The expression level and diagnostic value of PRR11 in glioma
Aiming at glioma-related information from CGGA, TCGA_GTEx and GEO datasets, PRR11 is significantly upregulated in glioma tissues (Figure 1A-C). More importantly, PRR11 positively correlates with pathological and World Health Organization (WHO) grades (Figure 1D-I). Besides, PRR11 expression in most of 56 glioma cell lines is obviously higher that of normal human astrocytes (NHAs), except 8-MG-BA, DBTRG-05MG, DK-MG, GOS-3, KG-1-C, KNS-60, LN-215, LN-428 and U-343Mga (Figure 1J).
Gathering matched clinical data of glioma patients, including age, gender, primary-recurrent-secondary (PRS) types, histological types, IDH mutation status and 1p/19q codeletion status, from the CGGA mRNA_325 dataset, the analysis of the age and gender is displayed in Figure 2A-B. In the analysis of PRS types, PRR11 expression of secondary glioma is evidently higher than primary ones, with no statistical significance between primary and recurrent groups (Figure 2C). To our knowledge, glioma patients with IDH-mutant or 1p/19q codel would have a better prognosis [25,26]. Likewise, PRR11 expression in IDH1-mutant and 1p/19q codel groups is much lower than IDH1 wild-type and 1p/19q non-codel groups, respectively (Figure 2D-E). Similarly in histological analysis, PRR11 expression in the anaplastic group is higher than the primary group, and GBM group has the highest PRR11 expression level, which is consistent with malignancy grades (Figure 2F).
To explore the diagnostic value of PRR11 in glioma, univariate Cox analysis discloses that PRR11 (HR = 2.71; 95% CI = 2.06–3.58; p < 0.001), age (≥42), gender (male), IDH mutation status (wildtype), 1p/19q codeletion status (non-codel) and grade (WHO Ⅳ) are high-risk factors (Figure 2G). Multivariate Cox analysis discloses that PRR11 (HR = 2.61; 95% CI = 1.98–3.43; p < 0.001) is independently associated with overall survival, suggesting that PRR11 might be an independent prognostic indicator for glioma (Figure 2H). Above all, PRR11 upregulates in glioma tissues and cell lines, upon correlation with PRS types, histological types, IDH mutation, 1p/19q codeletion, showing great diagnostic value in glioma.
The prognostic value of PRR11 in glioma
For further validation of the prognostic significance of PRR11 in glioma, we analyzed the correlation between PRR11 expression and survival time of 325 samples in the CGGA dataset and 689 samples in the TCGA_GTEx dataset, of which the baseline characteristics are shown in Table S1-2. When observing the survival time of each group, the results demonstrates that high PRR11 expression is accompanied by shortened OS in all grades of glioma patients of CGGA and TCGA_GTEx dataset (Figure 3A-B, p < 0.001).
Additionally, we performed the receiver operating characteristic (ROC) curve to verify the predictive role of PRR11 in the prognosis of glioma patients. In the CGGA and TCGA_GTEx dataset, the area under the curve (AUC) is 90.9% and 98.5% respectively, indicating that PRR11 has a particular predictive ability (Figure 3C-D). Further ROC analysis discloses that PRR11 is a predictor of 1-year (AUC = 0.724), 3-year (AUC = 0.759), and 5-year survival (AUC = 0.778) in CGGA dataset and a predictor of 1-year (AUC = 0.744), 3-year (AUC = 0.776), and 5-year survival (AUC = 0.780) in TCGA_GTEx dataset (Fig.3E-F). In summary, PRR11 serves as an independent prognostic factor for the overall survival of glioma patients.
Biological mechanisms of PRR11 in CGGA and TCGA_GTEx dataset
To probe the underlying mechanisms of PRR11 in affecting the occurrence and development of glioma, we preliminarily clarified the correlation between PRR11 and key genes in cell-cycle and transcription factors from CGGA and TCGA_GTEx dataset. In Figure 4A-B, PRR11 positively correlates with CDK1 and CDK2, activating serine/threonine axis to drive the cell cycle [25]. Subsequent exploration on functional pathways of PRR11, transcription factors E2F family members have been concerned. In Figure 4C-F, E2F1, E2F2, E2F7 and E2F8 are upregulated by PRR11 activation, indicating that PRR11 may affect the occurrence and development of gliomas by interfering with transcription factors.
Analysis of immune infiltration demonstrates that PRR11 is negatively associated with CD8+ T cells and macrophages, and positively correlates with tumor purity in GBMs. While in low grade gliomas (LGGs), PRR11 is positively correlated with B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages and dendritic cells (Figure 5A, Table S3). Univariate Cox survival analysis discloses that all types of immune cells and PRR11 are indicators of survival of patients with LGG, while only B cells and dendritic cells are associated with survival of patients with GBM (Figure 5B, Table S4). Multivariate Cox survival analysis reveals that age and CD4+ T cells are independent prognostic indicators for patients with GBMs (Tab S5), and age, macrophages and PRR11 are independent prognostic indicators for patients with LGGs (Table S6). Furthermore, arm-level deletion and gain in CNVs of PRR11 were associated with the extent of immune infiltration in glioma immune cells (Figure 6). These findings indicates that PRR11 affects the occurrence and development of glioma by interfering with cell-cycle, transcription factors and immune infiltration.
Cell type identification and biological mechanisms of PRR11 at scRNA-seq level
Subsequently, we performed 10x Genomics of scRNA sequencing to identify cell type and explore biological mechanisms of PRR11 in glioma. A total of 13553 cells from 9 patients are divided into 27 clusters and further divided into 8 main clusters, including AC-like malignant, CD8Tex, MES-like malignant, malignant, Mano/Macro, NPC-like malignant, OPC-like malignant and Oligodendrocytes according to specific marker genes (Figure 6A-B). Surprisingly, PRR11 is specifically overexpressed in Mano/Macro_C21 (Figure 6C-D), with a tight connection with G2/M checkpoint and E2F family targets (Figure 6E). Further cell-cell communication analysis shows that Mano/Macro_C21 communicates more frequently with MES-like malignant_C0, MES-like malignant_C3 and MES-like malignant_C10 than other cells (Figure 6F). Transcription factor (TF) enrichment analysis reveals that a group of transcription factors, including SPI1, SMAD1, KMT2A, ERG, BRD4, CDK8, STAT1, RUNX1, IRF1 and NCOR1, mainly modulate PRR11 expression at the transcription level (Figure 6G). In addition, we also analyzed upregulated and downregulated immunologic gene-sets in all types of cells for immunotherapeutic targets (Figure 6H).
While in Smart-seq of scRNA sequencing, 13553 cells are divided into 20 clusters and further divided into 7 main clusters, including AC-like malignant, CD8Tex, MES-like malignant, Mano/Macro, NPC-like malignant, OPC-like malignant and Oligodendrocytes (Figure 7A-B). In Smart-seq, PRR11 is specifically overexpressed in CD8Tex (Figure 7C-D), interfering with MYC targets and PI3K/AKT/mTOR signaling (Figure 7E). Further cell-cell communication analysis shows that CD8Tex communicates more frequently with MES-like malignant_C14 than other cells (Figure 7F). TF enrichment analysis reveals that a group of transcription factors, including TAF1, SUPT5H, SIN3A, RBBP5, GABPA, ETS1, MAF, NELFE, HEY1 and MAX, mainly modulate PRR11 expression at the transcription level (Figure 7G). In addition, we also analyzed upregulated and downregulated immunologic gene-sets in all types of cells for prediction of immunological response of glioma patients (Figure 7H). Therefore, we have confirmed that PRR11 is involved in malignancies via cell-cycle, transcription factors, MYC targets and PI3K/AKT/mTOR signaling at scRNA-seq level.
Exploration of underlying mechanisms of PRR11 in glioma
Finally, we preliminarily explored the possible mechanisms, by which PRR11 facilitates the progression of glioma. Firstly, interactions between PRR11 and other genes or proteins were detected (Fig.7A) and potential post-translational modification (PTM) sites are shown in Fig.7B. Secondly, Pearson correlation analysis was performed between the expression of PRR11 and other genes in the genomic map of the CGGA dataset. The results discloses that 171 genes (R > 0.7) and 38 genes (R < -0.5) are significantly correlated with PRR11 expression (Fig.7A). Next, GO function annotation analysis was performed on the biological process (BP), cellular component (CC) and molecular function (MF). In 171 genes (R > 0.7), the DEGs are mainly enriched in organelle fission, nuclear division, chromosome segregation, chromosomal region, condensed chromosome and chromosome, centromeric region. KEGG pathway analysis results discloses that the DEGs are mainly enriched in cell cycle, cellular senescence, progesterone-mediated oocyte maturation and other pathways. While in 38 genes (R < -0.5), the DEGs are mainly enriched in the small molecule catabolic process, synaptic membrane and coenzyme binding and KEGG pathway analysis results discloses that the DEGs are mainly enriched in oocyte meiosis, synaptic vesicle cycle, pyruvate metabolism and other pathways (Fig.7C).
Furthermore, the top 20 genes positively and negatively connected to PRR11 is plotted in the Fig.8A-B (Table S7). GO function annotation analysis illustrates that the DEGs are mainly enriched in chromosome segregation, mitotic nuclear division, mitotic sister chromatid segregation, spindle, microtubule, microtubule associated complex, tubulin binding, microtubule binding, microtubule motor activity, and coenzyme binding. While KEGG pathway analysis uncovers that the DEGs are mainly enriched in cellular senescence, cell cycle, progesterone-mediated oocyte maturation and pyruvate metabolism (Fig.8C-D). Therefore, PRR11 might exert its oncogenic effects via involvement with chromosome segregation, coenzyme binding, cell cycle and pyruvate metabolism.