Session: 803. Emerging Tools, Techniques, and Artificial Intelligence in Hematology: Poster III
Hematology Disease Topics & Pathways:
AML, Acute Myeloid Malignancies, Research, Translational Research, Diseases, Emerging technologies, Myeloid Malignancies, Technology and Procedures, Measurable Residual Disease , Molecular testing, Omics technologies
Whole exome sequencing (WES) of sorted leukemic cells of bone marrow (BM) samples collected from 26 children with AML at diagnosis was used to identify leukemia-specific mutations. For UDS tracking, we selected 1-2 clonal mutations (present in all leukemic cells) in any gene, and 1-2 subclonal mutations in cancer-associated genes. BM samples (n=96) from day 22, before start of second induction and first consolidation courses from 24/26 patients were assessed with patient-tailored UDS. In total, 68 mutations were assessed. Results of all samples were compared to parallel MRD analyses with 8 color MFC with a limit of detection of 0.1% cells, and when applicable RT-qPCR (8/24 patients). Single cell multi-omics analysis was performed on 15 BM samples from 7/24 patients at diagnosis and the same follow-up time-points using the Tapestri platform. The analysis included 45 primer-barcoded antibodies for cell surface protein and customized mutation-specific primers for DNA, enabling detection of mutations and copy number aberrations, followed by sequencing.
In the diagnostic samples, WES identified 1-16 leukemia-specific mutations/case (median 9 mutations). Samples during treatment were assessed with UDS and compared to MFC results. Interestingly, 51 of 96 analyzed samples (53.1%) were positive for at least one mutation with UDS but negative with MFC, 35/96 samples (36.5%) were positive with both methods, and 10/96 samples (10.4%) were negative with both methods. In the 8 patients that were also assessed with RT-qPCR, UDS and RT-qPCR showed similar performance. Thus, UDS was more sensitive than MFC, and importantly, leukemia-specific mutations were detectable before first consolidation course in patients that eventually relapsed, but also in some patients not experiencing relapse. To clarify this observation, we aimed to identify the origin of residual mutated cells using single cell multi-omics. First, a non-leukemic BM sample was used to verify single cell protein expression signatures by performing MFC in parallel. Using 42 protein markers and 957 single cells, UMAP clustering identified 16 human BM cell types. Overall, there was a good consistency between single cell analysis and MFC, with slightly higher abundance of mononuclear cell types, e.g. progenitors and lymphocytes, with single cell analysis. Next, we analyzed 15 AML samples with single cell multi-omics. At diagnosis, we could characterize leukemic clones, with good concordance with findings from WES. The detected patterns were patient-specific, and in addition to subclonality also revealed the presence of founding clone in stem/progenitor cells. In follow-up samples, single cell multi-omics provided detection of MRD on a single cell level. Single cell results confirmed findings with UDS in the respective children. Furthermore, they revealed the genomic and phenotypic characterization of residual leukemic cells, which in some cases represented the founding clone in progenitors, and in some cases represented leukemic clone in mature cells.
In conclusion, targeted UDS can enable a more sensitive detection of MRD than MFC and is applicable to most children with AML. Residual mutated cells during treatment can be stem/progenitor cells representing the founder clone, or mature cells originating from the leukemic clone. Further studies are needed to address the prognostic value of highly sensitive molecular MRD in childhood AML.
Disclosures: Molnar: Roche Diagnostics: Current Employment.