DOI QR코드

DOI QR Code

Serum miR-21 Expression in Human Esophageal Squamous Cell Carcinomas

  • Cai, Er-Hui (Department of Preventive Medicine, Shantou University Medical College) ;
  • Gao, Yong-Xin (Department of Preventive Medicine, Shantou University Medical College) ;
  • Wei, Zhong-Zhi (Department of Preventive Medicine, Shantou University Medical College) ;
  • Chen, Wei-Ying (Center for Teaching Laboratories, Shantou University Medical College) ;
  • Yu, Ping (Department of Computers, Shantou University Medical College) ;
  • Li, Ke (Department of Preventive Medicine, Shantou University Medical College)
  • Published : 2012.04.30

Abstract

To investigate the relationship between serum miRNA-21 (miR-21) expression in esophageal squamous cell carcinomas (ESCCs) and its clinicopathologic features, a 1:1 matched case-control study including 21 patients with ESCC and 21 age- and gender-matched healthy controls was carried out. Serum specimens were taken from all subjects. Total RNA was extracted and the stem-loop real time polymerase chain reaction was used to measure serum miR-21 in both groups. Clinical parameters were assessed to determine associations with serum miR-21 concentrations. Serum miR-21 expression in ESCC samples was significantly higher than in paired cancer-free samples (P<0.05). Metastasis was associated with mir-21 expression in serum (P<0.05), ESCC patients with metastasis having 8.4-fold higher serum miR-21 concentrations than healthy controls. There were no statistically significant associations between miR-21 expression and clinicopathologic parameters, such as gender (P>0.05), age (P>0.05), tumor location (P>0.05), cell differentiation (P>0.05), TNM staging (P>0.05), whether chemo/radiotherapy had been administered (P>0.05), or whether surgery had been performed (P>0.05). These findings suggest that the detection of microRNA-21 in serum might serve as a new tumor biomarker in diagnosis and assessment of prognosis of ESCCs.

Keywords

References

  1. Alvarez-Garcia I, Miska EA (2005). MicroRNA functions in animal development and human disease. Cell, 132, 4653-62.
  2. Ambros V (2003). MicroRNA pathways in flies and worms: Growth, death, fat, stress and timing. Cell, 113, 673-6. https://doi.org/10.1016/S0092-8674(03)00428-8
  3. Bartel DP (2004). MicroRNAs: Genomics, biogenesis, mechanism and function. Cell, 116, 281-97. https://doi.org/10.1016/S0092-8674(04)00045-5
  4. Bloomston M, Frankel WL, Petrocca F, et al (2007). MicroRNA expression patterns to differentiate pancreatic adenocarcinoma from normal pancreas and chronic pancreatitis. JAMA, 297, 1901-8. https://doi.org/10.1001/jama.297.17.1901
  5. Calin GA, Croce CM (2006). MicroRNA signatures in human cancers. Nat Rev Cancer, 6, 857-66. https://doi.org/10.1038/nrc1997
  6. Calin GA, Croce CM (2006). MicroRNA-cancer connection: the beginning of a new tale. Cancer Res, 66, 7390-4. https://doi.org/10.1158/0008-5472.CAN-06-0800
  7. Chan JA, Krichevsky AM, Kosik KS (2005). MicroRNA-21 is an antiapoptotic factor in human glioblastoma cells. Cancer Res, 65, 6029-33. https://doi.org/10.1158/0008-5472.CAN-05-0137
  8. Chen C, Ridzon DA, Broomer AJ, et al (2005). Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res, 33, e179. https://doi.org/10.1093/nar/gni178
  9. Chen X, Ba Y, Ma L, et al (2008). Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res, 18, 997-1006. https://doi.org/10.1038/cr.2008.282
  10. Cullen BR (2004). Transcription and processing of human microRNA procursors. Mol Cell, 16, 861-5. https://doi.org/10.1016/j.molcel.2004.12.002
  11. Dong Y, Wu WK, Wu CW, et al (2011). MicroRNA dysregulation in colorectal cancer: a clinical perspective. Br J Cancer, 104, 893-8. https://doi.org/10.1038/bjc.2011.57
  12. Duffy MJ (2007). Role of tumor markers in patients with solid cancers: a critical review. Eur J Intern Med, 18, 175-84. https://doi.org/10.1016/j.ejim.2006.12.001
  13. Esquela-Kerscher A, Slack FJ (2006). Oncomirs - microRNAs with a role in cancer. Nat Rev Cancer, 6, 259-69. https://doi.org/10.1038/nrc1840
  14. Feber A, Xi L, Luketich JD, et al (2008). MicroRNA expression profiles of esophageal cancer. J Thorac Cardiovasc Surg, 135, 255-60. https://doi.org/10.1016/j.jtcvs.2007.08.055
  15. Gilad S, Meiri E, Yogev Y, et al (2008). Serum microRNAs are promising novel biomarkers. PLoS One, 3, e3148. https://doi.org/10.1371/journal.pone.0003148
  16. Jiang J, Lee EJ, Gusev Y, et al (2005). Real-time expression profiling of microRNA precursors in human cancer cell lines. Nucleic Acids Res, 33, 5394-403. https://doi.org/10.1093/nar/gki863
  17. Kamangar F, Dores GM, Anderson WF (2006). Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world. J Clin Oncol, 24, 2137-50. https://doi.org/10.1200/JCO.2005.05.2308
  18. Kosaka N, Iguchi H, Ochiya T (2010). Circulating microRNA in body fluid: a new potential biomarker for cancer diagnosis and prognosis. Cancer Sci, 101, 2087-92. https://doi.org/10.1111/j.1349-7006.2010.01650.x
  19. Leman ES, Schoen RE, Weissfeld JL, et al (2007). Initial analyses of colon cancer-specific antigen (CCSA)-3 and CCSA-4 as colorectal cancer-associated serum markers. Cancer Res, 67, 5600-5. https://doi.org/10.1158/0008-5472.CAN-07-0649
  20. Matsuo K, Lin A, Procter JL, et al (2000). Variations in the expression of Granulocyte antigen NB1. Transfusion, 40, 654-62. https://doi.org/10.1046/j.1537-2995.2000.40060654.x
  21. Mitchell PS, Parkin RK, Kroh EM, et al (2008). Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA, 105, 10513-8. https://doi.org/10.1073/pnas.0804549105
  22. Ng EK, Chong WW, Jin H, et al (2009). Differential expression of microRNAs in plasma of patients with colorectal cancer: a potential marker for colorectal cancer screening. Gut, 58, 1375-81. https://doi.org/10.1136/gut.2008.167817
  23. Patrick S. Mitchell, Rachael K. et al (2008). Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA, 105, 10513-8. https://doi.org/10.1073/pnas.0804549105
  24. Resnick KE, Alder H, Hagan JP, et al (2009). The detection of differentially expressed microRNAs from the serum of ovarian cancer patients using a novel real-time PCR platform. Gynecol Oncol, 112, 55-9. https://doi.org/10.1016/j.ygyno.2008.08.036
  25. Schetter A, Leung SY, Sohn JJ, et al (2008). MicroRNA expression profiles associated with prognosis and therapeutic outcome in colon adenocarcinoma. JAMA, 299, 425-36. https://doi.org/10.1001/jama.299.4.425
  26. Schramedei K, Morbt N, Pfeiferl G, et al (2011). MicroRNA-21 targets tumor suppressor genes ANP32A and SMARCA4. Oncogene, 30, 2975-85. https://doi.org/10.1038/onc.2011.15
  27. WHO (2003). Global cancer rates could increase by 50% to 15 million by 2020. http://www.who.int/mediacentre/news/releases/2003/pr27/en/.
  28. Zhang C, Wang C, Chen X, et al (2010). Expression Profile of MicroRNAs in Serum: A Fingerprint for Esophageal Squamous Cell Carcinoma. Clin Chem, 56, 1871-9. https://doi.org/10.1373/clinchem.2010.147553
  29. Zhou SL, Wang LD (2010). Circulating microRNAs: Novel biomarkers for esophageal cancer. World J Gastroenterol, 16, 2348-54 https://doi.org/10.3748/wjg.v16.i19.2348

Cited by

  1. Serum miR-21 and miR-155 expression in idiopathic pulmonary fibrosis vol.50, pp.9, 2013, https://doi.org/10.3109/02770903.2013.822080
  2. Novel diagnostic and prognostic biomarkers in esophageal cancer vol.7, pp.6, 2013, https://doi.org/10.1517/17530059.2013.843526
  3. Deep sequencing identifies conserved and novel microRNAs from antlers cartilage of Chinese red deer (Cervus elaphus) vol.37, pp.5, 2015, https://doi.org/10.1007/s13258-015-0270-9
  4. Serum miRNA expression in patients with esophageal squamous cell carcinoma pp.1792-1082, 2015, https://doi.org/10.3892/ol.2015.3642
  5. Serum-based six-miRNA signature as a potential marker for EC diagnosis: Comparison with TCGA miRNAseq dataset and identification of miRNA-mRNA target pairs by integrated analysis of TCGA miRNAseq and RNAseq datasets vol.14, pp.5, 2018, https://doi.org/10.1111/ajco.12847
  6. NDAMDA: Network distance analysis for MiRNA-disease association prediction vol.22, pp.5, 2018, https://doi.org/10.1111/jcmm.13583