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Record W2912923795 · doi:10.1182/blood-2018-99-119318

Isolation of CD34− and CD34+ Leukemia Stem Cells from Acute Myeloid Leukemia Blasts Using CD200

2018· article· en· W2912923795 on OpenAlexaff
Jenny Ho, Stephanie M. Dobson, Jessica McLeod, Véronique Voisin, Alex Murison, Theodore A. Kennedy, Sasan Zandi, Kolja Eppert, Mark D. Minden, Mathieu Lupien, John E. Dick, Jean Wang

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsMcGill University Health CentreUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsCD34Myeloid leukemiaCD38PopulationBiologyStem cellHaematopoiesisMolecular biologyclone (Java method)LeukemiaMyeloidFlow cytometryImmunologyCancer researchMedicineCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Therapy resistance and relapse in acute myeloid leukemia (AML) are driven by leukemia stem cells (LSCs). Recent evidence highlighting functional and genetic heterogeneity among LSC subclones underscores the importance of capturing the entire LSC compartment in studies of LSC biology. Although LSCs are often enriched in the CD34+CD38- cell fraction, they are frequently detected in other phenotypic fractions, and in some cases are restricted to the CD34- population. In order to discover novel LSC markers, we examined genes differentially expressed between functionally-validated LSC+ and LSC- cell fractions obtained from primary AML samples, and identified CD200 as a candidate cell surface marker for LSCs. CD200 expression in 57 primary AML samples was analyzed by flow cytometry using anti-human CD200 clone 1B9(kindly provided by Trillium Therapeutics Inc.). CD200 was present on a greater proportion of CD45dim blasts compared to more differentiated CD45high non-blast populations (54.4% versus 21.7%, p<0.0001); CD200+ cells often represented a distinct blast population. Overall there was a positive but non-linear correlation (R2=0.46, p<0.0001) between CD34 and CD200 expression; the proportion of CD200+ blasts was significantly greater than that of CD34+ blasts in samples with low to intermediate CD34 expression. In AMLs where CD34 expression was lower than CD200, CD34 was present on a subset of CD200+ blasts; accordingly, CD200+ blasts comprised variable proportions of CD34- and CD34+ cells. These observations suggest that CD200 expression on blasts could be a better marker for LSCs than CD34. To validate CD200 as a LSC marker, leukemic blasts were sorted from 15 primary AML samples based on CD45 and CD200 expression and transplanted into NSG mice. Samples were selected based on either the presence of both CD200+ and CD200- blasts, or CD200 expression on <5% of mononuclear cells (MNCs). In 8 of 15 AMLs, LSCs were enriched within the CD200+ fraction (termed CD200+ LSCs). In 4 of these cases, LSCs comprised both CD34- and CD34+ cells, but the entire LSC compartment was captured within the CD200+ blast population. Limiting dilution studies showed that CD200 expression enriched for CD200+ LSCs by up to 20-fold. In 6 of the remaining samples, LSCs resided in the CD200- fraction (termed CD200- LSCs), while in one sample, LSCs were present in both CD200+ and CD200- fractions. In AMLs with CD200- LSCs, CD200 was expressed on <5% of MNCs and <5% of blasts, in contrast to AMLs with CD200+ LSCs where CD200 expression on MNCs was variable (3% to 85%) and >5% on blasts. Overall, these results indicate that CD200 expression can be used to segregate LSCs from bulk leukemia cells. CD200 expression may be a particularly useful LSC marker in cytogenetically normal AMLs with NPM1 mutation (CN-AMLNPM1c), which have low or negative CD34 expression and commonly possess CD34- LSCs. Among 20 CN-AMLNPM1c samples, the proportion of CD200+ blasts was higher than that of CD34+ blasts irrespective of FLT3-ITD status, although there was a trend towards higher CD200 expression in FLT3-ITD+ samples. In xenotransplantation assays, 7 of 8 CN-AMLNPM1c samples tested contained CD200+ LSCs while the remaining sample contained both CD200+ and CD200- LSCs. Principal component analysis of gene expression profiles demonstrated that functionally-validated CD200+ LSC-containing fractions from CN-AMLNPM1c patients clustered separately from LSC fractions from NPM1wt or cytogenetically-abnormal cases, and were enriched for stem cell genes by gene set enrichment analysis. Furthermore, ATAC-Seq analysis demonstrated greater chromatin accessibility in CD200+ LSC-containing versus CD200‒ LSC-depleted fractions from CN-AMLNPM1c patients, with unique enrichment of HOX motifs. These data validate CD200 as an LSC marker in CN-AMLNPM1c cases. In summary, CD200 is a valuable tool for capturing heterogeneous LSC populations including both CD34+ and CD34- LSCs in many primary AML samples. It will be particularly useful for future studies of LSCs in CN-AMLNPM1c where CD34 expression does not identify LSCs. Disclosures No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.022
GPT teacher head0.278
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations2
Published2018
Admission routes1
Has abstractyes

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