The Rocky Road from Cancer Stem Cell Discovery to Diagnostic Applicability
Bibliographic record
Abstract
Acute myeloid leukemia (AML) is the result of malignant transformation of hematopoietic progenitor cells. These altered cells proliferate and lead to the accumulation of AML blasts. Only a minority population of all AML cells are capable of proliferating in vitro and in vivo. This suggests that AML cells are potentially organized in a hierarchy, with only the most primitive of these cells capable of maintaining the leukemic clone. This hypothesis was the basis for identifying the AML initiating cell and the CSC theory that arose from the subsequent studies. As such, CSCs were first identified in AML in 1990's by John Dick's group in Toronto, Canada AML cells that were CD34+CD38-possessed stem cell like characteristics and de novo leukemia repopulating properties in immunocompromised mice While leukemia initiating cells (LSCs) are in the range of 0.00002 to 0.02% of all unsorted mononuclear blood cells, LSCs were in the range of 0.02 to 2% in the CD34+CD38-sorted cells of tested patient samples (sorting resulting in approximate 100-1000 fold enrichment of the CSC population). In further similarity to normal stem cells, CD34+CD38-expression is also a unique identifier for hematopoietic stem cells (HSCs). Since then, other leukemic stem cell (LSC) markers have been identified. In 1997 and Cancer Stem Cells Theories and Practice 336 (CD90) had the CSC phenotype Later that same group added lack of expression of c-kit (CD117) to the list of potential AML CSC markers, as AML cells from patients that were CD34 + c-kit -were enriched for the CSC population In 2000, Jordan et al., identified a cell surface molecule, interleukin-3 receptor alpha chain (CD123) as being uniquely expressed on AML CSCs, but not HSCs Other than the above described cell surface markers used for the isolation of CSCs, "functional markers" have been explored more recently. The functional marker strategy is based on stem cell characteristics, but does not rely on cell surface adhesion molecules for the viable isolation of a specific cell-subset. For example, Stemcell Technologies developed the aldefluor assay for the isolation of live hematopoietic stem cells based on increased expression of a cytoplasmic enzyme, aldehyde dehydrogenase (ALDH) isoform 1A1. ALDH1A1 is one of 19 ALDH isoforms expressed in humans, and it is a critical detoxifying enzyme responsible for oxidizing aldehydes to carboxylic acids While, predominantly expressed in the epithelium of testis, brain, eye, liver, and kidney, ALDH1A1, is also found in high levels in hematopoietic and neural stem cells ALDH1A1 is proposed to play a role in the differentiation of hematopoietic and neural stem cells via the oxidation of retinal to retinoic acid Retinoic acid activates nuclear retinoic acid receptors (RARs) and RARs subsequently regulate the transcription of genes with RAREs (retinoic acid response elements). Furthermore, ALDH1A1 is known to metabolize and detoxify chemotherapeutics like cyclophosphamide Using the aldefluor assay, Cheung et al., were the first to show that it was possible to isolate the LSCs based on the increased ALDH activity The researchers detected a population of ALDH + AML cells in 14 of 43 patient samples. In the remaining 29 samples an ALDH+ population was rare or unidentifiable. The ALDH + AML cells in most cases coexpressed CD34 + (the previously identified marker) and engrafted significantly better than the ALDH -AML cells in immunocompromised mice. As discussed later, ALDH activity would become one of the few markers discovered that has applicability across a wide range of cancers. It can be said that ALDH activity is a universal CSC marker.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 teacher head, 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".