Abstract
Acute Myeloid Leukemia (AML) is a hierarchically organized clonal malignant disorder with leukemia stem cells (LSC) at its apex. LSC have self-renewal activity and generate leukemic progeny, which make up the majority of leukemic cells. LSC can be quiescent and reside in specific niches in the bone marrow, rendering them resistant to conventional chemotherapy approaches. LSC are considered the source of relapse and thus further strategies to eradicate LSC are pivotal to improve patient outcomes of this dismal disease.
LSC present within cell populations can be detected by their capacity to re-initiate the leukemia after xenotransplantation into immune-compromised mice. However, using current methods, it is neither possible to prospectively isolate pure functional LSC nor distinguish them reliably from normal hematopoietic stem cells (HSC). In order to search for novel LSC-specific markers, we applied state-of-the-art proteomics and gene expression profiling by next-generation sequencing (RNA-Seq) to LSC-containing and LSC-free cell fractions from primary AML patient samples. To define functional LSC we FACS-sorted primary patient samples of different AML subtypes according to surface expression of CD34 and CD38 and transplanted each of the resulting four cell populations into conditioned NSG recipients. Thirteen AML samples showed human leukemic engraftment in at least one of the subsets, dissecting LSC-containing and LSC-free subpopulations within the same patient. AML engraftment was mainly observed within the CD34+CD38- fraction, but several cases showed LSC activity also in the CD34+CD38+ fraction or even in the CD34- subsets. As healthy age matched controls, we collected samples of bone marrow from individuals without hematological conditions older than 60 years, who underwent hip replacement surgery. Hematopoietic stem and progenitor cells (HSPC, Lineage-CD34+CD38-) were FACS-sorted and included into the transcriptome and proteome analyses.
Hierarchical clustering of transcriptomic data revealed that the similarity between LSC-containing and LSC-free subpopulations within the same patients was greater than the similarity of LSC and non-LSC fractions across different patients. As expected, AMLs with the same molecular subtype clustered together. Gene Set Enrichment Analysis showed enrichment of known LSC- and other stem cell gene sets in the LSC-containing fractions when compared to non-LSC fractions. Comparison of the expression pattern of LSC-containing fractions with healthy HSPC revealed distinct expression of previously proposed LSC markers including CD47, TIM-3, CD25, CD99, CD97, CD123 and CSF-1R. In addition, our approach allowed us to identify several differentially expressed new cell surface proteins, which may serve as novel marker candidates for AML LSC.
Quantitative proteomic analysis was performed by employing tandem mass tag labeling and high-resolution mass spectrometry. Using this approach, approximately 7,000 proteins were quantified from LSC-containing and LSC-free fractions from several individual AML samples of different subtypes. Importantly, our data include many low abundance proteins or others known to be difficult to detect by mass spectrometry, such as transcription factors and membrane proteins. Statistical analysis revealed a number of candidate proteins distinguishing the LSC-containing and LSC-free fractions.
Data sets derived from the RNA-Seq and proteomics approaches will be presented and both data sets will be bioinformatically integrated towards a comprehensive expression signature of normal and leukemic stem cells.
Disclosures:
No relevant conflicts of interest to declare.
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