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

Authors: Qi Huang; Jingjing Wu; Hui Wang; Na Li; Zhen Yang; Mingjun Zhang
Journal: Disease Markers
 (2021)

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## 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) (HR=1.70, p<0.001), shorter recurrence-free survival (RFS) (HR=2.40, p≤0.001), and shorter event-free survival (EFS) (HR=1.88, p<0.001) 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.


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## Body

## 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 HR>1 indicated that a high expression of TUG1 was an unfavorable factor in cancer, and an OR>1 implied a worse parameter correlated with elevated TUG1 expression. Heterogeneity assessment was conducted by a Chi-square-based Q statistical test and Higgins I-squared statistic. When the inconsistencyindexI2≥50% or p<0.10, this indicated that there was substantial heterogeneity among the studies, and a random effects model was applied. When I2<50% or p<0.10, 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 p<0.05 indicating a clear publication bias. p values less than 0.05 were considered statistically significant.


## 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 HR>1 indicated that a high expression of TUG1 was an unfavorable factor in cancer, and an OR>1 implied a worse parameter correlated with elevated TUG1 expression. Heterogeneity assessment was conducted by a Chi-square-based Q statistical test and Higgins I-squared statistic. When the inconsistencyindexI2≥50% or p<0.10, this indicated that there was substantial heterogeneity among the studies, and a random effects model was applied. When I2<50% or p<0.10, 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 p<0.05 indicating a clear publication bias. p values less than 0.05 were considered statistically significant.


## 3. Results

### 3.1. Study Characteristics

According to the strategy depicted in Figure1, 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.
StudyYearOrigin of populationCancer typeSample numberlncRNA TUG1 high/lowStageDetection methodStudy endpointsHazard ratiosNOSS-h Guo2020ChinaNSCLC13252/80I-IVqRT-PCROSK-M6N El-Khazragy2020EgyptOC10050/50I-IVqRT-PCROS/PFSK-M6G Jin2020ChinaESCC5027/23I-IVqRT-PCROSK-M6D-h Xiu2020ChinaPCa5025/25I-IVqRT-PCROSK-M7Y-h Hao2020ChinaGC11080/30I-IVqRT-PCROSK-M8J-b Zhong2020ChinaGC8349/34I-IVqRT-PCROSHR7Y-n Xu2020ChinaNSCLC7945/34I-IVqRT-PCROSK-M8X-z Chen2020ChinaPCa5416/38I-IVqRT-PCROS/PFSHR/K-M8Y Xia2020ChinaCC13769/68I-IIqRT-PCROSHR/K-M8X-d Lu2020ChinaBC9052/38I-IIIqRT-PCROSHR/K-M8Z-f Wang2020TCGAESCC8672/14NARNA-seqOSK-M6L-z Gu2020ChinaOC4121/20II-IVqRT-PCROSK-M6J Yang2019ChinaBLC6838/30II-IVqRT-PCROSHR/K-M8X-r Lv2019ChinaEC5837/21I-IVqRT-PCROSHR/K-M8Q Li2019ChinaAML3618/18NAqRT-PCROSK-M7Y-q Wang2019ChinaMelanoma40NANAqRT-PCROSHR/K-M5B-q Hui2019ChinaPC4221/21I-IVqRT-PCROSK-M8G Yu2019ChinaBLC8744/43NAqRT-PCROSK-M6X-l Yang2019ChinaPCa4623/23NAqRT-PCRDFSK-M6T Xu2019ChinaPCa7035/35I-IVqRT-PCROSK-M7M Wang2019ChinaCRC12462/62II-IIIqRT-PCRRFSK-M8H Zhou2019TCGAHCC37191/274NARNA-seqOSK-M5H Zhou2019TCGAMelanoma459115/344NARNA-seqOSK-M5H Zhou2019TCGAOSA25965/194NARNA-seqOSK-M5H Zhou2019TCGARCC28773/214NARNA-seqOSK-M5H Zhou2019TCGABLC406102/304NARNA-seqOSK-M5H Zhou2019TCGACRC27969/210NARNA-seqOSK-M5H Zhou2019TCGAGC39293/299NARNA-seqOSK-M5H Zhou2019TCGABC (triple negative)1081273/808NARNA-seqOSK-M5Y Zhang2019ChinaGC8548/37I-IVqRT-PCROSK-M7W Wang2018ChinaGBM51NANARNA-seqOSHR5X-f Wang2018ChinaAML18693/93NAqRT-PCROS/EFSHR/K-M7T-h Li2018ChinaOC96NAI-IVqRT-PCROSHR/K-M7Q-l Wang2018ChinaOSA9447/47IIA/IIB-IIIqRT-PCROSHR/K-M8C-h Xiao2018ChinaCRC9045/45I-IVqRT-PCROS/DFSK-M7W-f Luo2018ChinaAML73NANAqRT-PCROSHR/K-M6J Qin2018ChinaAML236NANAqRT-PCROS/EFSHR/K-M6C-h Xu2018ChinaESCC4221/21NAqRT-PCROSK-M7W Qian2018ChinaNPC4828/20I-IVqRT-PCROSK-M8Y-b Lu2018ChinaPC7250/22I-IVqRT-PCROSK-M8K Yao2018ChinaCRC185129/56I-IVqRT-PCROSHR/K-M8G-m Zheng2018ChinaCRC9051/39I-IVqRT-PCROSHR/K-M8Y-c Niu2017ChinaSCLC3316/17NAqRT-PCROSK-M7P-q Wang2017ChinaRCC (ccRCC)203100/103I-IVqRT-PCROSHR/K-M8Y Wang2017ChinaOSA4430/14I-IIA/IIB-IIIqRT-PCROSK-M8J Droop2017GermanyUC106NAI-IVqRT-PCROS/DFSHR/K-M8L Zhao2017ChinaPC3418/16I-IVqRT-PCROSK-M8G-q Yan2017ChinaOSCC4624/24I-IVqRT-PCROSHR/K-M8J Zhu2017ChinaCC5930/29I-IIA/IIB-IIIAqRT-PCROSK-M8Y Xu2017ChinaCCA5130/29I-IVqRT-PCROSK-M8B Zeng2017ChinaCCA102NAI-IVqRT-PCROS/DFSHR/K-M7D-f Gradia2017TCGABC (luminal B)12292/30I-IVRNA-seqDFSHR/K-M5D-f Gradia2017TCGABC (HER2-enriched)5614/42I-IVRNA-seqDFSHR/K-M5Z Baratieh2017TCGAGBM260130/130NARNA-seqOSK-M5D Liu2017ChinaNHL10861/47I-IVqRT-PCROSHR/K-M8T Shen2017ChinaGC4835/13I-IVqRT-PCROSK-M8J Li2016ChinaGBM12060/60I-IVqRT-PCROSK-M8J-f Sun2016ChinaCRC12072/48I-IVqRT-PCROSK-M8E Zhang2016ChinaGC10050/50I-IVqRT-PCROSHR/K-M8L Jiang2016ChinaESCC218109/109I-IVqRT-PCROSHR/K-M8R Iliev2016Czech RepublicBLC4726/21II-IVqRT-PCROSHR/K-M7P-c Lin2016ChinaNSCLC8931/58I-IVqRT-PCROSK-M8J-m Tan2015ChinaBLC5427/27I-IVqRT-PCROSK-M7B Ma2015ChinaOSA7641/35I-IIIqRT-PCROS/PFSHR/K-M8E-b Zhang2014ChinaNSCLC19296/96I-IVqRT-PCROSK-M6Abbreviations: 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 (I2=86.9%, p<0.001). 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, p<0.001) (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 (p=0.648) or DFS (p=0.437), but a tendency toward worse RFS (p=0.001) or EFS (p<0.001) 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 (Table2). The results revealed a marked association between high expression of TUG1 and unfavorable OS in patients from China (HR=1.93, 95% CI: 1.59-2.30, p<0.001) and patients who were not from China (HR=1.27, 95% CI: 1.05-1.54, p=0.013). Likewise, TUG1 overexpression predicted a worse outcome no matter in the subgroup containing patients more than 100 (HR=1.31, 95% CI: 1.08-1.60, p<0.001) and in the subgroup with less than 100 patients (HR=2.12, 95% CI: 1.72-2.63, p=0.007). 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, p<0.001) and 1.29 (95% CI: 1.07-1.57, p=0.009), respectively. When sorted by cancer type, TUG1 expression significantly predicted unfavorable OS in gastrointestinal cancer (HR=2.12, 95% CI: 1.69-2.67, p<0.001), urinary tumors (HR=1.89, 95% CI: 1.27-2.79, p=0.002), gynecologic tumors (HR=2.01, 95% CI: 1.40-2.89, p<0.001), hematological tumors (HR=2.44, 95% CI: 1.87-3.18, p<0.001), and osteosarcoma (HR=1.58, 95% CI: 1.16-2.14, p=0.003). Meanwhile, a high TUG1 level predicted favorable OS in respiratory tumors (HR=0.50, 95% CI: 0.36-0.70, p<0.001). 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 (HR=0.45, 95% CI: 0.35-0.58, p<0.001) and an unfavorable prognostic value for RCC (HR=1.61, 95% CI: 1.00-2.61, p=0.046). However, the merged HR indicated no significant relationship between TUG1 expression and OS in BLC (p=0.441) and GBM (p=1.135) (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 analysisNumber of cohortsNumber of patientsPooled HR (95% CI)p valueHeterogeneityI2 (%)p valueOriginChina4842721.93 (1.59-2.30)<0.00188.3<0.001Non-China1341331.27 (1.05-1.54)0.01376.6<0.001Cancer typeHead and neck neoplasms55250.83 (0.35-2.01)0.68790.3<0.001Respiratory tumor55250.50 (0.36-0.70)<0.00135.50.185Gastrointestinal cancer2126502.12 (1.69-2.67)<0.00182.2<0.001Urinary tumor1114321.89 (1.27-2.79)0.00287.4<0.001Gynecologic tumor816622.01 (1.40-2.89)<0.00176.5<0.001Hematological tumor56392.44 (1.87-3.18)<0.00100.587Osteosarcoma44731.58 (1.16-2.14)0.00350.20.110Melanoma24991.65 (0.80-3.38)0.17488.30.003Number of patients<1003722562.12 (1.72-2.63)0.00788.3<0.001≥1002461491.31 (1.08-1.60)<0.00184.1<0.001Detection methodqRT-PCR5046441.88 (1.57-2.25)<0.00188.0<0.001RNA-seq1141091.29 (1.07-1.57)0.00976.7<0.001Figure 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.
(a)(b)(c)(d)


### 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,p=0.023) with statistical heterogeneity (I2=80.7%, p<0.001). 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, p<0.001) with significant heterogeneity (I2=72.2%, p<0.001), 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 (HR=2.96, 95% CI: 2.23-3.92, p<0.001) and distant metastasis (HR=3.56, 95% CI: 1.97-6.41, p<0.001) 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 featuresNumber of cohortsNumber of patientsPooled OR (95%CI)p valueHeterogeneityI2 (%)p valueGender (male vs. female)3118691.03 (0.84-1.25)0.80300.872Age (<60 vs. ≥60)1511610.93 (0.73-1.18)0.53700.799Tumor grade (low vs. high+moderate)1513321.99 (1.10-3.60)0.02380.7<0.001Tumor stage (III+IV vs. I+II)2018282.82 (1.84-4.33)<0.00172.2<0.001Lymph node metastasis (+ vs. -)2018352.96 (2.23-3.92)<0.00139.60.036Distant metastasis (+ vs. -)108513.56 (1.97-6.41)<0.00157.10.013


### 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) (Figure5(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.Figure 5
Sensitivity analysis for the meta-analysis of OS (a) and DFS/RFS/EFS (b) in all patients.
(a)(b)


### 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 (Figure6), but the p value of the Begg’s test for OS (Pr>∣z∣=0.61) and DFS/RFS/EFS (Pr>∣z∣=0.95) indicated that there was no severe publication bias in our present meta-analysis.Figure 6
Funnel plot analysis of potential publication bias for OS (a) and DFS/RFS/EFS (b).
(a)(b)


## 3.1. Study Characteristics

According to the strategy depicted in Figure1, 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.
StudyYearOrigin of populationCancer typeSample numberlncRNA TUG1 high/lowStageDetection methodStudy endpointsHazard ratiosNOSS-h Guo2020ChinaNSCLC13252/80I-IVqRT-PCROSK-M6N El-Khazragy2020EgyptOC10050/50I-IVqRT-PCROS/PFSK-M6G Jin2020ChinaESCC5027/23I-IVqRT-PCROSK-M6D-h Xiu2020ChinaPCa5025/25I-IVqRT-PCROSK-M7Y-h Hao2020ChinaGC11080/30I-IVqRT-PCROSK-M8J-b Zhong2020ChinaGC8349/34I-IVqRT-PCROSHR7Y-n Xu2020ChinaNSCLC7945/34I-IVqRT-PCROSK-M8X-z Chen2020ChinaPCa5416/38I-IVqRT-PCROS/PFSHR/K-M8Y Xia2020ChinaCC13769/68I-IIqRT-PCROSHR/K-M8X-d Lu2020ChinaBC9052/38I-IIIqRT-PCROSHR/K-M8Z-f Wang2020TCGAESCC8672/14NARNA-seqOSK-M6L-z Gu2020ChinaOC4121/20II-IVqRT-PCROSK-M6J Yang2019ChinaBLC6838/30II-IVqRT-PCROSHR/K-M8X-r Lv2019ChinaEC5837/21I-IVqRT-PCROSHR/K-M8Q Li2019ChinaAML3618/18NAqRT-PCROSK-M7Y-q Wang2019ChinaMelanoma40NANAqRT-PCROSHR/K-M5B-q Hui2019ChinaPC4221/21I-IVqRT-PCROSK-M8G Yu2019ChinaBLC8744/43NAqRT-PCROSK-M6X-l Yang2019ChinaPCa4623/23NAqRT-PCRDFSK-M6T Xu2019ChinaPCa7035/35I-IVqRT-PCROSK-M7M Wang2019ChinaCRC12462/62II-IIIqRT-PCRRFSK-M8H Zhou2019TCGAHCC37191/274NARNA-seqOSK-M5H Zhou2019TCGAMelanoma459115/344NARNA-seqOSK-M5H Zhou2019TCGAOSA25965/194NARNA-seqOSK-M5H Zhou2019TCGARCC28773/214NARNA-seqOSK-M5H Zhou2019TCGABLC406102/304NARNA-seqOSK-M5H Zhou2019TCGACRC27969/210NARNA-seqOSK-M5H Zhou2019TCGAGC39293/299NARNA-seqOSK-M5H Zhou2019TCGABC (triple negative)1081273/808NARNA-seqOSK-M5Y Zhang2019ChinaGC8548/37I-IVqRT-PCROSK-M7W Wang2018ChinaGBM51NANARNA-seqOSHR5X-f Wang2018ChinaAML18693/93NAqRT-PCROS/EFSHR/K-M7T-h Li2018ChinaOC96NAI-IVqRT-PCROSHR/K-M7Q-l Wang2018ChinaOSA9447/47IIA/IIB-IIIqRT-PCROSHR/K-M8C-h Xiao2018ChinaCRC9045/45I-IVqRT-PCROS/DFSK-M7W-f Luo2018ChinaAML73NANAqRT-PCROSHR/K-M6J Qin2018ChinaAML236NANAqRT-PCROS/EFSHR/K-M6C-h Xu2018ChinaESCC4221/21NAqRT-PCROSK-M7W Qian2018ChinaNPC4828/20I-IVqRT-PCROSK-M8Y-b Lu2018ChinaPC7250/22I-IVqRT-PCROSK-M8K Yao2018ChinaCRC185129/56I-IVqRT-PCROSHR/K-M8G-m Zheng2018ChinaCRC9051/39I-IVqRT-PCROSHR/K-M8Y-c Niu2017ChinaSCLC3316/17NAqRT-PCROSK-M7P-q Wang2017ChinaRCC (ccRCC)203100/103I-IVqRT-PCROSHR/K-M8Y Wang2017ChinaOSA4430/14I-IIA/IIB-IIIqRT-PCROSK-M8J Droop2017GermanyUC106NAI-IVqRT-PCROS/DFSHR/K-M8L Zhao2017ChinaPC3418/16I-IVqRT-PCROSK-M8G-q Yan2017ChinaOSCC4624/24I-IVqRT-PCROSHR/K-M8J Zhu2017ChinaCC5930/29I-IIA/IIB-IIIAqRT-PCROSK-M8Y Xu2017ChinaCCA5130/29I-IVqRT-PCROSK-M8B Zeng2017ChinaCCA102NAI-IVqRT-PCROS/DFSHR/K-M7D-f Gradia2017TCGABC (luminal B)12292/30I-IVRNA-seqDFSHR/K-M5D-f Gradia2017TCGABC (HER2-enriched)5614/42I-IVRNA-seqDFSHR/K-M5Z Baratieh2017TCGAGBM260130/130NARNA-seqOSK-M5D Liu2017ChinaNHL10861/47I-IVqRT-PCROSHR/K-M8T Shen2017ChinaGC4835/13I-IVqRT-PCROSK-M8J Li2016ChinaGBM12060/60I-IVqRT-PCROSK-M8J-f Sun2016ChinaCRC12072/48I-IVqRT-PCROSK-M8E Zhang2016ChinaGC10050/50I-IVqRT-PCROSHR/K-M8L Jiang2016ChinaESCC218109/109I-IVqRT-PCROSHR/K-M8R Iliev2016Czech RepublicBLC4726/21II-IVqRT-PCROSHR/K-M7P-c Lin2016ChinaNSCLC8931/58I-IVqRT-PCROSK-M8J-m Tan2015ChinaBLC5427/27I-IVqRT-PCROSK-M7B Ma2015ChinaOSA7641/35I-IIIqRT-PCROS/PFSHR/K-M8E-b Zhang2014ChinaNSCLC19296/96I-IVqRT-PCROSK-M6Abbreviations: 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 (I2=86.9%, p<0.001). 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, p<0.001) (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 (p=0.648) or DFS (p=0.437), but a tendency toward worse RFS (p=0.001) or EFS (p<0.001) 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 (Table2). The results revealed a marked association between high expression of TUG1 and unfavorable OS in patients from China (HR=1.93, 95% CI: 1.59-2.30, p<0.001) and patients who were not from China (HR=1.27, 95% CI: 1.05-1.54, p=0.013). Likewise, TUG1 overexpression predicted a worse outcome no matter in the subgroup containing patients more than 100 (HR=1.31, 95% CI: 1.08-1.60, p<0.001) and in the subgroup with less than 100 patients (HR=2.12, 95% CI: 1.72-2.63, p=0.007). 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, p<0.001) and 1.29 (95% CI: 1.07-1.57, p=0.009), respectively. When sorted by cancer type, TUG1 expression significantly predicted unfavorable OS in gastrointestinal cancer (HR=2.12, 95% CI: 1.69-2.67, p<0.001), urinary tumors (HR=1.89, 95% CI: 1.27-2.79, p=0.002), gynecologic tumors (HR=2.01, 95% CI: 1.40-2.89, p<0.001), hematological tumors (HR=2.44, 95% CI: 1.87-3.18, p<0.001), and osteosarcoma (HR=1.58, 95% CI: 1.16-2.14, p=0.003). Meanwhile, a high TUG1 level predicted favorable OS in respiratory tumors (HR=0.50, 95% CI: 0.36-0.70, p<0.001). 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 (HR=0.45, 95% CI: 0.35-0.58, p<0.001) and an unfavorable prognostic value for RCC (HR=1.61, 95% CI: 1.00-2.61, p=0.046). However, the merged HR indicated no significant relationship between TUG1 expression and OS in BLC (p=0.441) and GBM (p=1.135) (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 analysisNumber of cohortsNumber of patientsPooled HR (95% CI)p valueHeterogeneityI2 (%)p valueOriginChina4842721.93 (1.59-2.30)<0.00188.3<0.001Non-China1341331.27 (1.05-1.54)0.01376.6<0.001Cancer typeHead and neck neoplasms55250.83 (0.35-2.01)0.68790.3<0.001Respiratory tumor55250.50 (0.36-0.70)<0.00135.50.185Gastrointestinal cancer2126502.12 (1.69-2.67)<0.00182.2<0.001Urinary tumor1114321.89 (1.27-2.79)0.00287.4<0.001Gynecologic tumor816622.01 (1.40-2.89)<0.00176.5<0.001Hematological tumor56392.44 (1.87-3.18)<0.00100.587Osteosarcoma44731.58 (1.16-2.14)0.00350.20.110Melanoma24991.65 (0.80-3.38)0.17488.30.003Number of patients<1003722562.12 (1.72-2.63)0.00788.3<0.001≥1002461491.31 (1.08-1.60)<0.00184.1<0.001Detection methodqRT-PCR5046441.88 (1.57-2.25)<0.00188.0<0.001RNA-seq1141091.29 (1.07-1.57)0.00976.7<0.001Figure 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.
(a)(b)(c)(d)


## 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,p=0.023) with statistical heterogeneity (I2=80.7%, p<0.001). 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, p<0.001) with significant heterogeneity (I2=72.2%, p<0.001), 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 (HR=2.96, 95% CI: 2.23-3.92, p<0.001) and distant metastasis (HR=3.56, 95% CI: 1.97-6.41, p<0.001) 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 featuresNumber of cohortsNumber of patientsPooled OR (95%CI)p valueHeterogeneityI2 (%)p valueGender (male vs. female)3118691.03 (0.84-1.25)0.80300.872Age (<60 vs. ≥60)1511610.93 (0.73-1.18)0.53700.799Tumor grade (low vs. high+moderate)1513321.99 (1.10-3.60)0.02380.7<0.001Tumor stage (III+IV vs. I+II)2018282.82 (1.84-4.33)<0.00172.2<0.001Lymph node metastasis (+ vs. -)2018352.96 (2.23-3.92)<0.00139.60.036Distant metastasis (+ vs. -)108513.56 (1.97-6.41)<0.00157.10.013


## 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) (Figure5(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.Figure 5
Sensitivity analysis for the meta-analysis of OS (a) and DFS/RFS/EFS (b) in all patients.
(a)(b)


## 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 (Figure6), but the p value of the Begg’s test for OS (Pr>∣z∣=0.61) and DFS/RFS/EFS (Pr>∣z∣=0.95) indicated that there was no severe publication bias in our present meta-analysis.Figure 6
Funnel plot analysis of potential publication bias for OS (a) and DFS/RFS/EFS (b).
(a)(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 p 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 (HR=0.62, 95% CI: 0.39-0.97, p=0.012). 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 (HR=0.46, 95% CI: 0.27-0.80, p=0.061), 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 p 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.



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