Improving Our Early Warning System for AML
A more sensitive approach to monitoring acute myeloid leukemia relapse after bone marrow transplant
Amanda Winters | | Longer Read
At a Glance
- Bone marrow transplants can be a curative therapy for acute myeloid leukemia, but a significant proportion of patients still relapse
- Chimerism testing is routinely used to monitor relapse in transplanted patients, but a more sensitive, effective method is needed
- Droplet digital PCR measures the concentration of bone marrow-derived DNAs containing AML-associated mutations to offer a reliable approach to relapse monitoring
- The technique enables physicians to detect signs of relapse sooner, giving them more time to plan treatment regimens for their patients
Acute myeloid leukemia (AML) can be a devastating disease – but it’s not without treatment options; for example, allogeneic bone marrow transplantation (BMT), which replaces a patient’s cancer-producing hematopoietic stem cells with ones that produce healthy cells. But even though it’s meant to conclude a patient’s cancer care, even BMT is not a guaranteed cure: 40–50 percent of patients who receive a transplant still relapse (1).
Patients who undergo BMT do not typically receive any additional therapy to prevent relapse. If a patient’s body does not accept the graft and the transplant fails, they will likely also respond poorly to any alternative treatment. However, using more sensitive methods to detect relapse earlier – even before it appears using standard clinical measures – might provide patients with more effective options with respect to chemotherapies and targeted agents.
Our current approach
At the moment, the gold standard method for early detection of relapse post-transplant is chimerism testing. In this method, we analyze short tandem repeats in the patient’s bone marrow to identify the cells’ origin and calculate the proportion of donor marrow to recipient marrow. A higher-than-expected percentage of patient-derived bone marrow is an early sign of graft failure and an early indication of leukemia relapse. These clinical diagnostic tests usually take place one, three, and 12 months after transplant – but beyond this test, we have to depend on non-specific symptoms (such as weight loss, fatigue, and muscle weakness), which are less precise measures of cancer recurrence.
There is a paucity of research on the effectiveness of chimerism testing in monitoring AML following a BMT. The research that does exist has produced mixed results; whereas some studies have confirmed that chimerism testing predicts relapse, others have not (2). In fact, one study found that chimerism testing yields a false positive rate of over 10 percent, which could expose patients to unnecessary toxicity from treatments, and a false negative rate of over 40 percent, which leaves patients without a course of treatment that could improve their outcome (3).
A recent study highlights two potential reasons why we don’t yet have a firm grasp on the sensitivity and specificity of chimerism testing. First, a significant subset of the few existing studies focus only on pediatric patients. Second, those that do address adult patients use a small or heterogenous population that includes people with several different subtypes of leukemia (2). The lack of a consistent body of literature makes it difficult to assess the test’s appropriateness for monitoring AML relapse after transplant. Therefore, although chimerism is the gold standard method for predicting relapse to AML following a BMT, we cannot say with certainty that the technique is effective in every case.
An alternative way to detect relapse in AML is by minimal residual disease (MRD) testing. MRD is defined as leukemic cells that persist in the body following therapy at levels below the limit of morphological detection. Researchers have found that patients with MRD following treatment are at a greater risk for relapse and survive for a shorter amount of time (4).
The most common methods for detecting MRD are flow cytometry and quantitative PCR (qPCR). Multi-parameter flow cytometry can be used for detecting aberrantly expressed proteins associated with AML, but this technique has not been quantitatively or qualitatively standardized (5) and, depending on the case at hand, it is only sensitive down to 0.1 percent, the clinical flow cytometry-based threshold for MRD (4)(6). qPCR, on the other hand, is used to detect AML-associated genetic abnormalities. It is more sensitive than flow cytometry – in some cases, down to 0.01 percent (4). This measure, however, yields a relative result that must be compared with a standard curve, meaning that AML-associated mutations cannot be quantified in absolute terms. Instead, the accuracy of the result depends on the accuracy of the standard curve (7).
A new hope
At the 2018 American Society of Hematology Annual Meeting, my colleagues at the University of Colorado and I presented data on a highly specific and sensitive new assay for detecting AML-associated mutations in post-transplant bone marrow samples. Our goal? To determine MRD and predict relapse with greater certainty (8). The new assay, based on droplet digital PCR (ddPCR), can detect, track, and quantify cancer-related mutations in the blood down to a 0.01 percent variant allele frequency, which is at least equal in sensitivity to qPCR. In other cases, ddPCR has been shown to reach a sensitivity of 0.001 percent (9).
Why is ddPCR is so sensitive? It partitions a blood or tissue sample into thousands of separate PCR reactions, which renders the method less sensitive to the PCR inhibitors that often plague qPCR, while also eliminating the need for a standard curve (10). To execute a ddPCR reaction, a sample is divided into 20,000 nanoliter-sized droplets, each of which contains no more than a few copies of DNA. The PCR reaction is run to endpoint separately in each droplet, amplifying the template molecules. Importantly, though, only the template molecules that contain the target sequence – for instance, an AML-associated mutation – will be amplified. When this happens, the droplets fluoresce, and we can directly count the number of target sequences in the sample. Finally, the data is analyzed using Poisson statistics to determine the concentration of target DNA in the original sample.
Unlike chimerism testing, a ddPCR-based liquid biopsy directly quantifies the presence of cancer in the bone marrow and indicates if the patient is progressing towards relapse – well before any clinical symptoms or even morphological signs of disease appear.
In our study, we tracked 21 cancer-associated mutations in bone marrow-derived DNA among a cohort of 36 patients (see Figure 1). These mutations appear in 5–20 percent of patients with AML. We examined samples taken during patients’ bone marrow testing, which meant we could quantify mutation levels at one, three, and 12 months. We found that our ddPCR-based liquid biopsy (8) could predict relapse-free survival and overall survival at one month after a BMT (see Figure 2) and, although our sample size was small, we also saw signs that ddPCR might be more sensitive than chimerism testing – a finding that warrants more investigation to confirm.
Although we initially tested our assay on samples from a biobank, we are now examining ddPCR’s ability to monitor relapse in AML patients who are currently on targeted therapies and haven’t received a BMT. We are already seeing some evidence that our ddPCR-based assay can predict relapse before it happens, and we are hoping to publish those results soon.
As ddPCR proves its effectiveness in monitoring AML following BMT, it can potentially begin to serve as an adjunct to chimerism testing. Physicians can order a ddPCR-based liquid biopsy at regular intervals – for instance, once a month – to enable closer monitoring of MRD after BMT. Furthermore, ddPCR’s sensitivity allows physicians to detect signs of relapse earlier, opening the door to more effective treatment options that will hopefully yield better outcomes for patients. Although more research must be done to directly compare ddPCR with chimerism, it’s likely that ddPCR could play a significant role in surveilling patients with AML who have received BMTs, and will give physicians greater confidence in their treatment decisions.
- DA Breems et al., “Prognostic index for adult patients with acute myeloid leukemia in first relapse”, J Clin Oncol, 12, 1969–1878 (2005). PMID: 15632409.
- HC Lee et al., “Mixed T lymphocyte chimerism after allogeneic hematopoietic transplantation is predictive for relapse of acute myeloid leukemia and myelodysplastic syndromes”, Biol Blood Marrow Transplant, 21, 1948–1954 (2015). PMID: 26183077
- E Wong et al., “Prognostic limitations of donor T cell chimerism after myeloablative allogeneic stem cell transplantation for acute myeloid leukemia and myelodysplastic syndromes”, Biol Blood Marrow Transplant, 23, 840–844 (2017). PMID: 28167152
- F Ravandi et al., “Evaluating measurable residual disease in acute myeloid leukemia”, Blood Adv, 2, 1356–1366 (2018). PMID: 29895626.
- G Schuurhuis et al., “Minimal/measurable residual disease in AML: consensus document from ELN MRD Working Party”, Blood, 131, 1275–1291 (2018). PMID: 29330221.
- N Schaap et al., “Long-term follow-up of persisting mixed chimerism after partially T cell-depleted allogeneic stem cell transplantation”, Leukemia, 16, 13–21 (2002). PMID: 11840258.
- SA Bustin and T Nolan., “Pitfalls of quantitative real-time reverse-transcription polymerase chain reaction”, J Biomol Tech, 15, 155–166 (2004). PMID: 15331581.
- A Winters et al., “Tracking of AML-associated mutations via droplet digital PCR is predictive of outcome post-transplant”. Poster presented at the American Society of Hematology Annual Meeting; December 1, 2018; San Diego, USA. Poster #2138.
- CM Hindson et al., “Absolute quantification by droplet digital PCR versus analog real-time PCR”, Nat Methods, 10, 1003–1005 (2013). PMID: 23995387.
- TC Dingle et al., “Tolerance of droplet-digital PCR vs real-time quantitative PCR to inhibitory substances”, Clin Chem, 59, 1670–1672 (2013). PMID: 24003063.