Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Low serum level of miR-485-3p predicts poor survival in patients with glioblastoma

  • Zhi-Qiang Wang,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing – original draft

    Affiliations Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China

  • Mei-Yin Zhang,

    Roles Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing – original draft

    Affiliations State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China

  • Mei-Ling Deng,

    Roles Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing – original draft

    Affiliations Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China

  • Nuo-Qing Weng,

    Roles Data curation, Formal analysis, Investigation, Validation, Visualization, Writing – review & editing

    Affiliations State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China

  • Hui-Yun Wang ,

    Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – review & editing

    wanghyun@mail.sysu.edu.cn (HYW); wushx@sysucc.org.cn (SXW)

    Affiliations State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China

  • Shao-Xiong Wu

    Roles Conceptualization, Formal analysis, Project administration, Resources, Supervision, Writing – review & editing

    wanghyun@mail.sysu.edu.cn (HYW); wushx@sysucc.org.cn (SXW)

    Affiliations Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China

Abstract

MicroRNAs (miRNAs) are short noncoding RNAs that play critical roles in human malignancies and can be used as biomarkers for cancer. Until now, a number of biomarkers for prognosis of glioblastoma (GBM) have been reported in tumor tissues but only a few biomarkers in circulating fluid. Using a custom microarray, we previously identified 19 differentially expressed miRNAs in serum of patients with GBM. In this study, we investigated whether 3 of the 19 miRNAs in serum could be used as prognostic biomarkers for patients with GBM. We first validated the serum levels of 3 candidate miRNAs in an independent cohort of 24 GBM patients and 12 healthy volunteers by real-time quantitative reverse transcription PCR (qRT-PCR), and then evaluated the prognostic value of these miRNAs in a total of 36 GBM patients. The results show that the serum levels of the 3 miRNAs (miR-451a, miR-485-3p and miR-4298) determined by qRT-PCR are significantly different between 24 GBM patients and 12 healthy volunteers (all P <0.05) and are in concordance with the results of microarray analysis. High serum level of miR-451a is correlated with positive tumor O(6)-methylguanine-DNA methyltransferase (MGMT) expression (P = 0.040). Survival analysis showed that low serum miR-485-3p level is associated with poor progression-free survival (PFS) (P < 0.004) and overall survival (OS) (P < 0.023). Furthermore, univariate and multivariate Cox analyses demonstrated that that serum miR-485-3p expression is a significant independent prognostic factor for PFS and OS in GBM patients. In conclusion, serum miR-485-3p level is reduced and might be a potential prognostic biomarker in GBM patients.

Introduction

Glioblastoma (GBM) is the most common malignant primary brain tumor in adults. Despite advances in treatment, patients with GBM have a very poor outcome with a 5-year overall survival rate of less than 10% [1, 2]. To improve the survival of GBM patients, it is critical to understand the molecular mechanism of GBM development and progression and identify the molecular biomarkers for prognosis and targeted therapy. At present, many molecular biomarkers for prognosis have been identified from GBM tissues, such as O-6-methylgua-nine-DNA methyltransferase (MGMT), isocitrate dehydrogenase 1 and 2 (IDH1/2), p53, epidermal growth factor receptor (EGFR), platelet-derived growth factor receptor (PDGFR), phosphatase and tensin homolog (PTEN), phosphoinositide 3-kinase (PI3K), and 1p/19q [3]. These biomarkers also might be used as targets of gene therapy. However, though some of these biomarkers, such as p53 [4] and IDH1 [5] can be detected in peripheral blood, most of these biomarkers only can be detected in tumor tissues from GBM patients with surgical resection. Therefore, easily accessible and non-invasive biomarkers, which can be detected in GBM patients with or without surgery, is critical to more effective management of GBM.

MicroRNAs (miRNAs) are small endogenous noncoding RNA molecules that play important roles in a variety of physiological and pathological processes including tumorigenesis and tumor progression [611]. Tumor specific circulating miRNAs were first detected in the serum of patients with diffuse large B-cell lymphoma in the year 2008 [12]. Recently, more and more studies suggested that circulating miRNAs can be very stable in biofluid and might be used as potential molecular biomarkers for human malignancies [1315]. However, there are only a few studies on circulating miRNAs in serum, plasma or cerebrospinal fluid (CSF) of glioma patients, including GBM [1618]. Therefore, identification of circulating miRNAs as biomarkers will be helpful for clinicians in the diagnosis, prognosis and treatment of GBM patients.

Using a custom microarray platform containing 1843 species of miRNAs, we previously identified 19 serum miRNAs with differential expression between 22 GBM patients and 8 healthy volunteers [19]. Here, we first validated expressions of 3 serum miRNAs of the 19 miRNAs in a cohort of 24 GBM patients and 12 healthy volunteers using real-time quantitative reverse transcription PCR (qRT-PCR), and then determined which serum miRNAs might be used as a molecular biomarker for predicting the prognosis in 36 GBM patients.

Materials and methods

Patients and clinical samples

Blood samples were obtained from 36 patients with GBM before surgery at the Sun Yat-Sen University Cancer Center between July 2011 and April 2014. The patients meeting the following inclusion and exclusion criteria were included in this study: (1) macroscopically complete resection of tumor; (2) no treatment before surgery; (3) first diagnosed as GBM by pathology after surgery; (4) receiving intensity-modulated radiotherapy plus concomitant temozolomide treatment with or without adjuvant temozolomide chemotherapy; (5) no other cancers at diagnosis. All patient characteristics are shown in Table 1. The patients included 21 males and 15 females. The median age of patients at the time of diagnosis was 48 years (range 16–76 years). None of the patients had received chemotherapy or radiotherapy before surgery. After surgery, all patients received radiotherapy combined with chemotherapy. The latest follow-up was updated in March 2015, and the median time of follow-up was 17.4 months (range 5.6–44.8 months). Overall survival (OS) is defined as the time from the date of surgery to the date of death from GBM or last date of follow-up; Progression-free survival (PFS) is defined as the time from the date of surgery to the date of relapse or metastasis of GBM or death from GBM or last date of follow-up. Control blood samples were collected from 12 healthy age- and sex-matched volunteers (median age: 48 years, age range 18–70 years). Blood samples (3 mL) were drained into tubes, and then centrifuged for 15 min at 1200g to separate buffy coats and serum. The serum was aspirated, aliquoted and stored at -80°C until use. This study was approved by the Research Ethics Committee of Sun Yat-Sen University Cancer Center. In this study, all participants or guardians on behalf of the participants whose age was under 18 years old signed a written informed consent form for the use of their blood samples before surgery.

thumbnail
Table 1. Correlation of serum levels of three miRNAs with clinicopathological factors in GBM patients.

https://doi.org/10.1371/journal.pone.0184969.t001

MicroRNA isolation

RNA was isolated from serum samples using the Plasma/Serum Circulating and Exosomal RNA Purification Mini Kit (Slurry Format) (Norgen Biotek Corporation, Thorold, Ontario, Canada, L2V4Y6) according to manufacturer’s instructions. Briefly, 0.3 mL of Slurry C2 solution and 2.7 mL of Lysis Buffer A were added to 1.5 mL of serum and mixed well. The mixture was incubated for 10 minutes at 60°C. After incubation, 4.5 mL of 100% ethanol was added into the tubes and mixed well. The tubes were centrifuged for 30 seconds at 201 g (1000 RPM), and then the supernatants were discarded. Lysis buffer A (0.45 mL) was added into the tubes again to dissolve the slurry pellet and incubated for another 10 minutes at 60°C. After adding 0.45 mL of ethanol, the mixtures were loaded onto the provided column and centrifuged for 1 minute at 20871 g (14000 RPM). After discarding the eluate and washing the column with 400 μL of Wash Solution A for 3 times, 100 μL of Elution Solution A was applied to the column, centrifuged and collected the eluate. The concentration and purity of Eluted RNA were determined by NanoDrop 1000 (Thermo Fisher Scientific, Wilmington, DE). The yields of total eluted RNA were 140–360 ng per 1500μL of serum.

Real-time quantitative reverse transcription-PCR

The isolated serum RNA was first reverse transcribed using the TaqMan miRNA reverse transcription kit (Applied Biosystems) according to the instruction of the manufacturer. The quantitative PCR was performed using TaqMan microRNA assays (Applied Biosystems) in an ABI PRISM 7900 real-time PCR system. The primers of human miR-16, used as an endogenous control [2023], were also purchased from Applied Biosystems. The assay ID number is 001141 for mir-451a, 001277 for mir-485-3p, 465290_mat for mir-4298, 000391 for mir-16. Reaction mixtures were incubated at 95°C for 10 minutes, followed by 40 cycles at 95°C for 15 seconds and 60°C for 1 minute. Signals were detected at the end of each cycle. The cycle threshold (Ct) values were calculated with SDS 2.4 software (Applied Biosystems). The assays were undertaken in triplicate for all samples. 2–ΔCt represents the normalized miRNAs expression level.

Statistical analyses

All statistical analyses were carried out using the software of SPSS 16.0 (SPSS Inc.). Data are expressed as mean ± SD. ANOVA was used to determine the statistical differences among groups. 2–ΔCt was used to represent serum expression levels of miRNA in GBM patients and healthy volunteers detected by qRT-PCR. Unpaired t test was conducted to analyze the differential miRNA expression levels between tumors and normal controls. The correlation between two dichotomous variables was assessed using Chi-square test or Fisher's exact test. OS/PFS was calculated from the date of the initial surgery to the time of death. Survival curves were made by the Kaplan-Meier method, and the log-rank test was used to assess survival differences between the groups. Cox regression analysis was used to assess predictors related to survival. The significance level was set at P<0.05.

Results

Verification of the selected serum miRNA levels by qRT-PCR

We previously used a microarray-based technique to genome-widely analyze serum miRNA profile and identified 19 miRNAs that have significantly differential expression levels between 22 GBM patients and 8 normal volunteers [19], and the microarray data had been deposited into the GEO database in NCBI website with accession number GSE93850 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE93850). To verify the serum level of the miRNAs, we detected three of the 19 differentially expressed miRNAs using qRT-PCR in another 24 GBM patients and 12 matched healthy volunteers. Of the 3 detected miRNAs, miR-451a level was the highest and miR-4298 level was the lowest among the 19 differentially expressed miRNAs in our previous study. Another miRNA, miR-485-3p, was decreased in serum of GBM patients and also selected for validation based on the published data that showed its aberrant expression in human cancer cell lines [2427].

The relative expression of serum miR-451a, miR-485-3p and miR-4298 were depicted in the scatter plot of Fig 1. The results showed that the expression of the three miRNAs detected by qRT-PCR were significantly different between 24 GBM patients and 12 healthy volunteers (all P<0.05, Fig 1), of which 2 serum miRNAs (miR-485-3p, Fig 1B and miR-4298, Fig 1C) were significantly lower, while another serum miRNA (miR-451a, Fig 1C) was significantly higher in GBM patients than in healthy volunteers. The results are consistent with the microarray data, suggesting that microarray data is reliable and reproducible.

thumbnail
Fig 1. Validation of serum levels of miR-451a, miR-485-3p and miR-4298 by qRT-PCR in GBM patients.

The average serum levels of the 3 miRNAs in GBM patients (n = 24) were compared with those in healthy volunteer controls (n = 12). (A) serum level of miR-451a in GBM patients is significantly higher than that in healthy controls. (B) serum level of miR-485-3p in GBM patients is significantly lower than that in healthy controls. (C) serum level of miR-4298 in GBM patients is significantly lower than that in healthy controls. The serum levels of the 3 miRNAs in GBM patients are in concordance with the results of microarray analysis. miRNA levels in each sample were normalized to miR-16. ΔCt = mean value of Ct (reference miRNA16)–mean value of Ct (target miRNA).

https://doi.org/10.1371/journal.pone.0184969.g001

Correlation of serum miRNAs with clinicopathological factors of GBM patients

We next examined the expression levels of the 3 miRNAs in another 12 patients with GBM by qRT-PCR. To further investigate the roles of serum miR-485-3p expression levels in GBM progression, the relationship between the 3 serum miRNAs expression levels and clinicopathological features was statistically analyzed in all 36 GBM patients. Patients were classified into a low- or high-expression group according to their miRNA expression levels used the median expression level of miRNAs as the cutoff point. Statistical analysis shows that high miR-451a level is associated with positive MGMT expression in tumor (detected by immunohistochemistry) (P = 0.040, Table 1), and no significant relationship has been observed between the 3 serum miRNAs expression and other clinicopathological features (P > 0.05, Table 1).

Serum miR-485-3p is a prognostic marker in patients with GBM

To evaluate the prognostic significance of the serum miRNAs in GBM patients, the three miRNAs were analyzed by Kaplan-Meier and Log-rank models. It was demonstrated that patients with a low expression of miR-485-3p had significantly shorter PFS and significantly worse OS in GBM patients (n = 36) (P = 0.004 and P = 0.023, Fig 2B). No significant correlation was found between survival rates (PFS and OS) and the expression levels of miR-451a and miR-4298 in GBM patients (both P >0.05, Fig 2A and 2C).

thumbnail
Fig 2. Comparison of overall survival (OS) and progression-free survival (PFS) of the GBM patients with lowand high levels of serum miR-451a, miR-485-3p and miR-4298.

(A) There is no difference of survivals (OS and PFS) between patients with a low and high level of serum miR-451a (B) Patients with a low level of serum miR-485-3p had significantly shorter OS (P = 0.023) and PFS (P = 0.004) than those with a high level. (C) There is no difference of survivals (OS and PFS) between patients with a low and high level of serum miR-4298.

https://doi.org/10.1371/journal.pone.0184969.g002

To determine whether serum miR-485-3p expression level was an independent risk factor for prognosis of GBM patients, the Cox univariate and multivariate hazard regression models were employed to analyze the miRNAs and clinical features. As shown in Tables 2 and 3, serum miR-485-3p expression level was an independent factor for predicting the PFS (RR: 0.135, 95% CI: 0.048–0.382, P <0.001, Table 2) and OS (RR: 0.171, 95% CI: 0.056–0.523, P = 0.002, Table 3) in GBM patients. Other independent prognostic factors for PFS and OS include age, preoperative Karnofsky Performance Scale (KPS) and surgery procedure (Tables 2 and 3).

thumbnail
Table 2. Univariate and multivariate COX proportional hazard analyses of prognostic factors for progression-free survival in GBM patients.

https://doi.org/10.1371/journal.pone.0184969.t002

thumbnail
Table 3. Univariate and multivariate COX proportional hazard analyses of prognostic factors for overall survival in GBM patients.

https://doi.org/10.1371/journal.pone.0184969.t003

Discussion

GBM is the most lethal neurological malignancy with a very poor prognosis [2]. Thus, it is a major clinical challenge to identify sensitive and specific biomarkers for the prognosis of this malignancy, as well as to develop new molecularly targeted therapeutic agents for this lethal disease. Multiple studies have explored miRNA as biomarkers in GBM based on the deregulation of miRNA expression in tumor tissue [2830]. However, tissue-specific miRNAs can be detected only in tumor tissues, which limits their potential application in clinical practice. Circulating biomarkers, such as miRNAs in serum or plasma, can be measured noninvasively and would be easily testable. Therefore, increasing efforts have been made in developing tumor biomarkers in blood, serum or plasma. In 2011, Roth et al profiled miRNA expression of peripheral blood mononuclear cells in 20 GBM patients and matched healthy volunteers with biochip containing 1158 human mature miRNAs, and found miR-128, miR-342-3p and a signature (consisting of 180 miRNAs) could be used to distinguish patients and healthy volunteers [16]. Interestingly, they also found that miR-485-3p was decreased in GBM patients, which is concordant with our result. In 2012, Wang et al reported 3 serum miRNAs measured by qRT-PCR could be used as diagnostic markers for glioma including GBM [17]. In 2013, Yang et al identified a serum seven-miRNA signature to diagnose malignant astrocytoma [18]. Recently, Tang and Yue groups discovered that plasma/serum miR-185 and miR-205 could be potential biomarkers for diagnosis and/or prognosis in human glioma including GBM [31, 32]. However, most of these studies are focused on single miRNAs, which is not derived from high-throughput screening experiments on a suitable GBM sample size and may not be the best biomarkers for diagnosis and/or prognosis of GBM patients.

In a previous study, we made a genome-wide profiling of miRNA expression in the serum in 22 GBM patients and 8 healthy volunteers with a custom microarray containing 1849 miRNAs and identified 19 differentially expressed miRNAs between patients and healthy controls (fold change>1.5) [19]. In the present study, based on the profiling result of serum miRNAs in GBM patients, we first carried out qRT-PCR on 3 miRNAs (miR-451a, miR-485-3p and miR-4298) in an new cohort (24 GBM patients and 12 healthy volunteers) to validate the microarray data. The results show that the expression levels of the 3 miRNAs detected by qRT-PCR are significantly different between GBM patients and healthy volunteers, which are consistent with the microarray data. Then, we detected the 3 serum miRNA expressions with qRT-PCR in another 12 GBM patients, and analyzed their clinical significance in all 36 GBM patients. The result shows that serum miR-485-3p is significantly reduced in GBM patients than in healthy volunteer and associated with PFS and OS of GBM patients. Multivariate Cox regression analysis demonstrates that serum miR-485-3p is an independent prognostic factor for PFS and OS in GBM patients, which suggests that miR-485-3p may be involved in GBM development and prognosis, and functions as a tumor suppressor.

miR-485-3p, together with miR-154, miR-299-5p, miR-376a, etc, is mapped to the 14q32.31 region in which allelic deletions [33] and translocations [34] are frequently identified in cancer, suggesting that miR-485-3p may be a tumor suppressor. Lou et al reported that miR-485-3p is decreased in breast cancer tissues and can inhibit migration and invasion of breast cancer cells by targeting PGC-1α [35]. In 2011, Chen et al. provided evidence that increased levels of miR-485-3p can decrease the chemoresistance of human leukemic lymphoblastic cells to Teniposide by targeting NFYB gene [26]. In sharp contrast, Lucotti et al found that miR-485-3p increased the chemoresistance of DU-145 prostate cancer cells to Fludarabine by targeting NFYB [27], implying that miR-485-3p may have different functions in different conditions. In addition, miR-485-3p may promote proliferation, migration/invasion or apoptosis by targeting NTRK3 or MAT1A in HCC cells [36, 37]. These studies demonstrate that miR-485-3p has different functions in different cancers.

In conclusion, we have demonstrated for the first time that serum miR-485-3p is a potential prognostic marker for GBM patients. In future research, we will investigate the roles of miR-485-3p in GBM pathogenesis and analyze its relevant molecular mechanisms.

Acknowledgments

We would like to thank Dr. Qi Wang, Pharm.D., a student of Robert Wood Johnson Medical School, Rutgers University, USA, for proofreading this manuscript. The authenticity of this article has been validated by uploading the key raw data onto the Research Data Deposit (RDD) public platform (www.researchdata.org.cn), with the approval No: RDDB2017000195.

References

  1. 1. Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. The New England journal of medicine. 2005;352(10):987–96. Epub 2005/03/11. pmid:15758009.
  2. 2. Stupp R, Hegi ME, Mason WP, van den Bent MJ, Taphoorn MJ, Janzer RC, et al. Effects of radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 5-year analysis of the EORTC-NCIC trial. Lancet Oncol. 2009;10(5):459–66. pmid:19269895.
  3. 3. Karsy M, Neil JA, Guan J, Mahan MA, Colman H, Jensen RL. A practical review of prognostic correlations of molecular biomarkers in glioblastoma. Neurosurg Focus. 2015;38(3):E4. pmid:25727226.
  4. 4. De Mattos-Arruda L, Weigelt B, Cortes J, Won HH, Ng CK, Nuciforo P, et al. Capturing intra-tumor genetic heterogeneity by de novo mutation profiling of circulating cell-free tumor DNA: a proof-of-principle. Ann Oncol. 2014;25(9):1729–35. pmid:25009010.
  5. 5. Garcia-Romero N, Carrion-Navarro J, Esteban-Rubio S, Lazaro-Ibanez E, Peris-Celda M, Alonso MM, et al. DNA sequences within glioma-derived extracellular vesicles can cross the intact blood-brain barrier and be detected in peripheral blood of patients. Oncotarget. 2017;8(1):1416–28. pmid:27902458.
  6. 6. Mizoguchi M, Shono T. [Molecular genetic analysis for malignant gliomas: clinical implications and future directions]. No shinkei geka Neurological surgery. 2008;36(1):83–91. Epub 2008/02/01. pmid:18232326.
  7. 7. Iorio MV, Croce CM. MicroRNAs in cancer: small molecules with a huge impact. Journal of clinical oncology: official journal of the American Society of Clinical Oncology. 2009;27(34):5848–56. Epub 2009/11/04. pmid:19884536.
  8. 8. Calin GA, Sevignani C, Dumitru CD, Hyslop T, Noch E, Yendamuri S, et al. Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proceedings of the National Academy of Sciences of the United States of America. 2004;101(9):2999–3004. Epub 2004/02/20. pmid:14973191.
  9. 9. Chen T. The role of MicroRNA in chemical carcinogenesis. Journal of environmental science and health Part C, Environmental carcinogenesis & ecotoxicology reviews. 2010;28(2):89–124. Epub 2010/06/17.
  10. 10. Shenouda SK, Alahari SK. MicroRNA function in cancer: oncogene or a tumor suppressor? Cancer metastasis reviews. 2009;28(3–4):369–78. Epub 2009/12/17. pmid:20012925.
  11. 11. Wu W, Sun M, Zou GM, Chen J. MicroRNA and cancer: Current status and prospective. International journal of cancer Journal international du cancer. 2007;120(5):953–60. Epub 2006/12/14. pmid:17163415.
  12. 12. Lawrie CH, Gal S, Dunlop HM, Pushkaran B, Liggins AP, Pulford K, et al. Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma. British journal of haematology. 2008;141(5):672–5. Epub 2008/03/06. pmid:18318758.
  13. 13. Wang F, Zheng Z, Guo J, Ding X. Correlation and quantitation of microRNA aberrant expression in tissues and sera from patients with breast tumor. Gynecologic oncology. 2010;119(3):586–93. Epub 2010/08/31. pmid:20801493.
  14. 14. Li J, Wang Y, Yu W, Chen J, Luo J. Expression of serum miR-221 in human hepatocellular carcinoma and its prognostic significance. Biochemical and biophysical research communications. 2011;406(1):70–3. Epub 2011/02/08. pmid:21295551.
  15. 15. Wang ZX, Bian HB, Wang JR, Cheng ZX, Wang KM, De W. Prognostic significance of serum miRNA-21 expression in human non-small cell lung cancer. Journal of surgical oncology. 2011;104(7):847–51. Epub 2011/07/02. pmid:21721011.
  16. 16. Roth P, Wischhusen J, Happold C, Chandran PA, Hofer S, Eisele G, et al. A specific miRNA signature in the peripheral blood of glioblastoma patients. Journal of neurochemistry. 2011;118(3):449–57. Epub 2011/05/13. pmid:21561454.
  17. 17. Wang Q, Li P, Li A, Jiang W, Wang H, Wang J, et al. Plasma specific miRNAs as predictive biomarkers for diagnosis and prognosis of glioma. Journal of experimental & clinical cancer research: CR. 2012;31:97. Epub 2012/11/24. pmid:23174013.
  18. 18. Yang C, Wang C, Chen X, Chen S, Zhang Y, Zhi F, et al. Identification of seven serum microRNAs from a genome-wide serum microRNA expression profile as potential noninvasive biomarkers for malignant astrocytomas. International journal of cancer Journal international du cancer. 2013;132(1):116–27. Epub 2012/06/08. pmid:22674182.
  19. 19. Wang Z-Q, Wang H-Y, Deng M-L, Wu S-X. Plasma MicroRNA Expression Profiles in Glioblastoma. Pract J Cancer. 2015;30(4):4.
  20. 20. Shen J, Todd NW, Zhang H, Yu L, Lingxiao X, Mei Y, et al. Plasma microRNAs as potential biomarkers for non-small-cell lung cancer. Laboratory investigation; a journal of technical methods and pathology. 2011;91(4):579–87. Epub 2010/12/01. pmid:21116241.
  21. 21. Kirschner MB, Kao SC, Edelman JJ, Armstrong NJ, Vallely MP, van Zandwijk N, et al. Haemolysis during sample preparation alters microRNA content of plasma. PloS one. 2011;6(9):e24145. Epub 2011/09/13. pmid:21909417.
  22. 22. van Schooneveld E, Wouters MC, Van der Auwera I, Peeters DJ, Wildiers H, Van Dam PA, et al. Expression profiling of cancerous and normal breast tissues identifies microRNAs that are differentially expressed in serum from patients with (metastatic) breast cancer and healthy volunteers. Breast cancer research: BCR. 2012;14(1):R34. Epub 2012/02/23. pmid:22353773.
  23. 23. Huang Z, Huang D, Ni S, Peng Z, Sheng W, Du X. Plasma microRNAs are promising novel biomarkers for early detection of colorectal cancer. International journal of cancer Journal international du cancer. 2010;127(1):118–26. Epub 2009/10/31. pmid:19876917.
  24. 24. Anaya-Ruiz M, Bandala C, Perez-Santos JL. miR-485 acts as a tumor suppressor by inhibiting cell growth and migration in breast carcinoma T47D cells. Asian Pacific journal of cancer prevention: APJCP. 2013;14(6):3757–60. Epub 2013/07/28. pmid:23886178.
  25. 25. Formosa A, Markert EK, Lena AM, Italiano D, Finazzi-Agro E, Levine AJ, et al. MicroRNAs, miR-154, miR-299-5p, miR-376a, miR-376c, miR-377, miR-381, miR-487b, miR-485-3p, miR-495 and miR-654-3p, mapped to the 14q32.31 locus, regulate proliferation, apoptosis, migration and invasion in metastatic prostate cancer cells. Oncogene. 2014;33(44):5173–82. Epub 2013/10/30. pmid:24166498.
  26. 26. Chen CF, He X, Arslan AD, Mo YY, Reinhold WC, Pommier Y, et al. Novel regulation of nuclear factor-YB by miR-485-3p affects the expression of DNA topoisomerase IIalpha and drug responsiveness. Molecular pharmacology. 2011;79(4):735–41. Epub 2011/01/22. pmid:21252292.
  27. 27. Lucotti S, Rainaldi G, Evangelista M, Rizzo M. Fludarabine treatment favors the retention of miR-485-3p by prostate cancer cells: implications for survival. Molecular cancer. 2013;12(1):52. Epub 2013/06/06. pmid:23734815.
  28. 28. Lakomy R, Sana J, Hankeova S, Fadrus P, Kren L, Lzicarova E, et al. MiR-195, miR-196b, miR-181c, miR-21 expression levels and O-6-methylguanine-DNA methyltransferase methylation status are associated with clinical outcome in glioblastoma patients. Cancer science. 2011;102(12):2186–90. Epub 2011/09/08. pmid:21895872.
  29. 29. Zhao S, Yang G, Mu Y, Han D, Shi C, Chen X, et al. MiR-106a is an independent prognostic marker in patients with glioblastoma. Neuro-oncology. 2013;15(6):707–17. Epub 2013/02/19. pmid:23416698.
  30. 30. Ma R, Yan W, Zhang G, Lv H, Liu Z, Fang F, et al. Upregulation of miR-196b confers a poor prognosis in glioblastoma patients via inducing a proliferative phenotype. PloS one. 2012;7(6):e38096. Epub 2012/06/23. pmid:22723849.
  31. 31. Yue X, Lan F, Hu M, Pan Q, Wang Q, Wang J. Downregulation of serum microRNA-205 as a potential diagnostic and prognostic biomarker for human glioma. Journal of neurosurgery. 2016;124(1):122–8. Epub 2015/08/01. pmid:26230475.
  32. 32. Tang H, Liu Q, Liu X, Ye F, Xie X, Xie X, et al. Plasma miR-185 as a predictive biomarker for prognosis of malignant glioma. Journal of cancer research and therapeutics. 2015;11(3):630–4. Epub 2015/10/16. pmid:26458593.
  33. 33. Suzuki T, Yokota J, Mugishima H, Okabe I, Ookuni M, Sugimura T, et al. Frequent loss of heterozygosity on chromosome 14q in neuroblastoma. Cancer research. 1989;49(5):1095–8. Epub 1989/03/01. pmid:2563671.
  34. 34. Avet-Loiseau H, Facon T, Grosbois B, Magrangeas F, Rapp MJ, Harousseau JL, et al. Oncogenesis of multiple myeloma: 14q32 and 13q chromosomal abnormalities are not randomly distributed, but correlate with natural history, immunological features, and clinical presentation. Blood. 2002;99(6):2185–91. Epub 2002/03/06. pmid:11877296.
  35. 35. Lou C, Xiao M, Cheng S, Lu X, Jia S, Ren Y, et al. MiR-485-3p and miR-485-5p suppress breast cancer cell metastasis by inhibiting PGC-1alpha expression. Cell Death Dis. 2016;7:e2159. pmid:27010860.
  36. 36. Xiong D, Sheng Y, Ding S, Chen J, Tan X, Zeng T, et al. LINC00052 regulates the expression of NTRK3 by miR-128 and miR-485-3p to strengthen HCC cells invasion and migration. Oncotarget. 2016. pmid:27351280.
  37. 37. Yang H, Cho ME, Li TW, Peng H, Ko KS, Mato JM, et al. MicroRNAs regulate methionine adenosyltransferase 1A expression in hepatocellular carcinoma. The Journal of clinical investigation. 2013;123(1):285–98. Epub 2012/12/18. pmid:23241961;