Open Access

The prognostic value of miR-126 expression in non-small-cell lung cancer: a meta-analysis

  • Wen Zheng1,
  • Ya Zhou2,
  • Jia Lu1,
  • Hualin Xu1,
  • Liangyu Lei1,
  • Chao Chen1,
  • Juanjuan Zhao1 and
  • Lin Xu1Email author
Cancer Cell International201717:71

https://doi.org/10.1186/s12935-017-0440-8

Received: 16 May 2017

Accepted: 6 July 2017

Published: 14 July 2017

Abstract

Objective

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related death. Growing evidence from recent studies have shown indicated that microRNA-126 (miR-126) played an important role in the progression of NSCLC. However, the potential value of miR-126 expression in prognosis of NSCLC remains to be fully elucidated. Here, we carried out a meta-analysis to assess the potential prognostic value of miR-126 for NSCLC.

Methods

PubMed, Embase, the Cochrane library, Web of Science, CNKI and WanFang database, as well as the reference of included studies, were searched to recognize pertinent studies until April 30, 2017. New castle-Ottawa scale was used to evaluate the quality of studies. Pooled hazard ratio (HR) with 95% confidence interval (CI) for overall survival (OS) was extracted by using a fixed-effects or a random-effects model on the basis of heterogeneity. Publication bias was evaluated by using Begg’s tests.

Results

We identified four eligible trials involving 666 non-small-cell lung cancer patients in this meta-analysis. The results indicated that a high level of miR-126 played a favorable role in the overall survival (HR 0.73, 95% CI 0.61–0.86, fixed-effects model). There was no bias existed in this study.

Conclusions

Our study showed that high expression level of miR-126 was a promising positive factor for OS for non-small cell lung cancer patients, and miR-126 might be a potential target for non-small-cell lung cancer therapy in the future.

Keywords

miR-21 NSCLC Prognosis Meta-analysis

Introduction

Lung cancer is the leading cause of cancer-related deaths in the world, and nearly 1 million new cases are expected annually by 2025, and non-small-cell lung cancer (NSCLC) accounts for 80% of cases [13], including major subtypes such as lung adenocarcinoma (ADC), squamous cell carcinoma (SCC), and large cell carcinoma (LCC) [4]. Although novel therapies have been developed, 5-year survival rate was still less than 15% due to its late diagnosis and poor outcome [5]. Therefore, further studies on prognostic assessment of these patients are essential for treatment stratification and ideal outcome of clinical lung cancer patients.

MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression through complementarity between the miRNA seed sequence and the target mRNA 3′untranslated region (UTR) [68]. Up to data, it was estimated that miRNAs may potentially regulate up to 30% of all human protein-coding genes [9], Recently, a large body of evidence showed that miRNAs exerted pivotal effects in the development and progression of human malignancies, including NSCLC [10]. As an important member of the miRNA family, microRNA-126 (miR-126), located within the seventh intron of epidermal growth factor-like protein 7 gene [11], was participated in a wide range of biological functions. Such as, in our previous study, we found that miR-126 could regulate the induction and function of CD4+Foxp3+ regulatory T cells through PI3K/AKT pathway [12]. Notably, MiR-126 also was documented played a vital role in the progression of NSCLC, For example, the expression level of miR-126 was significantly downregulated in NSCLC [1322]. Moreover, miR-126 could control the biological characters of NSCLC through different mechanisms. For instance, miR-126 could inhibit the proliferation of NSCLC through EGFL7 [23]. The upregulation of miR-126 in NSCLC A549 cells could reduce the expression of the target gene PIK3R2 and influence the PTEN/PI3K/AKT signaling pathway, suppressing the proliferation, migration, and invasive abilities of A549 cells [24]. In addition, decreased miR-126 expression could enhance the adhesion, migration and invasion of NSCLC cells through increased Crk protein [16, 25]. These results suggested that miR-126 may be function as an important regulatory gene in the development of NSCLC.

Furthermore, it has been reported that miRNA-126 has a potential prognostic role for predict outcome of non-small-cell lung cancer. However, there has been no systematic review of these literatures. Therefore, we firstly performed a meta-analysis of the data available from articles published in this field to evaluate the role of miR-126 expression as prognostic biomarker in non-small-cell lung cancer.

Materials and methods

Search strategy

Several relevant literature databases (PubMed, Embase, The Cochrane Library and Web of Science) and Chinese databases (CNKI and Wan Fang database) were searched for studies that estimated the diagnostic value of miR-126 in non-small-cell lung cancer. The studies were selected by using the following keywords in various combinations: ‘microRNA-126’, ‘miRNA-126’, ‘microRNA126’, ‘miR-126’, ‘miRNA126’, ‘miR-126-3p’, ‘carcinoma’, ‘non-small-cell lung’, ‘lung neoplasms’, and ‘non-small cell lung cancer’. The database was searched for the last time on April 30, 2017. The comprehensive database search was carried out independently by two authors.

Selection criteria

We used references manager software EndNote to check out duplications. The studies were selected and the data were extracted independently by two authors. And according to the follow inclusive criteria to choose studies: (1) it studied miR-126 in non-small-cell lung cancer; (2) it must be human samples; (3) it studied the association between miR-126 and survival outcome.

The exclusion criteria were the following: (1) studies related to the associations between miR-126 expression and prognosis that did not include survival analysis; (2) investigation of a set of miRNAs but not miR-126 alone. And (3) letters, case reports, reviews, conference abstracts, and animal or laboratory studies. (4) or lack of important information such as hazard ratio (HR), 95% CI and P value. (5) hazard ratio (HR) underwent subgroup analysis of pathological types of NSCLC.

Quality assessment

Newcastle–Ottawa scale was used to assess the methodological quality of studies incorporated in this meta-analysis [26], This standard assessed 3 sections (selection, comparability, exposure) and eight items. In the selection and exposure categories, a quality research item received 1 star, and a comparable category could receive at most two stars. The quality assessment values ranged from 0 to 9 stars. Generally, the study which scored at least five points was considered to be included in meta-analysis. The lowest score was 0 and the highest was 9. Studies with a score <5 in the present study were not included in the final analysis.

Data extraction

The data elements of this review including the following: (1) first author’s name, publication year, tumor grade, total number of Sample, miR-126 assay and cut-off values, (2) HR with 95% CI, outcomes and median follow-up (months). If the data were not provided visually and were only provided as Kaplan–Meier curves, the data were extracted from the graphical survival plots, and estimations of the HRs were then performed using a previously described method.

Statistical analyses

All data were pooled using STATA, version 12.0 (Stata Corp., College Station, TX). HR with 95% CI was used to combine the pooled data. We used the Chi square based Q-test to test the statistical heterogeneity of studies, then identified the absence of heterogeneity across studies, after used fixed-effects model (the Mantel–Haenszel method), Heterogeneity was defined as P < 0.10 or I2 > 50%. Finally, we used the methods of Begg plots test to analysis publication bias (P < 0.05 was considered representative of statistically significant publication bias).

Results

Literature research and characteristic of studies

A total of 320 studies were identified from the databases. 111 were duplicates, and the remaining 209 were further screened. Based on readings of the article titles and abstracts, as well as according to the inclusion and exclusion criteria, seven studies were selected for further investigation (as shown in Fig. 1). After reading the full texts of the remaining, 2 articles were excluded because they were recorded disease-free survival (DFS) and disease-specific survival (DSS) [27, 28], 1 articles were excluded because hazard ratio (HR) with 95% confidence interval (CI) for overall survival (OS) undergo subgroup analysis of pathological types of NSCLC [29]. Then, A total of 4 articles were eventually included [3033]. These four studies included a total of 666 patients. The method of miR-126 detection was all quantitative real-time polymerase chain reaction. MiR-126 expression level were measured in tumor tissue. The clinicopathological characteristics of the eligible studies are summarized in Table 1.
Fig. 1

Flow diagram of the studies identification and selection

Table 1

Characteristics of the studies included in this meta-analysis

Study

Year

Country

Sample number

Specimen

Stage

miR-126 assay

Cut-off value

Hazard ratio

Endpoint

Follow-up (months)

Chen et al. [30]

2015

China

103

Tissue

I–III

qRT-PCR

Median

DE

OS

NR

Kim et al. [31]

2014

South Korea

72

Tissue

I–IV

qRT-PCR

Median

Report

OS

31

Li et al. [32]

2014

China

49

Tissue

NR

qRT-PCR

Median

DE

OS

39

Yang et al. [33]

2012

China

442

Tissue

I–IV

qRT-PCR

Median

Report

OS

24.39–29.28

NR not reported, qRT-PCR quantitative real-time polymerase chain reaction, OS overall survival, DE data extrapolated

Quality assessment

The details of quality assessment based on the NOS are shown in Table 2. The last column in each row listed the total score of each study. Newcastle–Ottawa scale revealed that the study quality varied from 7 to 8 (Table 2). The quality of included studies was good and fair.
Table 2

Quality assessment based on the Newcastle–Ottawa scale

Study

Selection

Comparability

Exposure

Total

Chen et al. [30]

4

1

1

6

Kim et al. [31]

4

1

2

7

Li et al. [32]

4

1

2

7

Yang et al. [33]

4

2

2

8

Selection representativeness of studies (maximum score of 4), Comparability comparability of studies based on the design or analysis (maximum score of 2), Exposure assessment of outcome and follow-up (maximum score of 3)

Meta-analysis

For evaluating the association between miR-126 expression and OS for NSCLC, Forest plots of the individual HR estimates and the results of the meta analysis are presented in Fig. 2, No heterogeneity was detected between the studies, Therefore, a fix effects model was applied to calculate a pooled HR and its 95% CI (I2 = 26.6%, P = 0.252). These results showed that a higher expression level of miR-126 has significantly positive prognostic role in NSCLC and the pooled HR was 0.73 (95% CI 0.61–0.86).
Fig. 2

Forest plots of studies evaluating the pooled HR of elevated miR-126 level for overall survival (OS)

Publication bias

We used funnel plots and Begg’s tests to evaluate the publication bias of included studies. P < 0.05 indicated the presence of publication bias. The funnel plot of OS analysis was revealed in Fig. 3, and the P value of Begg’s regression intercept was 1.000, indicating that no evidence of significant publication bias was found in this meta-analysis.
Fig. 3

Begg’s funnel plots of publication bias test for overall survival (OS)

Discussion

MiR-126 has played a wide variety of function in non-small cell lung cancer. Such as, it was found at the cellular level, the upregulation of miR-126 in NSCLC A549 cells could reduce the expression of the target gene PIK3R2 and influence the PTEN/PI3K/AKT signaling pathway, suppressing the proliferation, migration, and invasive abilities of A549 cells [34]. Restoration of hsa-miR-126 more obviously inhibited cell growth, and the suppressive effect was more significant in H460 xenografts, which resulted from the inhibition of the activation of Akt and ERK [35]. Moreover, miR-126 was involved in regulating the response of NSCLC cells to cancer therapy. For example, miR-126 could promote non-small cell lung cancer cells apoptosis induced by irradiation through the PI3K-Akt pathway [36]. Enhanced expression of miR-126 could increase the sensitivity of NSCLC cells to anticancer agents through negative regulation of a VEGF/PI3K/Akt/MRP1 signaling pathway [37]. Furthermore, MiR-126 might be contributed to enhanced cytotoxicity induced by Gefitinib in lung cancer cells [35]. In addition, Matrine, as an active component of traditional Chinese medicine, could effectively induce cell cycle arrest and apoptosis, and recovered the expression of miR126 in NSCLC A549 cells [38]. These studies indicated that miR-126 played a key role in the biology of NSCLC cells, indicating it was a promising target for gene therapy against NSCLC patients.

Interestingly, recent evidence further showed that the expression level of miR-126 also changed in clinical NSCLC patients [39]. Such as, lower level of miR-126 was associated with poor pathological stage [14], large tumor diameter and lymph node metastasis [30, 40]. Recently, Shang et al. [41] reported that the specificity and sensitivity of serum miR-126 level in predicting NSCLC development were 82.68 and 96.40%, respectively. Meanwhile, the specificity and sensitivity of serum miR-126 level in predicting NSCLC metastasis were 84.00 and 62.30%. This study indicated that serum miR-126 level may be used as the predicative biomarkers for NSCLC development and metastasis. Furthermore, there was statistical difference on the serum level of hsa-miR-126 between in the Stage IV NSCLC patients and in the health control [42]. And, miR-126 was independently associated with a dismal prognosis (HR 4.1, 95% CI 2.0–8.4, P < 0.001) in lymph node-positive patients [28]. Further studies showed that miR-126 also played an important role in the diagnosis of non-small-cell lung cancer patients [43, 44]. For example, Zhu et al. revealed that the serum miR-126, miR-182, miR-183 and miR-21 levels could serve as a diagnostic biomarker for NSCLC early detection, with a high sensitivity and specificity (sensitivity, 81.3%; specificity, 100.0%; and accuracy, 90.8%) [45]. Expression levels of miR-126, -296, -145, -199a, -191, -223, -24, -152, -320, and let-7 in the plasma of NSCLC including stage-I patients were significantly higher than these in controls. The combination of these microRNAs yielded 87% sensitivity and 90% specificity (AUC = 0.934) in discriminating NSCLC patients from controls [46]. Similarly, an eleven-plasma miRNA panel (including miR-126) that could distinguish NSCLC patients from healthy subjects (AUC = 0.879) [27]. Song et al. also reported that combination of three miRNAs miR-126, miR-205 and miR-182 could also predict NSCLC at the accuracy of 84.49%, sensitivity of 91.40% and specificity of 77.14%, respectively [47]. Interestingly, exosomes miR-126 could also be reported as a marker of diagnosis of NSCLC patient. For example, Exosomes miR-126 and let-7a were present in significantly higher levels in the BAL fluid of lung adenocarcinoma patients, and they could serve as diagnostic biomarkers in early stage lung adenocarcinoma [48]. Combining these data showed that miR-126 was a potential biomarker for the diagnosis of NSCLC.

Notably, MiR-126 has also been reported was a promising index in the prognosis of NSCLC patients. For Example, the levels of miR-126 were significantly associated with disease free survival (DFS) rate [32, 49, 50]. And, low plasma level of miR-126-3p were significantly associated with poor DFS in lung adenocarcinoma patients(HR = 0.497,95% CI = 0.191–1.295). Jusufović et al. discovered that lower miR-126 expression was a negative prognostic factor for both progression free survival (HR 0.10, 95% CI 0.04–0.21) in NSCLC patients, which may be attributed to elevated tumor angiogenesis [29]. In line with these findings, in present study, our analysis showed that elevated miR-126 expression alone also could be positively related to the overall survival (OS) in patients with NSCLC, indicating an important value of miR-126 expression alone in the prognosis of NSCLC patients. Interestingly, Lønvik et al. also reported that Drosha/miR-126 coexpression had a significant negative impact on the disease-specific survival (DSS) rate (P < 0.001) [51]. Donnem et al. also demonstrated that coexpression of VEGF-A and miR-126 had an independent prognostic impact (P = 0.017). For NSCLC patients with high VEGF-A/high miR-126 expression, HR was 2.5 (95% CI = 1.4–4.3) on the disease-specific survival (DSS) compared with patients who had low VEGF-A/low miR-126 expression [28]. Furthermore, NSCLC patients with low expression of miR-126 or both miRNAs combined (let-7b and miR-126) were highly associated with Progression-free survival (PFS), HR = 0.22 (95% CI = 0.07–0.74) or HR = 0.09 (0.01–0.65) [29]. However, the possible difference and significance between the expression of miR-126 alone and the coexpression of miR-126 and other factors on the prognosis of NSCLC patients still remained to be elucidated in future. Finally, it should be noted that Jusufovic et al. reported overall survival (OS) in patients with NSCLC (HR = 0.33 95% CI = 0.09–1.21) [29], which did not be included in this study. Because we found that HR for overall survival (OS) were obtained from subgroup analysis of pathological types of NSCLC, which was different from the other 4 literatures included in current study. Interestingly, we also noticed that the patients of this article were from Serbia, however, all of the patients in our study were from Asia, which could lead to increased heterogeneity (I2 = 78.8%, P = 0.001). Therefore, we presumed that difference of racial and pathological types might be potential cofactors for the prognosis of miR-126 expression in NSCLC, which was much valuable to be validated in successive research work.

Although, miR-126 has been widely investigated, however, there are still some limitations to be considered. Firstly, only four studies were eligible for pooled analysis, which might affect the results of the present study. Secondly, the expression of miR-126 was detected in tumor tissue samples but not in serum or plasma. However, circulating prognostic markers were found to be more valuable than tissue markers in cancer patients. Therefore, the conclusions from our study should be tempered. Thus, further large studies taking into account the effects of gender, age and ethnicity, just as mentioned above, are warranted to obtain a more robust assessment of the association between miR-126 and the prognosis of NSCLC. In conclusion, our results supported a value prognostic role for miR-126 in NSCLC, which might be ultimately useful for the understanding on the role of miR-126 in occurrence of NSCLC and development of effectively therapeutic agents of NSCLC patients.

Conclusion

Our study showed that high expression level of miR-126 was a promising positive factor for OS of non-small cell lung cancer patients, which indicated that miR-126 might be a potential target for non-small-cell lung cancer therapy and ultimately benefit the outcome of clinical therapy in the future.

Abbreviations

NSCLC: 

non-small cell lung cancer

miR-126: 

microRNAs-126

OS: 

overall survival

PFS: 

progression-free survival

DSS: 

disease-specific survival

CI: 

confidence interval

Declarations

Authors' contributions

WZ collected and analyzed the data, wrote the paper; YZ, HX and LL analyzed the data; CC and JZ wrote the paper; LX conceived and designed this study, analyzed the data, wrote the paper; and all authors reviewed the paper. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

Competing interests

All authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential competing interests.

Availability of data and materials

Please contact author for data requests.

Funding

This manuscript was supported by Program for High level innovative talents in Guizhou Province (QKH-RC-2016-4018), New Century Excellent Talents in University, Ministry of Education of China (NCET-12-0661), National Natural Science foundation of China (31370918), Program for Excellent Young Talents of Zunyi Medical University (15ZY-001) and Project of Guizhou Provincial Department of Science and Technology (2009C491).

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Immunology, Zunyi Medical College
(2)
Department of Medical Physics, Zunyi Medical College

References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66(1):7–30.View ArticlePubMedGoogle Scholar
  2. Torre LA, Bray F, Siegel RL, et al. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87–108.View ArticlePubMedGoogle Scholar
  3. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65(1):5–29.View ArticlePubMedGoogle Scholar
  4. Watanabe T, Miura T, Degawa Y, et al. Comparison of lung cancer cell lines representing four histopathological subtypes with gene expression profiling using quantitative real-time PCR. Cancer Cell Int. 2010;10:2.View ArticlePubMedPubMed CentralGoogle Scholar
  5. Torre LA, Siegel RL, Jemal A. Lung cancer statistics. Adv Exp Med Biol. 2016;893:1–19.View ArticlePubMedGoogle Scholar
  6. Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75(5):843–54.View ArticlePubMedGoogle Scholar
  7. Garzon R, Fabbri M, Cimmino A, et al. MicroRNA expression and function in cancer. Trends Mol Med. 2006;12(12):580–7.View ArticlePubMedGoogle Scholar
  8. Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136(2):215–33.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005;120(1):15–20.View ArticlePubMedGoogle Scholar
  10. Li W, Wang W, Ding M, et al. MiR-1244 sensitizes the resistance of non-small cell lung cancer A549 cell to cisplatin. Cancer Cell Int. 2016;16:30.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Meister J, Schmidt MH. miR-126 and miR-126*: new players in cancer. Sci World J. 2010;10:2090–100.View ArticleGoogle Scholar
  12. Qin A, Wen Z, Zhou Y, et al. MicroRNA-126 regulates the induction and function of CD4(+) Foxp3(+) regulatory T cells through PI3K/AKT pathway. J Cell Mol Med. 2013;17(2):252–64.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Tafsiri E, Darbouy M, Shadmehr MB, et al. Abberent expression of oncogenic and tumor-suppressive microRNAs and their target genes in human adenocarcinoma alveolar basal epithelial cells. J Cancer Res Ther. 2016;12(1):395–400.View ArticlePubMedGoogle Scholar
  14. Tafsiri E, Darbouy M, Shadmehr MB, et al. Expression of miRNAs in non-small-cell lung carcinomas and their association with clinicopathological features. Tumor Biol. 2015;36(3):1603–12.View ArticleGoogle Scholar
  15. Hu X, Zhang F, Liu XR, et al. Efficacy and potential microRNA mechanism for computed tomography-guided percutaneous radiofrequency ablation of primary lung cancer and lung metastasis from liver cancer. Cell Physiol Biochem. 2014;33(5):1261–71.View ArticlePubMedGoogle Scholar
  16. Tsay JJ, Tchou-Wong K, Yie T, et al. Bronchial brushings’ microRNA and field cancerization in lung adenocarcinoma. Am J Respir Criti Care Med. 2013;187:A4753.Google Scholar
  17. Markou A, Sourvinou I, Vorkas PA, et al. Clinical evaluation of microRNA expression profiling in non small cell lung cancer. Lung Cancer. 2013;81(3):388–96.View ArticlePubMedGoogle Scholar
  18. Wang Y, Shi J, Wu Y, et al. Use of Luminex xMAP bead-based suspension array for detecting microRNA in NSCLC tissues and its clinical application. Tumori. 2012;98(6):792–9.PubMedGoogle Scholar
  19. Guan P, Yin Z, Li X, et al. Meta-analysis of human lung cancer microRNA expression profiling studies comparing cancer tissues with normal tissues. J Exp Clin Cancer Res. 2012;31(1):54.View ArticlePubMedPubMed CentralGoogle Scholar
  20. Kausar H, Jeyabalan J, Aqil F, et al. Berry anthocyanidins synergistically suppresses non-small-cell lung cancer cell growth and metastasis and enhances sensitivity to the chemotherapeutic drug paclitaxel. J Thorac Oncol. 2011;6(6):S930–1.Google Scholar
  21. Guo M, Huang M, Calin GA, et al. Altered microRNA expression in adenocarcinoma of lung from smokers and never-smokers. Lab Invest. 2011;91:443A.Google Scholar
  22. Yang Y, Li X, Yang Q, et al. The role of microRNA in human lung squamous cell carcinoma. Cancer Genet Cytogenet. 2010;200(2):127–33.View ArticlePubMedGoogle Scholar
  23. Sun Y, Bai Y, Zhang F, et al. miR-126 inhibits non-small cell lung cancer cells proliferation by targeting EGFL7. Biochem Biophys Res Commun. 2010;391(3):1483–9.View ArticlePubMedGoogle Scholar
  24. Song L, Li D, Gu Y, et al. MicroRNA-126 targeting PIK3R2 inhibits NSCLC A549 cell proliferation, migration, and invasion by regulation of PTEN/PI3K/AKT pathway. Clin Lung Cancer. 2016;5:e65–75.View ArticleGoogle Scholar
  25. Crawford M, Brawner E, Batte K, et al. MicroRNA-126 inhibits invasion in non-small cell lung carcinoma cell lines. Biochem Biophys Res Commun. 2008;373(4):607–12.View ArticlePubMedGoogle Scholar
  26. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5.View ArticlePubMedGoogle Scholar
  27. Sanfiorenzo C, Ilie MI, Belaid A, et al. Two panels of plasma microRNAs as non-invasive biomarkers for prediction of recurrence in resectable NSCLC. PLoS ONE. 2013;8(1):e54596.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Donnem T, Lonvik K, Eklo K, et al. Independent and tissue-specific prognostic impact of miR-126 in nonsmall cell lung cancer: coexpression with vascular endothelial growth factor-A predicts poor survival. Cancer. 2011;117(14):3193–200.View ArticlePubMedGoogle Scholar
  29. Jusufovic E, Rijavec M, Keser D, et al. let-7b and miR-126 are down-regulated in tumor tissue and correlate with microvessel density and survival outcomes in non-small-cell lung cancer. PLoS ONE. 2012;7(9):e45577.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Chen S-W, Wang T-B, Tian Y-H, et al. Down-regulation of microRNA-126 and microRNA-133b acts as novel predictor biomarkers in progression and metastasis of non small cell lung cancer. Int J Clin Exp Pathol. 2015;8(11):14983–8.PubMedPubMed CentralGoogle Scholar
  31. Kim MK, Jung SB, Kim J-S, et al. Expression of microRNA miR-126 and miR-200c is associated with prognosis in patients with non-small cell lung cancer. Virchows Arch. 2014;465(4):463–71.View ArticlePubMedGoogle Scholar
  32. Li X, Wan YL, Sun C, et al. Effect of miR-126 on cell cycle regulation and prognosis of lung cancer patients. J Pract Oncol. 2014;29(5):440–5.Google Scholar
  33. Yang J, Lan H, Huang X, et al. MicroRNA-126 inhibits tumor cell growth and its expression level correlates with poor survival in non-small cell lung cancer patients. Plos ONE. 2012;7(8):e42978.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Song L, Li D, Gu Y, et al. MicroRNA-126 targeting PIK3R2 inhibits NSCLC A549 cell proliferation, migration, and invasion by regulation of PTEN/PI3K/AKT pathway. Clin Lung Cancer. 2016;17(5):e65–75.View ArticlePubMedGoogle Scholar
  35. Zhong M, Ma X, Sun C, et al. MicroRNAs reduce tumor growth and contribute to enhance cytotoxicity induced by gefitinib in non-small cell lung cancer. Chem Biol Interact. 2010;184(3):431–8.View ArticlePubMedGoogle Scholar
  36. Wang XC, Du LQ, Tian LL, et al. Expression and function of miRNA in postoperative radiotherapy sensitive and resistant patients of non-small cell lung cancer. Lung Cancer. 2011;72(1):92–9.View ArticlePubMedGoogle Scholar
  37. Zhu X, Li H, Long L, et al. MiR-126 enhances the sensitivity of non-small cell lung cancer cells to anticancer agents by targeting vascular endothelial growth factor A. Acta Biochim Biophys Sin. 2012;44(6):519–26.View ArticlePubMedGoogle Scholar
  38. An Q, Han C, Zhou Y, et al. Matrine induces cell cycle arrest and apoptosis with recovery of the expression of miR-126 in the A549 non-small cell lung cancer cell line. Mol Med Rep. 2016;14(5):4042–8.PubMedPubMed CentralGoogle Scholar
  39. Jin X, Xie C. Evaluation of exosomal miRNAs from plasma as potential biomarker for NSCLC. J Thorac Oncol. 2017;12(1):S350–1.View ArticleGoogle Scholar
  40. Chen Q, Hu H, Jiao D, et al. MiR-126-3p and miR-451a correlate with clinicopathological features of lung adenocarcinoma: the underlying molecular mechanisms. Oncol Rep. 2016;36(2):909–17.PubMedGoogle Scholar
  41. Shang AQ, Xie YN, Wang J, et al. Predicative values of serum microRNA-22 and microRNA-126 levels for non-small cell lung cancer development and metastasis: a case-control study. Neoplasma. 2017;64(3):453–9.View ArticlePubMedGoogle Scholar
  42. Lin Q, Mao W, Shu Y, et al. A cluster of specified microRNAs in peripheral blood as biomarkers for metastatic non-small-cell lung cancer by stem-loop RT-PCR. J Cancer Res Clin Oncol. 2012;138(1):85–93.View ArticlePubMedGoogle Scholar
  43. Yan J, Ma S, Zhang Y, et al. Potential role of microRNA-126 in the diagnosis of cancers: a systematic review and meta-analysis. Medicine (Baltimore). 2016;95(35):e4644.View ArticleGoogle Scholar
  44. Shen J, Todd NW, Zhang H, et al. Plasma microRNAs as potential biomarkers for non-small-cell lung cancer. Lab Invest. 2011;91(4):579–87.View ArticlePubMedGoogle Scholar
  45. Zhu W, Zhou K, Zha Y, et al. Diagnostic value of serum miR-182, miR-183, miR-210, and miR-126 levels in patients with early-stage non-small cell lung cancer. PLoS ONE. 2016;11(4):e0153046.View ArticlePubMedPubMed CentralGoogle Scholar
  46. Ilie M, Sanfiorenzo C, Brest P, et al. Plasma miR-155, miR-152, miR-20a, miR-223, miR-126 and miR-199a expression as a novel prognostic signature of resectable non-small cell lung carcinoma (NSCLC). Virchows Arch. 2012;461(1):S51–2.Google Scholar
  47. Song R, Liu Q, Hutvagner G, et al. Rule discovery and distance separation to detect reliable miRNA biomarkers for the diagnosis of lung squamous cell carcinoma. BMC Genom. 2014;15(9):S16.View ArticleGoogle Scholar
  48. Kim MH, Jo EJ, Eom JS, et al. Diagnostic value of microRNAs derived exosomes from bronchoalveolar lavage fluid in early stage lung adenocarcinoma. Chest. 2016;150(4):703A.View ArticleGoogle Scholar
  49. Ilie M, Sanfiorenzo C, Brest P, et al. Plasma miR-155, miR-152, miR-20a, miR-223, miR-126 and miR-199a expression as a novel prognostic signature of resectable non-small cell lung carcinoma (NSCLC). Virchows Arch. 2012;461:S51–2.Google Scholar
  50. Markou A, Sourvinou I, Vorkas PA, et al. Clinical evaluation of microRNA expression profiling in non small cell lung cancer. Lung Cancer. 2013;81(3):388–96.View ArticlePubMedGoogle Scholar
  51. Lønvik K, Wsørbye S, Nilsen MN, et al. Prognostic value of the microRNA regulators Dicer and Drosha in non-small-cell lung cancer:co-expression of Drosha and miR-126 predicts poor survival. BMC Clin Pathol. 2014;14(1):45.View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© The Author(s) 2017

Advertisement