Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Clinical Trial
. 2015 May;50(5):642-51.
doi: 10.1038/bmt.2014.326. Epub 2015 Feb 9.

A multigene array for measurable residual disease detection in AML patients undergoing SCT

Affiliations
Clinical Trial

A multigene array for measurable residual disease detection in AML patients undergoing SCT

M Goswami et al. Bone Marrow Transplant. 2015 May.

Abstract

AML is a diagnosis encompassing a diverse group of myeloid malignancies. Heterogeneous genetic etiology, together with the potential for oligoclonality within the individual patient, have made the identification of a single high-sensitivity marker of disease burden challenging. We developed a multiple gene measurable residual disease (MG-MRD) RQ-PCR array for the high-sensitivity detection of AML, retrospectively tested on 74 patients who underwent allo-SCT at the NHLBI in the period 1994-2012. MG-MRD testing on peripheral blood samples prior to transplantation demonstrated excellent concordance with traditional BM-based evaluation and improved risk stratification for post-transplant relapse and OS outcomes. Pre-SCT assessment by MG-MRD predicted all clinical relapses occurring in the first 100 days after allo-SCT compared with 57% sensitivity using WT1 RQ-PCR alone. Nine patients who were negative for WT1 prior to transplantation were correctly reclassified into a high-risk MG-MRD-positive group, associated with 100% post-transplant mortality. This study provides proof of principle that a multiple gene approach may be superior to the use of WT1 expression alone for AML residual disease detection.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Overexpressed genes in AML patients with low levels of WT1 expression. Samples of peripheral blood from 30 newly diagnosed, untreated, AML patients were assayed for gene overexpression by quantitative real-time PCR as previously described. Data were reanalyzed to identify genes overexpressed at least 50-fold in those patients with less than 50-fold WT1 overexpression compared with the normal donors. Red: 50–99-fold overexpression; bright red: 100-fold or greater overexpression; black: not detected; white: transcript detected but less than 50-fold overexpressed compared with normal donors. CCNA1, cyclin A1; MSLN, mesothelin; PRAME, preferentially expressed antigen in melanoma; PRTN3, proteinase 3; WT1, Wilms tumor 1.
Figure 2
Figure 2
Patterns of MG-MRD expression. Level of expression of the constituent gene transcripts of the MG-MRD array in normal healthy donor control and pre-transplant AML patient peripheral blood samples. Gene expression normalized to expression of the ABL control gene. Selected threshold values are indicated by a horizontal dotted line. Two non-relapsing patients with pathologist-detectable disease pre-SCT also had 4G-MRD values above the threshold, one with both WT1 and CCNA1, the other with WT1 and PRTN3. Several patients in this historical self-described healthy donor cohort had MSLN expression above the selected threshold; MSLN is not a specific AML antigen and has also been described as being overexpressed in a variety of solid tumors. CCNA1, cyclin A1; MSLN, mesothelin; PRAME, preferentially expressed antigen in melanoma; PRTN3, proteinase 3; WT1, Wilms tumor 1.
Figure 3
Figure 3
MG-MRD correlates with pathological diagnosis and relapse risk. (a) Peripheral blood-based MG-MRD testing has good concordance with pathologist BM diagnosis pre-SCT. Blue: pathologist determination of active disease based on clinical examination of BM (Path+), but negative for peripheral blood MRD testing. Purple: both BM pathological diagnosis and MRD positive. Red: negative for active AML by pathologist examination (‘remission marrow'), but positive for residual disease by peripheral blood-based MRD testing. (b) MG-MRD can identify patients mistakenly classified as low risk by WT1 MRD. Patients with pre-SCT positivity for WT1 represent the high-risk group. MG-MRD testing can identify additional high-risk individuals from the ‘low risk' WT1-negative group. The mortality in the additional nine patients (12%) reclassified as high risk was 100%. Six of those nine patients reclassified as high risk by MG-MRD were in a CR pre-transplant. (c) Pre-SCT MG-MRD testing improves prediction of early clinical relapses post SCT. All 28 relapses post SCT are plotted by day of clinical relapse aligned with the result of pre-SCT MRD testing. MG-MRD prior to transplantation correctly predicted all relapses in the first 180 days after SCT and was particularly useful in correctly identifying those at risk of early (that is, before median relapse of 99 days) relapse but not identified by WT1 testing. Patients relapsing at 33, 56, 59, 87, 91, 122, 181, 303, 304, 493 and 1089 days post SCT were in a CR prior to SCT (bold).
Figure 4
Figure 4
MG-MRD allows stratification into highly polarized groups for survival and relapse risk. (a) Three-year OS. MG-MRD can effectively segregate patients based on pre-SCT peripheral blood gene expression profile into groups with high and low risk of survival following transplantation. Color pie chart below survival curve illustrates the fraction of the entire cohort triaged to the high-risk category (red) based on the MRD method used. (b) Relapses in the first year after transplantation. Including only patients in pathologist-confirmed CR prior to transplantation and excluding patients dying of non-relapse causes. The green pie chart illustrates sensitivity of each pre-SCT MRD test to predict relapse in the year following transplantation. Statistical analysis was performed using GraphPad Prism with comparison between survival and relapse curves performed using the log-rank (Mantel–Cox) test.

References

    1. Cancer Genome Atlas Research N Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med. 2013;368:2059–2074. - PMC - PubMed
    1. Welch JS, Ley TJ, Link DC, Miller CA, Larson DE, Koboldt DC, et al. The origin and evolution of mutations in acute myeloid leukemia. Cell. 2012;150:264–278. - PMC - PubMed
    1. Valk PJ, Verhaak RG, Beijen MA, Erpelinck CA, Barjesteh van Waalwijk van Doorn-Khosrovani S, Boer JM, et al. Prognostically useful gene-expression profiles in acute myeloid leukemia. N Engl J Med. 2004;350:1617–1628. - PubMed
    1. Bullinger L, Dohner K, Bair E, Frohling S, Schlenk RF, Tibshirani R, et al. Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia. N Engl J Med. 2004;350:1605–1616. - PubMed
    1. Patel JP, Gönen M, Figueroa ME, Fernandez H, Sun Z, Racevskis J, et al. Prognostic relevance of integrated genetic profiling in acute myeloid leukemia. N Engl J Med. 2012;366:1079–1089. - PMC - PubMed

Publication types