Disease Markers
Volume 2021 (2021), Article ID 8818363, 14 pages
https://doi.org/10.1155/2021/8818363

Research Article

LncRNA Taurine Upregulated Gene 1 as a Potential Biomarker in the Clinicopathology and Prognosis of Multiple Malignant Tumors: A Meta-Analysis

Qi Huang,1,2 Jingjing Wu,¹ Hui Wang,¹ Na Li,¹ Zhen Yang,¹ and Mingjun Zhang¹

¹Department of Oncology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
²Cancer Institute (Key Laboratory of Cancer Prevention & Intervention, National Ministry of Education, Provincial Key Laboratory of Molecular Biology in Medical Sciences), Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China

Correspondence should be addressed to Mingjun Zhang; zhangmingjun@ahmu.edu.cn

Received 9 September 2020; Revised 9 February 2021; Accepted 17 February 2021; Published 2 March 2021

Academic Editor: Yuzhen Xu

Copyright © 2021 Qi Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Background. The lncRNA taurine upregulated gene 1 (TUG1) is a recently identified potential biomarker in cancer. However, its prognostic role in various cancers is inconsistent among published data. We conducted this meta-analysis to comprehensively confirm the prognostic effect of TUG1 in malignant tumors. Methods. We systemically analyzed the prognostic-predictive capacity of TUG1 through amplifying sample sizes and cancer types. STATA 12.0 was applied for this meta-analysis. Results. A total of 57 eligible studies were included in our meta-analysis. The pooled results suggested that overexpression of TUG1 was significantly correlated with unfavorable overall survival (OS) (, ), shorter recurrence-free survival (RFS) (, ), and shorter event-free survival (EFS) (, ) in patients with cancer. In the subgroup analysis by cancer type, elevated TUG1 expression was associated with poorer survival in patients with gastrointestinal cancer, urinary tumors, gynecological tumors, hematological tumors, and osteosarcoma. However, high expression of TUG1 in respiratory tumors indicated a better prognosis. There was no correlation between high TUG1 expression and OS in patients with head and neck neoplasms or melanoma. Additionally, overexpression of TUG1 was found to be correlated with low-grade tumor differentiation, advanced tumor stage, positive lymphatic metastasis, and positive distant metastasis. Conclusions. High TUG1 expression correlates with poor prognosis and advanced clinicopathological features, verifying the prognostic-predictive capacity of TUG1 in tumors, especially in gastrointestinal cancer, urinary tumors, gynecological tumors, hematological tumors, and osteosarcoma. Meanwhile, the prognostic role of TUG1 in respiratory tumor may be opposite to other tumors.

1. Introduction

Long noncoding RNAs (lncRNAs) are an emerging class of vital regulators participating in various biological functions and disease processes to different degrees [1, 2]. Next-generation sequencing has revealed that specific lncRNAs are mutated or aberrantly expressed in cancers, and the specific role of lncRNAs in different tumors is yet to be annotated [3].

The lncRNA taurine upregulated gene 1 (TUG1) has been reported to exert oncogenic or tumor suppressive function in cancer through altering cancer-related gene expression at the transcriptional level. According to previous studies, TUG1 was found to be upregulated and oncogenic in a broad spectrum of cancers, including colorectal cancer, bladder cancer, esophageal squamous cell carcinoma, and osteosarcoma [4–7]. Meanwhile, in some types of breast cancer, non-small-cell lung cancer, and glioma, TUG1 was expressed at a low level when compared with noncancerous tissues and acts as a tumor suppressor [8–10]. Meta-analyses have attempted to demonstrate the potential diagnostic or prognostic role of TUG1 in cancer, but the conclusions were not consistent [11–18]. In recent years, studies examining TUG1 expression have been conducted through high-throughput whole-genome sequencing or quantitative real-time polymerase chain reaction (qRT-PCR), and we carried out the current meta-analysis to evaluate the role of TUG1 in tumors by expanding the number of samples and tumor types. This research may provide additional evidence for TUG1 in predicting the prognosis of tumors.

2. Materials and Methods

2.1. Literature Search Strategy

Until January 15, 2021, relevant literature concerning the expression of the lncRNA TUG1 in cancer was extracted from databases including PubMed, Embase, and Web of Science, together with three Chinese databases: China National Knowledge Infrastructure (CNKI), Wanfang, and Weipu. Key terms and all possible combinations were as follows: ‘taurine upregulated gene 1 OR TUG1’ AND ‘cancer OR tumor OR neoplasm OR carcinoma.’ The reference lists of all primary studies were also examined to identify additional eligible studies.

2.2. Study Selection

All eligible literature included in our meta-analysis met the following criteria: (1) The expression of the lncRNA TUG1 was measured in human tumors, and patients were grouped according to the expression levels of TUG1. (2) Assessment of the relationship between TUG1 expression and overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), recurrent-free survival (RFS), event-free survival (EFS), or clinical-pathological parameters such as tumor differentiation, tumor stage, and metastasis. (3) Sufficient information was provided to estimate the hazard ratio (HR) or odds ratio (OR) and their 95% confidence intervals (CIs).

The articles were excluded if they had the following characteristics: (1) letters, reviews, case reports, and conference abstracts without original data; (2) laboratory studies conducted at the cellular level only; (3) lack of available data or survival curves to compute HRs, ORs, or the corresponding 95% CIs, and (4) multiple duplicate publications with overlapping populations, excluding the smaller sample cohort.

2.3. Data Extraction and Assessment of Study Quality

Two investigators (Jingjing Wu and Hui Wang) independently extracted data and assessed study quality using a standardized form. Any discrepancy was arbitrated by a third reviewer (Qi Huang). The following characteristics were retrieved: first author’s name, publication year, country of patients’ origin, tumor type, sample size, number of patients in the TUG1 level group, tumor stage, detection method of TUG1 expression, survival data (obtained directly or extracted from Kaplan-Meier survival curve), clinical-pathological data, and Newcastle-Ottawa Quality Assessment Scale (NOS) score.

The quality assessment of eligible studies was in accordance with the NOS. Our quality score was judged on three sections: selection, comparability, and exposure or outcome. With a mean score of 6.9 from enrolled studies, we defined studies scored 7 or above as high quality.

2.4. Statistical Analysis

All data analysis was performed using STATA software version 12.0 (Stata Corporation, College Station, TX, USA). We calculated the pooled HRs and the 95% CIs of the included articles to assess the impact of TUG1 on patient prognosis and clinical-pathological characteristics. OS, PFS, DFS, RFS, and EFS were all included in outcome analyses. HRs and their corresponding 95% CIs described in the literature were adopted directly. Otherwise, they were extracted from Kaplan-Meier curves by Engauge Digitizer version 4.1 (http://digitizer.sourceforge.net/). Additionally, we computed the ORs and their 95% CIs to explore the correlation between TUG1 expression and the clinical-pathological parameters of all tumors. In our analysis, an indicated that a high expression of TUG1 was an unfavorable factor in cancer, and an implied a worse parameter correlated with elevated TUG1 expression. Heterogeneity assessment was conducted by a Chi-square-based statistical test and Higgins -squared statistic. When the % or , this indicated that there was substantial heterogeneity among the studies, and a random effects model was applied. When % or , a fixed effects pattern was used. Sensitivity analysis was performed to assess the robustness of the overall results. Begg’s test was conducted to determine the potential publication bias, with indicating a clear publication bias. values less than 0.05 were considered statistically significant.

3. Results

3.1. Study Characteristics

According to the strategy depicted in Figure 1, a total of 57 eligible studies involving 8753 patients were included to assess the association of TUG1 with survival and clinicopathological characteristics [4, 6, 9, 10, 19–71]. Among them, Zhou et al. [40] contained 8 eligible cohorts with different types of tumors, and Gradia et al. [62] analyzed two subtypes of breast cancer. These cohorts were analyzed separately. The detailed characteristics of the included studies are summarized in Table 1, which shows that we included 8753 patients, and the studies were published from 2014 to 2021. Among the 57 studies (65 cohorts), 48 cohorts were conducted in China, 12 cohorts data were extracted from the Cancer Genome Atlas (TCGA), and the remaining three cohorts were performed in Egypt, Germany, and the Czech Republic. Thirty-seven of the included cohorts enrolled less than 100 patients and 24 cohorts recruited more than 100 patients. The incorporated cancer types included glioblastoma (GBM) [10, 42, 63], nasopharyngeal carcinoma (NPC) [49], oral squamous cell carcinoma (OSCC) [58], esophageal squamous cell carcinoma (ESCC) [6, 21, 29, 67], breast cancer (BC) [28, 40, 62], small cell lung cancer (SCLC) [53], non-small-cell lung cancer (NSCLC) [9, 19, 25, 69], hepatocellular carcinoma (HCC) [40], gastric cancer (GC) [23, 24, 40, 41, 65, 66], cholangiocarcinoma (CCA) [60, 61], pancreatic carcinoma (PC) [35, 50, 57], colorectal cancer(CRC) [4, 39, 40, 46, 51, 52], renal cell carcinoma(RCC) [54], urothelial carcinoma(UC) [56], bladder cancer(BLC) [31, 36, 40, 68, 70], prostate cancer (PCa) [22, 26, 37, 38], cervical cancer (CC) [27, 59], endometrial carcinoma (EC) [32], ovarian cancer (OC) [20, 30, 44], osteosarcoma (OSA) [40, 45, 55, 71], acute myeloid leukemia (AML) [33, 43, 47, 48], non-Hodgkin’s lymphoma (NHL) [64], and melanoma [34, 40]. RNA sequencing and qRT-PCR methods were used to determine TUG1 expression level, and the median value was applied as a cut-off value in most studies. As to the prognostic analysis, 61 cohorts evaluated the prognostic impact of TUG1 on OS, and 12 cohorts reported the impact of TUG1 on RFS, DFS, RFS, and EFS.

Figure 1: Flow diagram of the selection procedure for the studies.

Table 1: Characteristics summary of the 57 eligible studies in this meta-analysis.

Study
Year
Origin of population
Cancer type
Sample number
lncRNA TUG1 high/low
Stage
Detection method
Study endpoints
Hazard ratios
NOS

S-h Guo
2020
China
NSCLC
132
52/80
I-IV
qRT-PCR
OS
K-M
6

N El-Khazragy
2020
Egypt
OC
100
50/50
I-IV
qRT-PCR
OS/PFS
K-M
6

G Jin
2020
China
ESCC
50
27/23
I-IV
qRT-PCR
OS
K-M
6

D-h Xiu
2020
China
PCa
50
25/25
I-IV
qRT-PCR
OS
K-M
7

Y-h Hao
2020
China
GC
110
80/30
I-IV
qRT-PCR
OS
K-M
8

J-b Zhong
2020
China
GC
83
49/34
I-IV
qRT-PCR
OS
HR
7

Y-n Xu
2020
China
NSCLC
79
45/34
I-IV
qRT-PCR
OS
K-M
8

X-z Chen
2020
China
PCa
54
16/38
I-IV
qRT-PCR
OS/PFS
HR/K-M
8

Y Xia
2020
China
CC
137
69/68
I-II
qRT-PCR
OS
HR/K-M
8

X-d Lu
2020
China
BC
90
52/38
I-III
qRT-PCR
OS
HR/K-M
8

Z-f Wang
2020
TCGA
ESCC
86
72/14
NA
RNA-seq
OS
K-M
6

L-z Gu
2020
China
OC
41
21/20
II-IV
qRT-PCR
OS
K-M
6

J Yang
2019
China
BLC
68
38/30
II-IV
qRT-PCR
OS
HR/K-M
8

X-r Lv
2019
China
EC
58
37/21
I-IV
qRT-PCR
OS
HR/K-M
8

Q Li
2019
China
AML
36
18/18
NA
qRT-PCR
OS
K-M
7

Y-q Wang
2019
China
Melanoma
40
NA
NA
qRT-PCR
OS
HR/K-M
5

B-q Hui
2019
China
PC
42
21/21
I-IV
qRT-PCR
OS
K-M
8

G Yu
2019
China
BLC
87
44/43
NA
qRT-PCR
OS
K-M
6

X-l Yang
2019
China
PCa
46
23/23
NA
qRT-PCR
DFS
K-M
6

T Xu
2019
China
PCa
70
35/35
I-IV
qRT-PCR
OS
K-M
7

M Wang
2019
China
CRC
124
62/62
II-III
qRT-PCR
RFS
K-M
8

H Zhou
2019
TCGA
HCC
371
91/274
NA
RNA-seq
OS
K-M
5

H Zhou
2019
TCGA
Melanoma
459
115/344
NA
RNA-seq
OS
K-M
5

H Zhou
2019
TCGA
OSA
259
65/194
NA
RNA-seq
OS
K-M
5

H Zhou
2019
TCGA
RCC
287
73/214
NA
RNA-seq
OS
K-M
5

H Zhou
2019
TCGA
BLC
406
102/304
NA
RNA-seq
OS
K-M
5

H Zhou
2019
TCGA
CRC
279
69/210
NA
RNA-seq
OS
K-M
5

H Zhou
2019
TCGA
GC
392
93/299
NA
RNA-seq
OS
K-M
5

H Zhou
2019
TCGA
BC (triple negative)
1081
273/808
NA
RNA-seq
OS
K-M
5

Y Zhang
2019
China
GC
85
48/37
I-IV
qRT-PCR
OS
K-M
7

W Wang
2018
China
GBM
51
NA
NA
RNA-seq
OS
HR
5

X-f Wang
2018
China
AML
186
93/93
NA
qRT-PCR
OS/EFS
HR/K-M
7

T-h Li
2018
China
OC
96
NA
I-IV
qRT-PCR
OS
HR/K-M
7

Q-l Wang
2018
China
OSA
94
47/47
IIA/IIB-III
qRT-PCR
OS
HR/K-M
8

C-h Xiao
2018
China
CRC
90
45/45
I-IV
qRT-PCR
OS/DFS
K-M
7

W-f Luo
2018
China
AML
73
NA
NA
qRT-PCR
OS
HR/K-M
6

J Qin
2018
China
AML
236
NA
NA
qRT-PCR
OS/EFS
HR/K-M
6

C-h Xu
2018
China
ESCC
42
21/21
NA
qRT-PCR
OS
K-M
7

W Qian
2018
China
NPC
48
28/20
I-IV
qRT-PCR
OS
K-M
8

Y-b Lu
2018
China
PC
72
50/22
I-IV
qRT-PCR
OS
K-M
8

K Yao
2018
China
CRC
185
129/56
I-IV
qRT-PCR
OS
HR/K-M
8

G-m Zheng
2018
China
CRC
90
51/39
I-IV
qRT-PCR
OS
HR/K-M
8

Y-c Niu
2017
China
SCLC
33
16/17
NA
qRT-PCR
OS
K-M
7

P-q Wang
2017
China
RCC (ccRCC)
203
100/103
I-IV
qRT-PCR
OS
HR/K-M
8

Y Wang
2017
China
OSA
44
30/14
I-IIA/IIB-III
qRT-PCR
OS
K-M
8

J Droop
2017
Germany
UC
106
NA
I-IV
qRT-PCR
OS/DFS
HR/K-M
8

L Zhao
2017
China
PC
34
18/16
I-IV
qRT-PCR
OS
K-M
8

G-q Yan
2017
China
OSCC
46
24/24
I-IV
qRT-PCR
OS
HR/K-M
8

J Zhu
2017
China
CC
59
30/29
I-IIA/IIB-IIIA
qRT-PCR
OS
K-M
8

Y Xu
2017
China
CCA
51
30/29
I-IV
qRT-PCR
OS
K-M
8

B Zeng
2017
China
CCA
102
NA
I-IV
qRT-PCR
OS/DFS
HR/K-M
7

D-f Gradia
2017
TCGA
BC (luminal B)
122
92/30
I-IV
RNA-seq
DFS
HR/K-M
5

D-f Gradia
2017
TCGA
BC (HER2-enriched)
56
14/42
I-IV
RNA-seq
DFS
HR/K-M
5

Z Baratieh
2017
TCGA
GBM
260
130/130
NA
RNA-seq
OS
K-M
5

D Liu
2017
China
NHL
108
61/47
I-IV
qRT-PCR
OS
HR/K-M
8

T Shen
2017
China
GC
48
35/13
I-IV
qRT-PCR
OS
K-M
8

J Li
2016
China
GBM
120
60/60
I-IV
qRT-PCR
OS
K-M
8

J-f Sun
2016
China
CRC
120
72/48
I-IV
qRT-PCR
OS
K-M
8

E Zhang
2016
China
GC
100
50/50
I-IV
qRT-PCR
OS
HR/K-M
8

L Jiang
2016
China
ESCC
218
109/109
I-IV
qRT-PCR
OS
HR/K-M
8

R Iliev
2016
Czech Republic
BLC
47
26/21
II-IV
qRT-PCR
OS
HR/K-M
7

P-c Lin
2016
China
NSCLC
89
31/58
I-IV
qRT-PCR
OS
K-M
8

J-m Tan
2015
China
BLC
54
27/27
I-IV
qRT-PCR
OS
K-M
7

B Ma
2015
China
OSA
76
41/35
I-III
qRT-PCR
OS/PFS
HR/K-M
8

E-b Zhang
2014
China
NSCLC
192
96/96
I-IV
qRT-PCR
OS
K-M
6

Abbreviations: AML: acute myeloid leukemia; BC: breast cancer; BLC: bladder cancer; CC: cervical cancer; CCA: cholangiocarcinoma; CRC: colorectal cancer; EC: endometrial carcinoma; ESCC: esophageal squamous cell carcinoma; GBM: glioblastoma; GC: gastric cancer; HCC: hepatocellular carcinoma; NHL: non-Hodgkin’s lymphoma; NPC: nasopharyngeal carcinoma; NSCLC: non-small-cell lung cancer; OC: ovarian cancer; OSA: osteosarcoma; OSCC: oral squamous cell carcinoma; PC: pancreatic carcinoma; PCa: prostate cancer; RCC: renal cell carcinoma; SCLC: small cell lung cancer; UC: urothelial carcinoma.

3.2. Correlation of TUG1 Expression with Survival

A total of 8405 patients were enrolled to assess the association between TUG1 level and OS. A random effect model was employed due to clear heterogeneity (%, ). A significant correlation was found between high TUG1 expression and unfavorable OS, and the pooled HR was 1.70 (95% CI: 1.48-1.95, ) (Figure 2). Twelve cohorts were included to investigate the relationship between TUG1 expression and PFS, DFS, RFS, and EFS. The results showed that TUG1 expression was not significantly correlated with PFS () or DFS (), but a tendency toward worse RFS () or EFS () was revealed in patients with high level of TUG1 expression, although the number of included studies was extremely small (Figure 3).

Figure 2: Forest plot for the association between high TUG1 expression and OS of patients with different tumor types.

Figure 3: Forest plot for the relationship between high TUG1 expression and PFS/DFS/RFS/EFS of patients with different tumor types.

3.3. Subgroup Analyses of the Correlation between High TUG1 Expression and OS in Cancer

To address the heterogeneity among OS datasets, we performed subgroup analyses according to patients’ origin, cancer type, sample size, and detection method (Table 2). The results revealed a marked association between high expression of TUG1 and unfavorable OS in patients from China (, 95% CI: 1.59-2.30, ) and patients who were not from China (, 95% CI: 1.05-1.54, ). Likewise, TUG1 overexpression predicted a worse outcome no matter in the subgroup containing patients more than 100 (, 95% CI: 1.08-1.60, ) and in the subgroup with less than 100 patients (, 95% CI: 1.72-2.63, ). When grouped according to TUG1 detection method, the pooled HRs for the qRT-PCR subgroup and RNA sequencing subgroup were 1.88 (95% CI: 1.57-2.25, ) and 1.29 (95% CI: 1.07-1.57, ), respectively. When sorted by cancer type, TUG1 expression significantly predicted unfavorable OS in gastrointestinal cancer (, 95% CI: 1.69-2.67, ), urinary tumors (, 95% CI: 1.27-2.79, ), gynecologic tumors (, 95% CI: 1.40-2.89, ), hematological tumors (, 95% CI: 1.87-3.18, ), and osteosarcoma (, 95% CI: 1.16-2.14, ). Meanwhile, a high TUG1 level predicted favorable OS in respiratory tumors (, 95% CI: 0.36-0.70, ). TUG1 expression had no significant prognostic value in head and neck neoplasms and melanoma (Figures 4(a)–4(c)). Still, further stratified analysis indicated that elevated TUG1 exhibited a favorable prognostic value for NSCLC (, 95% CI: 0.35-0.58, ) and an unfavorable prognostic value for RCC (, 95% CI: 1.00-2.61, ). However, the merged HR indicated no significant relationship between TUG1 expression and OS in BLC () and GBM () (Figure 4(d)). Significant heterogeneity existed in all subgroups except for the hematological tumor subgroup (Table 2).

Table 2: Subgroup analysis of the pooled HRs of OS with overexpressed lncRNA TUG1 in patients with cancer.

Stratified analysis
Number of cohorts
Number of patients
Pooled HR (95% CI)
value
Heterogeneity

(%)
value

Origin

    China
48
4272
1.93 (1.59-2.30)
<0.001
88.3
<0.001

    Non-China
13
4133
1.27 (1.05-1.54)
0.013
76.6
<0.001

Cancer type

    Head and neck neoplasms
5
525
0.83 (0.35-2.01)
0.687
90.3
<0.001

    Respiratory tumor
5
525
0.50 (0.36-0.70)
<0.001
35.5
0.185

    Gastrointestinal cancer
21
2650
2.12 (1.69-2.67)
<0.001
82.2
<0.001

    Urinary tumor
11
1432
1.89 (1.27-2.79)
0.002
87.4
<0.001

    Gynecologic tumor
8
1662
2.01 (1.40-2.89)
<0.001
76.5
<0.001

    Hematological tumor
5
639
2.44 (1.87-3.18)
<0.001
0
0.587

    Osteosarcoma
4
473
1.58 (1.16-2.14)
0.003
50.2
0.110

    Melanoma
2
499
1.65 (0.80-3.38)
0.174
88.3
0.003

Number of patients

    <100
37
2256
2.12 (1.72-2.63)
0.007
88.3
<0.001

    ≥100
24
6149
1.31 (1.08-1.60)
<0.001
84.1
<0.001

Detection method

    qRT-PCR
50
4644
1.88 (1.57-2.25)
<0.001
88.0
<0.001

    RNA-seq
11
4109
1.29 (1.07-1.57)
0.009
76.7
<0.001

(a)

(b)

(c)

(d)

Figure 4: Stratified analyses for the association between high TUG1 expression with OS by cancer type. (a) Gastrointestinal cancer. (b) Gynecologic tumor, hematological tumor, melanoma, or osteosarcoma. (c) Respiratory tumor, urinary tumor, or head and neck neoplasm. (d) Non-small-cell lung cancer, bladder cancer, renal cell carcinoma, or glioblastoma.

3.4. Impact of High TUG1 Expression on Clinicopathological Parameters

Clinicopathological analyses were conducted according to common parameters, such as patients’ age, gender, tumor grade, tumor stage, lymph node metastasis, and distant metastasis. 1332 patients in fifteen cohorts were collected to assess the relationship between TUG1 expression and tumor differentiation. A significant connection was found between high TUG1 expression and low tumor differentiation in cancer patients, and the pooled OR was 1.99 (95% CI: 1.10-3.60, ) with statistical heterogeneity (%, ). Twenty cohorts with 1828 patients showed an association between TUG1 overexpression and tumoral TNM stage. The pooled OR was 2.82 (95% CI: 1.84-4.33, ) with significant heterogeneity (%, ), demonstrating that patients with up-regulated TUG1 expression are more likely to develop higher tumor stage. Subsequently, we investigated the prognostic value of TUG1 with lymph node metastasis and distant metastasis. The results indicated that patients with evaluated TUG1 expression progress to lymph node metastasis and distant metastasis by comparing the incidence of lymph node metastasis (, 95% CI: 2.23-3.92, ) and distant metastasis (, 95% CI: 1.97-6.41, ) between the high and low TUG1 expression groups. However, no significant correlation was detected for age or gender, and the pooled ORs are shown in Table 3.

Table 3: Correlation between lncRNA TUG1 and clinicopathological characteristics of tumors.

Clinicopathologial features
Number of cohorts
Number of patients
Pooled OR (95%CI)
value
Heterogeneity

(%)
value

Gender (male vs. female)
31
1869
1.03 (0.84-1.25)
0.803
0
0.872

Age (<60 vs. ≥60)
15
1161
0.93 (0.73-1.18)
0.537
0
0.799

Tumor grade (low vs. high+moderate)
15
1332
1.99 (1.10-3.60)
0.023
80.7
<0.001

Tumor stage (III+IV vs. I+II)
20
1828
2.82 (1.84-4.33)
<0.001
72.2
<0.001

Lymph node metastasis (+ vs. -)
20
1835
2.96 (2.23-3.92)
<0.001
39.6
0.036

Distant metastasis (+ vs. -)
10
851
3.56 (1.97-6.41)
<0.001
57.1
0.013

3.5. Sensitivity Analysis

Sensitivity analysis was conducted to evaluate the robustness of the overall outcome. The pooled HRs were recalculated after excluding each single cohort successively, and the results indicated that the HR of high TUG1 expression on OS ranged from 1.67 (95% CI: 1.47-1.91) to 1.75 (95% CI: 1.53-2.01) (Figure 5(a)), and the HR of high TUG1 expression on PFS/DFS/RFS/EFS ranged from 1.51 (95% CI: 1.06-2.16) to 1.77 (95% CI: 1.31-2.38) (Figure 5(b)), suggesting that a positive association between high TUG1 level and the prognosis of cancer patients existed no matter which study was removed.

(a)

(b)

Figure 5: Sensitivity analysis for the meta-analysis of OS (a) and DFS/RFS/EFS (b) in all patients.

3.6. Publication Bias

The potential for publication bias was assessed by funnel plots and Begg’s test. The shape of the funnel plots for OS or PFS/DFS/RFS/EFS were asymmetric (Figure 6), but the value of the Begg’s test for OS () and DFS/RFS/EFS () indicated that there was no severe publication bias in our present meta-analysis.

(a)

(b)

Figure 6: Funnel plot analysis of potential publication bias for OS (a) and DFS/RFS/EFS (b).

4. Discussion

lncRNAs participate in regulating tumoral biological processes by competitively interacting with certain microRNAs, altering the expression of key component proteins in the gene regulatory system [72, 73]. To date, numerous studies have confirmed that mutation or misregulation of lncRNAs may promote tumorigenesis and metastasis and show that they are novel biomarkers and therapeutic targets for cancer [3, 74, 75].

TUG1, a 7.1 kb lncRNA, was first identified as a transcript upregulated in response to taurine treatment, which affects mouse retinal development [76]. Increasing numbers of studies have revealed that TUG1 is related to tumors. In most malignancies, TUG1 has been reported to be overexpressed and be involved in regulating of multiple processes in tumor progression, invasion and angiogenesis [77]. It has been confirmed by immunoprecipitation that TUG1 may recruit and bind to polycomb repressive complex 2 (PRC2) to regulate gene expression involved in tumorigenesis and tumor development [78, 79]. Additionally, TUG1 can also exert its oncogenic role via sponging tumoral suppressor microRNAs or modulating cancer-related signaling pathways like Wnt, MAPK, or Notch1 [80–82]. However, TUG1 was found to be downregulated and acted as a tumor suppressing gene in some types of breast cancer, NSCLC, and glioma [8–10]. For example, TUG1 can promote tumor cell apoptosis and inhibit the growth of glioma by activating caspase 3- and caspase 9-mediated proapoptosis, inhibiting bcl-2 mediated antiapoptosis [10, 83]. Thus, the prognostic-predictive value of TUG1 in cancer is still uncertain and needs further evaluation. The expression level of TUG1 in tumors and the correlation of TUG1 with patients’ survival and clinicopathological characteristics have been previously assessed. In this study, we collected specific data of TUG1 involvement in tumor progression and survival of patients with different types of tumors, and we analyzed and summarized whether TUG1 is suitable as a prognostic marker for these tumors.

Although multiple meta-analyses have suggested that TUG1 could be used as a tumor-related prognostic marker, most studies were conducted before 2017 [12–18]. The prognostic value of TUG1 in some particular types of tumors is still controversial, and its clinical application is relatively limited. With the development of tumoral genome sequencing technology, more data on TUG1 have been published over the past few years. In this study, a total of 57 articles (65 cohorts) were included to comprehensively analyze the role of TUG1 in 22 types of tumors from across the body, and the results provide more information for TUG1 as a tumor prognostic biomarker to be applied in clinical prognostic risk analysis. Additionally, almost all the incorporated research data were from China in the previous analyses. Our research included multiple TCGA cohorts to increase the sample size and the diversity of the data, making the research results more convincing.

In our study, the results suggest that high TUG1 expression is significantly associated with worse OS in patients with malignant tumors, which is consistent with the conclusions drawn from previous studies [13, 14, 16–18]. In addition, the correlation between TUG1 expression and PFS/DFS/RFS/EFS in patients with tumors was analyzed for the first time. No significant association between TUG1 expression and PFS/DFS was found. Meanwhile, since only one included paper reported RFS and two articles reported EFS, the prognostic value of TUG1 on PFS/EFS is uncertain, even though we observed a significant value by survival analysis.

In the subgroup analysis, we found that the high expression of TUG1 was related to poor OS of patients with gastrointestinal cancers (ESCC, GC, CRC, PC, HCC, and CCA), gynecological tumors (BC, OC, CC, and EC), hematological tumors (AML and NHL), urinary tumors (RCC, BLC, UC, and PCa), and OSA. This result was not reported in previous analyses, which may be due to the limited number of eligible studies for each tumor type. In urinary tumors, only one study on UC showed that a high expression of TUG1 was significantly related to better prognosis (, 95% CI: 0.39-0.97, ). BLC included five eligible studies. One study enrolling 406 patients from the TCGA database suggested that patients with high expression of TUG1 tended to have better prognosis, but no statistical difference was found [40]. Another 4 studies included 256 bladder cancer patients, 3 studies from China and 1 from the Czech Republic, with the results suggesting that patients with higher TUG1 expression have a lower survival rate. Although the overall analysis of urinary system tumors confirmed that the high expression of TUG1 has a prognostic value for patients, it is still necessary to expand the sample size to evaluate whether TUG1 plays a role in UC that can be distinguished from other urinary tumors, and the prognostic value of TUG1 in BLC also needs to be further verified. In respiratory tumors, 4 NSCLC studies indicated that patients with upregulated TUG1 levels have better prognosis (, 95% CI: 0.27-0.80, ), which was opposite to other tumor types. While only one SCLC article showed that patients with upregulated TUG1 expression tend to have worse prognosis, no statistical significance was found. The difference in the role of TUG1 in NSCLS and SCLC must be clarified by expanding the included studies in the future, and the specific lung tissue and pathological type may determine the prognostic role of TUG1 in lung cancer. In head and neck neoplasms and malignant melanoma, the expression of TUG1 was not significantly correlated with the survival of tumor patients. Head and neck neoplasm analysis included 3 GBM, 1 NPC, and 1 OSCC study. Of the 3 GBM articles, 2 were from China, indicating that patients with high TUG1 level have better prognosis. One TCGA data analysis was contrary to the previous two studies, suggesting that patients with low TUG1 expression have a longer survival time. Two melanoma studies displayed an association between upregulated TUG1 and poor prognosis, with no statistical significance. All these tumors need to be further studied to clarify whether TUG1 has prognostic value. The subgroup analysis based on patients’ origin, sample size, and TUG1 detection method suggested that the prognostic value of TUG1 was not affected by these factors.

Furthermore, we analyzed the clinicopathological parameters related to TUG1. Different from previous analyses, the high expression of TUG1 was positively associated with tumor TNM stage, tumor differentiation, lymph node metastasis, and distant metastasis, which further confirmed the meaningful prognostic value of TUG1 in various tumors.

There are some limitations in the current study, and it should be interpreted with caution. First, the survival analysis data were not provided directly in some studies and needed to be extracted from Kaplan-Meier curves. However, some Kaplan-Meier curves were relatively difficult to extract due to the low pixel count [69] or the large sample size [40, 63], and the data obtained may contain errors. For example, the value displayed in Zhou et al.’ work suggested that no statistical difference was found between TUG1 expression and the survival of patients in gastric cancer or breast cancer, whereas a statistical difference appeared in these two tumors through repeated extraction and calculation [40]. Thus, we utilized the data acquired by actual extraction for statistical analysis. Second, the prognostic role of TUG1 in head and neck neoplasms and malignant melanoma has not been confirmed. This may be due to the limitation of the study samples, and more sample analysis is needed in the future. Third, there was statistical heterogeneity among the studies included in this research. This may be due to differences in tumor types, the number of cases, the patient sources, the detection methods, and the cut-off values of TUG1. Of note, the difference in TUG1 cut-off values and units may influence the application of TUG1 in the clinic.

5. Conclusions

Despite the limitations described above, our meta-analysis still showed that elevated TUG1 is significantly related to favorable prognosis of respiratory tumors and poor prognosis of gastrointestinal cancers, gynecological tumors, hematological tumors, urinary tumors, and osteosarcoma. No definite conclusion has been reached for head and neck neoplasms and malignant melanoma, and further analysis with a larger sample size is needed. Furthermore, the high expression of TUG1 is significantly associated with late tumor stage, poor differentiation, more lymph node metastases, and distant metastasis of tumors.

Data Availability

All data generated or analyzed during this study are included in this article.

Conflicts of Interest

All authors declare that no conflict of interest exists.

Authors’ Contributions

Qi Huang did the literature research, data analysis, and manuscript preparation. Jingjing Wu did the literature research, data analysis, and manuscript preparation. Hui Wang did the data extraction. Na Li did the manuscript editing. Zhen Yang did the manuscript editing. Mingjun Zhang did the study design. Qi Huang and Jingjing Wu contributed equally to this work.

Acknowledgments

This study was supported by grants from Natural Science Foundation of Anhui Province of China (Nos. 1908085MH262, 2008085QH379, and 2008085QH413) and Incubation Program of National Natural Science Foundation from the Second Hospital of Anhui Medical University (No. 2019GQFY09, No. 2019GQFY12).

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