Gastrointestinal malignancy is extremely harmful to humans, including gastric, pancreatic, esophageal, liver, and colorectal cancers and other types of cancer in the digestive tract. Their morbidity and mortality rates are really high, especially in less-developed countries [
MicroRNAs (miRNAs) are a kind of small noncoding RNA, which can modulate gene expression by cleaving targeted messenger RNA (mRNA) or repressing translation [
In the present study, a systematic review and meta-analysis was carried out to assess the association of miR-19 with gastrointestinal cancers. At first, miR-19 expression in gastrointestinal cancer tissue and normal tissue was compared, and then, the correlation of the miR-19 level with several clinical characteristics was evaluated. In addition, the role of miR-19 in prognosis for patients with gastrointestinal cancers was also determined.
Original researches reporting the association of miR-19 with the progression or prognosis of gastrointestinal cancers were retrieved in Embase, Web of Science, PubMed, and other databases until December 31, 2019. No language restriction was used. We selected studies according to the following keywords: “miR-19”, “microRNA-19”, or “miRNA-19” for miR-19; “colorectal carcinoma” or “colorectal cancer” for colorectal cancer; “esophageal cancer” or “esophagus neoplasm” for esophageal cancer; “gastric neoplasm”, “gastric cancer”, or “stomach cancer” for gastric cancer; “liver cancer”, “hepatocellular carcinoma”, or “hepatocellular cancer” for liver cancer; and “pancreatic neoplasm” or “pancreatic cancer” for pancreatic cancer.
Then, full texts of the relevant studies were evaluated deeply. The inclusion criteria were the following: (1) the expression level of miR-19 was detected by PCR, (2) the clinicopathological parameters or patient survival of gastrointestinal cancers were investigated, and (3) the association of miR-19 with clinicopathological parameters or patient survival was assessed. Studies were excluded if (1) they were not original articles, such as letters, case reports, or reviews; (2) they were focusing on cancer cells or animal models, rather than human samples; or (3) the full texts were not available. Two authors, Xiaoxu Song and Lin-Lin Cao, performed the evaluations independently, and disagreement was settled according to the original article.
Data were extracted by Xiaoxu Song and Wenyi Li independently. The extracted information included the first author’s name, country, publication year, age and number of patients, the method of miR-19 detection, cut-off point, histology, clinical stage, and survival. If the cut-off point of miR-19 was not described in the studies, the mean value was used as the cut-off point. If there was only a histogram and no original data for miR-19 expression were provided, Engauge Digitizer 4.1 was applied to extract the needed data. In addition, Engauge Digitizer 4.1 was also used for the survival data if there were only Kaplan-Meier curves in the included studies [
The quality evaluation of the retrieved studies was completed by Xiaoxu Song and Wenyi Li independently based on the Newcastle-Ottawa Scale (NOS), which includes three parts: sample selection, comparability, and exposure ascertainment.
All analyses were carried out with Review Manager 5.3 (Cochrane Collaboration, Oxford, UK). The odds ratio (OR) with 95% confidence interval (CI) was calculated to compare miR-19 levels between the tumor group and the control group and to analyze the correlation between miR-19 and clinicopathologic characters of gastrointestinal cancers. The association of miR-19 levels with patient prognosis was determined using the hazard ratio (HR) with 95% confidence interval (CI). The model of random effect was used if
There is no patient involved.
In this analysis, 711 studies were identified through searching Embase, PubMed, and Web of Science, and 646 studies were identified in other databases. In total, 1357 studies were found initially (Figure
Methodological flow chart of study selection.
Main characteristics and results of the included studies.
Study | Year | Country or area | Sample number | Age | Detection method | Cut-off point | Histology | Stage | Follow-up period (month) | Survival |
---|---|---|---|---|---|---|---|---|---|---|
Yamada | 2015 | USA | 48 | NR | RT-PCR | >median | CRC | NR | NR | NR |
Kahlert | 2011 | Germany | 29 | NR | RT-PCR | NR | CRC | NR | 60 | OS, RFS |
Cellura | 2015 | UK | 10 | NR | RT-PCR | ≥median | CRC | NR | NR | NR |
Huang | 2015 | China | 275 | 60 (mean) | RT-PCR | ≥0.22 | CRC | I-IV | NR | OS |
Jiang | 2017 | China | 211 | 65 (mean) | RT-PCR | >median | CRC | I-IV | 59 (median) | OS, DFS |
Mastumura | 2015 | Japan | 209 | 65 (mean) | RT-PCR | NR | CRC | I-IV | 60 | OS, DFS |
Cruz-Gil | 2018 | Spain | 126 | NR | RT-PCR | NR | CRC | II-III | NR | DFS |
Koga | 2010 | Japan | 62 | 60 (median) | RT-PCR | >median | CRC | NR | NR | NR |
Zhu | 2017 | China | 166 | 60 (mean) | RT-PCR | >median | CRC | I-IV | NR | NR |
Zhang | 2018 | China | 56 | 60 (mean) | RT-PCR | >median | CRC | I-IV | 80 | OS |
Yin | 2019 | China | 30 | 50 (mean) | RT-PCR | >median | CRC | I-IV | NR | NR |
Marcuello | 2019 | Spain | 59 | 62 (mean) | RT-PCR | NR | CRC | I-IV | NR | NR |
Guo | 2014 | China | 51 | 50 (mean) | RT-PCR | >median | HCC | I-IV | 60 | OS |
Han | 2012 | China | 105 | 56.5 (mean) | RT-PCR | NR | HCC | I-IV | 80 | OS, DFS |
Hu | 2018 | China | 20 | NR | RT-PCR | >median | HCC | NR | NR | NR |
Hung | 2015 | Taiwan | 81 | 60 (mean) | RT-PCR | ≥median | HCC | II-IV | 37 (mean) | OS, DFS |
Yu | 2016 | China | 43 | NR | RT-PCR | ≥median | HCC | NR | NR | NR |
Zhang | 2015 | China | 130 | 50 (mean) | RT-PCR | ≥median | HCC | I-IV | 60 | OS, DFS |
Zhu | 2010 | China | 95 | 50 (mean) | RT-PCR | HCC | I-III | 62.6 (mean) | OS | |
Jiang | 2018 | China | 22 | NR | RT-PCR | ≥median | HCC | NR | NR | NR |
Cai | 2016 | China | 60 | NR | RT-PCR | >median | GC | NR | NR | NR |
Li | 2014 | China | 30 | 50 (mean) | RT-PCR | NR | GC | I-IV | NR | NR |
Ibarrola-Villava | 2015 | Spain | 45 | NR | RT-PCR | ≥median | GC | NR | NR | NR |
Wang | 2016 | China | 90 | 65 (mean) | RT-PCR | >median | GC | I-IV | 60 | OS, DFS |
Wang | 2017 | China | 120 | 60 | RT-PCR | GC | I-IV | NR | NR | |
Wu | 2014 | China | 141 | 60 (mean) | RT-PCR | ≥median | GC | I-IV | 70 | OS |
Zhu | 2018 | China | 180 | 60 (mean) | RT-PCR | GC | I-IV | NR | NR | |
Liu | 2018 | China | 80 | 65.1 (mean) | RT-PCR | 2.072 | GC | I-IV | NR | NR |
Li | 2018 | China | 42 | NR | RT-PCR | ≥median | GC | NR | NR | NR |
Zhu | 2019 | China | 40 | NR | RT-PCR | ≥median | GC | NR | NR | NR |
Peng | 2018 | China | 333 | 59.42 (mean) | RT-PCR | ≥median | GC | I-IV | 60 | OS, PFS |
Xu | 2014 | China | 105 | 55 (mean) | RT-PCR | EC | I-IV | 34.5 (median) | OS, PFS | |
Bai | 2017 | China | 89 | 58 (mean) | RT-PCR | ≥0.2909 | EC | I-IV | NR | NR |
Tan | 2015 | China | 58 | NR | RT-PCR | ≥median | PC | NR | NR | OS |
Qu | 2014 | China | 39 | 65 (mean) | RT-PCR | NR | PC | I-IV | NR | NR |
Zou | 2019 | China | 129 | 60 (mean) | RT-PCR | >median | PC | I-IV | NR | OS |
Hu | 2016 | China | 63 | NR | RT-PCR | ≥median | PC | NR | NR | NR |
Abbreviations: NR: not reported; RT-PCR: real-time polymerase chain reaction; T/N: tumor/normal; CRC: colorectal cancer; EC: esophagus cancer; GC: gastric cancer; PC: pancreatic cancer; LC: liver cancer; OS: overall survival; DFS: disease-free survival; RFS: recurrence-free survival; PFS: progression-free survival.
Newcastle-Ottawa Scale for each included study.
Study | Selection | Comparability | Exposure | Total quality score |
---|---|---|---|---|
Yamada, 2015 | 3 | 1 | 3 | 7 |
Kahlert, 2011 | 3 | 2 | 3 | 8 |
Cellura, 2015 | 3 | 0 | 3 | 6 |
Huang, 2015 | 3 | 2 | 3 | 8 |
Jiang, 2017 | 3 | 2 | 3 | 8 |
Mastumura, 2015 | 4 | 2 | 3 | 9 |
Cruz-Gil, 2018 | 3 | 1 | 3 | 7 |
Koga, 2010 | 3 | 1 | 3 | 7 |
Zhu, 2017 | 3 | 2 | 3 | 8 |
Zhang, 2018 | 3 | 3 | 3 | 9 |
Yin, 2019 | 3 | 3 | 2 | 8 |
Marcuello, 2019 | 3 | 3 | 3 | 9 |
Guo, 2014 | 3 | 2 | 2 | 7 |
Han, 2012 | 3 | 2 | 3 | 8 |
Hu, 2018 | 3 | 0 | 3 | 6 |
Hung, 2015 | 3 | 2 | 3 | 8 |
Yu, 2016 | 3 | 1 | 3 | 7 |
Zhang, 2015 | 3 | 2 | 3 | 8 |
Zhu, 2010 | 3 | 2 | 2 | 7 |
Jiang, 2018 | 3 | 2 | 2 | 7 |
Cai, 2016 | 3 | 2 | 3 | 8 |
Li, 2014 | 4 | 2 | 3 | 9 |
Ibarrola-Villava, 2015 | 3 | 2 | 3 | 8 |
Wang, 2016 | 4 | 2 | 3 | 9 |
Wang, 2017 | 4 | 2 | 3 | 9 |
Wu, 2014 | 3 | 2 | 3 | 8 |
Zhu, 2018 | 3 | 2 | 3 | 8 |
Liu, 2018 | 3 | 3 | 3 | 9 |
Li, 2018 | 3 | 2 | 2 | 7 |
Zhu, 2019 | 2 | 3 | 2 | 7 |
Peng, 2018 | 3 | 3 | 3 | 9 |
Xu, 2014 | 4 | 2 | 3 | 9 |
Bai, 2017 | 3 | 2 | 3 | 8 |
Tan, 2015 | 3 | 0 | 3 | 6 |
Qu, 2014 | 2 | 1 | 3 | 6 |
Zou, 2019 | 3 | 2 | 3 | 8 |
Hu, 2016 | 3 | 1 | 3 | 7 |
Most of the included studies have compared miR-19 levels between gastrointestinal cancers and noncancerous controls, including 7 studies focusing on colorectal cancer, 8 studies focusing on gastric cancer, 5 studies focusing on liver cancer, 3 studies focusing on pancreatic cancer, and only 1 study focusing on esophageal cancer. The result is shown in Figure
Forest plot of odds ratio (OR). Relative miR-19 abundance of overall gastrointestinal malignancy in comparison to noncancerous controls.
Then, we carried out subgroup analysis according to different cancers. As shown in Figure
Forest plot of odds ratio (OR). (a) Comparison of the expression level of miR-19 between liver cancer and control. (b) Comparison of the expression level of miR-19 between colorectal cancer and control. (c) Comparison of the expression level of miR-19 between gastric cancer and control. (d) Comparison of the expression level of miR-19 between pancreatic cancer and control.
Next, we determined the correlation between miR-19 and the clinicopathologic characteristics of patients with gastrointestinal malignancy. Unfortunately, there is no significant correlation between the miR-19 level and some clinical features, such as the tumor stage, differentiation degree, or distant metastasis of overall gastrointestinal cancers (Figures
Forest plot of odds ratio (OR). Association between miR-19 expression and tumor stage in overall gastrointestinal malignancy.
Forest plot of odds ratio (OR). Association between miR-19 expression and tumor differentiation degree in overall gastrointestinal malignancy.
Forest plot of odds ratio (OR). Association between miR-19 expression and distant metastasis in overall gastrointestinal malignancy.
Forest plot of odds ratio (OR). Association between miR-19 expression and lymph node metastasis in overall gastrointestinal malignancy.
The results of subgroup analyses are displayed in Table
Subgroup analyses were stratified on the basis of histology.
Stage | Grade | Lymph node metastasis | Distant metastasis | |||||
---|---|---|---|---|---|---|---|---|
Colorectal cancer | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | ||||
6 | 2.74 (1.45, 5.18) | 3 | 1.36 (0.74, 2.51) | 7 | 1.89 (0.99, 3.63) | 8 | 2.02 (0.77, 5.32) | |
Gastric cancer | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | ||||
2 | 0.42 (0.17, 1.04) | 2 | 0.31 (0.14, 0.70) | 3 | 0.46 (0.14, 1.52) | 1 | 0.31 (0.10, 0.97) | |
Esophagus cancer | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | ||||
1 | 1.72 (0.95, 3.12) | 1 | 1.65 (0.86, 3.16) | 1 | 1.87 (0.91, 3.85) | None | None | |
Liver cancer | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | ||||
4 | 0.66 (0.18, 2.45) | 4 | 0.80 (0.47, 1.35) | 1 | 4.75 (1.37, 16.47) | None | None | |
Pancreatic cancer | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | ||||
None | None | None | None | None | None | None | None |
Abbreviations:
Finally, the correlation between miR-19 and OS as well as disease-free survival (DFS) of gastrointestinal malignancy was investigated. Firstly, the analysis result showed that gastrointestinal cancer patients with low and high miR-19 expression showed comparable OS (Figure
Forest plot of hazard ratio (HR). Association between miR-19 expression and the OS of overall gastrointestinal cancer patients.
Forest plot of hazard ratio (HR). Association between miR-19 expression and the OS of liver cancer (a), colorectal cancer (b), gastric cancer (c), and pancreatic cancer (d) patients.
In addition, gastrointestinal cancer patients with low and high miR-19 expression showed comparable DFS as well (Figure
Forest plot of hazard ratio (HR). Association between miR-19 expression and the DFS of overall gastrointestinal cancer patients.
Forest plot of hazard ratio (HR). Association between miR-19 expression and the DFS of liver cancer (a) and colorectal cancer (b).
We conducted sensitivity analysis by removing a cohort one time. Results of meta-analyses were not altered greatly, suggesting the stability of these analyses. In addition, no significant publication biases existed according to the symmetric funnel plots (Supplement Figures.
In this study, an analysis of 37 studies revealed a potential role of miR-19 in the progression and prognosis of gastrointestinal cancers. At first, miR-19 levels in gastrointestinal cancers are significantly higher than those in controls. In addition, the association of miR-19 expression with clinical characteristics, such as the clinical stage, tumor differentiation degree, and lymph node and distant metastasis state, was described in subgroup analysis. At last, we depicted that liver cancer patients with higher miR-19 levels showed better DFS than those with low miR-19.
miR-19 expression levels in different gastrointestinal malignancies are inconsistent. For liver and colorectal cancers, most studies showed that miR-19 is overexpressed in cancer patients compared with normal controls. However, miR-19 expression in gastric and pancreatic cancers is controversy. For example, it has been illustrated that the miR-19 levels were upregulated significantly in gastric cancer patients [
In the present study, significant correlation between miR-19 levels and lymph node metastasis was observed in gastrointestinal malignancy, suggesting the role of miR-19 as a potential biomarker to diagnose patients with lymph node metastasis. Although the correlations between miR-19 and clinical stage, tumor differentiation degree, or distant metastasis state in the overall gastrointestinal malignancy were not significant, subgroup analysis has shown that miR-19 has diagnostic value in specific cancer types. In addition, no correlation between miR-19 and OS or DFS of overall gastrointestinal malignancy was observed, but the miR-19 level was positively correlated with the DFS of liver cancer patients as depicted in subgroup analyses, indicating that miR-19 shows its potential as a prognostic biomarker for liver cancer and would be beneficial for screening out high-risk liver cancer patients.
This study revealed the clinical significance of the miR-19 level in gastrointestinal malignancy. miR-19 could be a potential clinical biomarker for the progress and survival evaluation for gastrointestinal cancers and used as a new target for gastrointestinal cancer treatment.
The authors declared no conflicts of interest.
Figure 1: funnel plots of publication bias in the meta-analysis as shown in Figure
Figure 2: funnel plots of publication bias in the meta-analysis of miR-19 expression and tumor stage.
Figure 3: funnel plots of publication bias in the meta-analysis of miR-19 expression and tumor differentiation degree.
Figure 4: funnel plots of publication bias in the meta-analysis of miR-19 expression and lymph node metastasis.
Figure 5: funnel plots of publication bias in the meta-analysis of miR-19 expression and distant metastasis.
Figure 6: funnel plots of publication bias in the meta-analysis of miR-19 expression and OS as shown in Figure
Figure 7: funnel plots of publication bias in the meta-analysis of miR-19 expression and DFS as shown in Figure