Literature DB >> 30083911

Long Noncoding RNA PVT1 as a Novel Predictor of Metastasis, Clinicopathological Characteristics and Prognosis in Human Cancers: a Meta-Analysis.

Congmin Liu1, Jing Jin1, Di Liang1, Zhaoyu Gao1, Yachen Zhang1, Tiantian Guo1, Yutong He2.   

Abstract

The present meta-analysis aimed to systematically evaluates the metastasis, clinical stage, and prognostic value regarding the expression levels of PVT1 in various cancers. Relevant literatures were searched in PubMed、Cochrane Library、Wed of science、Embase databases、Chinese National Knowledge Infrastructure and Wanfang from inception up to 22 August 2017. After data were extracted, a meta-analysis was performed using Review Manager 5.3 and Stata 12.0 software. The meta-analysis showed that high expression of PVT1 could predict more lymph node metastasis (LNM) (Odds ratio, OR = 2.83, 95% confidence interval, CI: 1.76-4.54, P < 0.0001), distant metastasis (DM) (OR = 3.60, 95% CI: 1.08-12.03, P = 0.04), advanced clinical stage (OR = 4.37, 95% CI: 3.45-5.54, P < 0.00001) and poor overall survival (Hazard ratio, HR = 2.08, 95% CI: 1.82-2.37, P < 0.00001)in cancer. Subgroup analysis in different systems also showed the same results, including respiratory system、digestive system、urinary system and other systems, especially in respiratory system (LNM, OR = 4.57, 95% CI: 2.41-8.68, P < 0.00001; clinical stage, OR = 5.59, 95% CI: 3.59-8.71, P < 0.00001; OS, HR = 2.43, 95% CI: 1.98-2.99, P < 0.00001). These results suggest that PVT1 could serve as a novel biomarker for metastasis, clinical stage and poor prognosis in various tumors.

Entities:  

Keywords:  Clinical stage; Long non-coding RNA; Meta-analysis; Metastasis; Plasmacytoma variant translocation1; Prognosis

Mesh:

Substances:

Year:  2018        PMID: 30083911      PMCID: PMC6614374          DOI: 10.1007/s12253-018-0451-3

Source DB:  PubMed          Journal:  Pathol Oncol Res        ISSN: 1219-4956            Impact factor:   3.201


Introduction

With the incidence and mortality increased year by year, cancer is becoming a major public health problem and a leading cause of death worldwide. According to GLOBCAN 2012, there were 14.1 million new cancer cases and 8.2 million cancer deaths in 2012 worldwide [1]. In the United States, cancer is the second leading cause of death with an estimated 1,685,210 new cases and 595,690 deaths cancer in 2016 [2]. In China, cancer has been the leading cause of death with an estimated 4,292,000 new cases and 2,814,000 death cases in 2015 [3]. Lymph node metastasis, distant metastasis and clinical stage play an important role in the progression of cancer and are closely related to the prognosis of cancer. The presence of lymph node metastasis and distant metastasis also determines the treatment of cancer, such as surgery, radiotherapy or chemotherapy. Therefore, looking for molecular markers associated with metastasis, clinical stage and prognosis is becoming imminent for the therapy of cancer. Long noncoding RNAs (lncRNAs) are a class of RNAs with a length greater than 200 nucleotides and no protein coding ability. Recently, with the rapid development of high throughput sequencing technology, lncRNAs have been found to be abnormally regulated in various types of cancer and played an indispensable role in the metastasis, advanced clinical stage and prognosis of cancer [4]. Plasmacytoma variant translocation1(PVT1) was first discovered in 2013 in human colorectal cancer and was a copy number amplification associated lncRNA which located on chromosome 8q24 and near MYC [5]. Accumulating evidence revealed that PVT1 was unregulated and played vital regulatory roles in a variety of cancers, including colorectal [6], pancreatic [7], breast and ovarian cancer [8]. High PVT1 expression was strongly correlated with clinicopathologic characteristics, such as metastasis, clinical stage and prognosis [9, 10]. However, since the results of the studies were not consistent (15 articles displayed positive results and 9 articles showed negative results) and small sample size in individual study, we collected relevant publications and performed a meta-analysis to investigate the relationship between PVT1 expression and metastasis, clinical stage or prognosis, aiming to further evaluate whether the PVT1 could be served as a potential molecular biomarker for cancers.

Material and Methods

Search Strategy and Literature Selection

We searched the electronic databases PubMed、Cochrane Library、Wed of science、Embase databases、Chinese National Knowledge Infrastructure and Wanfang, by using “PVT1 or plasmacytoma variant translocation1” as the keyword, in order to obtain potential articles referenced in the publications. Retrieval time for the last update is up to 22 August 2017.

Inclusion and Exclusion Criteria

Inclusion criteria for the articles were as the following: (1) Case-control studies that evaluate the relationship between PVT1 expression and metastasis, clinical stage or prognosis of patients in human cancer. (2) Patients were divided into high and low expression group according to PVT1 expression. (3) Related clinicopathologic parameters were described, such as lymph node metastasis、distant metastasis and clinical stage. (4) Related outcomes were reported, including overall survival (OS)、disease-free survival (DFS)、progression free survival (PFS)、recurrence free survival (RFS). (5) Sufficient data for calculating OR、HR and its corresponding 95% confidence intervals (CI). Exclusion criteria for the articles were as follows: (1) Nonhuman research, reviews, editorials, expert opinions, letters and case reports. (2) Duplicate publications. (3) Studies without valuable data.

Date Extraction and Quality Assessment

Two investigators(YTH, CML)extracted and reviewed the essential data according to the inclusion and exclusion criteria independently. For each eligible study, we extracted the following information: first author, publication year, tumor type, country, total number of patients, detection method of PVT1 expression levels, number of high PVT1 expression group and low PVT1 expression group, number of patients with lymph node metastasis, distant metastasis and different clinical stage, follow-up duration, cut-off value, HRs as well as their 95% CIs. The quality of all eligible studies was assessed by two investigators (YCZ, ZYG) according to the Newcastle-Ottawa Scale independently. NOS scores ranged from 0 to 9 points, with higher scores indicated a better quality and all included eligible studies were assessed to be of high quality by using the NOS in this meta-analysis.

Statistical Analysis

The association between PVT1 and cancer metastasis, clinical stage, or prognosis was assessed by OR and HR with its corresponding 95% CI. The current meta-analysis was performed through Review Manager 5.3 and Stata 12.0 software. We use the Chi square-based Q test and I2 statistics evaluate the heterogeneity of the eligible studies. The random-effects model was used to analyze the results when heterogeneity was present (I > 50%, P < 0.05); while the fixed-effects model was applied for this meta-analysis when the heterogeneity was absent (I < 50%, P > 0.05). The potential publication bias was assessed with the Begg’s funnel-plot. P-value less than 0.05 were considered to be statistically significant.

Results

Literature Search and Study Characteristics

According to the inclusion and exclusion criteria, a total of 24 eligible studies [9-32] were screened upon an electrical search (Fig. 1). These studies included a total of 2212 patients; and the patient’s sample size ranges from 28 to 214 with the mean value of 92. Among the 24 studies, 6 studies focused on gastric cancer, 4 on non-small cell lung cancer and hepatocellular cancer respectively, one on lung cancer, colorectal cancer, pancreatic cancer, pancreatic ductal adenocarcinoma, renal cancer, bladder cancer, esophageal cancer, cervical cancer, epithelial ovarian cancer, and osteosarcoma respectively. All the diagnoses of lymph node metastasis, distant metastasis and tumor–node–metastasis (TNM) were based on pathology. In all of the included studies, the patients were divided into two groups: high and low expression of PVT1. All studies used qRT-PCR to detect the expression of PVT1. The main characteristics of the eligible studies were summarized in Tables 1 and 2.
Fig 1

Flowchart of selecting studies for inclusion in this meta-analysis

Table 1

Metastasis and clinical stage of the eligible studies in this meta-analysis

AuthorYearTumor typeCountrySample sizeDetection methodcut-off valuePVT1 expression
High expressionHigh with LNMHigh with DMHigh with advanced clinical stageLow expressionLow with LNMLow with DMLow with early clinical stage
Cui2015NSCLCChina108qRT-PCRmedian value53292285519113
HuangCS2016SCLCChina120qRT-PCRmedian value604527466015417
Wan2016NSCLCChina105qRT-PCRmedian value5636NA484919NA27
Wu2017NSCLCChina31qRT-PCRmedian expression159NA12163NA6
Yang2014NSCLCChina82qRT-PCRmedian value6537NA39172NA3
DingJ2014GCChina31qRT-PCRcancer/noncancerous tissue > 1.0191531412404
Gou2017HCCChina92qRT-PCRNA48NANA2344NANA10
HuangC2015PDACChina85qRT-PCRmean value67281146181347
Huang T2017GCChina68qRT-PCRfold-change ≥/≤ mean ratio30NANA2138NANA16
Kong2015GCChina80qRT-PCRmedian value4024NA264018NA13
Lan2017HCCChina48qRT-PCRmedian value24NANA1924NANA11
Ren2016GCChina28qRT-PCRNA131111015609
Takahashi2014CRCJapan164qRT-PCRexpression higher or lower than the 20 percentile value1316937433919
Wang2014HCCChina89qRT-PCRmedian value4518NA194415NA9
Yuan2016GCChina111qRT-PCRmedian value55302295619114
Zhao2017PCChina34qRT-PCRNA18NA171616NA35
Zheng2016ECChina77qRT-PCRmedian value3923NA27387NA15
HuangY2015RCChina54qRT-PCRmedian value3916NA24153NA4
Zhuang2015BCChina32qRT-PCRNA201NA19122NA5
Song2017OCChina46qRT-PCRmean value24NANA1622NANA3
Total14858613916655662415414200

NSCLC: non-small cell lung cancer, SCLC: small cell lung cancer, GC: gastric cancer, PDAC: pancreatic ductal adenocarcinoma, CRC: colorectal cancer, HCC: hepatocellular carcinoma, EC: esophageal cancer, RC: renal carcinoma, BC: bladder cancer, PC: pancreatic carcinoma, OC: osteosarcoma, qRT-PCR: quantitative real-time PCR, NA: not available

Table 2

Overall survival of the eligible studies in this meta-analysis

StudyYearDiseaseCountryNumberDetection methodSurvival analysisMultivariate analysisHR statisticHazard ratios (95% CI)Follow up (months)
Cui2015NSCLCChina108qRT-PCROS DFSYesData in paper1.72 (1.14–3.25)40
HuangCS2016SCLCChina120qRT-PCROSYesData in paper1.782 (1.078–2.945)96
Wan2016NSCLCChina105qRT-PCROS PFSYesData in paper2.464 (1.214–4.999)40
Wu2017NSCLCChina31qRT-PCROSNOSurvival curve3.19 (1.16–8.77)80
Yang2014NSCLCChina82qRT-PCROSYesData in paper

3.273

(2.184–6.937)

60
DingC2015HCCChina214qRT-PCROS RFSYesData in paper0.91 (0.59–1.41)120
HuangC2015PDACChina85qRT-PCROSYesData in paper3.3013 (1.574–6.673)60
Kong2015GCChina80qRT-PCROS DFSYesData in paper2.092 (1.068–4.096)40
Lan2017HCCChina48qRT-PCROSNOSurvival curve2.65 (0.89–7.92)48
Takahashi2014CRCJapan164qRT-PCROSYesData in paper

2.532

(1.152–10.747)

>120
Wang2014HCCChina89qRT-PCROS RFSNOSurvival curve1.77(0.69–4.50)50
Yuan2016GCChina111qRT-PCROS PFSYesData in paper2.280 (1.054–4.930)40
Zhao2017PCChina34qRT-PCROSNOSurvival curve1.66 (0.57–4.84)>14
Marissa2015CervicalUSA121qRT-PCROSNOSurvival curve1.84(0.88–3.84)60
Paolo2017EOCItaly202qRT-PCROS PFSYesData in paper2.1 (1.4–3.3)200
Song2017OCChina46qRT-PCROSNOSurvival curve1.79 (0.51–6.32)72
Total1640

NSCLC: non-small cell lung cancer, SCLC: small cell lung cancer, GC: gastric cancer, PDAC: pancreatic ductal adenocarcinoma, CRC: colorectal cancer, HCC: hepatocellular carcinoma, PC: pancreatic carcinoma, OC: osteosarcoma, EOC: epithelial ovarian cancer, OS: overall survival, DFS: disease-free survival, PFS: progression free survival, RFS: recurrence free survival

Flowchart of selecting studies for inclusion in this meta-analysis Metastasis and clinical stage of the eligible studies in this meta-analysis NSCLC: non-small cell lung cancer, SCLC: small cell lung cancer, GC: gastric cancer, PDAC: pancreatic ductal adenocarcinoma, CRC: colorectal cancer, HCC: hepatocellular carcinoma, EC: esophageal cancer, RC: renal carcinoma, BC: bladder cancer, PC: pancreatic carcinoma, OC: osteosarcoma, qRT-PCR: quantitative real-time PCR, NA: not available Overall survival of the eligible studies in this meta-analysis 3.273 (2.184–6.937) 2.532 (1.152–10.747) NSCLC: non-small cell lung cancer, SCLC: small cell lung cancer, GC: gastric cancer, PDAC: pancreatic ductal adenocarcinoma, CRC: colorectal cancer, HCC: hepatocellular carcinoma, PC: pancreatic carcinoma, OC: osteosarcoma, EOC: epithelial ovarian cancer, OS: overall survival, DFS: disease-free survival, PFS: progression free survival, RFS: recurrence free survival

Meta-Analysis Results

Association between PVT1 and LNM

15 studies reported 1197 patients with LNM based on different PVT1expression levels. The random-effects model was adopted as the significant heterogeneity (I = 65%, P = 0.0002). Analysis showed that the OR of high PVT1 expression group versus low PVT1 expression group was 2.83 (95% CI: 1.76–4.54, P < 0.0001) (Fig. 2), which revealed that a higher PVT1 expression predicted more LNM.
Fig. 2

Forest plot for the association between PVT1 expression levels with LNM

Forest plot for the association between PVT1 expression levels with LNM The subgroup analysis according to different systems in cancer types revealed a significant association between increased PVT1 expression and LNM in patients with respiratory system tumors (OR = 4.57, 95% CI: 2.41–8.68, P < 0.00001) and digestive system tumors (OR = 2.31, 95% CI: 1.18–4.49, P = 0.01). However, in urinary system tumors, the pooled result showed that cancer patients with high PVT1 expression were more likely to develop to LNM through no statistical significance was observed (OR = 1.09, 95% CI: 0.11–10.45, P = 0.94) (Fig. 2). This may be due to the too few literatures inclusion in the urinary system.

Association between PVT1 and DM

681 patients were included in 8 studies assessed the association between PVT1 expression and DM. The random-effects model was applied as the significant heterogeneity (I = 63%, P = 0.008). Analysis showed that high PVT1 expression was more prone to DM (OR = 3.60, 95% CI: 1.08–12.03, P = 0.04) (Fig. 3).
Fig. 3

Forest plot of the correlation between PVT1 expression levels and DM in different cancer patients

Forest plot of the correlation between PVT1 expression levels and DM in different cancer patients

Association between PVT1 and Clinical Stage

20 studies contain 1485 patients with clinical stage were included. The fix-effect model was used as no heterogeneity existed (I = 0%, P = 0.81). Analysis showed the OR of 4.37 with 95% CI: 3.45–5.54 (P < 0.00001) (Fig. 4), which revealed that a higher PVT1 expression was predictive of advanced clinical stage.
Fig. 4

Forest plot for the association between PVT1 expression levels and clinical stage in different cancer patients

Forest plot for the association between PVT1 expression levels and clinical stage in different cancer patients The subgroup analysis according to different systems in cancer types revealed a significant association between increased PVT1 expression and advanced clinical stage in patients with respiratory system tumors (OR = 5.59, 95% CI: 3.59–8.71, P < 0.00001), digestive system tumors (OR = 3.59, 95% CI: 2.66–4.83, P < 0.00001) and other system tumors (OR = 8.75, 95% CI: 3.61–21.20, P < 0.00001) (Fig. 4).

Association between PVT1 and OS

16 studies reporting 1640 patients with OS were included according to different PVT1 expression levels. The fixed-effect model was used as the small heterogeneity existed (I = 38%, P = 0.06). Data of pooled HRs (HR = 2.08, 95% CI: 1.82–2.37, P < 0.00001) (Fig. 5) showed high PVT1 expression correlated with a worse survival.
Fig. 5

Forest plot for the association between PVT1 expression levels and OS for the included studies

Forest plot for the association between PVT1 expression levels and OS for the included studies The subgroup analysis also revealed a significant association between increased PVT1 expression and OS in patients with respiratory system tumors (HR = 2.43, 95% CI: 1.98–2.99, P < 0.00001), digestive system tumors (HR = 1.80, 95% CI: 1.43–2.26, P < 0.00001) and other system tumors (HR = 1.94, 95% CI: 1.47–2.55, P < 0.00001) (Fig. 5). In additional, we investigated the association between PVT1 expression and DFS, PFS or RFS, respectively. The results revealed that significant negative association between PVT1 expression levels and DFS (HR = 1.87, 95% CI: 1.40–2.49, P < 0.0001), PFS (HR = 1.85, 95% CI: 1.47–2.32, P < 0.00001) or RFS (HR = 1.76, 95% CI: 1.19–2.61, P = 0.005) were existed. All the results were listed in the Table 3.
Table 3

Results of this meta-analysis about the association between PVT1 expression and DFS, PFS or RFS

Survival periodEligible studiesSample sizeHeterogeneity (fixed)Pool HR (95% CI)Meta regression (p value)
I2 (%)p value
Disease-free survival (DFS)337800.821.87 (1.40–2.49)P < 0.0001
Progression free survival (PFS)341800.451.85 (1.47–2.32)P < 0.00001
Recurrence free survival (RFS)230300.611.76 (1.19–2.61)P = 0.005
Results of this meta-analysis about the association between PVT1 expression and DFS, PFS or RFS

Publication Bias and Sensitivity Analysis

We use Egger’s test and funnel plot evaluate the publication bias of the present meta-analysis. Egger’s test (P = 0.728) revealed that there was no publication bias in analysis of LNM, and funnel plot (Fig. 6) showed no evidence of obvious asymmetry for LNM. Additionally,Similar results were also shown in the clinical stage and prognosis groups. Sensitivity analysis was carried out to evaluate the influence of a single study on the overall meta-analysis results by removing one study at a time in total population. When each study was omitted sequentially, the results were not significantly altered in this meta-analysis (Fig 7).
Fig. 6

Funnel plot analysis of potential publication bias in LNM group

Fig. 7

Sensitivity analyses of studies concerning PVT1 and overall survival

Funnel plot analysis of potential publication bias in LNM group Sensitivity analyses of studies concerning PVT1 and overall survival

Discussion

PVT1 was a novel lncRNA which was first discovered in 2013 in human colorectal cancer. In recent years, a growing number of studies have shown that PVT1 upregulated in several cancers. The further comprehensive mechanism between PVT1 and cancers was reported in continuance. PVT1 involved in tumor proliferation, invasion, migration and apoptosis and played an important role in tumor progression, metastasis and prognosis. In order to combine previous research results about PVT1 and cancers to arrive at a summary conclusion, we clarified the relationships between PVT1 expression levels and metastasis, clinical stage or prognosis in cancers in this meta-analysis. As far as we know, this is the first meta-analysis providing comprehensive insights into the correlation of PVT1 and cancer clinical stage. Results showed that the risk of lymph node metastasis and distant metastasis in high PVT1 expression group was 2.83 and 3.60 folds than those with low PVT1 expression group, respectively. The risk of developing into advanced clinical stage in PVT1 over expression patients was 4.37 times higher than those with low PVT1expression. PVT1 over expression patients with poor prognosis were 2.08 times lower in patients with low PVT1 expression. The same results were also shown in the subgroup analysis of different system tumors. First, in respiratory system tumors, Wan et al. found that Over expression PVT1 inhibited the expression of LATS2 by binding to enhancer of zeste homolog 2 (EZH2) and promoted cell proliferation in non-small cell lung cancer [15]. Digestive system tumors such as in esophageal cancer, PVT1 upregulation decreased E-cadherinexpression and increased N-cadherin and vimentin expression, and induced epithelial-to-mesenchymal transition (EMT) process [12]. In gastric cancer, Xu et al. suggested that PVT1 facilitated gastric cancer cell proliferation and metastasis, and fulfilled its oncogenic functions in a FOXM1-mediated manner [26]. In hepatocellular carcinoma, Lan et al. demonstrated that PVT1 over expression was significantly correlated with vascular invasion, liver cirrhosis and TNM stage. Mechanism studies showed that PVT1 served as an endogenous sponge for miR-186-5p to reduce its inhibiting effect on yes-associated protein 1 and thus promoted the tumorigenesis of hepatocellular carcinoma [29]. In colorectal cancer, Takahashi et al. demonstrated high PVT1 expression exhibited greater lymph node metastasis, venous invasion and a poor OS compared with low PVT1 expression [21]. In pancreatic carcinoma, Zhao et al. found that PVT1 functions as an endogenous ‘sponge’ by competing for miR-448 binding to regulate the miRNA target SERBP1and therefore promotes the proliferation and migration of pancreatic carcinoma cells [28]. Furthermore, PVT1 expression levels were significantly correlated with metastasis and advanced clinical stage in urinary system tumors, such as bladder cancer and renal carcinoma. Huang et al. showed that high PTV1 expression was correlated with lymph node metastasis, advanced TNM stage and shorter OS. Knock down PVT1 decreased cell proliferation and enhanced cell apoptosis. Finally, PVT1 also functioned as critical regulator in the prognosis of other system tumors, including cervical carcinoma, ovarian cancer and osteosarcoma. Song et al. suggested that high PVT1 expression predicted poor prognosis. PVT1 over expression increased glucose uptake, lactate production, and the expression of HK2 in osteosarcoma cells. PVT1 could act as molecular sponge to repress the expression of miR-497 and promote the development of osteosarcoma [30]. To summarize, although mechanisms of PVT1 acted were not the same in various cancers, many similarities were still existed. First, PVT1 played a key role in cancers by interacting with miRNAs. An inverse association was observed between PVT1 and miR-186 expression levels which was observed in gastric cancer and hepatocellular cancer, while PVT1 functions as an endogenous ‘sponge’ by competing for miR-448 in pancreatic cancer. Second, PVT1 could also alter the expression of certain genes, including bind to EZH2 in non-small cell lung cancer and gastric cancer. PVT1 could interact with FOXM1 directly and increase its protein expression in gastric cancer and increased glucose uptake, lactate production, and the expression of HK2 in osteosarcoma cancer. Finally, PVT1 also affected cell cycle progression, such as promoted cell proliferation, migration and invasion and inhibited cell apoptosis in various cancers. In general, PVT1 expression was significantly associated with metastasis, clinical stage, and poor prognosis in various types of cancer in different systems. Otherwise, as with other meta-analysis, it should be acknowledged that some limitations existed in this meta-analysis. First, the cutoff values of PVT1 high expression and low expression were lack of uniform standard in different types of cancer, which may result in some heterogeneity and affect the results of the study. Second, different studies have different postoperative regimens that may have a significant impact on OS, DFS, PFS and RFS. Third, since most studies report positive results and negative results are rarely published, the results of this study may overestimate the effect of PVT1 on cancers to a certain extent. Although there are some limitations, but this meta-analysis still has its noteworthy advantages. First, 24 literatures including a total of 2212 cases were included in this meta-analysis. The sample size included was the largest, which significantly improved the statistical efficiency and accuracy of the test. Second, the search databases were the most and cancer types were the most comprehensive in this meta-analysis compared with the previous reports. Third, lymph node metastasis and distant metastasis, OS、DFS、PFS and RFS were included in this study, which made the results more complete and comprehensive. Finally, the inclusion and exclusion criteria were more stringent and the quality of the literatures incorporated was higher. In conclusion, despite the limitations described above, our meta-analysis reveals that upregulated PVT1 is significantly correlated with more metastasis, advanced clinical stage and poor prognosis in patients with various cancers. Furthermore, the significance of PVT1 in the metastasis, clinical stage and prognosis of respiratory system tumors is more obvious and can be used as a potential molecular marker to evaluate the prognosis of cancer. Nevertheless, the indication in the urinary system is relatively weak as the fewer samples; suggesting that we need to incorporate more studies in the urinary system tumors to validate this result.
  29 in total

Review 1.  Long non-coding RNA PVT1 and cancer.

Authors:  Ming Cui; Lei You; Xiaoxia Ren; Wenjing Zhao; Quan Liao; Yupei Zhao
Journal:  Biochem Biophys Res Commun       Date:  2016-02-03       Impact factor: 3.575

2.  Long noncoding RNA PVT1 promotes hepatocellular carcinoma progression through regulating miR-214.

Authors:  Xun Gou; Xiyan Zhao; Zhengrong Wang
Journal:  Cancer Biomark       Date:  2017-12-06       Impact factor: 4.388

3.  Knockdown of Lncrna PVT1 Enhances Radiosensitivity in Non-Small Cell Lung Cancer by Sponging Mir-195.

Authors:  Dapeng Wu; Yong Li; Huixiang Zhang; Xigang Hu
Journal:  Cell Physiol Biochem       Date:  2017-08-22

4.  Long non-coding RNA PVT1 as a novel biomarker for diagnosis and prognosis of non-small cell lung cancer.

Authors:  Di Cui; Cai-Hua Yu; Min Liu; Qing-Qing Xia; Yu-Feng Zhang; Wei-Long Jiang
Journal:  Tumour Biol       Date:  2015-10-21

5.  Cancer statistics in China, 2015.

Authors:  Wanqing Chen; Rongshou Zheng; Peter D Baade; Siwei Zhang; Hongmei Zeng; Freddie Bray; Ahmedin Jemal; Xue Qin Yu; Jie He
Journal:  CA Cancer J Clin       Date:  2016-01-25       Impact factor: 508.702

6.  Expression and clinical significance of the long non-coding RNA PVT1 in human gastric cancer.

Authors:  Jian Ding; Dan Li; Minzhen Gong; Jinpo Wang; Xunru Huang; Ting Wu; Chengdang Wang
Journal:  Onco Targets Ther       Date:  2014-09-18       Impact factor: 4.147

7.  The lncRNA PVT1 Contributes to the Cervical Cancer Phenotype and Associates with Poor Patient Prognosis.

Authors:  Marissa Iden; Samantha Fye; Keguo Li; Tamjid Chowdhury; Ramani Ramchandran; Janet S Rader
Journal:  PLoS One       Date:  2016-05-27       Impact factor: 3.240

8.  Tetracycline-inducible shRNA targeting long non-coding RNA PVT1 inhibits cell growth and induces apoptosis in bladder cancer cells.

Authors:  Chengle Zhuang; Jianfa Li; Yuchen Liu; Mingwei Chen; Jiancheng Yuan; Xing Fu; Yonghao Zhan; Li Liu; Junhao Lin; Qing Zhou; Wen Xu; Guoping Zhao; Zhiming Cai; Weiren Huang
Journal:  Oncotarget       Date:  2015-12-01

9.  The novel long noncoding RNA RP11-357H14.17 acts as an oncogene by promoting cell proliferation and invasion in diffuse-type gastric cancer.

Authors:  Biao Yang; Tianhang Luo; Meijing Zhang; Zhengmao Lu; Xuchao Xue; Guoen Fang
Journal:  Onco Targets Ther       Date:  2017-05-18       Impact factor: 4.147

10.  Amplification of PVT-1 is involved in poor prognosis via apoptosis inhibition in colorectal cancers.

Authors:  Y Takahashi; G Sawada; J Kurashige; R Uchi; T Matsumura; H Ueo; Y Takano; H Eguchi; T Sudo; K Sugimachi; H Yamamoto; Y Doki; M Mori; K Mimori
Journal:  Br J Cancer       Date:  2013-11-05       Impact factor: 7.640

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  5 in total

1.  Hypoxia induces the activation of hepatic stellate cells through the PVT1-miR-152-ATG14 signaling pathway.

Authors:  Fujun Yu; Buyuan Dong; Peihong Dong; Yanghuan He; Jianjian Zheng; Ping Xu
Journal:  Mol Cell Biochem       Date:  2019-12-21       Impact factor: 3.396

2.  Long noncoding RNA HOXD-AS1 in various cancers: a meta-analysis and TCGA data review.

Authors:  Fuhong Zhang; Xiaowan Chen; Kehu Xi; Zhiqiang Qiu; Youhu Wang; Yan Gui; Yun Hou; Kangbing Chen; Xiaobing Zhang
Journal:  Onco Targets Ther       Date:  2018-11-05       Impact factor: 4.147

Review 3.  Long non-coding RNA PVT1 interacts with MYC and its downstream molecules to synergistically promote tumorigenesis.

Authors:  Ke Jin; Shufei Wang; Yazhuo Zhang; Mengfang Xia; Yongzhen Mo; Xiaoling Li; Guiyuan Li; Zhaoyang Zeng; Wei Xiong; Yi He
Journal:  Cell Mol Life Sci       Date:  2019-07-15       Impact factor: 9.261

Review 4.  Long non-coding RNA MIR31HG as a prognostic predictor for malignant cancers: A meta- and bioinformatics analysis.

Authors:  Yuanfeng Wei; Yingjie Zhai; Xiaoang Liu; Shan Jin; Lu Zhang; Chengyan Wang; Hong Zou; Jianming Hu; Lianghai Wang; Jinfang Jiang; Xihua Shen; Lijuan Pang
Journal:  J Clin Lab Anal       Date:  2021-11-27       Impact factor: 2.352

5.  Long Noncoding RNA PVT1 Is Regulated by Bromodomain Protein BRD4 in Multiple Myeloma and Is Associated with Disease Progression.

Authors:  Hiroshi Handa; Kazuki Honma; Tsukasa Oda; Nobuhiko Kobayashi; Yuko Kuroda; Kei Kimura-Masuda; Saki Watanabe; Rei Ishihara; Yuki Murakami; Yuta Masuda; Ken-Ichi Tahara; Hisashi Takei; Tetsuhiro Kasamatsu; Takayuki Saitoh; Hirokazu Murakami
Journal:  Int J Mol Sci       Date:  2020-09-27       Impact factor: 5.923

  5 in total

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