Targeting MTHFD2 in Acute Myeloid Leukemia
Bibliographic record
Abstract
Abstract Alterations in differentiation pathways contribute to the development of acute myeloid leukemia (AML). Differentiation therapy with all-trans retinoic acid (ATRA) has dramatically altered the treatment of acute promyelocytic leukemia, transforming it from a nearly fatal disease to a curable one. We set out to identify cellular pathways that contribute to AML differentiation, with the goal of identifying new therapeutic targets. We analyzed gene expression data from AML cell lines treated with phorbol 12-myristate 13-acetate (PMA), ATRA, Vitamin D, the BET inhibitor JQ1 and the DOT1L inhibitor EPZ00477, treatments known to induce AML differentiation and impair growth. Folate-mediated one-carbon metabolism was one of only three metabolic pathways altered by these compounds, with expression of MTHFD2 consistently downregulated with each compound. MTHFD2 is an NAD-dependent, bi-functional mitochondrial methylenetetrahydrofolate dehydrogenase and cyclohydrolase. It is differentially expressed in embryonic and transformed tissues and is upregulated in myeloid progenitors. MTHFD2 is the most differentially expressed metabolic enzyme in cancer cells versus normal cells, including normal proliferating cells. We thus investigated the role of MTHFD2 in myeloid malignancy. First, we demonstrated using ChIP-qPCR, MYC knockdown and MYC inhibition with a BET inhibitor, that MYC directly regulates MTHFD2 expression in AML. Knockdown of MTHFD2 with two shRNAs confirmed to have on-target activity, induced myeloid differentiation in AML cell lines, as measured by Cd11b expression, morphologic changes and induction of a previously validated AML differentiation gene expression signature. MTHFD2 knockdown decreased cell growth in AML cell lines, as well as decreased colony formation in methylcellulose in both AML cell lines and primary patient blasts. AML cells transduced with these two MTHFD2-directed shRNAs demonstrated attenuated growth in an orthotopic mouse model of AML. Furthermore, three MTHFD2-directed shRNAs prolonged survival in an MLL-AF9 mouse leukemia model. Additionally, using a doxycycline inducible shRNA system, we demonstrated that two miR30-shRNAs directed against MTHFD2 decreased AML burden in mice with established disease and prolonged survival. To identify biomarkers of response to MTHFD2 suppression, we used single sample Gene Set Enrichment Analysis (ssGSEA) to identify primary patient AML samples enriched for gene expression signatures of folate-mediated one-carbon metabolism and MTHFD2. We found in both independent data sets that the cluster of patients enriched for expression of the one-carbon folate pathway gene signatures was also enriched for patients with FLT3-ITD mutations, a subset of AML with a particularly poor prognosis. In addition, in an shRNA screen targeting 11,194 genes and performed in 216 cancer cell lines, including 17 AML lines, FLT3-ITD was a biomarker of response to MTHFD2 knockdown. We next validated that while MTHFD2 suppression induced measureable differentiation in all six AML cell lines examined, it induced the most robust induction of apoptosis in FLT3-ITD mutant AML. The mitochondrial one-carbon folate pathway is thought to contribute to cellular oxidative balance by providing reducing power in the form of NAD(P)H, and suppression of MTHFD2 was previously shown to increase ROS levels. Indeed, suppression of MTHFD2 led to a marked increase in ROS in the FLT3-ITD positive AML cell lines in which apoptosis was induced. In summary, a decrement in MTHFD2 expression was found at the center of multiple AML perturbations that impair AML growth and induce differentiation. Our data support MTHFD2 as an AML dependency and FLT3-ITD as a potential biomarker of response. We thus provide critical preclinical evidence for targeting of MTHFD2 as a therapeutic strategy in AML. Disclosures Stone: Celgene: Consultancy; Merck: Consultancy. DeAngelo:Celgene: Consultancy; Pfizer: Consultancy; Incyte: Consultancy; Agios: Consultancy; Novartis: Consultancy; Ariad: Consultancy; Bristol Myers Squibb: Consultancy; Amgen: Consultancy. Stegmaier:Novartis Pharmaceuticals: Consultancy.
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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 | 0.000 |
| 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".