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Prognostic value of microRNAs in colorectal cancer: a meta-analysis

Authors Gao S, Zhao ZY, Wu R, Zhang Y , Zhang ZY 

Received 19 November 2017

Accepted for publication 12 February 2018

Published 30 April 2018 Volume 2018:10 Pages 907—929

DOI https://doi.org/10.2147/CMAR.S157493

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 4

Editor who approved publication: Dr Kenan Onel



Song Gao,1,* Zhi-Ying Zhao,2,* Rong Wu,1 Yue Zhang,3 Zhen-Yong Zhang1

1Second Department of Clinical Oncology, Shengjing Hospital of China Medical University, 2School of Computer Science and Engineering, Northeastern University, Shenyang, 3First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China

*These authors contributed equally to this work

Background: Numerous studies have shown that miRNA levels are closely related to the survival time of patients with colon, rectal, or colorectal cancer (CRC). However, the outcomes of different investigations have been inconsistent. Accordingly, a meta-analysis was conducted to study associations among the three types of cancers.
Materials and methods: Studies published in English that estimated the expression levels of miRNAs with survival curves in CRC were identified until May 20, 2017 by online searches in PubMed, Embase, Web of Science, and the Cochrane Library by two independent authors. Pooled HRs with 95% CIs were used to estimate the correlation between miRNA expression and overall survival.
Results: A total of 63 relevant articles regarding 13 different miRNAs, with 10,254 patients were ultimately included. CRC patients with high expression of blood miR141 (HR 2.52, 95% CI 1.68–3.77), tissue miR21 (HR 1.31, 95% CI 1.12–1.53), miR181a (HR 1.52, 95% CI 1.26–1.83), or miR224 (HR 2.12, 95% CI 1.04–4.34), or low expression of tissue miR126 (HR 1.55, 95% CI 1.24–1.93) had significantly poor overall survival (P<0.05).
Conclusion: In general, blood miR141 and tissue miR21, miR181a, miR224, and miR126 had significant prognostic value. Among these, blood miR141 and tissue miR224 were strong biomarkers of prognosis for CRC.

Keywords: microRNA, colorectal cancer, prognosis, meta-analysis

A Letter to the Editor has been received and published for this article.

Introduction

Numerous researchers have studied the associations between miRNA expression and the survival outcomes of colorectal cancer (CRC) patients.1258 CRC has a 10% cancer incidence and mortality worldwide,259 and thus, it is one of the most serious diseases threatening human health. Despite great success in the treatment of CRC, the prognosis of CRC patients is still poor. Therefore, it is fundamental for the diagnosis, treatment, and prognosis of CRC patients to understand its emphasized molecular origin.260 Despite a comprehensive study about the mechanisms of CRC, there are still some challenges that require recognizing prognostic biomarkers with minimal invasion and sensitivity. Accordingly, it is of vital significance to improve the survival rate of CRC patients, utilizing rapid and reliable tumor-prognosis biomarkers.

miRNAs, small noncoding RNA gene products of approximately 22 nucleotides, are found in various types of organisms. They account for 2%–5% of the entire genome, number about 1,000, and regulate the expression of ≥20% of human genes.261 In addition, they play crucial roles in regulating the translation and degradation of mRNAs via base pairing to partially complementary sites, predominantly in the 3′-untranslated areas of mRNAs.262264

In the study of CRC, a large number of articles have covered the fact that miRNAs are closely related to the survival time of patients.1258 There were relatively small samples in these papers, and the present work aims to estimate the most accurate prognostic value between miRNA level and survival outcome of CRC patients, better to comprehend the miRNAs with prognostic pertinence that are potential candidates for clinical verification in the future.

Materials and methods

Search strategy

We used four online databases – PubMed, Embase, Web of Science, and the Cochrane Library – to find pertinent literature published until May 20, 2017. The combination term “miR and colorectal cancer” was employed for the literature search. Two authors (S Gao and ZY Zhao) independently performed this comprehensive online search.

Inclusion criteria

Articles qualified if they satisfied the following criteria: patients with colon/rectal cancer or CRC; miRNA levels in tissue, plasma, or serum and survival results were measured; at least one survival curve was measured of overall survival (OS), cause-specific survival (CSS), disease-free survival (DFS), recurrence-free survival (RFS), progression-free survival (PFS), and metastasis-free survival (MFS), with or without HRs/95% CIs; and full text published in English.

Exclusion criteria

Exclusion criteria were experimental studies, reviews, or letters without primary data and retracted papers; frequency of research evaluating prognostic value of miRNAs in tissue of four or less. Only the most comprehensive study was included for this meta-analysis if more than one paper had been published in the same research group.

Quality assessment

SG and ZY Zhao identified all qualifying studies analyzing the prognostic value of miRNAs in CRC, and YZ reevaluated uncertain data.

Study selection

A flow diagram of the study selection process is presented in Figure 1. Our study found 1,843 articles for consideration within this meta-analysis, and 322 articles suitable for assessment of prognostic miRNA signatures in CRC and full-text papers were acquired by evaluating titles and abstracts. On elaborate review of research methodologies, 64 investigations were excluded, the details of which are shown in Figure 1. On the basis of the exclusion criteria, 63 studies were finally included in this meta-analysis.

Figure 1 Flow diagram of literature search and selection.

Study frequency

The frequency of studies estimating the prognostic value of miRNAs in CRC are shown in Tables 1 (blood) and 2 (tissue), including miRNA name, number of studies estimating prognostic value, and references.

Table 1 Frequency of studies estimating prognostic value of blood miRNA expression in colorectal cancer

Note: Highlighted studies were included in the present meta-analysis.

Table 2 Frequency of studies estimating prognostic value of tissue-miRNA expression in colorectal cancer

Note: Highlighted studies were included in the present meta-analysis.

Study characteristics

Literature with Kaplan–Meier survival curves for CRC are detailed in Table 3. If data were not provided visually and merely as curves, they were extracted from the curves, and estimated HRs with 95% CIs were subsequently calculated using the method of Tierney et al265 with Engauge Digitizer version 4.1 software. In addition, if outcomes of both univariate and multiple covariates were covered, only the latter was chosen, because of adjustment for confounders.

Table 3 Characteristics of studies included on colorectal cancer

Note: amultiple-covariate analysis; bUnivariate analysis;

Abbreviations: L/H, low versus high miRNA expression; H/L, high versus low miRNA expression; P, prospective; qRT-PCR, quantitative real-time polymerase chain reaction; OS, overall survival; DFS, disease-free survival; R, retrospective; RT-qPCR, reverse transcription qRT-PCR; RF-CSS, recurrence-free cause-specific survival; ROC, receiver-operating characteristic; FFPE, formalin-fixed, paraffin-embedded; ISH, in situ hybridization; MFS, metastasis-free survival; RFS, recurrence-free survival; PFS, progression-free survival; CSS, cause-specific survival; TCGA, the Cancer Genome Atlas; DCCG, Dutch Colorectal Cancer Group

Statistical analyses

All analyses were performed utilizing Stata version 13.0 (StataCorp, College Station, TX, USA). Merged HRs were regarded as significant at the P<0.05 level if 95% CIs did not contain the value 1. Effect values for HRs were regarded as large if ≥2. HRs for OS were regarded as the prime reference standard if OS P-values were inconsistent with other survival outcomes with respect to the associated miRNA level. All analyses employed random-effect models instead of fixed-effect models, because there existed differences among the studies, including tissue detected (frozen or formalin-fixed, paraffin-embedded), blood (plasma or serum), tumor stage (I–IV), cutoff values, and miRNA-analysis methods. Publication bias was measured by Begg’s funnel plot, and a two-tailed P-value <0.05 was regarded as significant. The trim-and-fill method was performed if publication bias occurred. Sensitivity analysis was employed to weigh how powerful merged HRs were after a single study had been removed. An individual study was suspected of having excess of influence if the point estimation was outside the 95% CI after removal from the analysis.

Results

Meta-analysis

An overview of HRs appraised from comprehensive analysis of all the miRNAs is given in Table 4. Thirteen miRNAs were involved in this meta-analysis: miR21, miR92a, miR106a, miR125b, miR126, miR141, miR143, miR145, miR181a, miR200b, miR203, miR224, and miR429. Results of survival analyses of these miRNAs are given in Figures 28.

Table 4 Meta-analysis results for miRNA expression in colorectal cancer

Notes: aMultiple-covariate analysis; badjusted with trim-and-fill method.

Abbreviations: OS, overall survival; DFS, disease-free survival; RFS, recurrence-free survival; CSS, cause-specific survival; MFS, metastasis-free survival; PFS, progression-free survival.

Figure 2 Pooled analyses of OS or DFS in association with high blood miR21-, miR92a-, miR141-, miR200b-, and miR203-expression levels.

Note: Weights are from random-effect analysis.

Abbreviations: OS, overall survival; DFS, disease-free survival.

Figure 3 (A) Forest plots of pooled analyses of OS or OS (multiple-covariate analysis) in association with high tissue miR21-expression levels; (B) Begg’s funnel plot of publication bias for pooled analysis of OS in association with high tissue miR21-expression levels; (C) sensitivity analysis of pooled analysis of OS in association with high tissue miR21-expression levels; (D) forest plots of pooled analyses of DFS or RFS/CSS/MFS/PFS in association with high tissue miR21-expression levels. Weights are from random-effects analysis in A and D. aMultiple-covariate analysis; bunivariate analysis.

Abbreviations: OS, overall survival; DFS, disease-free survival; RFS, recurrence-free survival; CSS, cause-specific survival; MFS, metastasis-free survival; PFS, progression-free survival.

Figure 4 (A) Funnel plot of pooled analysis adjusted with the trim-and-fill method of OS in association with high tissue miR21-expression levels. Circles, included studies; diamonds, presumed missing studies. (B) Forest plot of pooled analysis adjusted with the trim-and-fill method of OS in association with high tissue miR21-expression levels. (C) Sensitivity analysis of pooled analysis adjusted with the trim-and-fill method of OS in association with high tissue miR21-expression levels. Weights are from random-effects analysis. aMultiple-covariate analysis; bunivariate analysis.

Abbreviation: OS, overall survival.

Figure 5 Pooled analyses of OS or DFS/MFS in association with high tissue miR106a- and miR125b-expression levels. Weights are from random-effects analysis.

Abbreviations: OS, overall survival; DFS, disease-free survival; MFS, metastasis-free survival; TCGA, the Cancer Genome Atlas.

Figure 6 Pooled analyses of OS, PFS/RFS/CSS, or DFS/CSS/PFS in association with low tissue miR126- and miR143-expression levels. Weights are from random-effects analysis.

Abbreviations: OS, overall survival; DCCG, Dutch Colorectal Cancer Group; PFS, progression-free survival; RFS, recurrence-free survival; CSS, cause-specific survival; DFS, disease-free survival.

Figure 7 Pooled analyses of OS, MFS/DFS or DFS/CSS/PFS/RFS in association with high tissue miR145-expression levels or low tissue miR181a-expression levels. Weights are from random-effects analysis.

Abbreviations: OS, overall survival; TCGA, the Cancer Genome Atlas; MFS, metastasis-free survival; DFS, disease-free survival; CSS, cause-specific survival; PFS, progression-free survival; RFS, recurrence-free survival.

Figure 8 Pooled analyses of OS or DFS/MFS in association with high tissue miR224- and miR429-expression levels. Weights are from random-effects analysis.

Abbreviations: OS, overall survival; TCGA, the Cancer Genome Atlas; DFS, disease-free survival; MFS, metastasis-free survival.

CRC patients with high blood miR141, high tissue miR181a and miR224, or low tissue miR126 expression have significantly shorter OS

Two studies14,19 focused on associations between high blood miR141 levels and OS, indicating that CRC patients with high blood miR141 levels had significantly shorter OS than those with low miR141 expression (HR 2.52, 95% CI 1.68–3.77, P<0.01; Figure 2). Five papers120,122125 stressed connections between low tissue miR126 levels and OS, suggesting that CRC patients with low expression of tissue miR126 levels had significantly poorer OS than those with high miR126 expression (HR 1.55, 95% CI 1.24–1.93, P<0.01; Figure 6).

Three articles concentrated on the relationship between high tissue miR181a levels and OS, demonstrating that CRC patients with high miR181a levels had significantly worse OS than those with low miR181a expression (HR 1.52, 95% CI 1.26–1.83, P<0.01; Figure 7). Four studies paid attention to correlations between high expression of tissue miR224 levels and OS, showing that CRC patients with high tissue miR224 levels had significantly shorter OS than those with low miR224 expression (HR 2.12, 95% CI 1.04–4.34, P=0.04; Figure 8).

There was no significant relationship between high expression levels of blood miR21, miR92a, miR200b, miR203, tissue miR106a, miR125b, or miR429 or low expression levels of tissue miR143 or miR145 and OS

Details are given in Table 4 and Figures 2 and 58.

High tissue miR21 expression forecasts poor OS

Thirteen investigations5,6068,7073 analyzed the connection between high tissue miR21 levels and OS, showing that CRC patients with high tissue miR21 levels had significantly worse OS than those with low miR21 expression (HR 1.31, 95% CI 1.12–1.53, P<0.01; Figure 3A).

Publication bias

To assess publications showing some degree of bias for OS of CRC patients with high tissue miR21 levels, our study used Begg’s funnel plot (Figure 3B). The P-value was less than 0.01, indicating the presence of publication bias. As such, the trim-and-fill method was performed and the pooled HR recalculated with presumed missing studies to estimate asymmetry in the funnel plot (Figure 4A), indicating no publication bias (P=0.73). The recalculated HR changed significance for OS (HR 1.13, 95% CI 0.96–1.34, P=0.15; Figure 4B).

Sensitivity analysis

For research on OS of CRC patients with high tissue miR21 levels, the sensitivity analysis did not manifest alterations during outcomes on the basis of the exclusion of any single investigation (Figure 3C), showing that no sole study significantly affected the merged HR or 95% CI. This also proved true for the outcome of OS adjusted with the trim-and-fill method (Figure 4C).

Key findings

We carried out a meta-analysis of 13 miRNAs and OS. Serving as the most investigated miRNA, miR21 (high tissue levels) in CRC showed significantly shorter OS than low tissue miR21 levels (P<0.05). However, there was no significant relationship between high blood miR21 levels and OS (P=0.47). The different detected sample types and relatively small sample capacity of the miR21 blood group (only three studies analyzing the relationship between blood miR21 levels and OS) may have been potential clinical reasons and caused the statistical significance between tissue and blood miR21 levels.

Encouragingly, the HR from analysis of the association between high tissue miR21 levels and OS (multiple-covariate analysis)5,60,63,65,66,68,71,73 was 1.47, which was greater than that reported in any of the 13 articles.5,6078,7073 Nevertheless, the significance did not remain in accordance with the forest plot, which was adjusted with the trim-and-fill method because publication bias existed (P<0.01; Figure 3B). This result indicated that the prognostic value of tissue miR21 was not stable in CRC patients. There were other miRNAs with significant prognostic value in CRC, including blood miR141 and tissue miR21, miR181a, miR224, and miR126 (P<0.05). Among these, blood miR141 and tissue miR224 were powerful prognostic candidates in CRC (HR ≥2).

Discussion

Present situation

Increasing numbers of studies have indicated that diverse miRNAs are connected with survival results in CRC patients.1258 Nevertheless, no systematic review or meta-analysis has evaluated HRs between miRNA levels and survival outcomes of CRC patients. Therefore, it was of vital significance to launch a meta-analysis to comprehend the relationship between expression levels of miRNAs and prognoses of CRC patients.

Molecular mechanisms for miRNAs researched

An overview of miRNAs with dysregulated expression and their potential targets and pathways of entry is detailed in Figure 9. There was noticeable functional overlap and relationships among the miRNAs. Seven miRNAs (miR21, miR106a, miR126, miR143, miR181a, miR224, and miR429) touched upon cell functions, including cell apoptosis, cell cycle, and death. To sum up, these associations may refer to CRC progression.

Figure 9 Summary of microRNAs with altered expression and potential targets and pathways entered in this study.

Abbreviations: ATG7, autophagy related 7; E2F1, E2F transcription factor 1; TGFBR2, transforming growth factor beta receptor 2; CDKN1A, cyclin dependent kinase inhibitor 1A; TP53, tumor protein p53; BCL2, apoptosis regulator; CXCR4, C-X-C motif chemokine receptor 4; TLR2, toll like receptor 2; PTEN, phosphatase and tensin homolog; WIF1, WNT inhibitory factor 1; CDH1, cadherin 1; PHLPP1, PH domain and leucine rich repeat protein phosphatase 1; PHLPP2, PH domain and leucine rich repeat protein phosphatase 2; MBD2, methyl-CpG binding domain protein 2; SMAD4, SMAD family member 4; SOX2, SRY-box 2; HOXA5, homeobox A5; AKT1, AKT serine/threonine kinase 1; FOXO3, forkhead box O3; RHOA, ras homolog family member A.

Other CRC molecular pathways

In addition to miRNAs, there are some other molecular data that can be confounders, related to mortalities, such as the chromosomal instability pathway, the DNA mismatch repair system, and microsatellite instability (MSI). Features of distinctive pathways are different models of genetic instability, succeeding clinical presentations, and features of pathological behavior. A majority of CRC follows the chromosomal instability pathway, features of which are extensive loss of heterozygosis and gross chromosomal abnormalities.266,267 Second, about 15% of CRC is due to the derangement of the DNA mismatch repair system and consequential MSI. The former is in charge of protein production, which identifies and directly repairs mononucleotide mismatches at MS sequences that escape the proofreading system of DNA polymerase. Furthermore, a previous meta-analysis indicated that MSI-high CRC patients had a 40% better OS rate compared with MS-stable CRC patients.268

Molecular pathological epidemiology (MPE)

MPE is a multidisciplinary research field of associations between endogenous and exogenous ingredients, molecular cancer biomarkers, and cancer progression and also a comprehensive interdisciplinary science on the strength of the characteristic principal and continuum theory of diseases.269,270 Other than miRNAs, DNA mutation and methylation and other diagnostics, such as blood tests, also play crucial roles in cancer prognosis and MPE, which deeply investigates environmental exposure, intermediate phenotypes, such as blood biomarkers, and molecular changes in cancer using molecular pathologic analyses. MPE helps precision medicine by providing robust evidence for exposure–outcome associations, such as with drugs.

Strengths

This study has some strengths. Almost all the articles with survival consequences in CRC patients with disparate miRNAs were searched. Furthermore, the current expression profile of miRNAs is explicitly detailed in Tables 1 and 2 according to miRNAs and types of detected samples (blood or tissue). Papers assessing at least one of the survival curves of OS, CSS, DFS, RFS, PFS, and MFS were eventually included, and papers covering merely HRs or 95% CIs without any of the survival curves were excluded. Meta-analyses were performed on miRNAs investigated five or more times in CRC tissues. Virtually all the studies included had sample sizes ≥30 (except two),70,111 reinforcing the usability and enlarging the feasibility of consequences to CRC patients.

Limitations

Nevertheless, we cannot overemphasize the following limitations. There was much heterogeneity in designs of studies, and most of the outcomes from our meta-analyses contained high heterogeneity (I2≥50%). Statistical assessment of publication bias was suboptimal. There existed differences among the studies, including tissue-detected (frozen or formalin-fixed, paraffin-embedded), blood (plasma or serum), tumor stage (I–IV), cutoff values, and miRNA methods. The present meta-analysis simply included papers published in English, perhaps excluding potential studies published in other languages with respect to miRNA level and prognosis of CRC patients. Papers covering only HRs or 95% CIs without survival curves were excluded, lowering the sample sizes of the papers included. Because of the massive interrelation between papers and data about CRC, we subjectively and selectively included specific studies on the basis of the inclusion and exclusion criteria, bringing about the omission of several possible miRNAs with prognostic value and a relatively small number of included studies. The studies included contained three types of cancers (colon and rectal cancer and CRC), which blurred the division between tumor types. Some blood miRNAs were from cell-free RNA, while others were from exosome isolates. These were considered the same to some degree and may have caused some deviations in the final results.

Implications for prospective clinical and scientific study

It should be mentioned that the current meta-analysis is the first system assessment of the pertinence of miRNA level to the prognosis of CRC patients. This study presents foundations for prospective clinical and scientific study with respect to clinical staff and other health care providers, for whom simultaneous determination of miRNA expression is able greatly to reinforce assessment of life expectancy of CRC patients, thus enabling prompt therapy, and for scientific researchers. Current research progress and trends in connections between miRNAs and prognosis of CRC patients are shown in Tables 1 and 2. Selectively basic experiments can be conducted using these details (Figure 9). Conflicting results on the prognosis of miRNAs may be addressed based on the present meta-analysis.

Conclusion

In general, blood miR141 and tissue miR21, miR181a, miR224, and miR126 have significant prognostic value. Among these, blood miR141 and tissue miR224 are strong biomarkers of prognosis in CRC.

Author contributions

All authors contributed toward data analysis, drafting and critically revising the paper and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

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