PTTG3P is highly expressed in CRC
To evaluate potential lncRNAs involved in mediating CRC progression, we examined the lncRNA expression profile (GSE 84983) (Fig. 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 (Fig. S1b). Then, we found that PTTG3P had rarely the 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[7], indicating that PTTG3P was a long noncoding RNA with no protein-coding potential. Then we explored the subcellular location of PTTG3P by using lncRNA subcellular localization predictor software (lncLocator, http://www.csbio.sjtu.edu.cn/bioinf/lncLocator/) (Fig.S1c), suggesting PTTG3P was mainly localized to the cytoplasm, and subcellular fractionation confirmed the prediction (Fig. S1d). 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 was remarkably overexpressed in cell lines of CRC (Fig. 1a, 1b). Then, the cell lines of HT-29, SW620, HCT-8, SW480, HCT116, NCM460, and FHC were conducted for PTTG3P expression. As showed in Fig. 1c, the PTTG3P expression was exceedingly increased in HT-29, SW620, HCT-8, SW480, HCT116 cells, compared with NCM460 and FHC cells.
Further, we explored PTTG3P expression in a cohort of 120 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 the TCGA database (Fig. 1f, 1g). Besides, high PTTG3P expression was observed in other malignant tumors (Fig. 1h). Also, our specimens confirmed PTTG3P overexpression in stomach adenocarcinoma (STAD), and esophageal squamous cell carcinoma (ESCA) (Fig. 1i,1j). Intriguingly, there was no actionable EGFR, VEGFR or RAS mutations, indicating that higher expressed PTTG3P may be driven by oncogenic event (Fig. S1e-1g). Altogether, these data revealed that PTTG3P was elevated in CRC and might be an oncogene.
Table 1
Correlation between PTTG3P expression 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
|
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 groups 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 1). Moreover, the PTTG3P expression was higher in stage III-IV (advanced stage) than stage I-II (early stage) in tissues (Figure 2a). Additionally, Kaplan-Meier survival curves illustrated that patients with highly expressed PTTG3P had poorer survival time (Figure 2b). Further, we determined the prognostic ability of PTTG3P in CRC. As shown in Table 2, 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). A model that incorporated the independent predictor was proposed as the nomogram (Fig. S2). Subsequently, the 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) (Figure 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
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 is caused by metabolic stress and promotes glycolysis and proliferation in CRC
To investigate the biological function of PTTG3P, we transfected the PTTG3P overexpressed plasmids and shRNA targeting PTTG3P into HT-29 and HCT116 cells, respectively (Fig. 2d). By determining PTTG3P expression via gene set enrichment analysis (GSEA) the Cancer Genome Atlas (TCGA) profiles, we found that PTTG3P level was positively correlated with the glycolysis by affecting genes in glycolysis regulation (Fig. 2e). PTTG3P knockdown restrained the mRNA level of GLUT-1, ALDOA, PKM2, and LDHA, and the effect of sh-PTTG3P on glycolytic gene transcription could be rescued by PTTG3P re-expression (Fig. 2f). And glucose deprivation is a well-known feature of solid tumors. Subsequently, we wonder whether PTTG3P participated in cell survival under metabolic stress, then we carried out several experiments with different glucose concentrations and glycolysis inhibitor 2-deoxyglucose (2-DG) to make a condition of glucose deprivation. Obviously, PTTG3P expression was increased by glucose deprivation or 2-DG treatment in either dose-dependent or time-dependent manner (Fig. 2g, 2h). Thus, we elucidated that PTTG3P could play a crucial role in the progression of metabolic stress.
Next, we performed the glucose uptake analysis, ATP analysis, lactate production analysis, and discovered that sh-PTTG3P repressed these phenomena. In contrast, PTTG3P overexpression boosted 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, facilitated apoptosis of HCT116 cells, whereas upregulated PTTG3P increased the proliferation, 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 played a vital role in cell proliferation and tumor growth. Notably, the glycolic inhibitors 2-DG and 3-BP or depletion of LDHA, which catalyzed the final step of glycolysis, could partly abrogate cancer cell proliferation and tumor growth (Fig. 3i,3j,3k). Clinically, Oxaliplatin is used for the treatment of colorectal cancer. Previously, it is reported that suppression of glycolysis is an effective strategy to block cell proliferation and conquer drug resistance. As shown in Fig. 3l,3m, PTTG3P depletion and Oxaliplatin played a synergistic role in emancipating tumor growth. 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 is involved in PTTG3P-mediated 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 might be involved (Fig. 4a). Then the hub genes in the Hippo pathway, including LATS1/2, MST1/2 and YAP1, and Hippo pathway target genes, such as CDX2, FOXM1, CTGF and CYR61, were checked in sh-PTTG3P HCT116 cells. Subsequently, PTTG3P knockdown impaired the level of YAP1, FOXM1 and CTGF (Fig. 4b). Moreover, silenced PTTG3P decreased the enrichment of H3K27Ac at the YAP1 promoter, while that of H3K27me3 was increased (Fig. 4c). Next, we explored the TCGA database and drew the PTTG3P co-expression heat map. Then, we discovered that PTTG3P expression was correlated with genes in the Hippo pathway (YAP1, TEAD1-3), genes in the phenotype of proliferation (PCNA, MKI67, MCM2, MCM3, MCM5), genes in the phenotype of apoptosis (BAX, CASP1, CASP3, CASP10), genes in the phenotype of autophagy (ATG5), and genes in the phenotype of cell cycle (CDK1, CCDN1, CCND2, CCNB1), but not with MST1, an upstream factor of YAP1 (Fig. 4d).
It is commonly acknowledged that YAP1, a crucial factor in the Hippo pathway, involves in cell proliferation and suppresses apoptotic genes, and YAP1 was highly expressed in CRC (Fig. S1h, S1i), and associated with advanced characteristics of CRC (Table S4). Further, YAP1 had a higher diagnostic value (AUC=0.793, 95% CI:0.729-0.858) from the TCGA database (Fig. S1j). Additionally, we performed rescue assays in HT-29 cells. PTTG3P OE plus YAP1 KD could reverse the bioeffect of PTTG3P. Besides, we applied YAP1 inhibitors, CA3 (a novel specific YAP1 inhibitor) and verteporfin (an inhibitor of YAP1/TEAD interaction), got the same conclusion (Fig. 4e-4h). Intriguingly, the treatment of Hippo pathway inhibitor, XMU-MP-1 (inhibiting MST1/2), could not recover the effect of PTTG3P on proliferation, apoptosis and tumor growth (Fig. 4i, 4j).In brief, all the data uncovered that PTTG3P hedges the key factor MST1/2, while modulates YAP1 in the Hippo pathway to exhibit pivotal functions in CRC progression.
Methylation and deacetylation are not involved in PTTG3P upregulation in CRC
We first determined whether DNA methylation can regulate PTTG3P expression. No CpG islands were found in the PTTG3P promoter, as shown by analyzing PTTG3P promoter sequences via the online software MethPrimer (http://www.urogene.org/cgi-bin/methprimer/methprimer.cgi) and DBCAT (http://dbcat.cgm. ntu.edu.tw/) (Figure 5a, b). To validate the role of DNA methylation on the regulation of PTTG3P expression, HT29 and HCT-116 cells were transfected with small interfering RNA (siRNA) for DNA (cytosine-5)-methyltransferase 1,3A,3B (DNMT1,3A,3B), crucial enzymes catalyzing the transfer of methyl groups to certain CpG structures of DNA. Our results demonstrated that these DNA methylation enzymes could barely influence PTTG3P expression(Figure 5c). Additionally, we treated CRC cells with 5 μM 5-azacytidine (5-AZA), an inhibitor of DNA methylation, our results revealed that 5-AZA treatment did not affect PTTG3P levels in CRC cells (Figure 5d). 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 carried out experiments with SAHA and NaB, the broad-spectrum HDAC inhibitors, and we discovered that these HDAC inhibitors failed to alter PTTG3P level in HT29 cells (Figure 5e). In addition, overexpressed HDAC6 and HDAC8 did not affect increasing PTTG3P expression (Figure 5f). Next, histone methylation may also influence gene transcription. We knocked down EZH2 and LSD1 in HT29 and HCT-116 cells and measure the PTTG3P expression. As a result, silencing EZH2 or LSD1 did not markedly influence PTTG3P expression, indicating that histone methylation is not involved in PTTG3P upregulation in CRC cells (Figure 5g). In summary, our findings preliminarily demonstrated that methylation and deacetylation are not participating in the upregulation of PTTG3P in CRC.
miR-1271-5p regulates PTTG3P expression and rescues the function of PTTG3P
Immunoprecipitation assay confirmed that PTTG3P bound to Ago2, the main component of the microRNA-related silencing complex (Fig. 6a). We assumed that PTTG3P could be regulated by miRNAs. MicroRNAs (miRNAs) are endogenous small non-coding RNAs, binding to the 3′-untranslated regions (3′-UTRs) of target genes to regulate target gene expression. Bioinformatics analysis was performed to predict the candidate microRNAs. The most promising candidate gene is miR-1271-5p, which is relatively low expressed in CRC (figure 6b, 6c) and has a diagnostic value with an AUC of 0.919 (95%CI, 0.861-0.977) (figure 6d). Ago2 RIP assay showed that miR-1271-5p was the highest enriched microRNAs in PTTG3P overexpression group than the vector group (Fig. 6e). PTTG3P expression was suppressed by overexpression of miR-1271-5p but promoted by the specific microRNA inhibitors (Fig. 6f, 6g). Next, we designed a reporter construct in which the putative miR-1271-5p binding sites in the PTTG3P sequence were mutated by site-directed mutagenesis (Fig. 6h). Transfection of miR-1271-5p mimics significantly inhibited the luciferase activity of reporters containing PTTG3P-WT, instead of PTTG3P-Mut (Fig. 6i). MS2-RIP assay was used to further verify the direct interaction between miR-1271-5p and PTTG3P. The MS2-tagged wild-type PTTG3P vector was enriched for miR-1271-5p compared to the empty and mutant plasmids (Fig. 6j). These data strongly suggested that PTTG3P could be regulated by miR-1271-5p in CRC cells. Besides, higher miR-1271-5p expression associated with advanced characteristics (Table S5), and poor prognosis (Fig. 6k). Intriguingly, miR-1271-5p mimics could abolish the PTTG3P function (figure 7a-7g).
We also investigated whether hypoxia could regulate PTTG3P expression in CRC cells.
Then, we treated CRC cells with hypoxia or CoCl2 (hypoxia chemical inducer) and found the PTTG3P expression in HT-29 cells was obviously increased as well as the elevation of HIF1A (Fig. 7h). While, depletion of HIF1A strikingly ameliorated PTTG3P expression in both normoxia and hypoxia conditions (Fig. 7i, 7j). We also indicated that HIF1A and PTTG3P had a positive correlation (Fig. 7k, S3h). Interestingly, HIF1A could diminish miR-1271-5p expression (Fig. 7l). Hence, HIF1A/miR-1271-5p/PTTG3P/YAP1 axis conducted a pivotal role in CRC progression.
PTTG3P plays crucial functions in cancer immunology
Cancer cells have high glucose uptake and glycolysis, resulting in a low level of glucose in the tumor, thus inhibiting the production of IFN-r by CD8+T cells in the tumor. Tumor immune environment is widely involved in tumor progression different malignant tumors, including CRC. Recently, the treatment of CRC with immune checkpoint inhibitors (ICI) has provided a potential clinical treatment. Interestingly, our findings from the TCGA database proposed that low PTTG3P expression relates with CD8+ T, NK and TFH cells infiltration in the microenvironment of CRC, not with Treg or macrophages infiltration (Figure S3a-f). And the results of ELISA showed that the level of inflammatory cytokines TNF-α, IL-1β and IL-6 were decreased with PTTG3P depletion (Figure S3g).
In addition, PTTG3P was correlated with TNF-α, IL-1β and IL-6 from the TCGA-COAD database (Fig. S3h).