The expression of PRMT6 in different human tissues and cancers
To clarify the differences between PRMT6 in healthy tissues and tumor tissues, we performed a visual analysis of the expression of PRMT6 in healthy tissues. As can be observed in Figure 1a, PRMT6 expression level was low in healthy brain tissues. Then we also analyzed the expression of PRMT6 in different tumors and normal tissues. Tumors with significant positive associations included: Adrenocortical carcinoma (ACC), Bladder Urothelial Carcinoma (BLCA), Breast invasive carcinoma (BRCA), Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), Colon adenocarcinoma (COAD), Esophageal carcinoma(ESCA), Glioblastoma multiforme (GBM), LGG, Liver hepatocellular carcinoma (LIHC), Lung adenocarcinoma(LUAD), Lung squamous cell carcinoma (LUSC), Ovarian serous cystadenocarcinoma (OV), Pancreatic adenocarcinoma (PAAD), Prostate adenocarcinoma (PRAD), Skin Cutaneous Melanoma (SKCM), Stomach adenocarcinoma (STAD), Testicular Germ Cell Tumors (TGCT), Thyroid carcinoma (THCA), Uterine corpus endometrial carcinoma (UCEC), Uterine Carcinosarcoma (UCS). There were also some negatively correlated tumors: Kidney renal clear cell carcinoma (KIRC), Acute Myeloid Leukemia (LAML), Kidney Chromophobe(KICH), Kidney renal papillary cell carcinoma (KIRP).
Analysis of survival prognosis
We used clinical information from the TCGA database to study the correlation between PRMT6 and survival prognosis. It can be seen from the forest graph of OS, DSS and PFI that the expression of PRMT6 is a risk factor in BLCA, LGG and UCEC and a protection factor in BRCA. In addition, PRMT6 expression was divided into high and low groups, and survival analysis curves were drawn. In OS analysis, the high and low expression of PRMT6 was significant in LGG and UCEC. In DSS analysis, the high and low expression of PRMT6 was significant in LGG, LUAD and UCEC. In PFI analysis, the high and low expression of PRMT6 was significant in LGG, COAD and LUAD. These evidence suggest that PRMT6 has important reference value for prognosis in tumors.
Multidimensional immune correlation analysis
To study the effect of PRMT6 on immunity level, we analyzed its interaction with different immune infiltrating cells, immune microenvironment, immune subtype and immune checkpoint genes from different angles. As we can see from Additional file 1 Figure S1, PRMT6 expression in BRCA, CESC, Head and Neck squamous cell carcinoma(HNSC), KIRC, LGG, LIHC, PAAD, SKCM, Thymoma(THYM), UCEC significantly correlation with the immune cells existed. These results indicate that PRMT6 expression is strongly correlated with immune cells in tumors.
Next, we analyzed the relationship between PRMT6 expression and stromal cell and immune cell score in tumors. The stronger the correlation, and the higher the score, the more significant the proportion of stromal cells and immune cells in the tumor tissue. We can see from the Additional file 2 Figure S2, in BLCA, CESC, GBM, LAML, LUSC, OV, Pheochromocytoma and Paraganglioma(PCPG), PRAD, Sarcomav(SARC), STAD, TGCT, THCA, THYM and UCEC, gene expression and immune cells or stromal cells of score was negatively correlated. And the interesting thing is that it's only positive in LGG, which can further prove the intrinsic relationship between PRMT6 expression in g and immune cells.
Also, we analyzed the expression relationship between PRMT6 and 47 common immune checkpoint genes. From Figure 3b, we can see that the expression of PRMT6 in a variety of tumours have a strong correlation with immune checkpoint genes.
Finally, we used the TISIDB online tool to analyze the relationship between gene expression and immune or molecular subtypes(Additional file 3 Figure S3).The results show that the expression of LGG is significantly higher than others.
Mutation correlation analysis
We calculated TMB in each cancer tumor, we can see from the radar map in ACC, THCA, PRAD, PAAD, OV, LGG, COAD and CESC has significantly correlation. In the MSI radar map, SKCM, PAAD, LUAD, KIRC, Lymphoid Neoplasm Diffuse Large B-cell Lymphoma(DLBC) and COAD have significant differences. In the MSI, COAD, DLBC KIRC, LUAD, PAAD, SKCM have statistically significant differences.
Various clinical indicators correlation analysis
To further elucidate the potential clinical value of PRMT6 in gliomas, we analyzed a variety of clinically common indicators including age, tumor grade, IDH mutation status, 1p19q co-deletion status, chemotherapy status. As can be seen from Figure 5, the expression level of PRMT6 in TCGA and CGGA databases was significantly correlated with a variety of clinically common risk factors.
Independent prognostic risk factor analysis
We considered high and low expression of PRMT6 as an independent risk factor. First, survival analysis curves were performed based on TCGA and CGGA data, and the results showed that the high and low expression of PRMT6 significantly affected the prognosis of the patients. Next, we constructed the nomogram by screening for a variety of independent risk factors. TCGA database was used as the training set and CGGA database as the validation set for external validation. From the results of the nomogram, PMRT6 is potentially valuable as an independent prognostic risk factor. In order to test the accuracy of the nomogram model, we calculated the C-index. The C-index of the nomogram of TCGA was 0.84 (95%CI:0.865-0.815), and the C-index of the nomogram of CGGA was 0.772 (95%CI:0.801-0.743). The calibration curves of the 1-year and 3-year survival rates of the two models were drawn respectively, and the results showed that the two models had better validation performance.
Gene enrichment results
According to the results of KEGG and GO enrichment analysis, the role of PRMT6 in gliomas is mainly related to the regulation of cell cycle, the involvement of DNA damage and repair, and the conduction of some signaling pathways. In Table 2, some representative pathways and related functions of enrichment are selected for demonstration.
Table 2: Gene enrichment results
Gene set names
|
NOM p-val
|
FDR q-val
|
KEGG gene set
|
|
|
KEGG_BLADDER_CANCER
|
0
|
0.038
|
KEGG_SMALL_CELL_LUNG_CANCER
|
0.002
|
0.038
|
KEGG_PANCREATIC_CANCER
|
0.006
|
0.044
|
KEGG_SYSTEMIC_LUPUS_ERYTHEMATOSUS
|
0.002
|
0.046
|
KEGG_P53_SIGNALING_PATHWAY
|
0
|
0.031
|
KEGG_MISMATCH_REPAIR
|
0
|
0.045
|
KEGG_NUCLEOTIDE_EXCISION_REPAIR
|
0.006
|
0.043
|
KEGG_ECM_RECEPTOR_INTERACTION
|
0.008
|
0.047
|
KEGG_PYRIMIDINE_METABOLISM
|
0.002
|
0.034
|
KEGG_GLUTATHIONE_METABOLISM
|
0.002
|
0.049
|
KEGG_AMINO_SUGAR_AND_NUCLEOTIDE_SUGAR_METABOLISM
|
0
|
0.045
|
GO gene set
Cell cycle regulation
|
|
|
GO_CELL_CYCLE_G1_S_PHASE_TRANSITION
GO_POSITIVE_REGULATION_OF_CELL_CYCLE_PHASE_TRANSITION
|
0
0
|
0.029
0.033
|
GO_REGULATION_OF_CELL_CYCLE_PHASE_TRANSITION
|
0.002
|
0.032
|
GO_REGULATION_OF_DNA_TEMPLATED_TRANSCRIPTION_IN_RESPONSE_TO_STRESS
|
0
|
0.032
|
GO_REGULATION_OF_POSTTRANSCRIPTIONAL_GENE_SILENCING
|
0
|
0.037
|
GO_REGULATION_OF_TRANSCRIPTION_FROM_RNA_POLYMERASE_II_PROMOTER_IN_RESPONSE_TO_HYPOXIA
|
0.002
|
0.038
|
GO_SIGNAL_TRANSDUCTION_INVOLVED_IN_CELL_CYCLE_CHECKPOINT
|
0
|
0.041
|
GO_MITOTIC_CELL_CYCLE_CHECKPOINT
|
0.002
|
0.035
|
DNA damage and repair
|
|
|
GO_DNA_DAMAGE_RESPONSE_DETECTION_OF_DNA_DAMAGE
|
0
|
0.042
|
GO_DNA_DAMAGE_RESPONSE_SIGNAL_TRANSDUC GO_DNA_SYNTHESIS_INVOLVED_IN_DNA_REPAIR
|
0
0.002
|
0.042
0.041
|
GO_G1_DNA_DAMAGE_CHECKPOINT
|
0.004
|
0.047
|
GO_NUCLEOTIDE_EXCISION_REPAIR_DNA_GAP_FILLING
|
0.004
|
0.045
|
GO_SIGNAL_TRANSDUCTION_IN_RESPONSE_TO_DNA_DAMAGE
Signal transduction
GO_REGULATION_OF_SIGNAL_TRANSDUCTION_BY_P53_CLASS_MEDIATOR
GO_SIGNAL_TRANSDUCTION_BY_P53_CLASS_MEDIATOR
|
0
0.004
0.002
|
0.04
0.042
0.039
|
GO_TUMOR_NECROSIS_FACTOR_MEDIATED_SIGNALING_PATHWAY
|
0
|
0.042
|
Gene sets with NOM p-val and FDR q-value<0.05 are considered as significant.
Immunohistochemical results
Immunohistochemical results showed that PRMT6 protein was positively expressed in the nucleus and was brownish yellow or brown in color. The positive rate was 87.5% in glioma and 25% in normal tissue.And there was a statistical difference, with a P value of 0.0055. In addition, the expression of PRMT6 in normal tissues, LGG and GBM was significantly different, and showed a significant upward trend. Based on the obtained clinical information, we drew a survival analysis curve, which further verified the significant correlation between high and low expression of PRMT6 and prognosis.
Table 3: Expression of PRMT6 in glioma and normal tissues
Tissue types
|
Number of cases
|
PRMT6
|
P value
|
Negative
Expression
|
Low
Expression
|
High
Expression
|
Glioma tissue
|
32
|
4
|
16
|
11
|
0.0055
|
Normal tissue
|
4
|
3
|
1
|
0
|