Characteristics of eligible studies
As shown in Figure 1, a total of 672 records about lncRNA expression and human cancer were retrieved in PubMed, Web of Science, Embase and Medline electronic databases according to our settings. 619 records among them were excluded after reviewing the titles and abstracts. Subsequently, remaining 53 full-text articles were assessed for eligibility, and 18 studies were further excluded because of the irrelevant analysis. Finally, 35 articles were chosen for this meta-analysis. Among these 35 studies, the specific cancer we concerned was human renal cell carcinoma; 33 articles came from China and 2 came from Japan; all the metastasis were diagnosed by pathology; all the tissue specimens were well preserved before RNA extraction.
Clinical features
The basic research features and related results about metastasis and prognosis from the 35 including studies were listed in Table 1. A total of 3535 participants from China and Japan were involved in these 35 studies. Among these 35 articles, 28 studies reported the lymph node metastasis or distant metastasis or both. However, only 11 studies reported overall survival (OS).
Among these lncRNAs, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) [15-17], H19 [18], promoter of CDKN1A antisense DNA damage activated RNA (PANDAR) [19], renal cell carcinoma related transcript-1 (RCCRT1) [20], protein sprouty homolog 4 intronic transcript-1 (SPRY4-IT1) [21], nuclear paraspeckle assembly transcript 1 (NEAT1) [14, 22], HOX transcript antisense RNA (HOTAIR) [13, 23], cytoskeleton regulator RNA (linc00152) [24], Small nucleolar RNA host genes 3,5,6 (SNHG3,5,6) [25-28], AGAP2-AS1 [29], Epidermal growth factor receptor-antisense 1 (EGFR-AS1) [30], Titin-antisense 1 (TTN-AS1) [31], ZNFX1-antisense 1 (ZFAS1) [32], Plasmacytoma variant translocation 1 (PVT1) [33], Lung cancer-associated transcript 1 (LUCAT1) [34], Gastric carcinoma high expressed transcript 1 (GHET1) [35], The HOXA transcript at the distal tip (HOTTIP) [36], Transforming growth factor-b (ATB) [37], High-expressed in renal cell carcinoma (HEIRCC) [38] and taurine up-regulated 1 (TUG1) [9, 39] were up-regulated while PGM5-AS1 [40], Serum deprivation response-antisense (SDPR-AS) [41], DUXAP10 [42], LncRNA downregulated in liver cancer stem cells (LncRNA-DILC) [43], DHRS4-AS1[44], LOC389332 [45], neuroblastoma associated transcript 1 (NBAT1) [46] and T-cell leukemia/lymphoma 6 (TCL6) [12] were down-regulated.
As for the methods used to detect lncRNA expression levels in tumor tissues, all studies used qRT-PCR. The cut-off values were various in these studies due to the different cut-off definitions. Finally, all these studies did not report that these lncRNAs were significantly associated with age and gender of patients. However, some studies showed that lncRNAs were significantly correlated to tumor size [17], histological grade [18] or tumor stage [14].
Relationship between lncRNAs expression levels and LNM
The 28 selected studies reported a total number of 921 patients with LNM in the form of different lncRNA expression levels. These studies have passed the Q test and the I2 test (I2=79%, P<0.00001), which indicated that the heterogeneity was significant. Labbe Graph and Galbraith Plot for heterogeneity were shown in Figure 2A and Figure 2B. The random-effects models were selected, and the RR was 1.43 (95% CI:1.10-1.86, P=0.008) (Figure 2C), which means the incidence of LNM in the lncRNA high expression group was 1.43 times that in the low expression group, and it was statistically significant. Visual inspection of the Begg’s funnel plot revealed symmetry (Figure 2D). The symmetry of the above funnel plot was tested, and the result showed no publication bias (P=2.31) (Figure 2E).
Due to the significant heterogeneity, we explored the reasons for heterogeneity via sensitivity analysis (Figure 2F) and meta regression (Figure 2G). It was suggested that the up-regulated group and the down-regulated group were the sources of heterogeneity. Therefore, we performed subgroup analysis to these studies (Figure 2H). As for the up-regulated lncRNAs subgroup (RR=2.06, 95% CI: 1.53-2.78, P<0.00001), high lncRNA expression had a significant elevated LNM rate compared with low lncRNA expression. On the contrary, low lncRNA expression had a significant increased LNM rate compared with high lncRNA expression in the down-regulated lncRNAs subgroup (RR=0.49, 95% CI: 0.01-0.53, P=0.002).
The publication bias test was performed to the subgroups. As shown in Figure 2I and Figure 2J, a publication bias was found in the up-regulated group (P=0.000). For the asymmetric funnel plot of the up-regulated group, the trim and fill analysis was selected for correction, and 8 articles were finally virtualized. After the trim and fill analysis, no publication bias was found in the up-regulated group (Figure 2K and Figure 2L).
Relationship between lncRNAs expression levels and DM
Likewise, all chosen studies reported a total number of 730 patients with DM according to the different lncRNA expression levels. Labbe Graph and Galbraith Plot for heterogeneity were shown in Figure 3A and Figure 3B. As the heterogeneity was also significant (I2=78%, P=0.00001), a random-effects model was still adopted. As shown in Figure 3C, the results indicated that high lncRNA expression versus low lncRNA expression, had a statistic significant elevated DM rate for the up-regulated lncRNAs subgroup (RR=1.67, 95% CI: 1.21-2.29, P=0.002). Visual inspection of the Begg’s funnel plot revealed asymmetry (Figure 3D). The asymmetry of the above funnel plot was tested, and the result displayed a publication bias (P=0.002) (Figure 3E). For the asymmetric funnel plot of the eligible studies, the trim and fill analysis was selected for correction, and 5 articles were finally virtualized. After the trim and fill analysis, no publication bias was found in the up-regulated group (Figure 3F and Figure 3G).
We also explored the reasons for heterogeneity via sensitivity analysis (Figure 3H) and meta regression (Figure 3I). The results suggested that up/down regulation was not the source of heterogeneity and was not statistically significant.
Relationship between lncRNAs expression levels and prognosis
11 studies including 1850 patients reported the relationship between lncRNAs expression levels and prognosis (OS) of RCC patients in this meta-analysis. Due to the significant heterogeneity (I2=73%, P<0.0001), the random-effects model was used. As shown in Figure 4A, lncRNA expression levels were closely related to OS (HR=1.71, 95% CI: 1.28-2.28, P=0.0003) of RCC patients. Moreover, high lncRNA expression had a significant reduced clinical survival compared with low lncRNA expression. Visual inspection of the Begg’s funnel plot revealed symmetry (Figure 4B). The symmetry of the above funnel plot was tested, and the result showed no publication bias (P=0.448) (Figure 4C).
We also explored the reasons for heterogeneity via sensitivity analysis (Figure 4D) and meta regression (Figure 4E). The results suggested that up/down regulation was not the source of heterogeneity and was not statistically significant.
Publication bias, sensitivity analysis and meta regression
We used Stata 16.0 software to evaluate the sensitivity, publication bias and meta regression. In this meta-analysis, Begg’s test was used in publication bias due to the possible excessive assessment. Meanwhile, the sensitivity analysis was also used to assess the reliability and stability of the combined results and to see whether the individual study affected the overall results. Finally, meta regression was used to explore the causes of heterogeneity.