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Application of Next-Generation Sequencing in RNA Biomarker Discovery in Cancer Research

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Next Generation Sequencing in Cancer Research

Abstract

The advent of next-generation sequencing (NGS) technology has opened up a plethora of possibilities in cancer research by allowing for an unprecedented characterization of the cancer genome. The sensitivity, broad dynamic range, speed, and reduced cost per sample make the NGS technology a highly attractive platform in biomedical research compared to other sequencing and expression profiling techniques. NGS is being currently employed in several malignancies for both quantitative and qualitative profiling of nucleic acids and has already uncovered novel genetic determinants that play an important role during tumor development. In particular, the use of NGS technology for profiling the transcriptome from tumor tissues and body fluids has led to the identification of novel molecular targets that could potentially be translated in the clinic as diagnostic, prognostic, and therapeutic biomarkers. Currently, efforts are also being undertaken in the clinic to characterize an individual’s cancer genome for guiding evidence-based molecular therapies tailored for individual patients. In this chapter, we review recent advances in the use of NGS technology for RNA-based biomarker studies in cancer and its potential implications in the overall management of the disease.

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References

  1. Kim C, Paik S. Gene-expression-based prognostic assays for breast cancer. Nat Rev Clin Oncol. 2010;7:340–7.

    Article  PubMed  CAS  Google Scholar 

  2. Salazar R, Roepman P, Capella G, Moreno V, Simon I, Dreezen C, et al. Gene expression signature to improve prognosis prediction of stage II and III colorectal cancer. J Clin Oncol. 2011;29:17–24.

    Article  PubMed  Google Scholar 

  3. Tothill RW, Kowalczyk A, Rischin D, Bousioutas A, Haviv I, van Laar RK, et al. An expression-based site of origin diagnostic method designed for clinical application to cancer of unknown origin. Cancer Res. 2005;65:4031–40.

    Article  PubMed  CAS  Google Scholar 

  4. Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer. 2006;6:857–66.

    Article  PubMed  CAS  Google Scholar 

  5. Prensner JR, Chinnaiyan AM. The emergence of lncRNAs in cancer biology. Cancer Discov. 2011;1:391–407.

    Article  PubMed  CAS  Google Scholar 

  6. Hoshino I, Matsubara H. MicroRNAs in cancer diagnosis and therapy: from bench to bedside. Surg Today. 2012;43:467–78.

    Article  PubMed  Google Scholar 

  7. Farazi TA, Horlings HM, ten Hoeve JJ, Mihailovic A, Halfwerk H, Morozov P, et al. MicroRNA sequence and expression analysis in breast tumors by deep sequencing. Cancer Res. 2011;71:4443–53.

    Article  PubMed  CAS  Google Scholar 

  8. Hou J, Lin L, Zhou W, Wang Z, Ding G, Dong Q, et al. Identification of miRNomes in human liver and hepatocellular carcinoma reveals miR-199a/b-3p as therapeutic target for hepatocellular carcinoma. Cancer Cell. 2011;19:232–43.

    Article  PubMed  CAS  Google Scholar 

  9. Hu Z, Chen X, Zhao Y, Tian T, Jin G, Shu Y, et al. Serum MicroRNA signatures identified in a genome-wide serum MicroRNA expression profiling predict survival of non-small-cell lung cancer. J Clin Oncol. 2010;28:1721–6.

    Article  PubMed  Google Scholar 

  10. Hu Z, Dong J, Wang LE, Ma H, Liu J, Zhao Y, et al. Serum microRNA profiling and breast cancer risk: the use of miR-484/191 as endogenous controls. Carcinogenesis. 2012;33:828–34.

    Article  PubMed  CAS  Google Scholar 

  11. Kim YH, Liang H, Liu X, Lee J-S, Cho JY, Cheong J-H, et al. AMPKα modulation in cancer progression: multilayer integrative analysis of the whole transcriptome in Asian gastric cancer. Cancer Res. 2012;72:2512–21.

    Article  PubMed  CAS  Google Scholar 

  12. Leidner RS, Ravi L, Leahy P, Chen Y, Bednarchik B, Streppel M, et al. The microRNAs, MiR-31 and MiR-375, as candidate markers in Barrett’s esophageal carcinogenesis. Genes Chromosomes Cancer. 2012;51:473–9.

    Article  PubMed  CAS  Google Scholar 

  13. Li D, Liu X, Lin L, Hou J, Li N, Wang C, et al. MicroRNA-99a inhibits hepatocellular carcinoma growth and correlates with prognosis of patients with hepatocellular carcinoma. J Biol Chem. 2011;286:36677–85.

    Article  PubMed  CAS  Google Scholar 

  14. Li LM, Hu ZB, Zhou ZX, Chen X, Liu FY, Zhang JF, et al. Serum microRNA profiles serve as novel biomarkers for HBV infection and diagnosis of HBV-positive hepatocarcinoma. Cancer Res. 2010;70:9798–807.

    Article  PubMed  CAS  Google Scholar 

  15. Liu R, Chen X, Du Y, Yao W, Shen L, Wang C, et al. Serum microRNA expression profile as a biomarker in the diagnosis and prognosis of pancreatic cancer. Clin Chem. 2012;58:610–8.

    Article  PubMed  CAS  Google Scholar 

  16. Liu R, Zhang C, Hu Z, Li G, Wang C, Yang C, et al. A five-microRNA signature identified from genome-wide serum microRNA expression profiling serves as a fingerprint for gastric cancer diagnosis. Eur J Cancer. 2011;47:784–91.

    Article  PubMed  CAS  Google Scholar 

  17. Witten D, Tibshirani R, Gu SG, Fire A, Lui WO. Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls. BMC Biol. 2010;8:58.

    Article  PubMed  Google Scholar 

  18. Wu Q, Lu Z, Li H, Lu J, Guo L, Ge Q. Next-generation sequencing of MicroRNAs for breast cancer detection. J Biomed Biotechnol. 2011;2011:597145.

    PubMed  Google Scholar 

  19. Wu Q, Wang C, Lu Z, Guo L, Ge Q. Analysis of serum genome-wide microRNAs for breast cancer detection. Clin Chim Acta. 2012;413:1058–65.

    Article  PubMed  CAS  Google Scholar 

  20. Wu X, Somlo G, Yu Y, Palomares MR, Li AX, Zhou W, et al. De novo sequencing of circulating miRNAs identifies novel markers predicting clinical outcome of locally advanced breast cancer. J Transl Med. 2012;10:42.

    Article  PubMed  CAS  Google Scholar 

  21. 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. Int J Cancer. 2013;132:116–27.

    Article  PubMed  CAS  Google Scholar 

  22. Yu S, Liu Y, Wang J, Guo Z, Zhang Q, Yu F, et al. Circulating microRNA profiles as potential biomarkers for diagnosis of papillary thyroid carcinoma. J Clin Endocrinol Metab. 2012;97:2084–92.

    Article  PubMed  CAS  Google Scholar 

  23. Zhang C, Wang C, Chen X, Yang C, Li K, Wang J, et al. Expression profile of microRNAs in serum: a fingerprint for esophageal squamous cell carcinoma. Clin Chem. 2010;56:1871–9.

    Article  PubMed  CAS  Google Scholar 

  24. Koshiol J, Wang E, Zhao Y, Marincola F, Landi MT. Strengths and limitations of laboratory procedures for microRNA detection. Cancer Epidemiol Biomarkers Prev. 2010;19:907–11.

    Article  PubMed  CAS  Google Scholar 

  25. Li J, Smyth P, Flavin R, Cahill S, Denning K, Aherne S, et al. Comparison of miRNA expression patterns using total RNA extracted from matched samples of formalin-fixed paraffin-embedded (FFPE) cells and snap frozen cells. BMC Biotechnol. 2007;7:36.

    Article  PubMed  Google Scholar 

  26. Xi Y, Nakajima G, Gavin E, Morris CG, Kudo K, Hayashi K, et al. Systematic analysis of microRNA expression of RNA extracted from fresh frozen and formalin-fixed paraffin-embedded samples. RNA. 2007;13:1668–74.

    Article  PubMed  CAS  Google Scholar 

  27. Zhang B, Farwell MA. microRNAs: a new emerging class of players for disease diagnostics and gene therapy. Journal of Cellular and. Mol Med. 2008;12:3–21.

    CAS  Google Scholar 

  28. Chen X, Ba Y, Ma L, Cai X, Yin Y, Wang K, et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res. 2008;18:997–1006.

    Article  PubMed  CAS  Google Scholar 

  29. Zhang X, Chen J, Radcliffe T, Lebrun DP, Tron VA, Feilotter H. An array-based analysis of microRNA expression comparing matched frozen and formalin-fixed paraffin-embedded human tissue samples. J Mol Diagn. 2008;10:513–9.

    Article  PubMed  Google Scholar 

  30. Markowitz SD, Dawson DM, Willis J, Willson JK. Focus on colon cancer. Cancer Cell. 2002;1:233–6.

    Article  PubMed  CAS  Google Scholar 

  31. Ludwig JA, Weinstein JN. Biomarkers in cancer staging, prognosis and treatment selection. Nat Rev Cancer. 2005;5:845–56.

    Article  PubMed  CAS  Google Scholar 

  32. Prasad GA, Bansal A, Sharma P, Wang KK. Predictors of progression in Barrett’s esophagus: current knowledge and future directions. Am J Gastroenterol. 2010;105:1490–502.

    Article  PubMed  Google Scholar 

  33. Reid BJ, Li X, Galipeau PC, Vaughan TL. Barrett’s oesophagus and oesophageal adenocarcinoma: time for a new synthesis. Nat Rev Cancer. 2010;10:87–101.

    Article  PubMed  CAS  Google Scholar 

  34. Peltier HJ, Latham GJ. Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. RNA. 2008;14:844–52.

    Article  PubMed  CAS  Google Scholar 

  35. Mercer TR, Dinger ME, Mattick JS. Long non-coding RNAs: insights into functions. Nat Rev Genet. 2009;10:155–9.

    Article  PubMed  CAS  Google Scholar 

  36. Cabili MN, Trapnell C, Goff L, Koziol M, Tazon-Vega B, Regev A, et al. Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev. 2011;25:1915–27.

    Article  PubMed  CAS  Google Scholar 

  37. Brunner AL, Beck AH, Edris B, Sweeney RT, Zhu SX, Li R, et al. Transcriptional profiling of lncRNAs and novel transcribed regions across a diverse panel of archived human cancers. Genome Biol. 2012;13:R75.

    Article  PubMed  Google Scholar 

  38. Kannan K, Wang L, Wang J, Ittmann MM, Li W, Yen L. Recurrent chimeric RNAs enriched in human prostate cancer identified by deep sequencing. Proc Natl Acad Sci. 2011;108:9172–7.

    Article  PubMed  CAS  Google Scholar 

  39. Liu J, Lee W, Jiang Z, Chen Z, Jhunjhunwala S, Haverty PM, et al. Genome and transcriptome sequencing of lung cancers reveal diverse mutational and splicing events. Genome Res. 2012;22:2315–27.

    Article  PubMed  CAS  Google Scholar 

  40. Mosig RA, Lobl M, Senturk E, Shah H, Cohen S, Chudin E, et al. IGFBP-4 tumor and serum levels are increased across all stages of epithelial ovarian cancer. J Ovarian Res. 2012;5:3.

    Article  PubMed  CAS  Google Scholar 

  41. Nacu S, Yuan W, Kan Z, Bhatt D, Rivers CS, Stinson J, et al. Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples. BMC Med Genomics. 2011;4:11.

    Article  PubMed  CAS  Google Scholar 

  42. Pflueger D, Terry S, Sboner A, Habegger L, Esgueva R, Lin PC, et al. Discovery of non-ETS gene fusions in human prostate cancer using next-generation RNA sequencing. Genome Res. 2011;21:56–67.

    Article  PubMed  CAS  Google Scholar 

  43. Seshagiri S, Stawiski EW, Durinck S, Modrusan Z, Storm EE, Conboy CB, et al. Recurrent R-spondin fusions in colon cancer. Nature. 2012;488:660–4.

    Article  PubMed  CAS  Google Scholar 

  44. Tomlins SA, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun X-W, et al. Recurrent Fusion of TMPRSS2 and ETS Transcription Factor Genes in Prostate Cancer. Science. 2005;310:644–8.

    Article  PubMed  CAS  Google Scholar 

  45. Pajares MJ, Ezponda T, Catena R, Calvo A, Pio R, Montuenga LM. Alternative splicing: an emerging topic in molecular and clinical oncology. Lancet Oncol. 2007;8:349–57.

    Article  PubMed  CAS  Google Scholar 

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Correspondence to Kishore Guda D.V.M., Ph.D. .

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Fink, S.P., Guda, K. (2013). Application of Next-Generation Sequencing in RNA Biomarker Discovery in Cancer Research. In: Wu, W., Choudhry, H. (eds) Next Generation Sequencing in Cancer Research. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7645-0_9

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