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Identification and Characterization of Human Leukemia Stem Cell Functional Regulators

2011· article· en· W2529749106 on OpenAlexaff
Kolja Eppert, Karin G. Hermans, John E. Dick

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsOntario Institute for Cancer ResearchUniversity Health Network
Fundersnot available
KeywordsStem cellBiologyHaematopoiesisCancer stem cellLeukemiaHematopoietic stem cellCord bloodCancer researchGene signatureMyeloid leukemiaImmunologyCell biologyGeneGene expressionGenetics

Abstract

fetched live from OpenAlex

Abstract Abstract 2955 Emerging evidence shows that many cancers are organized as cellular hierarchies sustained by a subpopulation of cancer stem cells (CSC). It is thought that CSC properties influence therapy response, disease relapse, and overall survival. However, little is currently known about the molecular pathways that control stem cell behaviour. Our goal is to identify and characterize the molecular regulatory networks that govern the self-renewal and developmental program of human leukemia stem cells (LSC). To expand our understanding of LSC function, we selected genes from our previously established LSC transcriptional program as novel candidate regulators of stem cell function. The LSC transcriptional program was identified by fractionation of 16 primary human acute myeloid leukemia (AML) samples into four populations that were subjected to sensitive in vivo LSC assays. mRNA expression analysis was performed on each fraction and a global LSC-specific signature was determined from functionally defined LSC fractions. Using similar methodology, a hematopoietic stem cell (HSC) enriched gene signature was established from human cord blood. Bioinformatic analysis identified a core transcriptional program that LSCs and HSCs share, revealing the molecular machinery that underlies stemness properties. The LSC and HSC signatures have prognostic significance independent of other factors when validated on a large cohort of cytogenetically normal AML patients. We have begun experiments to determine the role of 17 candidate stem cell regulators using functional in vivo and in vitro assays. We first examined the effect of candidate gene overexpression in normal HSC using xenograft assays. Lineage negative cord blood cells were transduced with lentiviral overexpression vectors, injected into immune-deficient mice and engraftment of human cells was measured after 12 weeks. In the preliminary round of in vivo analysis, over-expression of GPR56 increased the engraftment capability of HSCs in immune-deficient recipients compared to control (p=0.0019). GPR56 is involved in cell adhesion and differentiation and evidence is accumulating for a role in various cancers such as melanoma, esophageal cancer, and glioma. By qPCR analysis we observed that GPR56 mRNA is more highly expressed in both LSC-enriched and primitive normal hematopoietic cell populations, including highly purified HSC, compared to more mature cell populations such as AML blasts and normal lineage committed progenitor cells. In conclusion, our LSC and HSC data established that determinants of stemness influence clinical outcome of AML patients. We have identified multiple novel candidate stem cell-related genes and provided evidence for a role for GPR56 in hematopoietic stem cell regulation. 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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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.

Opus teacher head0.029
GPT teacher head0.247
Teacher spread0.218 · 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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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