Role of minimal residual disease in the management of acute myeloid leukemia-a case-based discussion

Ultrasensitive quantitation of FLT3-ITD mutation in patients with acute myeloid leukemia using ddPCR

BACKGROUND

FLT3-ITD mutations occur in 45-50% of cytogenetically normal AML patients. Conventional fragment analysis using capillary electrophoresis is routinely used to quantitate FLT3-ITD mutations. Fragment analysis however has limited sensitivity.

METHODS AND RESULTS

Here, FLT3-ITD was quantified in AML patients using an in-house developed ultra-sensitive droplet digital polymerase chain reaction assay (ddPCR). The allelic ratio of FLT3-ITD was also absolutely measured by both Fragment analysis and ddPCR. The sensitivity of ddPCR in quantitation of FLT3-ITD mutation was superior to Fragment analysis.

CONCLUSION

This study demonstrates the feasibility of using the described in-house ddPCR method to quantify the FLT3-ITD mutation and measure FLT3-ITD AR in AML patients.

Current and Emerging Techniques for Diagnosis and MRD Detection in AML: A Comprehensive Narrative Review

Acute myeloid leukemia (AML) comprises a group of hematologic neoplasms characterized by abnormal differentiation and proliferation of myeloid progenitor cells. AML is associated with poor outcome due to the lack of efficient therapies and early diagnostic tools. The current gold standard diagnostic tools are based on bone marrow biopsy. These biopsies, apart from being very invasive, painful, and costly, have low sensitivity. Despite the progress uncovering the molecular pathogenesis of AML, the development of novel detection strategies is still poorly explored. This is particularly important for patients that check the criteria for complete remission after treatment, since they can relapse through the persistence of some leukemic stem cells. This condition, recently named as measurable residual disease (MRD), has severe consequences for disease progression. Hence, an early and accurate diagnosis of MRD would allow an appropriate therapy to be tailored, improving a patient's prognosis. Many novel techniques with high potential in disease prevention and early detection are being explored. Among them, microfluidics has flourished in recent years due to its ability at processing complex samples as well as its demonstrated capacity to isolate rare cells from biological fluids. In parallel, surface-enhanced Raman scattering (SERS) spectroscopy has shown outstanding sensitivity and capability for multiplex quantitative detection of disease biomarkers. Together, these technologies can allow early and cost-effective disease detection as well as contribute to monitoring the efficiency of treatments. In this review, we aim to provide a comprehensive overview of AML disease, the conventional techniques currently used for its diagnosis, classification (recently updated in September 2022), and treatment selection, and we also aim to present how novel technologies can be applied to improve the detection and monitoring of MRD.

Eradication of Measurable Residual Disease in AML: A Challenging Clinical Goal

In non-promyelocytic (non-M3) AML measurable residual disease (MRD) detected by multi-parameter flow cytometry and molecular technologies, which are guided by Consensus-based guidelines and discover very low leukemic cell numbers far below the 5% threshold of morphological assessment, has emerged as the most relevant predictor of clinical outcome. Currently, it is well-established that MRD positivity after standard induction and consolidation chemotherapy, as well as during the period preceding an allogeneic hematopoietic stem cell transplant (allo-HSCT), portends to a significantly inferior relapse-free survival (RFS) and overall survival (OS). In addition, it has become absolutely clear that conversion from an MRD-positive to an MRD-negative state provides a favorable clinical outcome similar to that associated with early MRD negativity. Thus, the complete eradication of MRD, i.e., the clearance of the few leukemic stem cells-which, due to their chemo-radiotherapy resistance, might eventually be responsible of disease recurrence-has become an un-met clinical need in AML. Nowadays, this goal might potentially be achieved thanks to the development of novel innovative treatment strategies, including those targeting driver mutations, apoptosis, methylation patterns and leukemic proteins. The aim of this review is to analyze these strategies and to suggest any potential combination able to induce MRD negativity in the pre- and post-HSCT period.

Expression level of ACOT7 influences the prognosis in acute myeloid leukemia patients

BACKGROUND

ACOT plays an important role in lipid metabolism and recent studies found that ACOT participates in some kinds of tumorigenesis. However, both the role of ACOT and its significance have not been revealed in AML. Therefore, we conduct this study in order to investigate the association between AML and ACOT, and hopefully contributed to the management of AML.

METHODS

One hundred and fifty-six AML patients were enrolled in our study whose data were derived from the Cancer Genome Atlas database. There were 85 patients who received only chemotherapy and other 71 patients underwent allo-HSCT.

RESULTS

Patients in high ACOT7 group had a significant lower EFS and OS, while patients in high versus low expression levels of other types of ACOT showed no significant difference on the outcome. High level of ACOT7 related with poor outcome in both chemotherapy-only group and HSCT group.

CONCLUSIONS

High expression level of ACOT7 indicates unfavorable outcome in AML patients. Allo-HSCT could not overcome the unfavorable effect of ACOT7 in these patients.

Quality of Response in Acute Myeloid Leukemia: The Role of Minimal Residual Disease

In the acute myeloid leukemia (AML) setting, research has extensively investigated the existence and relevance of molecular biomarkers, in order to better tailor therapy with newly developed agents and hence improve outcomes and/or save the patient from poorly effective therapies. In particular, in patients with AML, residual disease after therapy does reflect the sum of the contributions of all factors associated with diagnosis and post-diagnosis resistance. The evaluation of minimal/measurable residual disease (MRD) can be considered as a key tool to guide patient’s management and a promising endpoint for clinical trials. In this narrative review, we discuss MRD evaluation as biomarker for tailored therapy in AML patients; we briefly report current evidence on the use of MRD in clinical practice, and comment on the potential ability of MRD in the assessment of the efficacy of new molecules.

MRD in AML: The Role of New Techniques

In the context of precision medicine, assessment of minimal residual disease (MRD) has been used in acute myeloid leukemia (AML) to direct individual treatment programs, including allogeneic stem cell transplantation in patients at high-risk of relapse. One of the limits of this approach has been in the past the paucity of AML markers suitable for MRD assessment. Recently, the number of biomarkers has increased, due to the identification of highly specific leukemia-associated immunophenotypes by multicolor flow-cytometry, and of rare mutated gene sequences by digital droplet PCR, or next-generation sequencing (NGS). In addition, NGS allowed unraveling of clonal heterogeneity, present in AML at initial diagnosis or developing during treatment, which influences reliability of specific biomarkers, that may be unstable during the disease course. The technological advances have increased the application of MRD-based strategies to a significantly higher number of AML patients, and the information deriving from MRD assessment has been used to design individual post-remission protocols and pre-emptive treatments in patients with sub-clinical relapse. This led to the definition of MRD-negative complete remission as outcome definition in the recently published European Leukemianet MRD guidelines. In this review, we summarized the principles of modern technologies and their clinical applications for MRD detection in AML patients, according to the specific leukemic markers.

Minimal/Measurable Residual Disease Monitoring in NPM1-Mutated Acute Myeloid Leukemia: A Clinical Viewpoint and Perspectives

Acute myeloid leukemia (AML) with NPM1 gene mutations is currently recognized as a distinct entity, due to its unique biological and clinical features. We summarize here the results of published studies investigating the clinical application of minimal/measurable residual disease (MRD) in patients with NPM1-mutated AML, receiving either intensive chemotherapy or hematopoietic stem cell transplantation. Several clinical trials have so far demonstrated a significant independent prognostic impact of molecular MRD monitoring in NPM1-mutated AML and, accordingly, the Consensus Document from the European Leukemia Net MRD Working Party has recently recommended that NPM1-mutated AML patients have MRD assessment at informative clinical timepoints during treatment and follow-up. However, several controversies remain, mainly with regard to the most clinically significant timepoints and the MRD thresholds to be considered, but also with respect to the optimal source to be analyzed, namely bone marrow or peripheral blood samples, and the correlation of MRD with other known prognostic indicators. Moreover, we discuss potential advantages, as well as drawbacks, of newer molecular technologies such as digital droplet PCR and next-generation sequencing in comparison to conventional RQ-PCR to quantify NPM1-mutated MRD. In conclusion, further prospective clinical trials are warranted to standardize MRD monitoring strategies and to optimize MRD-guided therapeutic interventions in NPM1-mutated AML patients.

Clinically validated machine learning algorithm for detecting residual diseases with multicolor flow cytometry analysis in acute myeloid leukemia and myelodysplastic syndrome

Background

Multicolor flow cytometry (MFC) analysis is widely used to identify minimal residual disease (MRD) after treatment for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). However, current manual interpretation suffers from drawbacks of time consuming and interpreter idiosyncrasy. Artificial intelligence (AI), with the expertise in assisting repetitive or complex analysis, represents a potential solution for these drawbacks.

Methods

From 2009 to 2016, 5333 MFC data from 1742 AML or MDS patients were collected. The 287 MFC data at post-induction were selected as the outcome set for clinical outcome validation. The rest were 4:1 randomized into the training set (n = 4039) and the validation set (n = 1007). AI algorithm learned a multi-dimensional MFC phenotype from the training set and input it to support vector machine (SVM) classifier after Gaussian mixture model (GMM) modeling, and the performance was evaluated in The validation set.

Findings

Promising accuracies (84·6% to 92·4%) and AUCs (0·921–0·950) were achieved by the developed algorithms. Interestingly, the algorithm from even one testing tube achieved similar performance. The clinical significance was validated in the outcome set, and normal MFC interpreted by the AI predicted better progression-free survival (10·9 vs 4·9 months, p < 0·0001) and overall survival (13·6 vs 6·5 months, p < 0·0001) for AML.

Interpretation

Through large-scaled clinical validation, we showed that AI algorithms can produce efficient and clinically-relevant MFC analysis. This approach also possesses a great advantage of the ability to integrate other clinical tests.

Fund

This work was supported by the Ministry of Science and Technology (107-2634-F-007-006 and 103–2314-B-002-185-MY2) of Taiwan.