Microrna Expression Profiling in Acute Myelogenous Leukemia.
Bibliographic record
Abstract
Abstract Acute myelogenous leukemia (AML) arises due to changes in gene expression that block or alter the normal differentiation program of hematopoietic stem cells. A variety of mutations in protein-encoding genes have been shown to contribute to the development of leukemia. Recently a new class of genes called microRNAs (miRNAs) have been identified. miRNAs are a subgroup of highly conserved, non-coding RNAs found only in eukaryotes. They do not encode proteins, and appear to have a significant effect on the proteome of a cell. Their conservation between species suggests their involvement in important biological functions, and in fact been shown to be involved in hematopoietic differentiation. While the function of most miRNAs is still unknown, it is believed that they regulate expression of target mRNAs by using the siRNA machinery either to promote degradation of the mRNA or to block its translation. To begin to understand the role of miRNAs in AML, we used Quantitative Polymerase Chain Reaction (QPCR) to measure the expression level of 20 miRNA precursors in the pro erythroid cell line K562, the pro-myelocytic cell line NB4, the myelomococytic cell line OCI/AML2, AML patients’ blasts and in normal bone marrow (NBM). The investigated miRNAs included some that are known to be specific for hematopoietic tissues or involved in hematopoietic differentiation, as well as all the miRNAs in chromosome 7, a hot spot for gene deletion in AML. Our findings indicate that miRNAs are differentially expressed in patients and cell lines when compared among themselves and against normal bone marrow. For example pre-miR-142 was expressed in NBM and K562 but was found to be elevated in OCI/AML2, NB4 and in all patient samples. Pre-miR-20 was found to be overexpressed in only a subset of patients. Other miRNAs like pre-miR-335 and pre-miR-148a were expressed in NBM and in some patients and not in the cell lines. In an effort to identify possible regulators of miRNA expression, we analyzed the upstream region of pre-miR-142 and found an LMO2 binding site. In AML, the LMO2 gene can be overexpressed relative to normal bone marrow and healthy lymphocytes. This transcription factor is involved in the regulation of genes important in the development of blood cells. To investigate if LMO2 could be involved in the regulation of miR-142 expression, we performed chromatin immunoprecipitation (ChIP) from K562 using an anti-LMO2 antibody. Only the LMO2 immunoprecipitation, and not those from the pre-immune control, were enriched in promoter DNA for pre-miR-142. This is consistent with the observation that miRNAs and coding RNAs can be regulated by the same environmental signals. Based on this observation we propose that oncogenes regulate in part the phenotype and biological behaviour of leukemia by affecting the expression of miRNAs. This further suggests that different forms of leukemia may be recognized based upon the spectrum of miRNAs they express.
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 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) | 0.001 | 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".