Skip to main content

Advertisement

SpringerLink
Log in

MicroRNA signature analysis in colorectal cancer: identification of expression profiles in stage II tumors associated with aggressive disease

  • Original Article
  • Published:
International Journal of Colorectal Disease Aims and scope Submit manuscript

Abstract

Purpose

Colorectal cancer (CRC) is a clinically diverse disease whose molecular etiology remains poorly understood. The purpose of this study was to identify miRNA expression patterns predictive of CRC tumor status and to investigate associations between microRNA (miRNA) expression and clinicopathological parameters.

Methods

Expression profiling of 380 miRNAs was performed on 20 paired stage II tumor and normal tissues. Artificial neural network (ANN) analysis was applied to identify miRNAs predictive of tumor status. The validation of specific miRNAs was performed on 102 tissue specimens of varying stages.

Results

Thirty-three miRNAs were identified as differentially expressed in tumor versus normal tissues. ANN analysis identified three miRNAs (miR-139-5p, miR-31, and miR-17-92 cluster) predictive of tumor status in stage II disease. Elevated expression of miR-31 (p = 0.004) and miR-139-5p (p < 0.001) and reduced expression of miR-143 (p = 0.016) were associated with aggressive mucinous phenotype. Increased expression of miR-10b was also associated with mucinous tumors (p = 0.004). Furthermore, progressively increasing levels of miR-10b expression were observed from T1 to T4 lesions and from stage I to IV disease.

Conclusion

Association of specific miRNAs with clinicopathological features indicates their biological relevance and highlights the power of ANN to reliably predict clinically relevant miRNA biomarkers, which it is hoped will better stratify patients to guide adjuvant therapy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Garcia M, Jemal A, Ward EM, Center MM, Hao Y, Siegel RL, Thun MJ (2007) Global cancer facts & figures. American Cancer Society, Atlanta, GA

    Google Scholar 

  2. Hurwitz H, Fehrenbacher L, Novotny W et al (2004) Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic colorectal cancer. N Engl J Med 350(23):2335–2342

    Article  PubMed  CAS  Google Scholar 

  3. Cunningham D, Humblet Y, Siena S et al (2004) Cetuximab monotherapy and cetuximab plus irinotecan in irinotecan-refractory metastatic colorectal cancer. N Engl J Med 351(4):337–345

    Article  PubMed  CAS  Google Scholar 

  4. Bardelli A, Siena S (2010) Molecular mechanisms of resistance to cetuximab and panitumumab in colorectal cancer. J Clin Oncol 28(7):1254–1261

    Article  PubMed  CAS  Google Scholar 

  5. Mamounas E, Wieand S, Wolmark N et al (1999) Comparative efficacy of adjuvant chemotherapy in patients with Duke’s B versus Duke’s C colon cancer: Results from four National Surgical Adjuvant Breast and Bowel Project adjuvant studies (C-01, C-02, C-03, and C-04). J Clin Oncol 17(5):1349–1355

    PubMed  CAS  Google Scholar 

  6. International Multicentre Pooled Analysis of Colon Cancer Trials (IMPACT) Investigators (1999) Efficacy of adjuvant fluorouracil and folinic acid in B2 colon cancer. J Clin Oncol 17(5):1356–1363

    Google Scholar 

  7. QUASAR Collaborative Group (2007) Adjuvant chemotherapy versus observation in patients with colorectal cancer: a randomized study. Lancet 370(9604):2020–2029

    Article  Google Scholar 

  8. Frederiksen CM, Knudsen S, Laurberg S, Orntoft TF (2003) Classification of Duke’s B and C colorectal cancers using expression arrays. J Cancer Res Clin Oncol 129(5):263–271

    PubMed  Google Scholar 

  9. Wang Y, Jatkoe T, Zhang Y et al (2004) Gene expression profiles and molecular markers to predict recurrence of Dukes’ B colon cancer. J Clin Oncol 22(9):1564–1571

    Article  PubMed  CAS  Google Scholar 

  10. Ghadimi BM, Grade M, Difilippantonio MJ et al (2005) Effectiveness of gene expression profiling for response prediction of rectal adenocarcinomas to preoperative chemoradiotherapy. J Clin Oncol 23(9):1826–1838

    Article  PubMed  CAS  Google Scholar 

  11. Sorlie T, Perou CM, Tibshirani R et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874

    Article  PubMed  CAS  Google Scholar 

  12. Lai EC (2002) Micro RNAs are complementary to 3′ UTR sequence motifs that mediate negative post-transcriptional regulation. Nat Genet 30(4):363–364

    Article  PubMed  CAS  Google Scholar 

  13. Engels BM, Hutvagner G (2006) Principles and effects of microRNA-mediated post-transcriptional gene regulation. Oncogene 25(46):6163–6169

    Article  PubMed  CAS  Google Scholar 

  14. Chen CZ, Li L, Lodish HF, Bartel DP (2004) MicroRNAs modulate hematopoietic lineage differentiation. Science 303(5654):83–86

    Article  PubMed  CAS  Google Scholar 

  15. Croce CM, Calin GA (2005) miRNAs, cancer, and stem cell division. Cell 122(1):6–7

    Article  PubMed  CAS  Google Scholar 

  16. Lu J, Getz G, Miska EA et al (2005) MicroRNA expression profiles classify human cancers. Nature 435(7043):834–838

    Article  PubMed  CAS  Google Scholar 

  17. Volinia S, Calin GA, Liu CG et al (2006) A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci USA 103(7):2257–2261

    Article  PubMed  CAS  Google Scholar 

  18. Bandrés E, Cubedo E, Agirre X et al (2006) Identification by real-time PCR of 13 mature microRNAs differentially expressed in colorectal cancer and non-tumoral tissues. Mol Cancer 5:29

    Article  PubMed  Google Scholar 

  19. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120(1):15–20

    Article  PubMed  CAS  Google Scholar 

  20. Griffiths-Jones S (2004) The microRNA registry. Nucleic Acid Res 32:D109–D111

    Article  PubMed  CAS  Google Scholar 

  21. Simon R, Radmacher MD, Dobbin K, McShane LM (2003) Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. J Natl Cancer Inst 95(1):14–18

    Article  PubMed  CAS  Google Scholar 

  22. Khan J, Wei JS, Ringner M et al (2001) Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med 7(6):673–679

    Article  PubMed  CAS  Google Scholar 

  23. Lancashire L, Schmid O, Shah H, Ball G (2005) Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principle components analysis. Bioinformatics 21(10):2191–2199

    Article  PubMed  CAS  Google Scholar 

  24. Matharoo-Ball GR, Lancashire L, Ugurel S et al (2007) Diagnostic biomarkers differentiating metastatic melanoma patients from healthy controls identified by an integrated MALDI-ToF mass spectrometry/bioinformatic approach. Proteomics 1:605–620

    PubMed  CAS  Google Scholar 

  25. Ball G, Mian S, Holding F et al (2002) An integrated approach utilizing artificial neural networks and SELDI mass spectrometry for the classification of human tumors and rapid identification of potential biomarkers. Bioinformatics 18(3):395–404

    Article  PubMed  CAS  Google Scholar 

  26. Lowery AJ, Miller N, Devaney A et al (2009) MicroRNA signatures predict oestrogen receptor, progesterone receptor and HER2/neu receptor status in breast cancer. Breast Cancer Res 11:R27

    Article  PubMed  Google Scholar 

  27. Sobin LH, Wittekind CH (2002) TNM classification of malignant tumors, 6th edn. John Wiley & Sons, New York, pp 170–173

    Google Scholar 

  28. Chang KH, Mestdagh P, Vandesompele J, Kerin MJ, Miller N (2010) MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer. BMC Cancer 10:173

    Article  PubMed  CAS  Google Scholar 

  29. Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real time quantitative PCR and the 2(−ΔΔC(T)) method. Methods 25(4):402–408

    Article  PubMed  CAS  Google Scholar 

  30. Akao Y, Nakagawa Y, Naoe T (2006) MicroRNAs 143 and 145 are possible common onco-microRNAs in human cancers. Oncol Rep 16(4):845–850

    PubMed  CAS  Google Scholar 

  31. Figueredo A, Coombes ME, Mukherjee S (2008) Adjuvant therapy for completely resected stage II colon cancer. Cochrane Database Syst Rev 16(3):CD005390

    Google Scholar 

  32. Meng F, Henson R, Wehbe-Janek H, Ghoshal K, Jacob ST, Patel T (2007) MicroRNA-21 regulates expression of the PTEN tumor suppressor gene in human hepatocellular cancer. Gastroenterology 133(2):647–658

    Article  PubMed  CAS  Google Scholar 

  33. Chen X, Guo X, Zhang H et al (2009) Role of miR-143 targeting KRAS in colorectal tumorigenesis. Oncogene 28(10):1385–1392

    Article  PubMed  CAS  Google Scholar 

  34. Wang CJ, Zhou ZG, Wang L et al (2009) Clinicopathological significance of microRNA-31, -143 and -145 expression in colorectal cancer. Dis Markers 26(1):27–34

    PubMed  Google Scholar 

  35. Lanza G, Ferracin M, Gafa R et al (2007) mRNA/microRNA gene expression profile in microsatellite unstable colorectal cancer. Mol Cancer 6:54

    Article  PubMed  Google Scholar 

  36. Monzo M, Navarro A, Bandres E et al (2008) Overlapping expression of microRNAs in human embryonic colon and colorectal cancer. Cell Res 18(8):823–833

    Article  PubMed  CAS  Google Scholar 

  37. Diosdado B, van de Wiel MA, Terhaar Sive Droste JS et al (2009) MiR-17-92 cluster is associated with 13q gain and c-myc expression during colorectal adenoma to adenocarcinoma progression. Br J Cancer 101(4):707–714

    Article  PubMed  CAS  Google Scholar 

  38. Aguda BD, Kim Y, Piper-Hunter MG, Friedman A, Marsh CB (2008) MicroRNA regulation of a cancer network: consequences of the feedback loops involving miR-17-92, E2F, and Myc. Proc Natl Acad Sci USA 105(50):19678–19683

    Article  PubMed  CAS  Google Scholar 

  39. Zhao HY, Ooyama A, Yamamoto M et al (2008) Down regulation of c-Myc and induction of an angiogenesis inhibitor, thrombospondin-1, by 5-FU in human colon cancer KM12C cells. Cancer Lett 270(1):156–163

    Article  PubMed  CAS  Google Scholar 

  40. Guo J, Miao Y, Xiao B, Huan R, Jiang Z, Meng D, Wang Y (2009) Differential expression of microRNA species in human gastric cancer versus non-tumorous tissues. J Gastroenterol Hepatol 24(4):652–657

    Article  PubMed  CAS  Google Scholar 

  41. Hiroki E, Akahira J, Suzuki F et al (2009) Changes in microRNA expression levels correlate with clinicopathological features and prognoses in endometrial serous adenocarcinomas. Cancer Sci 101(1):241–249

    Article  PubMed  Google Scholar 

  42. Schetter AJ, Leung SY, Sohn JJ et al (2008) MicroRNA expression profiles associated with prognosis and therapeutic outcome in colon adenocarcinoma. JAMA 299(4):425–436

    Article  PubMed  CAS  Google Scholar 

  43. Schepeler T, Reinert JT, Ostenfeld MS et al (2008) Diagnostic and prognostic microRNAs in stage II colon cancer. Cancer Res 68(15):6416–6424

    Article  PubMed  CAS  Google Scholar 

  44. 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(10):997–1006

    Article  PubMed  CAS  Google Scholar 

  45. 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(30):10513–10518

    Article  PubMed  CAS  Google Scholar 

  46. Heneghan HM, Miller N, Lowery AJ, Sweeney KJ, Newell J, Kerin MJ (2010) Circulating microRNAs novel minimally invasive biomarkers for breast cancer. Ann Surg 251(3):499–505

    Article  PubMed  Google Scholar 

  47. Ng EK, Chong WW, Jin H et al (2009) Differential expression of microRNAs in plasma of colorectal cancer patients: a potential marker for colorectal cancer screening. Gut 58(10):375–381

    Article  Google Scholar 

  48. Huang Z, Huang D, Ni S, Peng Z, Sheng W, Du X (2009) Plasma microRNAs are promising novel biomarkers for early detection of colorectal cancer. Int J Cancer 127(1):118–126

    Google Scholar 

Download references

Acknowledgments

We would like to acknowledge the National Breast Cancer Research Institute (NBCRI) for the continued financial support. The authors gratefully acknowledge Ms. Emer Hennessy and Ms. Catherine Curran for continued technical assistance and curation of the Department of Surgery BioBank.

Author information

Authors and Affiliations

  1. Department of Surgery, National University of Ireland, Galway, Ireland

    Kah Hoong Chang, Nicola Miller, Elrasheid A. H. Kheirelseid, Myles J. Smith, Mark Regan, Oliver J. McAnena & Michael J. Kerin

  2. John Van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Nottingham, UK

    Christophe Lemetre & Graham R. Ball

  3. Department of Surgery, Clinical Science Institute, University College Hospital Galway, Galway, Ireland

    Nicola Miller

Authors
  1. Kah Hoong Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nicola Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elrasheid A. H. Kheirelseid
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Christophe Lemetre
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Graham R. Ball
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Myles J. Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mark Regan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Oliver J. McAnena
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Michael J. Kerin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nicola Miller.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOC 48 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chang, K.H., Miller, N., Kheirelseid, E.A.H. et al. MicroRNA signature analysis in colorectal cancer: identification of expression profiles in stage II tumors associated with aggressive disease. Int J Colorectal Dis 26, 1415–1422 (2011). https://doi.org/10.1007/s00384-011-1279-4

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00384-011-1279-4

Keywords

Search

Navigation