways, such as the IL2-STAT5, IL6-STAT3, interferon-alpha (INF-α), interferon-gamma (INF-γ), and tumor necrosis factor alpha (TNF-α), were positively correlated with the CTL level and were significantly more activated in the high CTL group compared to the low CTL group (Figs. 2b, S2b, c and d; Table S2). Furthermore, the HRs of these pathways were higher in LGG than in GBM (Fig. S2e).

Fig. 2
figure 2

Hazard ratios of inflammation and EMT in UVM and LGG. a Hazard ratio of each state and process in LGG and GBM (top) and in UVM and SKCM (bottom). b Difference in activity score for some states and processes between the high and low CTL groups in LGG (top) and UVM (bottom). c Logarithm of hazard ratios for EMT (left) and inflammatory response (right) among different cancer types. Those with a p-value of < 0.05 are depicted in blue and others in gray. The names of the cancer types follow TCGA Study Abbreviations. EMT, epithelial mesenchymal transition

Next, we compared the HRs of each biological state/process for worse overall survival between UVM and SKCM. The IL6-JAK-STAT3, IL2-STAT5, INF-α/γ, and TNF-α pathways had significantly higher and lower HRs in UVM and SKCM, respectively (Fig. 2a; Table S3). The activities of these signaling pathways were positively correlated with CTL levels and were significantly activated in the high CTL group (Figs. 2b and S3a; Table S4). The HR of the EMT in LGG was significantly higher in UVM, and it was close to 1 in SKCM (Fig. 2a). In some eye diseases, EMT is enhanced after inflammation or the activation of the TGF-beta pathway [12]. Our results show that inflammation was enhanced, as described above, and the TGF-beta pathway was significantly activated in the high CTL group (Figs. 2b, S3a). Among all of the cancer types in TCGA, UVM and LGG had the two highest HRs of EMT, inflammatory response and hypoxia for worse survival (Figs. 2c and S3b).

Types of cells causing inflammatory effects and EMT in UVM and LGG

As presented in the previous section, inflammatory effects and EMT were found to be strongly correlated with worse prognosis in UVM and LGG. To determine which cells are responsible for the inflammatory effects and EMT, we used single-cell RNA-seq data from GEO (GSE139829 and GSE138794) [13, 14]. We calculated the activity score of IL6-STAT3, IL2-STAT5, INF-α/γ, TNF-α, and inflammatory states via ssGSEA using the single-cell data of eight primary UVM samples. The Umap analysis revealed several cell clusters with high inflammatory effects (Figs. 3a and S4b). In these clusters, CD68 and CD163 are expressed, both of which are known markers of macrophages (Figs. 3a, S4a and b). NFkB (NFKB1) and COX-2 (PTGS2), known as inflammation-related molecules associated with a bad prognosis of Uveal melanoma [15], were highly expressed mainly in the macrophage population. Also, consistent with the previous study’s finding, CXCL10, known as inflammation-inducing and lymphocyte-attracting chemokines [16], was highly expressed exclusively in the same population (Fig. S4c). The HR of angiogenesis was the highest in UVM compared to other cancer types and was also significantly enhanced in the high CTL group (Table S2). Next, cell populations with EMT had a high expression of endothelial and retinal pigmented epithelial cell markers (Figs. 3a, S4a and b). From the single-cell data of nine glioma samples, we identified inflammatory cell populations that were positive for CD68 (Fig. 3b, S4d and e). In contrast to UVM, CD163 positive cells showed only a slight inflammatory response in glioma (Figs. 3b, S4d and e). The cell populations in which EMT was activated were mainly cells expressing endothelial cell markers, similar to what was seen in UVM (Figs. 3b, S4d and e). Because CD163 indicates M2-like macrophages, the inflammatory effect, which was associated with worse prognosis in UVM and LGG, is mainly observed in macrophage populations that differ in phenotype from each other: M2-like macrophages in UVM and M0/M1-like macrophages in LGG.

Fig. 3
figure 3

Single-cell analysis and the macrophage relative abundance level in UVM and LGG. a, b Umap projection of clustering analysis (left), and the overview of activation scores of inflammation (middle) and EMT (right) across all cells in UVM (a) and LGG (b). c, d Correlation between M0, M1, and M2 macrophage levels determined using CIBERSORT (absolute = T) and CTL levels in UVM (c) and LGG (d). e, f The fraction of monocyte and M0, M1, and M2 macrophages in the tumor determined using CIBERSORT (absolute = F) in UVM and SKCM (e) and LGG and GBM (f). SKCM, skin cutaneous melanoma; UVM, uveal melanoma; LGG, low-grade glioma; GBM, glioblastoma

Next, to validate whether tumors with a higher immune activity have an increased abundance of macrophages, we evaluated the immune status of the tumors using CIBERSORT [17]. The absolute abundance scores of M1 and M2 macrophages in UVM were positively correlated with the CTL level. A similar correlation was observed in the xCell scores [18], indicating that macrophages were relatively more abundant in the state of high immune activity (Figs. 3c and S5a). The ratios of each immune cell showed that M2 macrophages were the most predominant cells in UVM (Fig. S5c). The percentages of macrophages and monocytes in the tumor were compared between UVM and SKCM. Results showed that M2 macrophages were more abundant in UVM than in SKCM (Fig. 3d).

In LGG, the proportion of M0, M1, and M2 macrophages was significantly increased in tumors with higher CTL levels, and a similar correlation was observed in the xCell scores (Figs. 3e and S5b). Furthermore, a survival analysis was performed by dividing the abundance scores of M1 and M2 macrophages by the median. Results showed that worse survival was significantly associated with a high macrophage invasion (Fig. S5c). Because the M0 macrophage score was 0 in more than half of the samples, survival analysis could not be performed for M0. In addition, we compared the percentage of macrophages (combined monocyte and M0, M1, and M2 macrophages) in all cancer types. In LGG and GBM, the macrophages were significantly abundant, and glioma was the macrophage-dominant cancer (Fig. S5f). By comparing the percentages of macrophages in LGG and GBM, the fraction of M0 and M1 macrophages increased in GBM (Fig. 3f). Results showed that increased relative abundance of macrophages was associated well with immune activation.

High correlation between the expression of inflammatory mediator chemokine CCL5 and CTL level

We investigated potential molecules that can improve the function of BRB and BBB and inhibit the infiltration of immune cells, such as macrophages. Here we focused on chemokines because they are a class of cytokines involved in the development of inflammation by promoting the migration of leukocytes and other immune cells, and they have recently attracted attention as targets for cancer therapeutics. We calculated the HR of each chemokine for worse prognosis based on expression level. Results showed that CCL5 had the highest HR in UVM (Fig. 4a; Table S5). CCL5 is known to promote BBB disruption, and the HR of CCL5 was significantly high in LGG, whereas it was low in SKCM and close to 1 in GBM. The expression of CCL5 was most positively correlated with CTL level in LGG, and a high correlation was also observed in UVM (Fig. 4b; Table S6). CXCL11, which is a ligand of CXCR3, had the highest HR in LGG. CXCR3 has ligands including CXCL9, CXCL10, and CXCL11. These chemokines had high HRs in both UVM and LGG, and they were also strongly correlated with CTL levels (Tables S5, S6 and S7).

Fig. 4
figure 4

Association between chemokine expression as well as overall survival and CTL levels. a Hazard ratio of each chemokine in UVM and SKCM (left) and LGG and GBM (right). b Correlation between CCL5 expression and CTL levels in UVM (top) and LGG (bottom). SKCM, skin cutaneous melanoma; UVM, uveal melanoma; LGG, low-grade glioma; GBM, glioblastoma

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