Enforced Expression Of Mir-125b Promotes the in vivo expansion Of Human Linneg cord Blood Multi-Lymphoid Progenitors and Leukemia Stem Cells
Bibliographic record
Abstract
Abstract Acute Myeloid Leukemia (AML) is a heterogeneous disease with a relapse rate of up to 80% depending on patient age and AML subtype. AML is organized as a functional cellular hierarchy and is sustained by a rare population of leukemia stem cells (LSC). Recent work suggests that LSC properties influence therapy response, overall survival, and disease relapse. In order to develop more effective novel therapies that target this rare cell population; it is imperative that we better understand LSCs at the molecular level. Although it is generally accepted that oncogenic mutations underlie cancer initiation and progression, most studies have focused on protein coding genes. However, there is increasing recognition that non-coding RNAs can also play a role in leukemogenesis. microRNAs (miRNA) are a family of small non-coding RNAs that function as important regulators of mRNA stability and translation of protein-coding genes with significant roles in maintenance of human hematopoietic stem cells (HSC) (Lechman et. al., Cell Stem Cell, 2012). To understand the functional role of miRNA in human hematopoiesis, we generated HSC- and leukemia stem cell (LSC)-specific microRNA (miRNA) profiles by microarray analysis of sorted cell fractions from umbilical cord blood (CB) and AML patient samples that have been validated in xenograft assays. We identified ten miRNA candidates over-represented in HSC and/or LSC. To determine whether these were functional and impacted on stem cell properties we transduced lineage depleted CB cells with lentivirus expressing either a candidate miRNA or control vector followed by transplantation into immune deficient mice. Three miRNAs (miR-125b, miR-130a, miR-155) conferred a competitive growth advantage while four miRNAs (miR-99a, miR133a, miR194, miR-196b) conferred a growth disadvantage. miR-125b, a top LSC array candidate, showed the most pronounced phenotype with an overt expansion of transduced cells (19% to 96.2%) and enlarged spleens (2.4 fold increase). Detailed flow cytometric analysis of the miR-125b human grafts in recipient mice revealed a greatly expanded proportion of multi-lymphoid progenitors (MLP), in comparison to HSC and multi-potent progenitors. Furthermore, upon enforced in vivo expression of miR-125b in three AML patient samples, we observed large increases in the primitive primitive CD34+CD117+ populations (CD34+: 2.4-4.6 fold increase; CD117+: 1.3-4.1 fold increase) and a decrease in the proportion of differentiated CD14+/CD15+ cells (CD14+: 6.2-7.6 fold decrease; CD15+: 1.2-6 fold decrease) in leukemic grafts. Limiting dilution assays into secondary recipients revealed up to a 34-fold increase in LSC frequency compared to control vector transduced AML cells. Overall, these data suggest that miR-125b normally functions in the limited self-renewal of lymphoid committed early progenitors and this function may be usurped during leukemogenesis to enhance LSC self-renewal. miR-125b belongs to an evolutionarily conserved family consisting of three paralogs (miR-125a; miR-125b1; miR-125b2). Recent studies present strong evidence for a role of the miR-125 family in normal and malignant murine hematopoiesis, yet comprehensive functional inconsistencies remain in regards to the precise roles for each paralog. We are currently carrying out additional enforced expression studies directly comparing these family members in vitro and in vivo in order to clarify the functional roles of miR-125a (a top HSC array candidate) and miR-125b (a top LSC array candidate) in both normal and malignant human hematopoiesis. These studies will determine whether the miR-125 family is a suitable target for therapy of hematological malignancies. 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".