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. 2016 Jun 17;7(28):44442–44447. doi: 10.18632/oncotarget.10142

Long non-coding RNA UCA1 is a predictive biomarker of cancer

Han-han Hong 1,#, Li-kun Hou 2,#, Xin Pan 3,#, Chun-yan Wu 2, Hai Huang 1, Bing Li 1, Wei Nie 1
PMCID: PMC5190109  PMID: 27329842

Abstract

Human urothelial carcinoma associated 1 (UCA1) is a long noncoding RNA that is putatively oncogenic in solid tumors. This meta-analysis investigated an association between UCA1 levels and survival times of cancer patients. The primary endpoints were overall survival (OS) and progression-free survival (PFS). A comprehensive, computerized literature search was conducted of the databases PubMed, EMBASE, Chinese National Knowledge Infrastructure (CNKI), and Wanfang. The strength of association between UCA1 and cancer prognosis was assessed by computing the hazard ratio (HR) with its corresponding 95% confidence interval (CI). Twelve studies comprising 954 cancer patients met the criteria for this meta-analysis. Overall, a significant negative association was found between UCA1 levels and OS time (HR1.81, 95% CI1.52−2.17), including the following cancers analyzed independently: colorectal (HR2.61, 95% CI1.56−4.37), non-small cell lung (HR1.49, 95% CI1.16−1.90), gastric (HR2.19, 95% CI1.36−3.51), and ovarian (HR1.89, 95% CI1.14−3.12). There was also a significant negative association between UCA1 levels and PFS time (HR2.59, 95% CI1.61−4.16). In conclusion, this meta-analysis indicated that higher levels of UCA1 correlate with shorter PFS and OS times in cancers.

Keywords: cancer, UCA1, biomarker

INTRODUCTION

Cancer is a major public health problem worldwide, with overall death rates that rose during most of the 20 th century. In the United States, cancer is the second leading cause of death [1]. In China, cancers are the leading cause of death, despite the development of effective drugs and supportive care [2].

Long noncoding RNAs (lncRNAs) are non-protein-coding molecules, longer than 200 nucleotides [3]. Many studies have reported that lncRNAs are deregulated in cancers, suggesting that the aberrant expression of lncRNAs is associated with tumorigenesis, metastasis, and prognosis in cancer.

Human UCA1 (urothelial carcinoma associated 1) is a lncRNA that was first identified in human bladder carcinoma [4], and whose oncogenic effect may be related to glucose metabolism [5]. Recently, some studies have reported the relevance of UCA1 in cancer prognosis and the acquired resistance to drugs [617]. For example, patients with advanced non-small cell lung cancer (NSCLC) that harbor mutations that activate epidermal growth factor receptor (EGFR) can be treated with EGFR-tyrosine kinase inhibitors (TKIs) such as gefitinib. However resistance to this treatment is often acquired, most commonly via a secondary T790M mutation. Cheng et al. found that the lncRNA UCA1 was upregulated in resistant cells, and that overexpression of UCA1 was associated with shorter progression-free survival (PFS) in non-resistant cells [8]. Furthermore, UCA1 knockdown restored sensitivity to gefitinib in acquired-resistant NSCLC cells without the T790M mutation, and inhibited the activation of the AKT/mTOR pathway and epithelial-mesenchymal transition.

No meta-analysis was been conducted to assess the association between UCA1 and the survival of patients with cancers. Therefore, this meta-analysis investigated an association between UCA1 and the survival of cancer patients. Overall survival (OS) and PFS were the primary endpoints.

RESULTS

Study characteristics

The initial search of the databases produced 53 studies (Figure 1). After excluding duplicate articles, 49 potentially eligible studies were selected. After a detailed evaluation, 12 studies were selected for the final meta-analysis with a total of 954 cancer patients (Table 1). Of the 12 studies, 2, 3, 2, and 2 concerned colorectal cancer, NSCLC, ovarian cancer, and gastric cancer, respectively, and there was one study each regarding esophageal squamous cell carcinoma and hepatocellular carcinoma.

Figure 1. Flow of study selection.

Figure 1

Table 1. Characteristics of the included studiesa.

First author Year nb Agec Men, % Reference FU, mo Cancer Outcome Co-variants NOS
Cheng 2015 94 NA* 46.4 GAPDH 24 NSCLC PFS Age 7
Gao 2015 20 NA NA GAPDH NA GC OS Lymph node; clinical stage 8
Han 2014 80 55 49 GAPDH 42.6 CRC OS NA 8
Kamel 2015 82 57 68.3 GAPDH NA HCC PFS Barcelona clinic liver Cancer stage;Child score; mean tumor size 8
Li 2014 90 60 55.6 GAPDH 43 ESCC OS Differentiation grade; lymph node; clinical stage 7
Ni 2015 54 NA 72.2 GAPDH NA CRC OS Lymphatic invasion; lymph node; distant metastasis; clinical stage 8
Nie 2015 112 63.2 59.8 GAPDH 45 NSCLC OS Lymph node; clinical stage 8
Tao 2015 80 65.1 60 RUN6 NA CRC OS Lymph node; clinical stage 7
Wang 2015 60 NA 61.7 GAPDH NA NSCLC OS Lymph node; clinical stage 7
Yang 2016 53 NA 0 GAPDH NA Ovary OS Lymph node 8
Zhang 2016 117 33 0 RUN6 22 Ovary OS Chemotherapy response; lymph node; clinical stage 8
Zheng 2015 112 NA 57.1 GAPDH NA GC OS, PFS Tumor size; invasion depth; lymphatic metastasis; invade adjacent organs; clinical stage 8
a

This study characterized patients as > 65 or < 65; technique used to quantify UCA1 was real-time PCR in all studies;

b

sample size;

c

median age, y.

CRC, colorectal cancer; ESCC, esophageal squamous cell carcinoma; FU, follow-up; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; GC, gastric cancer; HCC, hepatocellular carcinoma; NA, not available.

Not all studies examined both OS and PFS, because most of the studies were retrospective cohort studies; 10 studies investigated the association between UCA1 and OS, while 3 studies assessed the association between UCA1 and PFS.

Results of the meta-analysis

The association between the expression of UCA1 and OS was investigated in 10 studies (Figure 2). We found a statistically significant negative association between levels of UCA1 and OS (HR = 1.81, 95% CI = 1.52–2.17). In a subgroup analysis of cancer sites, significant negative associations were found between levels of UCA1 and OS in the following cancers: colorectal (HR2.61, 95% CI1.56–4.37), NSCLC (HR1.49, 95% CI1.16-1.90), gastric cancer (HR2.19, 95% CI1.36–3.51), and ovarian cancer (HR1.89, 95% CI1.14–3.12). When the studies that adjusted for lymph node and clinical stage were included, shorter OS was also observed (HR1.71, 95% CI = 1.42–2.07). We did not perform subgroup analyses for esophageal squamous cell carcinoma or hepatocellular carcinoma, because no more than one study each investigated these associations between UCA1 and OS.

Figure 2. Meta-analysis for the association between UCA1 and overall survival of cancer.

Figure 2

The association between UCA1 and PFS was investigated in 3 studies (Figure 3). There was a significant negative association between UCA1 levels and PFS (HR2.59, 95% CI1.61–4.16; Figure 3). All the results are listed in the Table 2.

Figure 3. Meta-analysis for the association between UCA1 and progression-free survival of cancer.

Figure 3

Table 2. Results of this meta-analysis.

HR (95% CI) P I2 (%) P
Overall survival 1.81 (1.52–2.17) < 0.00001 19 0.27
Site of cancer CRC 2.62 (1.56–4.37) 0.0002 0 0.46
NSCLC 1.49 (1.16–1.90) 0.001 0 0.34
GC 2.19 (1.36–3.51) 0.001 0 0.75
Ovary 1.89 (1.14–3.12) 0.01 51 0.15
Adjusted lymph node and clinical stage 1.71 (1.42–2.07) < 0.00001 0 0.43
Progression-free survival 2.59 (1.61–4.16) < 0.00001 0 0.86

CRC, colorectal cancer; NSCLC, non-small cell lung cancer; GC, gastric cancer.

DISCUSSION

This is the first meta-analysis to evaluate the association between UCA1 levels and cancer prognosis. We found that increased levels of UCA1 were significantly associated with shorter OS and PFS times in cancer patients. In the subgroup analyses, UCA1 levels were significantly and negatively associated with OS times in colorectal cancer, NSCLC, ovarian cancer, and gastric cancer.

UCA1 putatively influences the proliferation, apoptosis, and cell cycle progression of colorectal cancer cells [6]. Ni et al. [11]also found that knockdown of UCA1 was associated with suppressed cell proliferation and metastasis in colorectal cancer cells. Nie et al. [12] suggested that silencing of UCA1 impaired the proliferation and colony formation of NSCLC cells. Wang and coworkers [13] found that UCA1 levels were associated with histological grade and lymph node metastasis in NSCLC. In addition, a clinicopathologic analysis revealed that UCA1 levels correlated with worse differentiation, greater tumor size and invasion depth, and TNM stage in gastric cancer [14]. Thus, these data might explain why high levels of UCA1 were significantly associated with shorter OS and PFS in cancer patients in this meta-analysis.

The clinical implications of UCA1 in various cancers have not been studied well. Wang et al. [4] showed that a UCA1 assay was highly specific (91.8%, 78 of 85) and very sensitive (80.9%, 76 of 94) in the diagnosis of bladder cancer. However, Milowich et al. [18] indicated that the efficiency of the UCA1 test for detecting primary and recurring bladder cancer was low. Future studies should focus on the clinical utility of UCA1-based cancer diagnosis in clinical trials. In addition, UCA1 has been implicated in the acquired resistance to EGFR-TKIs in EGFR-mutant NSCLC that did not include a T790M mutation [8]. Thus, the expression of UCA1 should be evaluated before patients receive EGFR-TKIs.

Some limitations of this meta-analysis should be pointed out. Firstly, the number of included studies in our meta-analysis was moderate. Secondly, most of the studies were conducted with Chinese sample populations and, therefore, our results may be applicable only to this ethnic group. Thirdly, not all of the studies reported the cutoff values of UCA1. Finally, many factors, such as gender and chemotherapy, may also affect OS and PFS. Thus, the results of this meta-analysis should be confirmed in future studies.

In conclusion, the results of this meta-analysis suggest that UCA1 may be a risk factor for shorter OS and PFS in cancers. Well-designed studies with large sample sizes are needed to confirm further the association between UCA1 and clinical outcomes of cancers in various ethnic populations.

MATERIALS AND METHODS

Publication search

We searched the databases PubMed, EMBASE, Chinese National Knowledge Infrastructure (CNKI) and Wanfang, to 14 March 2016, for relevant articles. The search terms used were “UCA1” and “cancer or carcinoma or tumor”. Reference lists of relevant articles were also reviewed to identify potential eligible studies.

Inclusion and exclusion criteria

For inclusion in this meta-analysis, the studies met the following criteria: cohort design; investigated the association between UCA1 and cancer prognosis (OS or PFS); and sufficient original data for calculating a hazard ratio (HR) with its 95% confidence interval (CI). A study was excluded if it was not relevant to cancer, UCA1, or cancer prognosis; involved animals; or was an editorial, review, or abstract. If more than one study used the same patient cases, the one with the most comprehensive population was included. Differences in opinion among the authors were solved by discussion.

Data extraction and quality assessment

Two investigators extracted and reviewed the data independently. The following data were extracted: the first author's name, year of publication, patient ages and genders, duration of follow-up, sample size, site of cancer, PFS, OS, and co-variants. Since all included studies were cohort studies, the Newcastle-Ottawa Scale (NOS) was used to evaluate the methodological quality [19].

Statistical analysis

The strength of association between UCA1 and cancer prognosis (PFS and OS) was assessed by computing the HR with its corresponding 95% CI. OS was defined as the time between diagnosis and death. PFS was defined as the time between diagnosis and progression. The heterogeneity among eligible studies was checked by using the chi-squared based Q-statistic test. The random-effects model or fixed-effects model was used to analyze the pooled HRs. If the number of included studies in an analysis was more than 10, Egger's linear regression test and Begg's funnel-plot analysis were used to weigh the potential publication bias. All the P-values were determined by a 2-sided test. All statistical analyses were conducted using STATA software (version 12.0; Stata, College Station, Texas).

ACKNOWLEDGMENTS AND FUNDING

This work was supported by the National Natural Science Foundation of China (No.81172227), the Research Foundation of Shanghai Municipal Education Commission (No.12ZZ073), the Shanghai Natural Science Foundation (No.16ZR1428900), and the Shanghai Municipal Commission of Health and Family Planning (No. 201440398).

Footnotes

CONFLICTS OF INTEREST

None.

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