PTTG3P is highly expressed in CRC
To evaluate potential lncRNAs involved in mediating CRC progression, we examined the lncRNA expression profile (GSE 84983) (Figure S1a). Comparison between CRC tumor tissues and adjacent normal tissues, we focused on the upregulated lncRNAs (fold change > 5, P < 0.01), for these lncRNAs might be oncogenes and therapeutic targets. LncRNA PTTG3P was one of the most upregulated and chosen for consideration (Figure S1b). Then, we found that PTTG3P had rarely ability to code proteins, using the open-reading frames (ORFs) Finder and conserved domain database. Moreover, five other different online metrics got the same conclusion (Table S3). Additionally, we identified no valid Kozak consensus sequence in PTTG3P[13], indicating that PTTG3P is a long noncoding RNA with no protein-coding potential.
To verify the elevation of PTTG3P in CRC, we investigated the detailed annotative process of preclinical human cancer models via the Cancer Cell Line Encyclopedia (CCLE) (www.broadinstitute.org/ccle), indicating that PTTG3P is remarkably overexpressed in cell lines of CRC (Fig. 1a, 1b). Then, the cell lines of HT29, HCT-8, SW480, HCT-116 and FHC (human normal colorectal mucosal cell ) were conducted for PTTG3P expression. As showed in Fig. 1c, the PTTG3P expression was exceedingly increased in HT29, HCT-8, SW480 and HCT-116 cells, compared with FHC cells.
Further, we explored PTTG3P expression in a cohort of 60 paired and non-tumor tissues of CRC, the clinicopathologic characteristics are demonstrated in Table 1. Significantly, the PTTG3P level was overexpressed in CRC tissues compared to their counterparts (Fig. 1d, 1e), which was in accordance with the results of TCGA database (Fig. 1f, 1g). Besides, high PTTG3P expression was observed in many kinds of tumors compared with normal counterparts (Fig. 1h). Also, our specimens confirmed PTTG3P overexpression in stomach adenocarcinoma (STAD), and esophageal squamous cell carcinoma (ESCA) (Fig. 1i,1j). All together, these data revealed that PTTG3P was elevated in CRC and might be an oncogene.
Table 1
Clinicopathologic characteristics of studied patients in CRC
Characteristics
|
Number of cases (%)
|
Age (years)
≤ 60
> 60
|
52 ()
68 ()
|
Gender
Male
Female
|
56 ()
64 ()
|
Tumor size (cm)
< 5
> 5
|
81 ()
39 ()
|
Tumor invasion depth
T1-2
T3-4
|
95 ()
25 ()
|
Lymph node metastasis
N0
N1-2
|
40 ()
80 ()
|
Vessel invasion
Yes
No
|
65()
55 ()
|
Distant metastasis
Yes
No
|
115 ()
5()
|
Differentiation
Well
Moderate
Poor
|
38 ()
62 ()
20 ()
|
High PTTG3P level correlates with poor prognosis
To identify the connection between the level of PTTG3P and clinicopathologic features, we divided the cases into PTTG3P low-expression and high-expression group on the basis of median expression. Upregulated PTTG3P was positive linked with Tumor size (P = 0.02) and Differentiation (P = 0.01), but not with age (P = 0.86 ), gender (P = 0.74), tumor invasion depth (P = 0.28 ), lymph node metastasis (p = 0.09) or vessel invasion (P = 0.06) (Table 2). Moreover, the PTTG3P expression was higher in stage III-IV (advanced stage) than stage I-II (early stage) in tissues (Fig. 2a). Additionally, Kaplan-Meier survival curves illustrated that patents with highly expressed PTTG3P had poorer survival time (Fig. 2b). Further, we determined the prognostic ability of PTTG3P in CRC. As shown in Table 3, univariate analyses suggested highly expressed PTTG3P was associated with a dramatic risk of death (P < 0.01). Multivariate analysis demonstrated that PTTG3P expression could be an independent prognostic factor (P < 0.01). Subsequently, ROC curve was carried out to evaluate the diagnostic value of PTTG3P in CRC tissues compared with normal counterparts, the area under the ROC curve (AUC) was 0.776 (95% CI 0.733–0.819) (Fig. 2c). Thus, these data suggested that high expression of PTTG3P predicted a worse prognosis and may serve as a clinical biomarker for CRC patients.
Table 2
Correlation between PTTG3P expression in serum and clinicopathologic characteristics of ovarian cancer patients
Variable
|
PTTG3P expression
|
P-value
|
Total (n = 120)
|
High expression
|
Low expression
|
Age (years)
≤ 60
> 60
|
52
68
|
27
32
|
26
35
|
0.86
|
Gender
Male
Female
|
56
64
|
30
29
|
28
33
|
0.74
|
Tumor size (cm)
≤ 5
> 5
|
81
39
|
47
16
|
37
24
|
0.02
|
Tumor invasion depth
T1-2
T3-4
|
95
25
|
53
12
|
43
20
|
0.28
|
Lymph node metastasis
N0
N1-2
|
40
80
|
25
36
|
20
39
|
0.09
|
Vessel invasion
Yes
No
|
65
55
|
49
20
|
20
31
|
0.06
|
Differentiation
Well
Moderate
Poor
|
38
62
20
|
20
46
13
|
18
16
7
|
0.01
|
Table 3
Univariate and multivariate analyses of clinicopathologic characteristics for correlations with overall survival
Variables
|
Univariate analysis
|
Multivariate analysis
|
HR (95%CI)
|
P value
|
HR (95%CI)
|
P value
|
PTTG3P expression
|
1.758(1.085–2.850)
|
< 0.01
|
1.712 (1.053–2.782)
|
< 0.01
|
Tumor size
|
1.650(1.086–2.508)
|
< 0.01
|
1.923 (1.276–2.898)
|
< 0.01
|
Differentiation
|
1.724(1.183–2.511)
|
< 0.01
|
1.724 (1.183–2.511)
|
< 0.01
|
PTTG3P promotes glycolysis and proliferation in CRC
To investigate the biological function of PTTG3P, we respectively transfected the PTTG3P overexpressed plasmids and silenced shRNA targeting PTTG3P into HT-29 and HCT-116 cells,respectilvely (Fig. 2d). By determining PTTG3P expression via gene set enrichment analysis (GSEA) the Cancer Genome Atlas (TCGA) profiles, we found that PTTG3P levels were positively correlated with the glycolysis by affecting genes in glycolysis regulation (Fig. 2e). To verify results of this analysis, PTTG3P knockdown restrained the mRNA level of GLUT-1, ALDOA, PKM2 and LDHA. Intriguingly, the effect of sh-PTTG3P on glycolytic gene transcription could be rescued by PTTG3P re-expression (Fig. 2f). Next, we performed the glucose uptake analysis, ATP analysis, lactate production analysis, and discovered that sh-PTTG3P repressed these. In contrast, PTTG3P overexpression boosted the glucose uptake (Fig. 3a), lactate production (Fig. 3b), and ATP accumulation (Fig. 3c). Additionally, we calculated the level of ECAR, sh-PTTG3P notably repressed glycolytic capacity and vice verse (Fig. 3d). Also, we found that silenced PTTG3P suppressed the proliferation and facilitated apoptosis of HCT-116 cells, whereas upregulated PTTG3P increased the proliferation and inhibited apoptosis of HT-29 cells according to the CCK-8 assay and flow cytometry analysis (Fig. 3e,3f). In vivo, highly expressed PTTG3P efficiently increased the tumor growth (Fig. 3g,3h). We then explored whether glycolysis plays a vital role in PTTG3P modulation of cell proliferation and tumor growth. Notably, the glycotic inhibitors 2-DG and 3-BP or depletion of LDHA, which could catalyze the final step of glycolysis, could partly abrogate cancer cell proliferation and tumor growth (Fig. 3i,3j,3k).
Clinically, oxaliplatin is used for treatment of colorectal cancer. Previously, it is reported that suppression of glycolysis is an effective strategy to block cell proliferation and conquer drug resistance. Hence, we speculated that PTTG3P ablation in combination with oxaliplatin could strikingly repress tumor growth. As shown in Fig. 3l,3m, PTTG3P depletion could be conducted simultaneously with oxaliplatin. As a taken, PTTG3P knockdown plus oxaliplatin is a promising therapy for CRC.
PTTG3P regulates Hippo signaling pathway in CRC
In order to elucidate which pathway involved in PTTG3P-meddated CRC progression, GSEA in the published TCGA CRC database was explored. And we suggested that PTTG3P expression was associated with the YAP1-activated gene signatures, indicating that Hippo signaling pathway may participated in the biological function of PTTG3P (Fig. 4a). To verify the speculation, the hub genes in Hippo pathway, including LATS1/2, MST1/2 and YAP1, and Hippo pathway target genes, such as CDX2, FOXM1, CTGF and CYR61, were tested in sh-PTTG3P HCT-116 cells. Subsequently, PTTG3P knockdown impaired the mRNA level of YAP1, FOXM1 and CTGF (Fig. 4b).
It is commonly acknowledged that YAP1, a crucial factor in Hippo pathway, involves in cell proliferation and suppressed apoptotic genes. In our study, the level of PTTG3P and YAP1 displayed positive linkage in CRC tissues (Fig. 4c). And the association between YAP1 expression and clinicopathologic characteristics from TCGA indicated in table S4.
Besides, we performed rescue assays in HT-29 cells. PTTG3P overexpression plus YAP1 knockdown could reverse PTTG3P induced phenotype (Figure ,4d-4g). Intriguingly, the treatment of Hippo pathway inhibitor, XMU-MP-1 (inhibiting MST1/2), could not recover the promoting effect of PTTG3P on proliferation, apoptosis and tumor growth. (Fig. 4h-4k).In brief, all the data uncovered that PTTG3P hedges the key factor MST1/2, while modulates YAP1 in Hippo pathway to exhibit pivotal functions in CRC progression.
m6A modification is involved in the overexpression of PTTG3P in CRC cells
We next explored the upstream factors for PTTG3P elevation in CRC. Our study found no influence on PTTG3P expression using DNA methyltransferase inhibition (Fig. 5a). Accumulating evidence has shown that ectopic expression of lncRNAs could be regulated by transcriptional factors, and histone acetylation plays a critical role in this procession. Then, we explored whether histone acetylation exerted a role in PTTG3P expression using SAHA and NaB, the broad-spectrum HDAC inhibitors, and we discovered that these HDAC inhibitors failed to alter PTTG3P level in HT29 cells (Fig. 5b). Further, overexpressed HDAC6 and HDAC8 had no effect on increasing PTTG3P expression (Fig. 5c). Subsequently, MeRIP-qPCR discovered that the m6A modification expression was dramatically increasing in the CRC cells compared with normal cells (Fig. 5d). Then, we confirmed that METTL3, a writer of RNA modification, significantly elevated the PTTG3P expression in both HT-29 and HCT-116 cells (Fig. 5e). Besides, overexpressed ALKBH5, an eraser of RNA modification, greatly suppressed the PTTG3P expression (Fig. 5f). Moreover, we conducted RNA stability analysis by treating cells with Act-D, binding DNA at the initiation complex and preventing RNA chain elongation, our findings uncovered that highly expressed METTL3 strengthened the stability of PTTG3P (Fig. 5g). Therefore, m6A modification acts as an crucial factor in PTTG3P expression. As recently reported, Insulin-like growth factor-2 mRNA-binding proteins 1, 2, and 3 (IGF2BP1-3) are described as a type of m6A readers. We then evaluated the potential binding of PTTG3P and IGF2BP1-3, RIP-PCR was performed using an antibody against IGF2BP1-3. The results found that METTL3 overexpression increases binding between PTTG3P and IGF2BP2 in both HT-29 and HCT-116 cells (Fig. 5h). Interestingly, IGF2BP2 knockdown could partly abrogate the ability of Mettl3 upregulating PTTG3P (Fig. 5i). Finally, the association between METTL3,IGF2BP2 expression and clinicopathologic characteristics from TCGA indicated in table S5,S6.
The METTL3/PTTG3P/YAP1 axis facilitates the progression of CRC
To evaluate the role of METTL3/PTTG3P/YAP1 axis involved in proliferation and glycolysis, we perfomred a series of rescue experiments in HT-29 cells. Glucose uptake analysis, ATP analysis, lactate production analysis, and ECAR analysis showed that sh-METTL3 or sh-YAP1 repressed these phenomenon (Fig. 6a,6b,6c,6d). Whereas, sh-METTL3 plus overexpressed PTTG3P, or sh-YAP1 plus overexpressed PTTG3P could rescue these phenotype. In addition, the promotion of cancer cell proliferation could be counteracted by sh-PTTG3P plus overexpressed METTL3, or sh-YAP1 plus overexpressed PTTG3P (Fig. 6e,6f).
Hence, METTL3/PTTG3P/YAP1 axis conducted a pivotal role in CRC progression.
Additionally, METTL3/PTTG3P high and PTTG3P/YAP1 high group certified an unsatisfactory prognosis than low group (Fig. 6g,6h). We further found that higher levels of METTL3, ALKBH5, and IGF2BP2 predicted poor prognosis and diagnostic value in CRC (Figure S2).