Expansion of Primary Human AML by Aryl Hydrocarbon Receptor Antagonism Minimally Affects Leukemic Transcriptional Profiles but Alters Cellular Metabolism
Bibliographic record
Abstract
Small molecule-based antagonism of the aryl hydrocarbon receptor (AHR) by StemRegenin1 (SR1) promotes ex vivo expansion and maintenance of primary human hematopoietic stem cells (HSCs) as well as acute myeloid leukemia (AML) cells. However, basis and nature of SR1 induced expansion of human AML remains unknown. Here, global expression profiling on 7 clinically diverse human AML patient samples treated ex vivo with a synthesized analog of SR1 (aSR1) uncovered that only as few as 750 genes were differentially regulated. Uniquely, aSR1 treatment did not modulate self-renewal associated pathways including Hedgehog, Notch or Wnt across patient samples, but instead resulted in overall upregulation of the oxidative phosphorylation metabolic pathway. Higher oxygen consumption rates, along with increased sensitivity to the chemotherapeutic agent cytarabine (AraC) validated that aSR1-induced transcriptional profiles lead to functional enhancement of oxidative phosphorylation. Our study reveals that aSR1 induces minor alterations to the leukemic transcriptional profile leading to a shift in cellular metabolism. This finding should further instruct use of SR1-mediated expansion for mechanistic studies of leukemic self-renewal and the development of drug screening platforms using patient specific AML samples.
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 | 0.000 | 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 | 0.000 |
| 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 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".