Identification of immune checkpoint genes CD276 and HAVCR2
To identify the immune checkpoint genes of this study’s focus, it was observed that CD276, HAVCR2 and CD47 genes were significantly overexpressed in most tumors, including GBM (Fig. 1a). It was noticed that CD276, CD47 and HAVCR2 were also highly expressed in the GBM samples of TCGA and GEPIA database (Fig. 1b-d). Additional survival analysis of immune checkpoint gene revealed that CD276, TNFSF14, VTCN1, IDO1, CD40, TNFSF18, TIGIT, CD274, CD70 and HAVCR2 could influence the prognosis of GBM patients (Fig. 1e-h and Figure s1). In summary, this study identified CD276 and HAVCR2 as the genes of interest.
Correlation analysis between CD276, HAVCR2 and macrophages
Macrophages are important TAMS cells which play an important role in GBM, especially in the M2 macrophages. It was observed that primarily the CD276, HAVCR2 had higher expression in macrophages after clustering RNA single-cell sequencing data, whereas its expression in the neuronal cells was low (Fig. 2e-f and Figure s2)，and associated with macrophage M2 infiltration (Figure s4). The analysis outcome also showed that the macrophage expression could affect the prognosis of GBM patients (Figure s3).
GBM poor prognostic immune subtype determination and the relationship with IDH status and clinical information
While a positive correlation was observed between CD276, HAVCR2 and CD163, no significant correlation was noticed with NOS2 (Fig. 3). By further re-grouping the data by the cut-off best truncation values, namely I (CD276lowCD163low/HAVCR2lowCD163low), II (CD276low CD163high/HAVCR2lowCD163high), III (CD276highCD163low/HAVCR2highCD163low), IV (CD276high CD163high/HAVCR2highCD163high), it was found that the IV group had the worst prognosis, I group had the best prognosis, and the results were statistically significant (Fig. 4). Further analysis found that most of the IDH status in the IV group was wild type, and there was no significant relationship between gender and age (Fig. 5), which might imply that patients with group IV have higher potential for immunotherapy and have a better curative effect . To verify this study’s results, IHC staining was performed on paraffin sections of patients who had been in our hospital for the past five years and were pathologically diagnosed as high-grade glioma (Fig. 6a). It was noted that the degree of staining of paraffin sections was different in different patients undergoing the same treatment. The patients were also grouped as per the same best cut-off value after the quantification of the sections. The results showed that patients with IV group had the lowest survival whereas I group had the highest survival, which was also statistically significant (Fig. 6b and c). The four groups were associated with immune score and stromal score: I group had the lowest immune score and stromal score, while IV group had the highest immune score and stromal score (Figure s5), and macrophage infiltration in IV group was the highest (Figure s6).
GSVA enrichment analysis
Through the analysis of the GSE84465 data set, it was noted that the macrophages were divided into 0,2 clusters, wherein 0 cluster were basically tumor-associated macrophages and the 2 cluster were basically paracancerous cells. Furthermore, through the GSVA enrichment analysis and differential expression analysis, it was ascertained that there were differential signaling pathways (Fig. 7a). After further calculation gene set score, it was associated with EMT and JAK-STAT3 signaling pathway (Fig. 7b and c). GSVA analysis of CD276, HAVCR2 and CD163 showed that was positively correlated with macrophage activation, differentiation, EMT and JAK-STAT signaling pathway. This result can be verified in both TCGA and CGGA databases (Fig. 8).
High expression of CD276, HAVCR2 and CD163 was closely related to EMT and affected the prognosis of patients with high expression of PD-L1.
TAMS and EMT were closely related and enrichment analysis found significant enrichment in EMT signaling pathways, GSVA enrichment analysis of CD276, HAVCR2 and CD163 also found significant correlation with the EMT. Further analysis found that EMT most of the associated genes were significantly high expression in IV group (Fig. 9). Interestingly, IV group accounted for more than 30% of the patients in the PD-L1 high expression group, and IV group had a worse prognosis than the other three groups (Fig. 10). In order to further explore the reasons for the difference in prognosis, we establishing a risk model by EMT related genes, calculated the possible risk values for each patient (Figure s7), and found that IV group was also closely related to the high expression of EMT related genes in the PD-L1 high expression group, and were more likely to develop EMT high risk scores, and IV_EMT_scorehigh had a worse prognosis (Fig. 11). We speculated that this might be one of the reasons for the individualized differences in Anti-PDL1 treatment.
Determination of upstream transcription factors
We analyzed the differential expression of tumor-associated transcription factors (n=318) downloaded from the CISTROME database using TCGA GBM data combined with GET data, the screening conditions were |LogFC|>1, P<0.05, and finally 58 differentially expressed transcription factors were obtained. We further analyzed the correlation with CD276/HAVCR2, the screening conditions were |R|>0.5, P<0.05. We found that the positive correlation between RUNX1/IKZF1 with CD276/HAVCR2 was the highest (Fig. 12a), and the correlation coefficient was 0.7, 0.79, respectively. Meanwhile, we predicted the transcription factors that might bind to CD276/HAVCR2 by UCSC database (Minimum score=400), and then cross with CD276/HAVCR2 related transcription factors, finally, the RUNX1 and IKZF1 was obtained (Fig. 12b and c). Further analysis found that The RUNX1/IKZF1 binding peaks were found in CD276/HAVCR2 promoter region by UCSC analysis (Fig. 12C and E). To search for specific possible binding sites, we screened the possible binding sites in the CD276/HAVCR2 sense sequence or antisense strand by JASPAR database, the screening conditions were Relative profile score threshold>90%, and finally the possible binding sites were tcctgcggttg, caaagaggaagc, respectively (Fig. 12d and f).