Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Manuscript
  • Published:

Minimal Residual Disease

Evaluation of candidate control genes for diagnosis and residual disease detection in leukemic patients using ‘real-time’ quantitative reverse-transcriptase polymerase chain reaction (RQ-PCR) – a Europe against cancer program

Leukemia volume 17, pages 2474–2486 (2003)Cite this article

Abstract

Real-time quantitative RT-PCR (RQ-PCR) is a sensitive tool to monitor minimal residual disease (MRD) in leukemic patients through the amplification of a fusion gene (FG) transcript. In order to correct variations in RNA quality and quantity and to calculate the sensitivity of each measurement, a control gene (CG) transcript should be amplified in parallel to the FG transcript. To identify suitable CGs, a study group within the Europe Against Cancer (EAC) program initially focused on 14 potential CGs using a standardized RQ-PCR protocol. Based on the absence of pseudogenes and the level and stability of the CG expression, three genes were finally selected: Abelson (ABL), beta-2-microglobulin (B2M), and beta-glucuronidase (GUS). A multicenter prospective study on normal (n=126) and diagnostic leukemic (n=184) samples processed the same day has established reference values for the CG expression. A multicenter retrospective study on over 250 acute and chronic leukemia samples obtained at diagnosis and with an identified FG transcript confirmed that the three CGs had a stable expression in the different types of samples. However, only ABL gene transcript expression did not differ significantly between normal and leukemic samples at diagnosis. We therefore propose to use the ABL gene as CG for RQ-PCR-based diagnosis and MRD detection in leukemic patients. Overall, these data are not only eligible for quantification of fusion gene transcripts, but also for the quantification of aberrantly expressed genes.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

References

  1. Coustan-Smith E, Behm FG, Sanchez J, Boyett JM, Hancock ML, Raimondi SC et al. Immunological detection of minimal residual disease in children with acute lymphoblastic leukaemia. Lancet 1998; 351: 550–554.

    Article  CAS  PubMed  Google Scholar 

  2. Lucio P, Gaipa G, van Lochem EG, van Wering ER, Porwit-MacDonald A, Faria T et al. BIOMED-I concerted action report: flow cytometric immunophenotyping of precursor B-ALL with standardized triple-stainings. BIOMED-1 concerted action investigation of minimal residual disease in acute leukemia: international standardization and clinical evaluation. Leukemia 2001; 15: 1185–1192.

    Article  CAS  PubMed  Google Scholar 

  3. Brisco MJ, Condon J, Hughes E, Neoh SH, Sykes PJ, Seshadri R et al. Outcome prediction in childhood acute lymphoblastic leukaemia by molecular quantification of residual disease at the end of induction. Lancet 1994; 343: 196–200.

    Article  CAS  PubMed  Google Scholar 

  4. San Miguel JF, Martinez A, Macedo A, Vidriales MB, Lopez-Berges C, Gonzalez M et al. Immunophenotyping investigation of minimal residual disease is a useful approach for predicting relapse in acute myeloid leukemia patients. Blood 1997; 90: 2465–2470.

    CAS  PubMed  Google Scholar 

  5. Cave H, van der Werff ten Bosch J, Suciu S, Guidal C, Waterkeyn C, Otten J et al. Clinical significance of minimal residual disease in childhood acute lymphoblastic leukemia. European Organization for Research and Treatment of Cancer – Childhood Leukemia Cooperative Group. N Engl J Med 1998; 339: 591–598.

    Article  CAS  PubMed  Google Scholar 

  6. van Dongen JJ, Seriu T, Panzer-Grumayer ER, Biondi A, Pongers-Willemse MJ, Corral L et al. Prognostic value of minimal residual disease in acute lymphoblastic leukaemia in childhood. Lancet 1998; 352: 1731–1738.

    Article  CAS  PubMed  Google Scholar 

  7. Lion T, Henn T, Gaiger A, Kalhs P, Gadner H . Early detection of relapse after bone marrow transplantation in patients with chronic myelogenous leukaemia. Lancet 1993; 341: 275–276.

    Article  CAS  PubMed  Google Scholar 

  8. Diverio D, Rossi V, Avvisati G, De Santis S, Pistilli A, Pane F et al. Early detection of relapse by prospective reverse transcriptase-polymerase chain reaction analysis of the PML/RARalpha fusion gene in patients with acute promyelocytic leukemia enrolled in the GIMEMA-AIEOP multicenter ‘AIDA’ trial. GIMEMA-AIEOP Multicenter ‘AIDA’ Trial. Blood 1998; 92: 784–789.

    CAS  PubMed  Google Scholar 

  9. Romana SP, Poirel H, Leconiat M, Flexor MA, Mauchauffe M, Jonveaux P et al. High frequency of t(12;21) in childhood B-lineage acute lymphoblastic leukemia. Blood 1995; 86: 4263–4269.

    CAS  PubMed  Google Scholar 

  10. Pallisgaard N, Hokland P, Riishoj DC, Pedersen B, Jorgensen P . Multiplex reverse transcription-polymerase chain reaction for simultaneous screening of 29 translocations and chromosomal aberrations in acute leukemia. Blood 1998; 92: 574–588.

    CAS  PubMed  Google Scholar 

  11. Grimwade D . Screening for core binding factor gene rearrangements in acute myeloid leukemia. Leukemia 2002; 16: 964–969.

    Article  CAS  PubMed  Google Scholar 

  12. Gabert J . Detection of recurrent translocations using real time PCR; assessment of the technique for diagnosis and detection of minimal residual disease. Haematologica 1999; 84: 107–109.

    PubMed  Google Scholar 

  13. Bustin SA . Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol 2000; 25: 169–193.

    Article  CAS  PubMed  Google Scholar 

  14. Lion T . Current recommendations for positive controls in RT-PCR assays. Leukemia 2001; 15: 1033–1037.

    Article  CAS  PubMed  Google Scholar 

  15. Zhang Z, Harrison P, Gerstein M . Identification and analysis of over 2000 ribosomal protein pseudogenes in the human genome. Genome Res 2002; 12: 1466–1482.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Pallisgaard N, Clausen N, Schroder H, Hokland P . Rapid and sensitive minimal residual disease detection in acute leukemia by quantitative real-time RT-PCR exemplified by t(12;21) TEL-AML1 fusion transcript. Genes Chromosomes Cancer 1999; 26: 355–365.

    Article  CAS  PubMed  Google Scholar 

  17. Guerrasio A, Pilatrino C, De Micheli D, Cilloni D, Serra A, Gottardi E et al. Assessment of minimal residual disease (MRD) in CBFbeta/MYH11-positive acute myeloid leukemias by qualitative and quantitative RT-PCR amplification of fusion transcripts. Leukemia 2002; 16: 1176–1181.

    Article  CAS  PubMed  Google Scholar 

  18. Emig M, Saussele S, Wittor H, Weisser A, Reiter A, Willer A et al. Accurate and rapid analysis of residual disease in patients with CML using specific fluorescent hybridization probes for real time quantitative RT-PCR. Leukemia 1999; 13: 1825–1832.

    Article  CAS  PubMed  Google Scholar 

  19. Schoch C, Schnittger S, Bursch S, Gerstner D, Hochhaus A, Berger U et al. Comparison of chromosome banding analysis, interphase- and hypermetaphase-FISH, qualitative and quantitative PCR for diagnosis and for follow-up in chronic myeloid leukemia: a study on 350 cases. Leukemia 2002; 16: 53–59.

    Article  CAS  PubMed  Google Scholar 

  20. Hochhaus A, Reiter A, Saussele S, Reichert A, Emig M, Kaeda J . Molecular heterogeneity in complete cytogenetic responders after interferon-alpha therapy for chronic myelogenous leukemia: low levels of minimal residual disease are associated with continuing remission. German CML Study Group and the UK MRC CML Study Group. Blood 2000; 95: 62–66.

    CAS  PubMed  Google Scholar 

  21. Matsushita M, Ikeda H, Kizaki M, Okamoto S, Ogasawara M, Ikeda Y et al. Quantitative monitoring of the PRAME gene for the detection of minimal residual disease in leukaemia. Br J Haematol 2001; 112: 916–926.

    Article  CAS  PubMed  Google Scholar 

  22. Marcucci G, Livak KJ, Bi W, Strout MP, Bloomfield CD, Caligiuri MA . Detection of minimal residual disease in patients with AML1/ETO-associated acute myeloid leukemia using a novel quantitative reverse transcription polymerase chain reaction assay. Leukemia 1998; 12: 1482–1489.

    Article  CAS  PubMed  Google Scholar 

  23. Degan M, Mazzocco FT, Di Francia R, Rossi FM, Pinto A, Gattei V . Normalizing complementary DNA by quantitative reverse transcriptase-polymerase chain reaction of beta2-microglobulin: molecular monitoring of minimal residual disease in acute promyelocytic leukemia. Diagn Mol Pathol 2000; 9: 98–109.

    Article  CAS  PubMed  Google Scholar 

  24. Radich JP, Gooley T, Bryant E, Chauncey T, Clift R, Beppu L et al. The significance of bcr-abl molecular detection in chronic myeloid leukemia patients ‘late’, 18 months or more after transplantation. Blood 2001; 98: 1701–1707.

    Article  CAS  PubMed  Google Scholar 

  25. Krauter J, Hoellge W, Wattjes MP, Nagel S, Heidenreich O, Bunjes D et al. Detection and quantification of CBFB/MYH11 fusion transcripts in patients with inv(16)-positive acute myeloblastic leukemia by real-time RT-PCR. Genes Chromosomes Cancer 2001; 30: 342–348.

    Article  CAS  PubMed  Google Scholar 

  26. Cassinat B, Zassadowski F, Balitrand N, Barbey C, Rain JD, Fenaux P et al. Quantitation of minimal residual disease in acute promyelocytic leukemia patients with t(15;17) translocation using real-time RT-PCR. Leukemia 2000; 14: 324–328.

    Article  CAS  PubMed  Google Scholar 

  27. Ballerini P, Landman Parker J, Laurendeau I, Olivi M, Vidaud M, Adam M et al. Quantitative analysis of TEL/AML1 fusion transcripts by real-time RT-PCR assay in childhood acute lymphoblastic leukemia. Leukemia 2000; 14: 1526–1528.

    Article  CAS  PubMed  Google Scholar 

  28. Marcucci G, Caligiuri MA, Dohner H, Archer KJ, Schlenk RF, Dohner K et al. Quantification of CBFbeta/MYH11 fusion transcript by real time RT-PCR in patients with INV(16) acute myeloid leukemia. Leukemia 2001; 15: 1072–1080.

    Article  CAS  PubMed  Google Scholar 

  29. Gabert J, Beillard E, van der Velden VHJ, Bi W, Grimwade D, Pallisgaard N et al. Standardization and quality control studies of ‘real-time’ quantitative reverse transcriptase polymerase chain reaction (RQ-PCR) of fusion gene transcripts for residual disease detection in leukemia – A Europe Against Cancer Program. Leukemia 2003; (in press).

  30. van Dongen JJ, Macintyre EA, Gabert JA, Delabesse E, Rossi V, Saglio G et al. Standardized RT-PCR analysis of fusion gene transcripts from chromosome aberrations in acute leukemia for detection of minimal residual disease. Report of the BIOMED-1 concerted action: investigation of minimal residual disease in acute leukemia. Leukemia 1999; 13: 1901–1928.

    Article  CAS  PubMed  Google Scholar 

  31. Dirnhofer S, Berger C, Untergasser G, Geley S, Berger P . Human beta-actin retropseudogenes interfere with RT-PCR. Trends Genet 1995; 11: 380–381.

    Article  CAS  PubMed  Google Scholar 

  32. Arcari P, Martinelli R, Salvatore F . Human glyceraldehyde-3-phosphate dehydrogenase pseudogenes: molecular evolution and a possible mechanism for amplification. Biochem Genet 1989; 27: 439–450.

    Article  CAS  PubMed  Google Scholar 

  33. Kollia P, Stavroyianni N, Stamatopoulos K, Zoi K, Viniou N, Mantzourani M et al. Molecular analysis of transferrin receptor mRNA expression in acute myeloid leukaemia. Br J Haematol 2001; 115: 19–24.

    Article  CAS  PubMed  Google Scholar 

  34. Sposi NM, Cianetti L, Tritarelli E, Pelosi E, Militi S, Barberi T et al. Mechanisms of differential transferrin receptor expression in normal hematopoiesis. Eur J Biochem 2000; 267: 6762–6774.

    Article  CAS  PubMed  Google Scholar 

  35. Willenbrink W, Halaschek J, Schuffenhauer S, Kunz J, Steinkasserer A . Cyclophilin A, the major intracellular receptor for the immunosuppressant cyclosporin A, maps to chromosome 7p112-p13: four pseudogenes map to chromosomes 3, 10, 14, and 18. Genomics 1995; 28: 101–104.

    Article  CAS  PubMed  Google Scholar 

  36. Kidd V, Lion T . Debate round-table. Appropriate controls for RT-PCR. Leukemia 1997; 11: 871–881.

    Article  CAS  PubMed  Google Scholar 

  37. Stentoft J, Pallisgaard N, Kjeldsen E, Holm MS, Nielsen JL, Hokland P . Kinetics of BCR-ABL fusion transcript levels in chronic myeloid leukemia patients treated with STI571 measured by quantitative real-time polymerase chain reaction. Eur J Haematol 2001; 67: 302–308.

    Article  CAS  PubMed  Google Scholar 

  38. Cross NC, Feng L, Chase A, Bungey J, Hughes TP, Goldman JM . Competitive polymerase chain reaction to estimate the number of BCR-ABL transcripts in chronic myeloid leukemia patients after bone marrow transplantation. Blood 1993; 82: 1929–1936.

    CAS  PubMed  Google Scholar 

  39. Lyon MF . X-chromosome inactivation and human genetic disease. Acta Paediatr Suppl 2002; 91: 107–112.

    Article  CAS  PubMed  Google Scholar 

  40. Lupberger J, Kreuzer KA, Baskaynak G, Peters UR, le Coutre P, Schmidt CA . Quantitative analysis of beta-actin, beta-2-microglobulin and porphobilinogen deaminase mRNA and their comparison as control transcripts for RT-PCR. Mol Cell Probes 2002; 16: 25–30.

    Article  CAS  PubMed  Google Scholar 

  41. Hamalainen HK, Tubman JC, Vikman S, Kyrola T, Ylikoski E, Warrington JA et al. Identification and validation of endogenous reference genes for expression profiling of T helper cell differentiation by quantitative real-time RT-PCR. Anal Biochem 2001; 299: 63–70.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Additional contributors not listed in the authors list: M González, Servicio de Hematologia, Hospital Clinico Universitario, Salamanca, Spain; G Barbany, Department of Medical Sciences, Uppsala University Hospital, Uppsala, Sweden; F Pane, CEINGE-DasMelab, Universita di Napoli Federico II, Napoli, Italy; Hélène Cavé, Lab de Biochimie Génétique, Hopital Robert Debré, Paris, France; J Aerts, Experimentele Laboratoriumgeneeskunde, Leuven, Belgium; M Lafage-Pochitaloff, Laboratoire de Cytogénétique Hématologique, Institut Paoli Calmettes, Marseille, France; A Porwit, Department of Pathology, Karolinska Hospital, Stockholm, Sweden. We also thank the other laboratories of the Europe Against Cancer Network for their support and discussions. We thank W Mayser for his logistic support during meetings, K Livak and X Thirion for useful discussions, N Brochard for secretarial assistance and D Grimwade for critical review of the manuscript. This work was supported by the SANCO European Commission (no. SI2.129294 (99CVF2-016) and Applied Biosystems (Foster City, CA, USA). Additional support was provided by national grants: ARC no. 5484, Ligue Contre le Cancer, Dutch Cancer Society/Koningin Wilhelmina Fonds (Grant SNWLK 2000-2268); Associazione Italiana per la Ricerca sul Cancero (AIRC), MURST.

Author information

Author notes

  1. E Beillard & J Gabert

    Present address: Department of Biochemistry & Molecular Biology, Hôpital Universitaire Nord, ERT MEiDiA IFR Jean Roche, Université de la Méditerranée, Marseille, France

  2. J Gabert: JG is a consultant for Ipsogen

  3. E Beillard and N Pallisgaard: First co-authors

Authors and Affiliations

  1. Department of Hematological Biology, Institute Paoli Calmettes, Marseille, France

    E Beillard & J Gabert

  2. Department of Hematology, Laboratory of Immuno-hematology, Aarhus University Hospital, Aarhus, Denmark

    N Pallisgaard & P Hokland

  3. Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands

    V H J van der Velden & J J M van Dongen

  4. Applied Biosystems, Foster City, CA, USA

    W Bi

  5. Department of Experimental Immunohematology, CLB, Amsterdam, The Netherlands

    R Dee & E van der Schoot

  6. Department of Hematology, Necker Hospital, Paris, France

    E Delabesse & E Macintyre

  7. Department of Clinical and Biological Science, University of Turin, Ospedale San Luigi Gonzaga, Orbassano-Torino, Italy

    E Gottardi & G Saglio

  8. Children's Cancer Research Institute, St Anna Children's Hospital, Vienna, Austria

    F Watzinger & T Lion

Authors
  1. E Beillard
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N Pallisgaard
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V H J van der Velden
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. W Bi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. R Dee
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. E van der Schoot
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. E Delabesse
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. E Macintyre
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. E Gottardi
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. G Saglio
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. F Watzinger
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. T Lion
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. J J M van Dongen
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. P Hokland
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. J Gabert
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J Gabert.

Additional information

Supplementary Information Supplementary Information accompanies the paper on Leukemia website (http://www.nature.com/leu).

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Cite this article

Beillard, E., Pallisgaard, N., van der Velden, V. et al. Evaluation of candidate control genes for diagnosis and residual disease detection in leukemic patients using ‘real-time’ quantitative reverse-transcriptase polymerase chain reaction (RQ-PCR) – a Europe against cancer program. Leukemia 17, 2474–2486 (2003). https://doi.org/10.1038/sj.leu.2403136

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/sj.leu.2403136

Keywords

Search

Advanced search

Quick links