CD200 Is a Marker of LSC Activity in Acute Myeloid Leukemia
Bibliographic record
Abstract
Abstract Acute myeloid leukemia (AML) is a hierarchical disease in which the bulk blast population is sustained by a minority population of leukemia stem cells (LSC). Evidence of functional heterogeneity in the LSC compartment, including variable responses to chemotherapy, underscores the importance of examining the entire stem cell compartment in studies of LSC biology. However, there are currently no phenotypic markers that can consistently segregate LSCs within the leukemic blast population. Although LSC activity is most often enriched in the CD34+CD38- cell fraction, LSCs are also frequently detected in other phenotypic fractions, and in some cases are absent from CD34+ fractions. Thus, LSC studies that focus only on CD34+CD38- blasts may miss biologically important clones that are present in other phenotypic cell fractions. To identify novel markers that will enable better enrichment of LSC activity, we examined gene expression data obtained from functionally validated LSC+ and LSC- cell fractions sorted from primary AML samples, and identified CD200 as a candidate cell surface marker for LSCs. In normal adult bone marrow and cord blood samples, CD200 is expressed on >95% of CD34+CD38- cells, and expression decreases on CD34+38+ cells, suggesting that CD200, similar to CD34, is a stem cell marker. Flow cytometric analysis of AML patient samples (n=57) demonstrated that CD200 expression was present on a greater proportion of CD45dim blasts compared to CD45high non-blast populations (69.2% vs 4.5%, p<0.0001) and was significantly higher on CD34+ compared to CD34- cells (RFI 51.7 vs 3.5, p<0.0001). Although CD200 expression correlated with CD34 expression in many cases, some samples with low to no CD34 expression had high CD200 expression on CD45dim blasts, suggesting that CD200 can be used to identify CD34- LSCs. To test whether CD200 can segregate LSC activity within the CD45dim blast population, we sorted 14 primary AML samples into cell fractions based on CD45 and CD200 expression followed by transplantation into cohorts of NSG mice. AML samples were prescreened for leukemic engraftment ability and were selected for sorting if: 1) CD45dim blasts comprised both CD200+ and CD200- cells or 2) the CD200+ fraction was <5% of bulk cells. In 7 of 14 patients, LSC activity was enriched within the CD200+ fraction (CD200+ LSCs). For example, in AML40, in which CD200+ cells constituted only 5% of the bulk, as few as 5000 CD200+ blasts generated a leukemic graft at a mean level of 20.6%, whereas up to 500,000 CD200- blasts generated no graft. Importantly, LSC activity in these samples could not be segregated by CD34/CD38 expression; in contrast, the CD200+ fraction encompassed all cell fractions with LSC activity regardless of CD34/CD38 phenotype. In 1 of 14 patients, LSC activity was present in both the CD200+ and CD200- fractions. In the remaining 6 patients, LSC activity was enriched in the CD200- fraction (CD200- LSCs). In these samples, <3% of the bulk population expressed CD200; in 5 of the 6 samples, CD200+ cells generated multi-lineage (CD19+ B plus CD19‒CD33+ myeloid) rather than leukemic grafts, consistent with the presence of pre-leukemic-HSCs (preL-HSCs) in this cell fraction. In 2 additional AML patient samples that generated multi-lineage rather than leukemic grafts following transplantation of bulk cells, we refined our sorting strategy and were able to separate CD200+ LSCs from CD200+ preL-HSCs as evidenced by mutational analysis of xenografts. High CD200 expression was significantly associated with shorter overall survival in univariate analysis in multiple independent AML cohorts, but was not significant in multivariate analysis due to association with NPM1 mutation. NPM1-mutated samples exhibited low CD200 expression on the bulk cells. Interestingly, 7 of the 9 AML patients with CD200+ LSCs had normal karyotype and NPM1 mutation. Our results demonstrate that a CD200-based sorting strategy can successfully enrich and/or segregate LSC activity, and separate LSCs from preL-HSCs in primary AML patient samples. This will now enable direct functional studies of the biological properties of these related but distinct stem cell populations. Furthermore, CD200 will be a valuable tool for the study of LSCs in the subset of NPM1-mutated AML. Disclosures No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".