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Gut neuroendocrine tumor blood qPCR fingerprint assay: characteristics and reproducibility

  • Irvin M. Modlin EMAIL logo , Ignat Drozdov and Mark Kidd
Published/Copyright: October 14, 2013

Abstract

Background: We have developed a PCR-based tool that measures a 51-gene panel for identification of gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs) in peripheral blood. This manuscript assesses the robustness (performance metrics) of this tool with a specific focus on the effects of individual parameters including collection, storage, acid suppressive medication [proton pump inhibitor (PPI)], age, sex, race and food on accuracy.

Methods: Performance metrics were evaluated using a gold standard (mRNA derived from three individual human neuroendocrine tumor cell lines) and clinical samples using qPCR.

Results: One hundred percent of the 51 transcripts were amplified in the gold standard (NEN cell line-derived mRNA) (CQ<35, average efficiency 1.94). The inter- and intra-assay variations were 1%–2%. In clinical samples, 50 of 51 targets (98%) were amplified. The inter- and intra-assay reproducibility ranged between 0.4% and 1.2%. The coefficient of variation (CV) was 5.3%. Expression of the reference gene, ALG9, was robust [low variation, low M-value, high (99.5%) PCR efficiency] and unaffected by sample processing. Test meals, long-term PPI use (>1 year), age, sex and ethnicity had no effect on the signature. Expression of two genes, ALP2 and CD59 correlated strongly with RNA integrity (R=0.72, p<0.001) and could be used to assess storage and processing.

Conclusions: The 51 marker gene signature was robust and reproducible, exhibiting acceptable inter- and intra-assay metrics (<5%). Feeding, PPI intake, age, sex and ethnicity do not affect the signature. Expression levels of APLP2 and CD59 are effective surrogate markers of proper sample collection and processing.


Corresponding author: Irvin M. Modlin, Department of Surgery, Yale University School of Medicine, New Haven, CT 06510, USA, E-mail:

Daniele Alaimo and Steve Callahan for technical support.

Conflict of interest statement

Authors’ conflict of interest disclosure: The authors stated that there are no conflicts of interest regarding the publication of this article. Research funding played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

Research funding: Funding for this project was provided by Clifton Life Sciences.

Employment or leadership: None declared.

Honorarium: None declared.

References

1. Gabert J, Beillard E, van der Velden VH, Bi W, Grimwade D, Pallisgaard N, et al. Standardization and quality control studies of ′real-time′ quantitative reverse transcriptase polymerase chain reaction of fusion gene transcripts for residual disease detection in leukemia a Europe Against Cancer program. Leukemia 2003;17:2318–57.10.1038/sj.leu.2403135Search in Google Scholar

2. van ′t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530–6.10.1038/415530aSearch in Google Scholar

3. Huang E, Cheng SH, Dressman H, Pittman J, Tsou MH, Horng CF, et al. Gene expression predictors of breast cancer outcomes. Lancet 2003;361:1590–6.10.1016/S0140-6736(03)13308-9Search in Google Scholar

4. Hess KR, Anderson K, Symmans WF, Valero V, Ibrahim N, Mejia JA, et al. Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol 2006;24:4236–44.10.1200/JCO.2006.05.6861Search in Google Scholar

5. Cheng SH, Horng CF, West M, Huang E, Pittman J, Tsou MH, et al. Genomic prediction of locoregional recurrence after mastectomy in breast cancer. J Clin Oncol 2006;24:4594–602.10.1200/JCO.2005.02.5676Search in Google Scholar

6. Helland A, Johnsen H, Froyland C, Landmark HB, Saetersdal AB, Holmen MM, et al. Radiation-induced effects on gene expression: an in vivo study on breast cancer. Radiother Oncol 2006;80:230–5.10.1016/j.radonc.2006.07.007Search in Google Scholar

7. Schuster R, Max N, Mann B, Heufelder K, Thilo F, Grone J, et al. Quantitative real-time RT-PCR for detection of disseminated tumor cells in peripheral blood of patients with colorectal cancer using different mRNA markers. Int J Cancer 2004;108:219–27.10.1002/ijc.11547Search in Google Scholar

8. Wu DY, Ugozzoli L, Pal BK, Qian J, Wallace RB. The effect of temperature and oligonucleotide primer length on the specificity and efficiency of amplification by the polymerase chain reaction. DNA Cell Biol 1991;10:233–8.10.1089/dna.1991.10.233Search in Google Scholar

9. Dingemans AM, Brakenhoff RH, Postmus PE, Giaccone G. Detection of cytokeratin-19 transcripts by reverse transcriptase-polymerase chain reaction in lung cancer cell lines and blood of lung cancer patients. Lab Invest 1997;77:213–20.Search in Google Scholar

10. Zippelius A, Kufer P, Honold G, Kollermann MW, Oberneder R, Schlimok G, et al. Limitations of reverse-transcriptase polymerase chain reaction analyses for detection of micrometastatic epithelial cancer cells in bone marrow. J Clin Oncol 1997;15:2701–8.10.1200/JCO.1997.15.7.2701Search in Google Scholar

11. Henke W, Loening SA. Detection of illegitimate transcripts of prostate-specific antigen mRNA in blood by reverse transcription-polymerase chain reaction. Int J Cancer 1998;77:164–5.10.1002/(SICI)1097-0215(19980703)77:1<164::AID-IJC25>3.0.CO;2-DSearch in Google Scholar

12. Lambrechts AC, van’t Veer LJ, Rodenhuis S. The detection of minimal numbers of contaminating epithelial tumor cells in blood or bone marrow: use, limitations and future of RNA-based methods. Ann Oncol 1998;9:1269–76.10.1023/A:1008445604263Search in Google Scholar

13. Sokoloff MH, Tso CL, Kaboo R, Nelson S, Ko J, Dorey F, et al. Quantitative polymerase chain reaction does not improve preoperative prostate cancer staging: a clinicopathological molecular analysis of 121 patients. J Urol 1996;156:1560–6.10.1016/S0022-5347(01)65447-8Search in Google Scholar

14. Gala JL, Heusterspreute M, Loric S, Hanon F, Tombal B, Van Cangh P, et al. Expression of prostate-specific antigen and prostate-specific membrane antigen transcripts in blood cells: implications for the detection of hematogenous prostate cells and standardization. Clin Chem 1998; 44:472–81.10.1093/clinchem/44.3.472Search in Google Scholar

15. de la Taille A, Olsson CA, Katz AE. Molecular staging of prostate cancer: dream or reality? Oncology (Williston Park) 1999;13:187–94; discussion 94–8, 204–5 pas.Search in Google Scholar

16. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 2009;55:611–22.10.1373/clinchem.2008.112797Search in Google Scholar

17. Modlin I, Drozdov I, Kidd M. The identification of gut neuroendocrine tumor disease by multiple synchronous transcript analysis in blood. Plos One 2013;e63364.10.1371/journal.pone.0063364Search in Google Scholar

18. Liu W, Saint DA. Validation of a quantitative method for real time PCR kinetics. Biochem Biophys Res Commun 2002;294:347–53.10.1016/S0006-291X(02)00478-3Search in Google Scholar

19. Bustin SA. Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol 2000;25:169–93.10.1677/jme.0.0250169Search in Google Scholar

20. Lekanne Deprez RH, Fijnvandraat AC, Ruijter JM, Moorman AF. Sensitivity and accuracy of quantitative real-time polymerase chain reaction using SYBR green I depends on cDNA synthesis conditions. Anal Biochem 2002;307:63–9.10.1016/S0003-2697(02)00021-0Search in Google Scholar

21. Bustin SA. Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems. J Mol Endocrinol 2002;29:23–39.10.1677/jme.0.0290023Search in Google Scholar PubMed

22. Lawrence B, Gustafsson BI, Kidd M, Pavel M, Svejda B, Modlin IM. The clinical relevance of chromogranin A as a biomarker for gastroenteropancreatic neuroendocrine tumors. Endocrinol Metab Clin North Am 2011;40:111–34.10.1016/j.ecl.2010.12.001Search in Google Scholar PubMed

23. Raza A, Ali Z, Irfan J, Murtaza S, Shakeel S. Analytical variables influencing the HCV RNA determination by TaqMan real-time PCR in routine clinical laboratory practice. Mol Biol Rep 2012;39:7421–7.10.1007/s11033-012-1574-3Search in Google Scholar PubMed

24. Fleige S, Walf V, Huch S, Prgomet C, Sehm J, Pfaffl MW. Comparison of relative mRNA quantification models and the impact of RNA integrity in quantitative real-time RT-PCR. Biotechnol Lett 2006;28:1601–13.10.1007/s10529-006-9127-2Search in Google Scholar PubMed

25. Kidd M, Nadler B, Mane S, Eick G, Malfertheiner M, Champaneria M, et al. GeneChip, geNorm, and gastrointestinal tumors: novel reference genes for real-time PCR. Physiol Genomics 2007;30:363–70.10.1152/physiolgenomics.00251.2006Search in Google Scholar PubMed

26. Buh Gasparic M, Cankar K, Zel J, Gruden K. Comparison of different real-time PCR chemistries and their suitability for detection and quantification of genetically modified organisms. BMC Biotechnol 2008;8:26.10.1186/1472-6750-8-26Search in Google Scholar PubMed PubMed Central

27. Fink L, Seeger W, Ermert L, Hanze J, Stahl U, Grimminger F, et al. Real-time quantitative RT-PCR after laser-assisted cell picking. Nat Med 1998;4:1329–33.10.1038/3327Search in Google Scholar PubMed

28. Ginzinger DG, Godfrey TE, Nigro J, Moore DH, 2nd, Suzuki S, Pallavicini MG, et al. Measurement of DNA copy number at microsatellite loci using quantitative PCR analysis. Cancer Res 2000;60:5405–9.Search in Google Scholar

29. Palmieri G, Pirastu M, Strazzullo M, Ascierto PA, Satriano SM, Motti ML, et al. Clinical significance of PCR-positive mRNA markers in peripheral blood and regional nodes of malignant melanoma patients. Melanoma Cooperative Group. Recent Results Cancer Res 2001;158:200–3.10.1007/978-3-642-59537-0_20Search in Google Scholar PubMed

30. Van der Auwera I, Peeters D, Benoy IH, Elst HJ, Van Laere SJ, Prove A, et al. Circulating tumour cell detection: a direct comparison between the CellSearch System, the AdnaTest and CK-19/mammaglobin RT-PCR in patients with metastatic breast cancer. Br J Cancer 2010;102:276–84.10.1038/sj.bjc.6605472Search in Google Scholar PubMed PubMed Central

31. Freeman WM, Walker SJ, Vrana KE. Quantitative RT-PCR: pitfalls and potential. Biotechniques 1999;26:112–22, 24–5.10.2144/99261rv01Search in Google Scholar PubMed

32. Wong FL, Hamidah NH, Hawa AA, Nurul AN, Leong CF, Saw F, et al. Real-time quantification for BCR-ABL transcripts in chronic myeloid leukaemia patients in UKMMC, Malaysia. Malays J Pathol 2011;33:107–12.Search in Google Scholar

33. Jia X, Ju H, Yang L, Tian Y. A novel multiplex polymerase chain reaction assay for profile analyses of gene expression in peripheral blood. BMC Cardiovasc Disord 2012;12:51.10.1186/1471-2261-12-51Search in Google Scholar PubMed PubMed Central

34. Schmittgen TD, Zakrajsek BA, Mills AG, Gorn V, Singer MJ, Reed MW. Quantitative reverse transcription-polymerase chain reaction to study mRNA decay: comparison of endpoint and real-time methods. Anal Biochem 2000;285:194–204.10.1006/abio.2000.4753Search in Google Scholar PubMed

35. Ding C, Cantor CR. A high-throughput gene expression analysis technique using competitive PCR and matrix-assisted laser desorption ionization time-of-flight MS. Proc Natl Acad Sci USA 2003;100:3059–64.10.1073/pnas.0630494100Search in Google Scholar PubMed PubMed Central

36. Raterman HG, Vosslamber S, de Ridder S, Nurmohamed MT, Lems WF, Boers M, et al. The interferon type I signature towards prediction of non-response to rituximab in rheumatoid arthritis patients. Arthritis Res Ther 2012;14:R95.10.1186/ar3819Search in Google Scholar PubMed PubMed Central

37. Pratt AG, Swan DC, Richardson S, Wilson G, Hilkens CM, Young DA, et al. A CD4 T cell gene signature for early rheumatoid arthritis implicates interleukin 6-mediated STAT3 signalling, particularly in anti-citrullinated peptide antibody-negative disease. Ann Rheum Dis 2012;71:1374–81.10.1136/annrheumdis-2011-200968Search in Google Scholar PubMed PubMed Central

38. Martin M, Garcia-Saenz JA, Maestro De las Casas ML, Vidaurreta M, Puente J, Veganzones S, et al. Circulating tumor cells in metastatic breast cancer: timing of blood extraction for analysis. Anticancer Res 2009;29:4185–7.Search in Google Scholar

39. Giusti M, Sidoti M, Augeri C, Rabitti C, Minuto F. Effect of short-term treatment with low dosages of the proton-pump inhibitor omeprazole on serum chromogranin A levels in man. Eur J Endocrinol 2004;150:299–303.10.1530/eje.0.1500299Search in Google Scholar PubMed

40. Brisco MJ, Morley AA. Quantification of RNA integrity and its use for measurement of transcript number. Nucleic Acids Res 2012;25:25.10.1093/nar/gks588Search in Google Scholar

Received: 2013-07-02
Accepted: 2013-09-19
Published Online: 2013-10-14
Published in Print: 2014-03-01

©2014 by Walter de Gruyter Berlin Boston

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