Mutations in IDH genes occur frequently in acute myeloid leukemia (AML) and other human cancers to generate the oncometabolite R-2HG. Allosteric inhibition of mutant IDH suppresses R-2HG production in a subset of patients with AML; however, acquired resistance emerges as a new challenge, and the underlying mechanisms remain incompletely understood. Here we establish isogenic leukemia cells containing common IDH oncogenic mutations by CRISPR base editing. By mutational scanning of IDH single amino acid variants in base-edited cells, we describe a repertoire of IDH second-site mutations responsible for therapy resistance through disabling uncompetitive enzyme inhibition. Recurrent mutations at NADPH binding sites within IDH heterodimers act in cis or trans to prevent the formation of stable enzyme–inhibitor complexes, restore R-2HG production in the presence of inhibitors, and drive therapy resistance in IDH-mutant AML cells and patients. We therefore uncover a new class of pathogenic mutations and mechanisms for acquired resistance to targeted cancer therapies. Significance: Comprehensive scanning of IDH single amino acid variants in base-edited leukemia cells uncovers recurrent mutations conferring resistance to IDH inhibition through disabling NADPH-dependent uncompetitive inhibition. Together with targeted sequencing, structural, and functional studies, we identify a new class of pathogenic mutations and mechanisms for acquired resistance to IDH-targeting cancer therapies. This article is highlighted in the In This Issue feature, p. 1

Single-nucleotide variants account for about half of known pathogenic genetic variants in human. Genome editing strategies by reversing pathogenic point mutations with minimum side effects have great therapeutic potential and are now being actively pursued. The emerge of precise and efficient genome editing strategies such as base editing and prime editing provide powerful tools for nucleotide conversion without inducing double-stranded DNA breaks (DSBs), which have shown great potential for curing genetic disorders. A diverse toolkit of base editors has been developed to improve the editing efficiency and accuracy in different context of application. Here, we summarized the evolving of base editors (BEs), their limitations and future perspective of base editing-based therapeutic strategies.

Acute Myeloid Leukemia (AML) is a highly heterogeneous malignant hematologic cancer with poor clinical outcome. The presence of leukemia stem cells (LSC) is a significant factor contributing to the failure of AML treatments and frequent relapses. The quiescent and plastic nature of LSC decreases cell death under conventional chemotherapy. Programmed cell death (PCD) plays a critical role in the development and progression of various cancers including AML. We hypothesized that the expression of PCD gene in LSCs may predict the therapeutic outcome of AML patients in the clinic. In this study, we comprehensively analyzed the expression of PCD gene and identified the unique expression patterns of cell death genes of LSC. By integrating PCD- and LSC-related genes, we identified eight LSC death genes with prognostic values: OAZ1, S100A4, MPG, IL2RA, MMRN1, CDK6, HOXA9, and XIRP2. Based on these genes, we developed a leukemia stem cell prognostic death score (LSCD) and a prognostic nomogram. Our findings revealed that LSC, particularly Quiescent LSPC, exhibits a high LSCD score. AML patients with high LSCD score group showed characteristics of significant immune dysfunction and worse prognosis. Additionally, predictions regarding FDA-approved drugs indicated that the high LSCD score group is less sensitive to Venetoclax but more sensitive to Crenolanib, Tandutinib, or Midostaurin. In summary, we developed an LSCD model that shows the predictive potential of clinical prognosis and drug sensitivity. This model provides meaningful insights for personalized treatment of AML patients.

Background: Fatty acid metabolic reprogramming is critically implicated in tumorigenesis and progression. However, the role and prognostic significance of fatty acid metabolism-related genes (FMGs) in diffuse large B-cell lymphoma (DLBCL) remain largely unexplored. Methods: We analyzed transcriptomic data from the Gene Expression Omnibus (GEO) database to identify key prognostic FMGs. Through an integrative machine learning pipeline, we developed a prognostic signature termed the FAMscore. The association of the FAMscore with tumor immunity was assessed. Furthermore, we validated the dysregulation of multiple FMGs using quantitative real-time PCR and single-cell RNA sequencing data. Among these FMGs, we further investigated the role of CPT1A in DLBCL cell proliferation and apoptosis. Results: The FAMscore effectively distinguished between high- and low-risk DLBCL patients and served as an independent prognostic factor. A higher FAMscore was associated with poorer overall survival (OS). A nomogram integrating the cell-of-origin (COO) subtype, the International Prognostic Index (IPI) score, and the FAMscore was developed and demonstrated reliable predictive performance. Tumors in the high-FAMscore group exhibited higher tumor purity and an immune infiltration profile conducive to an immunosuppressive microenvironment. Functional assays revealed that knockdown of CPT1A significantly inhibited DLBCL cell proliferation and induced apoptosis. Conclusions: Our study highlights fatty acid metabolism as a key prognostic indicator and immune regulator in DLBCL. These findings advance the framework for personalized treatment strategies in this malignancy.

Supplementary Data from Disabling Uncompetitive Inhibition of Oncogenic IDH Mutations Drives Acquired Resistance