Expression level of CIB1 in patients with UVM
To determine the expression level of CIB1 in UVM, immumohistochemical staining was used firstly. As shown in Fig. 1A, a significant increase expression level of CIB1 was observed from UVM tissues (middle) when compared with that in normal tissues (surrounding normal choroidal melanocytes) and that in negative control groups. To detect the CIB1 expression profile in UVM based on individual cancer stage, tumor histology, and sex, weight, age of patients, UALCAN web resource was analyzed. As shown in Fig. 1B-F, there were no significantly difference expression levels of CIB1 based on gender (Fig. 1D) and weight (Fig. 1E) of the patient. However, individual cancer stages (Fig. 1B), patient’s age (Fig. 1C) and tumor histology (Fig. 1F) might be the potential impact factor for CIB1 expression in patients with UVM. In particular, the expression level of CIB1 is significantly elevated in stage 4 when compared with that in stage 3 (Fig. 1B, p < 0.001). As shown in Fig. 1C, older patients (81–100 years) exhibited higher CIB1 expression level than that in young patients (21–40 years, p < 0.05). Epithelioid cells expressed more CIB1 than that in spindle cells (Fig. 1F, p < 0.01).
As shown in Fig. 1G, cBioPortal for Cancer Genomic analysis demonstrated that there are no mutations have been detected in the current TCGA-UVM samples, but several gain, dioploid and shallow deletion were seen in patients with UVM. There are two isoforms of CIB1 have been identified, CIB1-001 and CIB1-201. To verify the two isoforms structural of CIB1 and compare the occurrence of the two major isoforms in patients with UVM, GEPIA2 dataset analysis was further used. As shown in Fig. 1H-I, two isoforms CIB1-001 and CIB1-201 consist of 191aa and 231aa, respectively. Each of them contains the EF-hands for their multiple functions. The occurrence of CIB1-001 is more frequent in patients with UVM compared with that in CIB1-201 (Fig. 1H).
Taken together, the result revealed that CIB1 high expression in UVM compared with that in normal tissues, but no mutations have been detected in TCGA-UVM cases.
Effect of CIB1 expression levels on patient survival in TCGA-UVM dataset
To evaluate the significant prognostic value of CIB1 in patients with UVM, the overall survival (OS) and disease free survival (DFS) of CIB1 expression level in UVM were analyzed. GEPIA2 results demonstrated that a higher CIB1 expression level resulted in significantly lower survival probability (Fig. 2A, OS, p < 0.0011 and Fig. 2B, RFS, p = 0.031). UALCAN web portal analysis further exhibited the consist conclusion (Fig. 2C, p < 0.0001).
In addition, the survival probability was also notably associated with body weight and sex of the patients. As shown in Fig. 2D, the male patients own poorer survival probability compared with that in female patients. Body weights of patient also effect the patient survival obviously, as shown in Fig. 2E, obese and overweight patients demonstrated shorter survival time. The contribution of the CIB1 isoforms to the survival probability of patients with UVM was determined. As shown in Fig. 2F, survival map analysis verified that CIB1-001 is the major isoform effect the survival of patient with UVM. These data indicated that CIB1 as a promising prognostic biomarker in patients with UVM.
Correlation genes with CIB1 in patients with UVM from TCGA dataset
To identify genes correlated with CIB1 in patients with UVM, correlation analysis was implemented. The top 20 correlated genes with CIB1 expression in UVM were mined using GEPIA2 online tool and listed in Table.1 (P CC > 0.78). Besides, the 50 top-rank positive and negative correlated genes with CIB1 expression in UVM were investigated using UALCAN tool and listed in Table.2.
Table 1
Top 50 ranked CIB1-positively and -negatively correlated genes TCGA-UVM dataset
Genes Number | Similar Genes Symbol | Genes ID | Pearson CC |
1 | ORMDL2 | ENSG00000123353.9 | 0.85 |
2 | MRPS34 | ENSG00000074071.13 | 0.85 |
3 | MRPS11 | ENSG00000181991.15 | 0.84 |
4 | ATOX1 | ENSG00000177556.11 | 0.83 |
5 | ZDHHC12 | ENSG00000160446.18 | 0.82 |
6 | MYL6 | ENSG00000092841.18 | 0.81 |
7 | POR | ENSG00000127948.13 | 0.80 |
8 | MSRB1 | ENSG00000198736.11 | 0.80 |
9 | MPV17L2 | ENSG00000254858.9 | 0.80 |
10 | LAMTOR2 | ENSG00000116586.11 | 0.80 |
11 | DHRS7B | ENSG00000109016.17 | 0.80 |
12 | ARPC1B | ENSG00000130429.12 | 0.80 |
13 | PAGR1 | ENSG00000238045.9 | 0.79 |
14 | NDUFAF1 | ENSG00000137806.8 | 0.79 |
15 | GLA | ENSG00000102393.9 | 0.79 |
16 | DNAJB12 | ENSG00000148719.14 | 0.79 |
17 | AIFM2 | ENSG00000042286.14 | 0.79 |
18 | ADCK5 | ENSG00000173137.11 | 0.79 |
19 | HM13 | ENSG00000101294.16 | 0.78 |
20 | ALG1 | ENSG00000033011.11 | 0.78 |
Table 2
Top 20-ranked similar genes with CIB1 in patients with UVM
Positive correlated Genes | Pearson CC | Negative correlated Genes | Pearson CC |
ORMDL2 | 0.82 | RPL32 | -0.7 |
MRPS34 | 0.82 | RPL14 | -0.67 |
MRPS11 | 0.81 | C6orf48 | -0.66 |
ATOX1 | 0.81 | LTA4H | -0.65 |
ZDHHC12 | 0.79 | FBL | -0.64 |
C15orf63 | 0.79 | RPL15 | -0.64 |
NDUFAF1 | 0.78 | RPSA | -0.63 |
GLA | 0.78 | RPL24 | -0.62 |
ARPC1B | 0.78 | RPSAP58 | -0.62 |
SEPX1 | 0.78 | RPL3 | -0.61 |
ROBLD3 | 0.78 | QARS | -0.61 |
ADCK5 | 0.77 | RPS3 | -0.61 |
TNFRSF1A | 0.77 | CSNK2A2 | -0.6 |
POR | 0.77 | RPS5 | -0.6 |
DNAJB12 | 0.77 | NCRNA00219 | -0.59 |
MYL6 | 0.77 | RPL35A | -0.59 |
HM13 | 0.77 | EEF1G | -0.59 |
MPV17L2 | 0.77 | RPSAP9 | -0.59 |
DHRS7B | 0.77 | RPL12 | -0.58 |
DYNLL1 | 0.76 | LGTN | -0.58 |
SFXN3 | 0.76 | SNHG7 | -0.58 |
AIFM2 | 0.76 | RPS4X | -0.58 |
S100A13 | 0.76 | RPS13 | -0.57 |
P4HA2 | 0.76 | ZNF677 | -0.57 |
SRA1 | 0.76 | RPL10A | -0.57 |
WDR25 | 0.75 | RPS18 | -0.56 |
TCIRG1 | 0.75 | LYRM4 | -0.56 |
ALG1 | 0.75 | RPL29 | -0.56 |
CHAC1 | 0.75 | EIF3L | -0.56 |
POLR3K | 0.75 | CTF1 | -0.56 |
C12orf62 | 0.75 | RPL23 | -0.56 |
ATP6V0B | 0.74 | RPL38 | -0.55 |
SIL1 | 0.74 | MTUS1 | -0.55 |
GSDMD | 0.74 | RPS2 | -0.55 |
PFN1 | 0.74 | RPL37 | -0.55 |
IDH2 | 0.74 | C14orf93 | -0.55 |
FKBP2 | 0.74 | RPL10 | -0.55 |
SLC22A18 | 0.74 | IMPDH2 | -0.55 |
STX4 | 0.74 | GLTSCR2 | -0.55 |
MVP | 0.74 | RPS9 | -0.55 |
IMP3 | 0.74 | CDCA7L | -0.55 |
COTL1 | 0.74 | GAS5 | -0.54 |
DOK1 | 0.73 | SLC25A38 | -0.54 |
KDELR3 | 0.73 | RPS23 | -0.53 |
IRAK1 | 0.73 | HNRNPA1 | -0.53 |
NCS1 | 0.73 | LETMD1 | -0.53 |
MAGIX | 0.73 | RPL22 | -0.53 |
MFSD5 | 0.73 | GNB2L1 | -0.53 |
RAB15 | 0.73 | NMNAT3 | -0.53 |
PSMB3 | 0.73 | SNHG8 | -0.53 |
As shown in Fig. 3A, correlation analysis of the top 5 CIB1-positively correlated genes (ORMDL2, MRPS34, MRPS11, ATOX1 and ZDHHC12) and CIB1-negatively correlated genes (RPL32, RPL14, C6orf48, LTA4H and FBL) with CIB1 were analyzed. To further confirm the similarity of the top 20 correlated genes, the expression heatmap and survival heatmap were evaluated. As shown in Fig. 3B, the positively correlated genes expressions across TCGA tumors are very similar to that in CIB1, especially in UVM cancer types. In contrast, the negatively correlated genes expressions in patients with UVM are widely divergent to that in CIB1 (Fig. 3C). To further analysis the survival heatmaps, as shown in Fig. 3D, the results confirmed that the top-20 positively correlated gene showed high hazards ratio in UVM, but not in additional cancers. The top-20 negatively correlated gene showed low hazards ratio in UVM (blue) when compared with that in additional cancer types (Fig. 3E).
Promoter Methylation Levels Of Cib1 In Patients With Uvm
Promoter methylation usually consider as a marker of gene inactivation [22]. To investigate the CIB1 promoter methylation profile based on individual cancer stage, and gender, weight and age of the patients, UALCAN online tool was used. As shown in Fig. 4, the results revealed that the individual cancer stage (A), and age (C), gender (D) of the patients might not contribute greatly to the CIB1 promoter methylation in patients with UVM. However, patient’s weight could alter the promoter methylation level of CIB1 in patients with UVM (Fig. 4B, normal vs obese, p < 0.05).
Ppi Network And Go Enrichment Analysis Of Cib1
The functional interactions between proteins can provide important information of the molecular mechanism involved. PPI network of CIB1 was presented using the STRING database (Fig. 5A). The result indicated that CIB1 has interactions with 11 functional partners, including GUF1, CRY2, PLK3, ACTN4, PSEN2, ITGA2B and ITGB3, MAP3K5, CABP1, SPICE1 and ARHGEF1. To be specific, translation factor GUF1[23], which promotes mitochondrial protein synthesis, and CRY2, transcriptional repressor which forms a core component of the circadian clock [24].
As shown in Fig. 5B, 20 interactive genes of CIB1 were further identified using GeneMANIA, including PSEN2, PLK3, ITGA2B and ITGB3, which consistent with the aforementioned correlated CIB1 genes from Fig. 5A. Moreover, 16 other correlated genes from GeneMANIA dataset are PAX3, RAC3, PLK2, PSEN1, POLG, IDH2, FEZ1, ATP6V0E1, CD151, LRP10, GPX4, UBR5, POLD4, S100A10, CSTB and C21orf33. Consistent with the aforementioned correlation analysis in Fig. 3, IDH2 is just belonging to the top 50 ranked CIB1 positively correlated genes in patients with UVM.
To determine the potential function CIB1 in UVM, GO enrichment analysis of CIB1 and the genes it interacts with were performed using Metascape tool (Fig. 5C and Fig. 5D). The results suggested that CIB1 and the genes it interacts with are significantly enriched in ITGA2B-ITGB3-CIB1 complex, regulation of intracellular protein transport, regulation of ion transport, cellular response to tumor necrosis factor and positive regulation of apoptotic process.