# The Association between Long Noncoding RNA over Expression and Poor Prognosis of Liver Cancer: A Meta-Analysis

Authors: Leiqing Wang; Junzhi Sheng; Haojie Zhang; Baoyuan Xie; Linbiao Xiang; Dong Liu; Xinyuan Zhang; Peihao Zhang; Jinjin Liu
Journal: Journal of Healthcare Engineering
 (2021)

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## Abstract

Background. Long noncoding RNA (lncRNA) is considered to be a mediator of carcinogenesis, which may be associated with liver cancer survival. However, the relationship remains inconclusive. Meta-analysis was conducted to analytically review the association between the lncRNA expression level and clinicopathological characteristics and prognostic value of hepatic carcinoma. Materials and Methods. Four databases including Embase, PubMed, Web of Science, and the Cochrane Library were searched to collect studies about the relation between lncRNA overexpression and prognosis of liver cancer, dating from the earliest records of these databases to March 2021. Two researchers independently screened the data and literature to perform a stringent evaluation of the quality of material involved in the study. Meta-analysis was performed by Stata 16.0 software on 42 case-control studies with 6293 samples. Results. The outcomes of meta-analysis are presented as follows: lncRNA overexpression patients had later TNM stage (OR = 0.36, 95% CI (0.31, 0.41), P < 0.001), lower histological grade (OR = 0.56, 95%CI (0.49, 0.65), P < 0.001), more vascular invasion (OR = 2.02, 95% CI (1.74, 2.35), P < 0.001), bigger tumor size (OR = 2.28, 95% CI (2.00, 2.60), P < 0.001), more severe liver cirrhosis (OR = 1.39, 95% CI(0.1.16, 1.66), P < 0.001), more likely to metastasize (OR = 1.80, 95%CI(1.49, 2.18), P < 0.001), and more tumor numbers (OR = 0.72, 95% CI (0.62, 0.84), P < 0.05). lncRNA over expression patients had shorter OS (HR = 2.32, 95 CI% (2.08, 2.59), P < 0.01, RFS (HR = 2.19, 95 CI% (1.72, 2.78), P < 0.01), and DFS (HR = 2.01, 95 CI% (1.57, 2.57), P < 0.01). Conclusions. Overexposure of lncRNA is a poor prognostic feature for patients with hepatic carcinoma. The scope of our study was limited because of a lack of relevant research and the poor representativeness and varying quality of the studies involved in the current meta-analysis. Our conclusion still requires higher studies for further validation. This trial is clinically registered with CRD4201920620.


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## Body

## 1. Introduction

Hepatic carcinoma is one of the most commonly occurring malignant cancers, with morbidity and mortality ranked sixth and second, respectively, causing serious threats to human health [1, 2]. According to statistics in 2012, there are about 780,000 novel patients reported and 740,000 deaths across the globe. The incidence of China accounts for 50%, and it shows an upward trend [3]. So far, it is believed that genetic and environmental factors, both cause tumorigenesis, but the specific pathogenesis of liver cancer has not been completely clarified. Currently, surgical treatment is still the most effective and radically curable method, but a considerable number of patients with liver cancer cannot be suffered from surgery or have lost the best time for surgery. Therefore, it is urgently necessary to find new effective markers that are specifically expressed in hepatic malignant to improve the diagnosis and the accuracy of judgment on prognosis. Over the last few years, the function of long noncoding RNA (lncRNA) in many pathological and physiological pathways has been gradually explored, and it is also aberrantly expressed in some malignant tumors, regulating the spread, variation, and metastasis of cancerous cells [4].lncRNA is a kind of endogenic RNA 200 or more nucleotides long, which is extensively present inHomo sapiens. It has no protein-coding function and lacks a specific open reading frame (ORF) [5], which was considered to be a nonsignificant byproduct of transcription in the early stage [6–8]. Over the years, due to the advancement of high-resolution chips and high-throughput sequencing technologies, the research on transcriptome regulation has been increasingly deepened, and it is found that lncRNA not only plays a significant role in transcriptional interference but also in the process of some histological development, tumorigenesis, and tumor metastasis [9–11]. Researchers have found that aberrant expression of lncRNA affects the prognosis of liver cancer, associated with metastasis, TNM stage, and other clinicopathological characteristics of liver cancer [12]. Therefore, lncRNA could be a novel marker for the diagnosis, prognosis of liver cancer, and a possible therapeutic target for the cure of liver cancer. This study is the first to systematically evaluate the association of lncRNA, the expression quantity, and the clinical attributes and prognostic value in liver cancer patients, providing a basis for clinical practice.


## 2. Materials and Methods

### 2.1. Literature Search Strategy

We searched computers for EMBASE, PubMed, Web of Science databases, and the Cochrane Library to collect studies related to the correlation between high expression of lncRNA and prognosis of hepatic carcinoma. Only articles in English were selected. The following keywords were used: lncRNA, long ncRNA, lincRNAs, long noncoding RNA, long noncoding RNA, long untranslated RNA, liver neoplasm, hepatic neoplasm, hepatocellular cancer, liver cancer, cancer of the liver, etc. At the same time, manually search for references as a supplement.


### 2.2. Inclusion and Exclusion Standard

The standard for eligible articles is mentioned as (1) the case-control studies related to the correlation between high levels of lncRNA and prognosis of patients with hepatic carcinoma were published at home and abroad. (2) The affected individuals were diagnosed with hepatic carcinoma by cytological and histopathological examination. (3) The expression of lncRNA was quantified by reverse transcription-polymerase chain reaction (RT-PCR). (4) The cutoff value of lncRNA expression level was described. (5) Every study performed the association between expression of lncRNA and OS, and the hazard ratio (HR) value and its corresponding 95% confidence interval (95% CI) for OS was either obtained directly from actual study or indirectly it will be calculated by Engauge Digitizer 4.1 software from survival curve. (6) No restrictions of age, race, gender, and region.The study exclusion standard is as follows: (1) repetitive published literature; (2) non-Chinese and English literature; (3) literature is unable to obtain full-text; (4) literature that does not report liver cancer prognosis outcomes or that cannot extract ending data from the text.


### 2.3. Data Extraction

Two researchers independently screen literature and extract data. Third researcher will handle if any disagreement occurs. Data was gathered and extracted based on the following criteria: (1) the basic information includes the topic of the study, author, and publication year; (2) baseline features of the included article, which included sample size, region, lncRNA type, lncRNA expression level, whether preoperative treatment, a cutoff value, lncRNA test method and TNM staging of liver cancer, etc. (3) Outcome indicators: OS, RFS, DFS, TNM stage, histological grade, vascular invasion, tumor numbers, tumor size, location, etc. The hazard ratio (HR) value and its corresponding 95% confidence interval (95% CI) for the OS, RFS, and DFS were either directly acquired from the original text or will be indirectly estimated by Engauge Digitizer 4.1 software from the survival curve [13]; (4) risk of bias assessed the key factors.


### 2.4. Quality Assessment of Included Studies

All the included studies were nonrandomized and retrospective studies. The quality was assessed using the Newcastle–Ottawa Scale (NOS). Each included study was assessed by two researchers for the quality from three mentioned items: “selection,” “comparability,” and “exposure.” There are evaluation items under each item, and each item is indicated by  when appropriate. The highest score of comparability is 2. Any discrepancies were resolved by consensus.


### 2.5. Statistical Analysis

We use Stata 16.0 software to perform statistical analysis.P < 0.01 was considered statistically significant. The odds ratio (OR) and hazard ratio (HR) were used to analyze the effect statistics, and each effect provided a 95% CI. Heterogeneousness between the comprised studies was analyzed using the I2 test. I2 ＜50% suggests no statistical heterogeneity between the outcomes of each research, using the fixed-effects model to perform the meta-analysis. Otherwise, the random-effect model would be used finally. After excluding the significant effects of clinical heterogeneity, use the random-effects model to perform the meta-analysis. Significant clinical heterogeneity is processed using methods such as subgroup analysis or sensitivity analysis [14].


## 2.1. Literature Search Strategy

We searched computers for EMBASE, PubMed, Web of Science databases, and the Cochrane Library to collect studies related to the correlation between high expression of lncRNA and prognosis of hepatic carcinoma. Only articles in English were selected. The following keywords were used: lncRNA, long ncRNA, lincRNAs, long noncoding RNA, long noncoding RNA, long untranslated RNA, liver neoplasm, hepatic neoplasm, hepatocellular cancer, liver cancer, cancer of the liver, etc. At the same time, manually search for references as a supplement.


## 2.2. Inclusion and Exclusion Standard

The standard for eligible articles is mentioned as (1) the case-control studies related to the correlation between high levels of lncRNA and prognosis of patients with hepatic carcinoma were published at home and abroad. (2) The affected individuals were diagnosed with hepatic carcinoma by cytological and histopathological examination. (3) The expression of lncRNA was quantified by reverse transcription-polymerase chain reaction (RT-PCR). (4) The cutoff value of lncRNA expression level was described. (5) Every study performed the association between expression of lncRNA and OS, and the hazard ratio (HR) value and its corresponding 95% confidence interval (95% CI) for OS was either obtained directly from actual study or indirectly it will be calculated by Engauge Digitizer 4.1 software from survival curve. (6) No restrictions of age, race, gender, and region.The study exclusion standard is as follows: (1) repetitive published literature; (2) non-Chinese and English literature; (3) literature is unable to obtain full-text; (4) literature that does not report liver cancer prognosis outcomes or that cannot extract ending data from the text.


## 2.3. Data Extraction

Two researchers independently screen literature and extract data. Third researcher will handle if any disagreement occurs. Data was gathered and extracted based on the following criteria: (1) the basic information includes the topic of the study, author, and publication year; (2) baseline features of the included article, which included sample size, region, lncRNA type, lncRNA expression level, whether preoperative treatment, a cutoff value, lncRNA test method and TNM staging of liver cancer, etc. (3) Outcome indicators: OS, RFS, DFS, TNM stage, histological grade, vascular invasion, tumor numbers, tumor size, location, etc. The hazard ratio (HR) value and its corresponding 95% confidence interval (95% CI) for the OS, RFS, and DFS were either directly acquired from the original text or will be indirectly estimated by Engauge Digitizer 4.1 software from the survival curve [13]; (4) risk of bias assessed the key factors.


## 2.4. Quality Assessment of Included Studies

All the included studies were nonrandomized and retrospective studies. The quality was assessed using the Newcastle–Ottawa Scale (NOS). Each included study was assessed by two researchers for the quality from three mentioned items: “selection,” “comparability,” and “exposure.” There are evaluation items under each item, and each item is indicated by  when appropriate. The highest score of comparability is 2. Any discrepancies were resolved by consensus.


## 2.5. Statistical Analysis

We use Stata 16.0 software to perform statistical analysis.P < 0.01 was considered statistically significant. The odds ratio (OR) and hazard ratio (HR) were used to analyze the effect statistics, and each effect provided a 95% CI. Heterogeneousness between the comprised studies was analyzed using the I2 test. I2 ＜50% suggests no statistical heterogeneity between the outcomes of each research, using the fixed-effects model to perform the meta-analysis. Otherwise, the random-effect model would be used finally. After excluding the significant effects of clinical heterogeneity, use the random-effects model to perform the meta-analysis. Significant clinical heterogeneity is processed using methods such as subgroup analysis or sensitivity analysis [14].


## 3. Results

### 3.1. Literature Screening Process and Results

Overall, 4140 articles were retrieved in the early inspection. Later on, forty-two studies were finally included on layer-by-layer screening. Figure1 shows the literature screening process and outcomes.Figure 1
The flow chart of literature screening process.


### 3.2. Basic Characteristics and Quality Assessment Results of the Included Studies

General characteristics of liver cancer patients include age, gender, sample size, region, lncRNA type, lncRNA expression level, whether preoperative treatment, a cutoff value, etc. These all are shown in Table1.Table 1
Basic characteristics of included studies.
Study IDRegionSample SizelncRNACutoff ValueTNM StageData extraction methodFollow-up (months)OutcomePostoperative treatmentGuo [15]China95NEAT1Median valueI–IVSurvival curveNoOSNOHua [10]China92ANRILMedian valueI–IVReported in text60OSNOLi [16]China179GHET1Median valueI–IVReported in textNoOS + DFSNOWang [17]China112HOXA-AS2Median valueI–IVSurvival curveNoOSNOZhou [18]China109BANCRMedian valueI–IIISurvival curveSDDOSNODing [19]China137TUG1Median valueI–IVReported in textNoOSNODing [20]China214PVT1ROC analysisI–IVReported in text27.58OS + RFSNRYang [21]China60HOTAIRROC analysis—Reported in text18.6OS + RFSNRYan [22]China117PCAT-1Median ratio—Reported in text60OSNOZhang [23]China144SNHG3Median valueI–IVReported in text60OSNODong [24]China84PlncRNA-1Median valueI–IVBothNoOS + RFSNRShi [25]China84Sox2otMedian ratioI–IVReported in text60OSNOLi [26]50China102ZEB1-AS1Median valueI–IIISurvival curveSDDOSNOShen [27]China100SNHG7Mean ratioI–IVBoth84OSNRZhang [28]China55UCA1Median valueI–IVBoth60OSNOZhang [29]China127RHPN1-AS1median valueI–IVBoth60OS + DFSNOJiao [30]China370SNHG4ROC analysisI–IVReported in textNoOS + RFSNOXiao [31]China100GIHCGROC analysisI–IVReported in text60OS + DFSNRZhang [32]China337ROR1-AS1Mean ratioI–IVReported in textNoOSNRZeng [53]China130CASC9Median valueI–IVReported in text60OSNRBai [54]China353PTTG3PYouden indexI–IVReported in text72OS + RFSNONie [33]China371ACVR2B-AS1—I–IVReported in textNoOS + DFSNOFu [34]China122CCAT2Median valueI–IVReported in text60OSNRZhao [35]China161ENST00000429227.1——Reported in textNoOSNOPan [36]China59circ0000267Median valueI–IVReported in text60OSNOZhong [55]China108SNHG16Median value—Reported in text60OSNRWang [37]China127LINC0051 1Median valueI–IVReported in text60OSNRGuo [38]China61SNGH16Positive evelsI–IVReported in text60OSNRWang [39]China101MIR210HGMedian valueI–IVBoth120OS + DFSNRWang [40]China40LINC01296—I–IVSurvival curveNoOSNRZhou [41]China197HOXC13-ASmedian valueI–IVReported in text60OS + DFSNOYu [42]China123SUMO1P3Median valueI–IVReported in text60OSNRHuang [43]China136PTTG3P—I–IVReported in text60OSNRTang [44]China66RUSC1ASN——Survival curve72OS + RFSNRQi [45]China70lncPARP1——Survival curve36OS + DFSNOJin [46]China161MINCR—I–IVReported in text60OSNOXu [47]China108TRPM2-ASNormal value—Survival curve72OSNOLi [48]China193AK021443Mean ratioI–IVReported in textNoOSNOLi [49]China68GHET1Mean ratio—Survival curve60OSNOWang [50]China326LRB1Median valueI–IVSurvival curve72OSNRZeng [51]China84LncDQ—I–IVReported in text60OSNRNote. Cutoff value: the critical value to distinguish between high and low lncRNA expression; OS : overall survival; mean ratio: average expression level of lncRNA; median value: median expression level of LncRNA; — : no mention in text; OS : overall survival; DFS : disease-free survival; RFS : relapse-free survival; both: reported in text and survival curve; SDD : surgery to the date of death.Newcastle–Ottawa Scale (NOS) marked included studies to be of high quality. All the studies have a score greater than 5 stars and meet the criteria for inclusion in the meta-analysis. The results are listed in Table2.Table 2
The quality evaluation results of included studies by NOS.
Study IDSelectionComparabilityOutcomeScoreYang [21]★★★★★★★7Guo [15]★★★★★★★7Hua [10]★★★★★★6Ding [20]★★★★★★★7Yan [22]★★★★★★★7Shi [25]★★★★★★★7Wang [17]★★★★★★★7Zhou [18]★★★★★★★7Zhang [23]★★★★★★★★8Dong [24]★★★★★★★7Li [26]★★★★★★6Li [16]★★★★★★★7Ding [19]★★★★★★★7Huang [43]★★★★★★★7Tang [44]★★★★★★★7Qi [45]★★★★★★★7Jin [46]★★★★★★★7Xu [47]★★★★★★6Li [48]★★★★★★★7Li [49]★★★★★★★7Wang [50]★★★★★★★7Zeng [51]★★★★★★★★8Zhang [32]★★★★★★★7Zeng [53]★★★★★★★7Bai [54]★★★★★★★★8Nie [33]★★★★★★6Fu [34]★★★★★★★7Zhao [35]★★★★★★6Pan [36]★★★★★★★7Zhong [55]★★★★★★6Wang [37]★★★★★★★7Guo [38]★★★★★★★7Wang [39]★★★★★★★7Wang [40]★★★★★★★7Zhou [41]★★★★★★★7Shen [27]★★★★★★★7Zhang [28]★★★★★★★7Zhang [29]★★★★★★★7Zhang [5]★★★★★★★7Jiao [30]★★★★★★★7Xiao [31]★★★★★★★★8Yu [42]★★★★★★★7Liang [52]★★★★★★★7


### 3.3. Meta-Analysis Results

#### 3.3.1. Clinical Features

A total of 42 studies were included, including 6293 samples. Meta-analysis showed that patients with high expression of lncRNA had later TNM stage (OR = 0.36, 95%CI (0.31, 0.41),P < 0.001), lower histological grade (OR = 0.56, 95%CI (0.49, 0.65), P < 0.001), more vascular invasion (OR = 2.02, 95%CI (1.74, 2.35), P < 0.001), bigger tumor size (OR = 2.28, 95%CI (2.00, 2.60), P < 0.001), more severe liver cirrhosis (OR = 1.39, 95%CI (0.1.16, 1.66), P < 0.001), more likely to metastasize (OR = 1.80, 95%CI (1.49, 2.18), P < 0.001), more expression of AFP (OR = 1.46, 95%CI (1.22, 1.75), P < 0.001 and OR = 1.79, 95%CI (1.40, 2.29), P < 0.001), and more tumor numbers (OR = 0.72, 95%CI (0.62, 0.84), P < 0.05). The differences of other clinical features, such as age, gender, and HBV infection were not statistically significant. The results are shown in Table 3.Table 3
Results of meta-analysis on the correlation between LncRNA expression level and clinical features of liver cancer.
Clinical CharacteristicsNumber of studies included (papers)Tests for heterogeneityEffect of the modelResults of meta-analysisI2 (%)P valueOR (95%CI)P valueAge39 [5, 10, 16–52]66.5%<0.001Random1.07 (0.96, 1.19)0.253Gender42 [5, 10, 16–55]0.0%0.66Fixed1.03 (0.92,1.15)0.648Tumor size33 [10, 16, 29, 31, 34, 36, 39, 41–52]71.8%<0.001Random2.28 (2.00,2.60)<0.001HBV infection25 [10, 16, 19, 20, 24, 25, 27, 29, 31, 34, 36, 39, 41, 43, 44, 46, 52, 55]0.0%0.712Fixed1.12 (0.95,1.31)0.182Liver cirrhosis18 [16, 20, 22, 25, 34, 38, 42, 44, 47, 49, 51, 55]0.0%0.799Fixed1.39 (1.16,1.66)<0.001Metastasis16 [22, 23, 27, 28, 30, 34, 37, 38, 40, 41, 48, 51, 52]72.5%<0.001Random1.80 (1.49,2.18)<0.001H- grade28 [5, 10, 16, 25, 28, 30, 32, 33, 35, 37, 39, 41, 42, 45, 48, 53, 54]67.5%<0.001Random0.54 (0.48,0.62)<0.001AFP (400)18 [10, 16, 22, 24, 26, 35, 36, 41, 45, 47, 51, 52, 55]41.5%0.034Fixed1.46 (1.22,1.75)<0.001AFP (20)9 [27, 29, 40, 42, 43, 46, 48, 50]76.9%<0.001Random1.79 (1.40,2.29)<0.001TNM stage33 [5, 10, 15, 20, 22, 24, 34, 36, 43, 46, 48, 50, 51, 54]78.9%<0.001Random0.46 (0.41,0.51)<0.001Tumor number25 [10, 16, 24, 26, 29, 31, 34, 35, 37, 42, 43, 46, 48, 50, 51, 55]53.4%0.001Random0.72 (0.62,0.84)<0.001V-invasion22 [16, 19, 24, 26, 30, 32, 35, 37, 41, 42, 44, 45, 47, 49, 51, 55]84.7%<0.001Random2.02 (1.74,2.35)<0.001AFP (400): the cutoff of AFP is 400μg/L; AFP (20): the cutoff of AFP is 20 μg/L; H-grade: histological grade; V-invasion: vascular invasion.


#### 3.3.2. OS

A total of 29 studies were included. The meta-analysis of the fixed effects model (I2 = 0.0%, P = 0.829) showed that compared with patients with low expression of lncRNA, patients of high expression of lncRNA have shorter OS. The difference was statistically significant (HR = 2.32, 95 CI% (2.08, 2.59), P < 0.01) (Figure 2).Figure 2
Forest plots for the relationship between the overexpressed lncRNA and OS. The center of each square represents the HR, the area of the square is the number of sample and the weight used in the meta-analysis, and the horizontal line indicates the 95%CI. CI indicates confidence interval; HR: hazard ratio.


#### 3.3.3. RFS

A total of 4 studies [21, 24, 30, 54] were included. The meta-analysis of the fixed effects model (I2 = 0.0%, P = 0.576) showed that compared with patients with low expression of lncRNA, patients with high expression of lncRNA have shorter RFS. The difference was statistically significant (HR = 2.19, 95 CI% (1.72, 2.78), P < 0.01) (Figure 3).Figure 3
Forest plots for the relationship between the overexpressed lncRNA and RFS. RFS indicates recurrence-free survival.


#### 3.3.4. DFS

A total of 7 studies [16, 20, 29, 31, 33, 41, 52] were included. The meta-analysis of the fixed effects model (I2 = 38.1%, P = 0.138) showed that compared with patients with low expression of lncRNA, patients with high expression of lncRNA have shorter DFS. The difference was statistically significant (HR = 2.01, 95 CI% (1.57, 2.57), P < 0.01) Figure 4.Figure 4
Forest plots for the relationship between the overexpressed lncRNA and DFS. RFS indicates disease-free survival.


## 3.1. Literature Screening Process and Results

Overall, 4140 articles were retrieved in the early inspection. Later on, forty-two studies were finally included on layer-by-layer screening. Figure1 shows the literature screening process and outcomes.Figure 1
The flow chart of literature screening process.


## 3.2. Basic Characteristics and Quality Assessment Results of the Included Studies

General characteristics of liver cancer patients include age, gender, sample size, region, lncRNA type, lncRNA expression level, whether preoperative treatment, a cutoff value, etc. These all are shown in Table1.Table 1
Basic characteristics of included studies.
Study IDRegionSample SizelncRNACutoff ValueTNM StageData extraction methodFollow-up (months)OutcomePostoperative treatmentGuo [15]China95NEAT1Median valueI–IVSurvival curveNoOSNOHua [10]China92ANRILMedian valueI–IVReported in text60OSNOLi [16]China179GHET1Median valueI–IVReported in textNoOS + DFSNOWang [17]China112HOXA-AS2Median valueI–IVSurvival curveNoOSNOZhou [18]China109BANCRMedian valueI–IIISurvival curveSDDOSNODing [19]China137TUG1Median valueI–IVReported in textNoOSNODing [20]China214PVT1ROC analysisI–IVReported in text27.58OS + RFSNRYang [21]China60HOTAIRROC analysis—Reported in text18.6OS + RFSNRYan [22]China117PCAT-1Median ratio—Reported in text60OSNOZhang [23]China144SNHG3Median valueI–IVReported in text60OSNODong [24]China84PlncRNA-1Median valueI–IVBothNoOS + RFSNRShi [25]China84Sox2otMedian ratioI–IVReported in text60OSNOLi [26]50China102ZEB1-AS1Median valueI–IIISurvival curveSDDOSNOShen [27]China100SNHG7Mean ratioI–IVBoth84OSNRZhang [28]China55UCA1Median valueI–IVBoth60OSNOZhang [29]China127RHPN1-AS1median valueI–IVBoth60OS + DFSNOJiao [30]China370SNHG4ROC analysisI–IVReported in textNoOS + RFSNOXiao [31]China100GIHCGROC analysisI–IVReported in text60OS + DFSNRZhang [32]China337ROR1-AS1Mean ratioI–IVReported in textNoOSNRZeng [53]China130CASC9Median valueI–IVReported in text60OSNRBai [54]China353PTTG3PYouden indexI–IVReported in text72OS + RFSNONie [33]China371ACVR2B-AS1—I–IVReported in textNoOS + DFSNOFu [34]China122CCAT2Median valueI–IVReported in text60OSNRZhao [35]China161ENST00000429227.1——Reported in textNoOSNOPan [36]China59circ0000267Median valueI–IVReported in text60OSNOZhong [55]China108SNHG16Median value—Reported in text60OSNRWang [37]China127LINC0051 1Median valueI–IVReported in text60OSNRGuo [38]China61SNGH16Positive evelsI–IVReported in text60OSNRWang [39]China101MIR210HGMedian valueI–IVBoth120OS + DFSNRWang [40]China40LINC01296—I–IVSurvival curveNoOSNRZhou [41]China197HOXC13-ASmedian valueI–IVReported in text60OS + DFSNOYu [42]China123SUMO1P3Median valueI–IVReported in text60OSNRHuang [43]China136PTTG3P—I–IVReported in text60OSNRTang [44]China66RUSC1ASN——Survival curve72OS + RFSNRQi [45]China70lncPARP1——Survival curve36OS + DFSNOJin [46]China161MINCR—I–IVReported in text60OSNOXu [47]China108TRPM2-ASNormal value—Survival curve72OSNOLi [48]China193AK021443Mean ratioI–IVReported in textNoOSNOLi [49]China68GHET1Mean ratio—Survival curve60OSNOWang [50]China326LRB1Median valueI–IVSurvival curve72OSNRZeng [51]China84LncDQ—I–IVReported in text60OSNRNote. Cutoff value: the critical value to distinguish between high and low lncRNA expression; OS : overall survival; mean ratio: average expression level of lncRNA; median value: median expression level of LncRNA; — : no mention in text; OS : overall survival; DFS : disease-free survival; RFS : relapse-free survival; both: reported in text and survival curve; SDD : surgery to the date of death.Newcastle–Ottawa Scale (NOS) marked included studies to be of high quality. All the studies have a score greater than 5 stars and meet the criteria for inclusion in the meta-analysis. The results are listed in Table2.Table 2
The quality evaluation results of included studies by NOS.
Study IDSelectionComparabilityOutcomeScoreYang [21]★★★★★★★7Guo [15]★★★★★★★7Hua [10]★★★★★★6Ding [20]★★★★★★★7Yan [22]★★★★★★★7Shi [25]★★★★★★★7Wang [17]★★★★★★★7Zhou [18]★★★★★★★7Zhang [23]★★★★★★★★8Dong [24]★★★★★★★7Li [26]★★★★★★6Li [16]★★★★★★★7Ding [19]★★★★★★★7Huang [43]★★★★★★★7Tang [44]★★★★★★★7Qi [45]★★★★★★★7Jin [46]★★★★★★★7Xu [47]★★★★★★6Li [48]★★★★★★★7Li [49]★★★★★★★7Wang [50]★★★★★★★7Zeng [51]★★★★★★★★8Zhang [32]★★★★★★★7Zeng [53]★★★★★★★7Bai [54]★★★★★★★★8Nie [33]★★★★★★6Fu [34]★★★★★★★7Zhao [35]★★★★★★6Pan [36]★★★★★★★7Zhong [55]★★★★★★6Wang [37]★★★★★★★7Guo [38]★★★★★★★7Wang [39]★★★★★★★7Wang [40]★★★★★★★7Zhou [41]★★★★★★★7Shen [27]★★★★★★★7Zhang [28]★★★★★★★7Zhang [29]★★★★★★★7Zhang [5]★★★★★★★7Jiao [30]★★★★★★★7Xiao [31]★★★★★★★★8Yu [42]★★★★★★★7Liang [52]★★★★★★★7


## 3.3. Meta-Analysis Results

### 3.3.1. Clinical Features

A total of 42 studies were included, including 6293 samples. Meta-analysis showed that patients with high expression of lncRNA had later TNM stage (OR = 0.36, 95%CI (0.31, 0.41),P < 0.001), lower histological grade (OR = 0.56, 95%CI (0.49, 0.65), P < 0.001), more vascular invasion (OR = 2.02, 95%CI (1.74, 2.35), P < 0.001), bigger tumor size (OR = 2.28, 95%CI (2.00, 2.60), P < 0.001), more severe liver cirrhosis (OR = 1.39, 95%CI (0.1.16, 1.66), P < 0.001), more likely to metastasize (OR = 1.80, 95%CI (1.49, 2.18), P < 0.001), more expression of AFP (OR = 1.46, 95%CI (1.22, 1.75), P < 0.001 and OR = 1.79, 95%CI (1.40, 2.29), P < 0.001), and more tumor numbers (OR = 0.72, 95%CI (0.62, 0.84), P < 0.05). The differences of other clinical features, such as age, gender, and HBV infection were not statistically significant. The results are shown in Table 3.Table 3
Results of meta-analysis on the correlation between LncRNA expression level and clinical features of liver cancer.
Clinical CharacteristicsNumber of studies included (papers)Tests for heterogeneityEffect of the modelResults of meta-analysisI2 (%)P valueOR (95%CI)P valueAge39 [5, 10, 16–52]66.5%<0.001Random1.07 (0.96, 1.19)0.253Gender42 [5, 10, 16–55]0.0%0.66Fixed1.03 (0.92,1.15)0.648Tumor size33 [10, 16, 29, 31, 34, 36, 39, 41–52]71.8%<0.001Random2.28 (2.00,2.60)<0.001HBV infection25 [10, 16, 19, 20, 24, 25, 27, 29, 31, 34, 36, 39, 41, 43, 44, 46, 52, 55]0.0%0.712Fixed1.12 (0.95,1.31)0.182Liver cirrhosis18 [16, 20, 22, 25, 34, 38, 42, 44, 47, 49, 51, 55]0.0%0.799Fixed1.39 (1.16,1.66)<0.001Metastasis16 [22, 23, 27, 28, 30, 34, 37, 38, 40, 41, 48, 51, 52]72.5%<0.001Random1.80 (1.49,2.18)<0.001H- grade28 [5, 10, 16, 25, 28, 30, 32, 33, 35, 37, 39, 41, 42, 45, 48, 53, 54]67.5%<0.001Random0.54 (0.48,0.62)<0.001AFP (400)18 [10, 16, 22, 24, 26, 35, 36, 41, 45, 47, 51, 52, 55]41.5%0.034Fixed1.46 (1.22,1.75)<0.001AFP (20)9 [27, 29, 40, 42, 43, 46, 48, 50]76.9%<0.001Random1.79 (1.40,2.29)<0.001TNM stage33 [5, 10, 15, 20, 22, 24, 34, 36, 43, 46, 48, 50, 51, 54]78.9%<0.001Random0.46 (0.41,0.51)<0.001Tumor number25 [10, 16, 24, 26, 29, 31, 34, 35, 37, 42, 43, 46, 48, 50, 51, 55]53.4%0.001Random0.72 (0.62,0.84)<0.001V-invasion22 [16, 19, 24, 26, 30, 32, 35, 37, 41, 42, 44, 45, 47, 49, 51, 55]84.7%<0.001Random2.02 (1.74,2.35)<0.001AFP (400): the cutoff of AFP is 400μg/L; AFP (20): the cutoff of AFP is 20 μg/L; H-grade: histological grade; V-invasion: vascular invasion.


### 3.3.2. OS

A total of 29 studies were included. The meta-analysis of the fixed effects model (I2 = 0.0%, P = 0.829) showed that compared with patients with low expression of lncRNA, patients of high expression of lncRNA have shorter OS. The difference was statistically significant (HR = 2.32, 95 CI% (2.08, 2.59), P < 0.01) (Figure 2).Figure 2
Forest plots for the relationship between the overexpressed lncRNA and OS. The center of each square represents the HR, the area of the square is the number of sample and the weight used in the meta-analysis, and the horizontal line indicates the 95%CI. CI indicates confidence interval; HR: hazard ratio.


### 3.3.3. RFS

A total of 4 studies [21, 24, 30, 54] were included. The meta-analysis of the fixed effects model (I2 = 0.0%, P = 0.576) showed that compared with patients with low expression of lncRNA, patients with high expression of lncRNA have shorter RFS. The difference was statistically significant (HR = 2.19, 95 CI% (1.72, 2.78), P < 0.01) (Figure 3).Figure 3
Forest plots for the relationship between the overexpressed lncRNA and RFS. RFS indicates recurrence-free survival.


### 3.3.4. DFS

A total of 7 studies [16, 20, 29, 31, 33, 41, 52] were included. The meta-analysis of the fixed effects model (I2 = 38.1%, P = 0.138) showed that compared with patients with low expression of lncRNA, patients with high expression of lncRNA have shorter DFS. The difference was statistically significant (HR = 2.01, 95 CI% (1.57, 2.57), P < 0.01) Figure 4.Figure 4
Forest plots for the relationship between the overexpressed lncRNA and DFS. RFS indicates disease-free survival.


## 3.3.1. Clinical Features

A total of 42 studies were included, including 6293 samples. Meta-analysis showed that patients with high expression of lncRNA had later TNM stage (OR = 0.36, 95%CI (0.31, 0.41),P < 0.001), lower histological grade (OR = 0.56, 95%CI (0.49, 0.65), P < 0.001), more vascular invasion (OR = 2.02, 95%CI (1.74, 2.35), P < 0.001), bigger tumor size (OR = 2.28, 95%CI (2.00, 2.60), P < 0.001), more severe liver cirrhosis (OR = 1.39, 95%CI (0.1.16, 1.66), P < 0.001), more likely to metastasize (OR = 1.80, 95%CI (1.49, 2.18), P < 0.001), more expression of AFP (OR = 1.46, 95%CI (1.22, 1.75), P < 0.001 and OR = 1.79, 95%CI (1.40, 2.29), P < 0.001), and more tumor numbers (OR = 0.72, 95%CI (0.62, 0.84), P < 0.05). The differences of other clinical features, such as age, gender, and HBV infection were not statistically significant. The results are shown in Table 3.Table 3
Results of meta-analysis on the correlation between LncRNA expression level and clinical features of liver cancer.
Clinical CharacteristicsNumber of studies included (papers)Tests for heterogeneityEffect of the modelResults of meta-analysisI2 (%)P valueOR (95%CI)P valueAge39 [5, 10, 16–52]66.5%<0.001Random1.07 (0.96, 1.19)0.253Gender42 [5, 10, 16–55]0.0%0.66Fixed1.03 (0.92,1.15)0.648Tumor size33 [10, 16, 29, 31, 34, 36, 39, 41–52]71.8%<0.001Random2.28 (2.00,2.60)<0.001HBV infection25 [10, 16, 19, 20, 24, 25, 27, 29, 31, 34, 36, 39, 41, 43, 44, 46, 52, 55]0.0%0.712Fixed1.12 (0.95,1.31)0.182Liver cirrhosis18 [16, 20, 22, 25, 34, 38, 42, 44, 47, 49, 51, 55]0.0%0.799Fixed1.39 (1.16,1.66)<0.001Metastasis16 [22, 23, 27, 28, 30, 34, 37, 38, 40, 41, 48, 51, 52]72.5%<0.001Random1.80 (1.49,2.18)<0.001H- grade28 [5, 10, 16, 25, 28, 30, 32, 33, 35, 37, 39, 41, 42, 45, 48, 53, 54]67.5%<0.001Random0.54 (0.48,0.62)<0.001AFP (400)18 [10, 16, 22, 24, 26, 35, 36, 41, 45, 47, 51, 52, 55]41.5%0.034Fixed1.46 (1.22,1.75)<0.001AFP (20)9 [27, 29, 40, 42, 43, 46, 48, 50]76.9%<0.001Random1.79 (1.40,2.29)<0.001TNM stage33 [5, 10, 15, 20, 22, 24, 34, 36, 43, 46, 48, 50, 51, 54]78.9%<0.001Random0.46 (0.41,0.51)<0.001Tumor number25 [10, 16, 24, 26, 29, 31, 34, 35, 37, 42, 43, 46, 48, 50, 51, 55]53.4%0.001Random0.72 (0.62,0.84)<0.001V-invasion22 [16, 19, 24, 26, 30, 32, 35, 37, 41, 42, 44, 45, 47, 49, 51, 55]84.7%<0.001Random2.02 (1.74,2.35)<0.001AFP (400): the cutoff of AFP is 400μg/L; AFP (20): the cutoff of AFP is 20 μg/L; H-grade: histological grade; V-invasion: vascular invasion.


## 3.3.2. OS

A total of 29 studies were included. The meta-analysis of the fixed effects model (I2 = 0.0%, P = 0.829) showed that compared with patients with low expression of lncRNA, patients of high expression of lncRNA have shorter OS. The difference was statistically significant (HR = 2.32, 95 CI% (2.08, 2.59), P < 0.01) (Figure 2).Figure 2
Forest plots for the relationship between the overexpressed lncRNA and OS. The center of each square represents the HR, the area of the square is the number of sample and the weight used in the meta-analysis, and the horizontal line indicates the 95%CI. CI indicates confidence interval; HR: hazard ratio.


## 3.3.3. RFS

A total of 4 studies [21, 24, 30, 54] were included. The meta-analysis of the fixed effects model (I2 = 0.0%, P = 0.576) showed that compared with patients with low expression of lncRNA, patients with high expression of lncRNA have shorter RFS. The difference was statistically significant (HR = 2.19, 95 CI% (1.72, 2.78), P < 0.01) (Figure 3).Figure 3
Forest plots for the relationship between the overexpressed lncRNA and RFS. RFS indicates recurrence-free survival.


## 3.3.4. DFS

A total of 7 studies [16, 20, 29, 31, 33, 41, 52] were included. The meta-analysis of the fixed effects model (I2 = 38.1%, P = 0.138) showed that compared with patients with low expression of lncRNA, patients with high expression of lncRNA have shorter DFS. The difference was statistically significant (HR = 2.01, 95 CI% (1.57, 2.57), P < 0.01) Figure 4.Figure 4
Forest plots for the relationship between the overexpressed lncRNA and DFS. RFS indicates disease-free survival.


## 4. Discussion

Liver cancer has a very powerful, invasive, and aggressive ability, and it is prone to distant metastasis and recurrence, which leads to extremely mortality rate. In China, most patients with liver cancer are in an advanced stage when they are diagnosed, and the treatment methods and the effects are fantastically limited for them. Hence, the initial diagnosis and treatment of hepatic carcinoma remains a global difficulty and generates a large amount of discussion. Although there is an ongoing emergence of new drugs and treatments for liver cancer, there remain many difficulties in the early diagnosis and postoperative prognosis. Thus, the development of novel effective molecular therapeutic targets is the need of time to enhance the rate of diagnosis rate of liver cancer and the accuracy of prognosis judgment [56]. In recent years, according to detecting the tissues and plasma of cancer patients by real-time reverse transcription-polymerase chain reaction (RT-PCR), a high quantity of aberrantly expressed lncRNAs is found to participate in tumor metabolism to promote tumor development in different ways [57]. It has been found that only 1.5% of nucleic acid sequences were coding that is they make proteins while the rest 98.5% of the sequences are noncoding RNAs in three billion base pairs of the human genome, the latter regulated gene expression and maintained intracellular homeostasis through chromosome alteration, regulation of transcription, and posttranscriptional regulation. LncRNA dysregulation can cause chromosome loss and translocation, leading to the occurrence of cancer [58, 59]. Thus, lncRNA may be a potential biological target or as a molecular drug for prognosis and early diagnostic screening of cancer. At present, the relationship between lncRNA and tumor is attracting worldwide attention. Wang et al. [60] identified PVT1 to be highly expressed in hepatocellular carcinoma and related cell lines, and the affected individuals with increased PVT1 expression have a poor prognosis. PVT1 can increase the stability of nuclear protein NOP2, which helps cell proliferation, tumorigenesis, and gaining the same characteristics as exhibited by stem cells. Li et al. [61] found significantly increased HOTAIR expression level in liver cancerous tissues than paracarcinoma tissue. Besides, HOTAIR could downregulate the expression and phosphorylation of SETD2 to inhibit repair of DNA damage, causing microsatellite variability and aberrant cell cycle-related gene expression, which could further promote the occurrence of liver cancer. Yang [62] reported a crucially high expression level of noncoding RNA HEIH in affected individuals as compared to healthy ones. With the increase of the TNM stage, the expression of plasma HEIH increased gradually. LAN [63] found SNHG12 to be increasingly expressed in liver cancer-specific individuals and are connected with cancer size, TNM stage, and vascular invasion. Affected individuals with increased expression of SNHG12 had a worse prognosis and a higher recurrence rate than patients with low expression. SNHG12 can adsorb miR-199a/b-5p to increase the expression of MLK3 and its downstream effector molecule in the NF-κB pathway. Wang [64] reported that CARLo-5 is highly expressed in HCCLM3 and MHCC97-L cell lines and promotes the proliferation and metastasis of HCC, causing threats to the general and disease-free survival of affected individuals. These outcomes suggest that different types of lncRNA play different characters, but they all have significant roles in the growth and prognosis of liver cancer. Consequently, if one or more specific lncRNAs related to liver cancer are screened, chip technology, real-time quantitative RT-PCR, in situ hybridization technique, and other technologies can help in measuring the expression level of patients’ blood, urine, and other body fluids during clinical diagnosis and treatment, thereby improving the early diagnosis and prognosis of liver cancer.The present work is the first one to analytically evaluate the relationship between the expression level of lncRNA and the clinical features and prognostic rate of affected individuals. The results show that vascular invasion, histological grade, number of tumors, size of the tumor, metastasis, and TNM stage of liver cancer patients are associated with the expression level of lncRNA. Furthermore, the patients with high expression of lncRNA have shorter OS, RFS, and DFS than those with low expression. The above results have statistically significant values, and the heterogeneity is very weak. So, the high expression of lncRNA may be a reason for decreased prognosis of hepatic carcinoma. But so far, the research on lncRNA is still in the preliminary stage. Currently, only a few lncRNAs are found, but there are still a high number of purposes and regulatory mechanisms of lncRNAs which are not clear. Moreover, these lncRNAs related to liver cancer have been confirmed by previous studies, but its clinical application in tumor diagnosis and treatment remain to be further explored. lncRNA has a good prospect of diagnosis and treatment, and it can become a new star of tumor marker in the future, providing new hope for the targeted therapeutic of hepatic carcinoma and the development of anticancer drugs.Limitations of present work: (1) the comprised studies were retrospective studies, and the study design may have the risk of recall, measurement, and reporting bias; (2) the comprised research studies were all from China, due to differences in etiology, pathology, and prognosis in different regions. Therefore, this conclusion cannot be extended to other regions; (3) HRs of some included studies are not directly given relevant outcome indicators and only manually retrieved from the survival curve and then calculated, which may influence the validity of the results.In conclusion, the highest expression of lncRNA in liver cancer patients is a poor prognosis factor for liver cancer. Owing to the limitations of the quantity and quality of researchers involved, the above deductions are subject to verification by further studies.



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*Source: 1395131-2021-11-24.xml*