{"doi":"10.1002/ctm2.1311","title":"SCD and MTHFD2 inhibitors for high‐risk acute myeloid leukaemia patients, as suggested by ELN2017‐pathway association","abstract":null,"journal":"Clinical and Translational Medicine","year":2023,"id":632971,"datarank":0.26876392038420827,"base_score":1.791759469228055,"endowment":1.791759469228055,"self_citation_contribution":0.26876392038420827,"citation_network_contribution":0.0,"self_endowment_contribution":0.26876392038420827,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1402125,"name":"Doyeon Kim","orcid":"0009-0003-5716-8664","position":1,"is_corresponding":false},{"id":1179387,"name":"Jiwoo Kim","orcid":"0009-0008-0898-8371","position":2,"is_corresponding":false},{"id":1640926,"name":"Sunghyouk Park","orcid":"0000-0003-1981-3274","position":3,"is_corresponding":false},{"id":1640928,"name":"Arvie Camille V. de Guzman","orcid":"0000-0003-0962-4824","position":4,"is_corresponding":false},{"id":1640922,"name":"Han Sun Kim","orcid":"0009-0007-8229-3933","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"SCD and MTHFD2 inhibitors for high‐risk acute myeloid leukaemia patients, as suggested by ELN2017‐pathway association","abstract":"Dear Editor, The European LeukemiaNet (ELN) 2017 criteria1 is widely accepted as the risk classification of acute myeloid leukaemia (AML) patients. However, their application to studying risk-related biological pathways is limited, failing to enhance treatment options for high-risk patients. Using multiomics databases, biological pathways and genes whose upregulations correlate with increased ELN2017 risks and poorer survival were investigated, followed by experimental and functional validation, exhibiting SCD and MTHFD2 inhibitors as potential therapeutics for treating high-risk AML patients. As shown in Figure 1A, we initially evaluated ELN2017 and its revision2 for prognostic risk categorisation in OHSU patient data.3 Survival prognoses showed significant disparity among risk groups (Figures 1B and S1). Specifically, the ‘Very Adverse’ group exhibited a much poorer prognosis than other groups, consistent with a previous report.2 However, the ‘Very Favourable’ and ‘Favourable’ groups did not reveal significant differences (Table S1). This analysis shows four distinguished survival risk groups existing in OHSU data. We then performed correlational screening between revised ELN2017 risks and pathway scores (FDR < 0.05), resulting in 690 pathways. Further refinement based on disease-specific survival (DSS) criteria (FDR < 0.05, hazard ratio (HR) > 3, and FDR of HR < 0.05) resulted in 34 pathways. These pathways were categorised into three distinct clusters and three unclustered pathways (Figure 1C). The largest cluster (26 pathways) was ‘cell-cycle related’; considering 71.2% (146/205) of the samples were from the initial diagnosis stage, a connection between the proliferative state at diagnosis and patient prognosis is suggested. As relapsed AML cells after chemotherapy exhibit higher dormancy4 and leukaemia stem cells often remain in a quiescent state,5 it will be an interesting future topic to specifically compare the relationship between the prognosis and the cell cycle progression at initial versus late-stage AML. Since the ‘cell-cyclerelated’ cluster already encompasses a standard regimen drug, cytarabine, we focused on other pathways (Figures 2A–D and S2–S4; Table 1). TCGA-LAML J-T test Proteomics J-T test Our correlations were further studied in two other large AML databases (TCGA-LAML6 and proteomics database7) for eight pathways outside the ‘cell-cyclerelated’ cluster. Patients were categorised into four groups using the revised ELN2017 as above. For the proteomics database, we leveraged Gene Set Variation Analysis (GSVA), originally used for transcriptomic data, to generate pathway scores. Combining analyses in all three databases revealed significant relationship between revised ELN2017 risk groups and ‘KEGG_BIOSYNTHESIS_OF_UNSATURATED_FATTY_ACIDS’ (‘UFA_Synthesis’) and ‘REACTOME_METABOLISM_OF_FOLATE_AND_PTERINES’ (‘Folate_Metabolism’) (Table 1). After identifying risk-correlated pathways, we examined targetable genes within those pathways. MTHFD2, a previously reported AML target,8, 9 was investigated for the Folate_Metabolism pathway. MTHFD2 gene expression exhibited a significant increasing trend across ELN2017 risk groups (Figure 2E), and patients with higher gene expression experienced significantly shorter overall survival (Figure 2F). Clinical trials of methotrexate, an antifolate drug, were unsuccessful in AML due to reduced polyglutamylation activity, which is essential for its effectiveness.10 Therefore, alternative drugs targeting this pathway seem necessary. For the UFA_Synthesis pathway, we analysed all 22 genes in the pathway in OHSU, TCGA-LAML, and proteomics databases since little has been known for this pathway (Table S2). ACOT7 (Figure S5) and SCD (Figure 2G and H) emerged as candidates. Among these, SCD exhibited the highest vulnerability upon knockout in AML cells (lowest median dependency score in the Depmap database; Figure S6). Therefore, we selected SCD as our target. Notably, while SCD level was higher in the ‘Normal’ group than in the ‘Favourable’ group, there was a clear and significant upward trend of SCD expression correlating with worse ELN2017 criteria (Figure 2G). This provides rationale for SCD as a target, aligning with our goal of finding targets for high-risk AML patients. With MTHFD2 and SCD bioinformatically suggested as risk-associated genes, we experimentally validated them using five AML (U937, MOLM-14, THP-1, KG-1 and HL-60) and one normal (HCC1954-BL) cell line. CCK-8 assay confirmed MTHFD2 inhibitor DS18561882 exhibited higher potency against all five AML cell lines compared to normal cell line (Figure 3A). SCD inhibitor A939572 also showed ∼8 times higher IC50s for normal cell line (Figure 3B). Trypan blue assay, along with normal peripheral blood mononuclear cells (PBMCs), also demonstrated the two inhibitors’ cancer cell selectivity (Figure S7).Additionally, SCD and MTHFD2 proteins’ expression was higher in AML cell lines than normal PBMCs (Figure S8). However, no significant correlations were observed among AML cell lines (Figure S9). DS18561882 treatment reduced MTHFD2 protein levels (Figure S10A), and A939572 treatment reduced unsaturated fatty acid levels without affecting SCD protein levels (Figure S10B and C), confirming the targeted effects of both drugs on the target proteins. Due to limited references regarding SCD in AML, we further validated its functional relevance. Unsaturated fatty acids (PUFA and UFA) were measured in AML cell lines using nuclear magnetic resonance (NMR). Among the 22 genes, SCD highly correlated with unsaturated fatty acids (Figures 3C and S11; Table S3). Our findings suggest the proposed inhibitors’ selectivity toward AML cells, indicating their potential use for high-risk AML groups. The ‘cell-cyclerelated’ cluster was found significantly correlated with AML-risk groups. Cytarabine, a DNA replication inhibitor and standard-of-care drug for AML, is also used to high-risk AML patients, along with hypomethylating agents and venetoclax regimen. When tested on cell lines, it exhibited a large variation in sensitivity (Figure S12). Combining A939572 or DS18561882 with cytarabine for cells with high cytarabine IC50 (THP-1 and KG-1; Figure S13) resulted in synergistic inhibition of cell survival (Figure 3D–G). In addition, dose reduction of cytarabine was observed in all four combinations (Table S4), suggesting the potential of A939572, DS18561882 or their derivatives in alleviating cytarabine toxicity. Overall, our study identified risk-associated pathways, target genes and potential synergistic drugs with cytarabine in AML through novel bioinformatic analysis on large multiomic datasets. Since not much is known about the roles of unsaturated fatty acids or folate metabolism in AML, our results could be further exploited to find a mechanistic relationship between those pathways and the malignancy of AML. More detailed discussion, including the significant advantage of our approach to finding new target genes/pathways (Table S5) or even in solid tumours, is in the Supplementary Information. HSK, DK and JK established the methodology, obtained the experimental data, performed the formal analysis and reviewed the manuscript. SP and ACVG conceptualised the study, obtained funding, supervised the study and wrote the manuscript. This work was supported by the Basic Science Research Program through the National Research Foundation of Korea grants funded by the Korean government Ministry of Science and ICT (NRF-2018R1A3B1052328 to). The authors declare no potential conflicts of interest. For the original data, please contact [email protected]. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.","is_dataset_classified":null,"base_score":1.791759469228055,"endowment":1.791759469228055,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"37381167","pmcid":"PMC10307990","openalex_id":"https://openalex.org/W4382501426","authors":[],"funders":[{"funder_name":"National Research Foundation of Korea","grant_id":"NRF‐2018R1A3B1052328","title":null}],"total_grants":1,"fwci":0.9182,"citation_percentile":0.74448841,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":1},{"year":2025,"count":1},{"year":2026,"count":2}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ctm2.1311","host_type":"journal"},{"url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ctm2.1311","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/ctm2.1311","host_type":"publisher"},{"url":"https://doi.org/10.1002/ctm2.1311","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/37381167","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10307990","host_type":"repository"},{"url":"https://doaj.org/article/cd99b2717b584580ace5eb7d6677a706","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10307990/pdf/CTM2-13-e1311.pdf","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC10307990","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC10307990?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Acute Myeloid Leukemia Research","Myeloproliferative Neoplasms: Diagnosis and Treatment","Protein Degradation and Inhibitors","Humans","Leukemia, Myeloid, Acute"],"mesh_terms":["Humans","Leukemia, Myeloid, Acute"],"keywords":["Medicine","Myeloid leukaemia","Association (psychology)","Chronic myeloid leukaemia","Myeloid","Oncology","Internal medicine","Psychology"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"No poverty"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T10:40:03.012824Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}