| Literature DB >> 31227613 |
Jing Ye1, Haiyan Sun2, Zhengquan Feng1, Qiqin Zhang3, Yongliang Xia2, Yunxi Ji2, Qiqing Zhang1.
Abstract
BACKGROUND: Dysregulated expression of long non-coding RNA gastric carcinoma high expressed transcript 1 (lncRNA GHET1) has been observed in several cancers, however, definite conclusion on the prognostic value of lncRNA GHET1 expression in human cancers has not been determined. The aim of this meta-analysis was to evaluate the prognostic significance of lncRNA GHET1 expression in cancers.Entities:
Keywords: Cancer; LncRNA GHET1; Meta-analysis; Prognosis
Year: 2019 PMID: 31227613 PMCID: PMC6822487 DOI: 10.1042/BSR20190608
Source DB: PubMed Journal: Biosci Rep ISSN: 0144-8463 Impact factor: 3.840
Figure 1Literature search and selection
Characteristics of included studies
| Study | Country | Sample size ( | Gender (M/F) ( | GHET1 expression (H/L) ( | Detection method | Cut-off value | Cancer | Outcomes | NOS |
|---|---|---|---|---|---|---|---|---|---|
| Guan (2017) [ | China | 52 | 40/12 | 25/27 | qRT-PCR | Median | NSCLC | CP, OS | 7 |
| Jin (2017) [ | China | 68 | 35/33 | 27/41 | qRT-PCR | Mean | HCC | CP, OS | 7 |
| Li (2014) [ | China | 80 | 43/37 | 39/41 | qRT-PCR | Median | Bladder cancer | CP, OS | 7 |
| Liu (2017) [ | China | 55 | 34/21 | 28/27 | qRT-PCR | Median | ESCC | CP | 6 |
| Liu (2018) [ | China | 86 | 61/25 | 43/43 | qRT-PCR | Median | HNC | CP,OS | 7 |
| Shen (2018) [ | China | 105 | 44/61 | 53/52 | qRT-PCR | Median | NSCLC | CP, OS, PFS | 7 |
| Song (2018) [ | China | 60 | 0/60 | 30/30 | qRT-PCR | Median | Breast cancer | CP, OS | 7 |
| Xia (2018) [ | China | 42 | 28/14 | 21/21 | qRT-PCR | Median | Gastric cancer | CP | 6 |
| Yang (2014) [ | China | 42 | 31/11 | 21/21 | qRT-PCR | Median | Gastric cancer | CP, OS | 7 |
| Zhou (2017) [ | China | 64 | 34/30 | 36/28 | qRT-PCR | Median | Pancreatic cancer | CP | 6 |
Abbreviations: CP, clinicopathological parameter; F, female; H, high GHET1 expression; L, low GHET1 expression; M, male.
Figure 2Meta-analysis of OS
Subgroup analysis of OS
| Variables | Studies ( | HR, 95%CI | Heterogeneity | Model | ||
|---|---|---|---|---|---|---|
| ≤60 | 3 | 2.07 (1.34, 3.21) | <0.01* | 0 | 0.60 | Fixed |
| >60 | 4 | 3.10 (1.47, 6.55) | <0.01* | 65 | 0.04 | Random |
| Median | 6 | 2.26 (1.66, 3.07) | <0.01* | 0 | 0.61 | Fixed |
| Mean | 1 | 8.95 (3.56, 22.50) | <0.01* | NA | NA | Fixed |
| NSCLC | 2 | 2.82 (1.90, 4.18) | <0.01* | 0 | 0.55 | Fixed |
| Others | 5 | 2.34 (1.06, 5.16) | 0.03* | 62 | 0.03 | Random |
Abbreviation: NA, not available.
*P<0.05 indicating significant association between GHET1 expression and OS.
Figure 3Online cross-validation using TCGA data
Association between GHET1 expression and clinicopathological features
| Variables | Studies ( | Patients ( | High expression group (%) | Low expression group (%) | OR 95% CI | Heterogeneity | Model | ||
|---|---|---|---|---|---|---|---|---|---|
| Age (old versus young) | 9 | 574 | 50.7 versus 49.3 | 52.1 versus 47.9 | 0.94 (0.67, 1.31) | 0.70 | 0 | 0.88 | Fixed |
| Gender (male versus female) | 8 | 514 | 59.1 versus 40.9 | 60.4 versus 39.6 | 0.94 (0.65, 1.35) | 0.74 | 0 | 0.81 | Fixed |
| Tumor size (large versus small) | 8 | 522 | 62.9 versus 37.1 | 35.7 versus 64.3 | 3.06 (2.14, 4.38) | <0.01* | 45 | 0.08 | Fixed |
| Tumor differentiation (poor versus well) | 6 | 345 | 63.6 versus 36.4 | 44.4 versus 55.6 | 2.32 (1.48, 3.64) | <0.01* | 27 | 0.23 | Fixed |
| Distant metastasis (yes versus no) | 3 | 148 | 15.4 versus 84.6 | 2.9 versus 97.1 | 4.63 (1.23, 17.38) | 0.02* | 0 | 0.59 | Fixed |
| Lymph node metastasis (yes versus no) | 7 | 442 | 59.7 versus 40.3 | 30.3 versus 69.7 | 3.81 (2.51, 5.77) | <0.01* | 49 | 0.07 | Fixed |
| Clinical stage (III/IV versus I/II) | 6 | 422 | 62.8 versus 37.2 | 30.4 versus 69.6 | 3.92 (2.60, 5.91) | <0.01* | 0 | 0.92 | Fixe |
*P<0.05 indicating significant association between GHET1 expression and clinicopathological features.
Figure 4Funnel plots for all meta-analyses
Figure 5Begg’s test and Egger’s test for the meta-analysis of OS
Figure 6Sensitivity analysis for the meta-analysis of OS