journal article·2026-05-29Open access

MiR‐940 Suppresses Ferroptosis by Controlling Expression of Key Regulatory Genes

Andrea Kolak, Juliane Tschuck, Stefanie A. I. Weiß, Daniel Kaemena, Karolin Klimm, Ana Galhoz, Larissa Ringelstetter, Myles Fennell, Juliane Merl‐Pham, Anna Artati, Stefanie Strasser, Ralph Garippa, Michael Witting, Hans Zischka, Joel A. Schick, Stefanie M. Hauck, Michael P. Menden, Michelle Vincendeau, Brent R. Stockwell, Kamyar Hadian

Abstract

ABSTRACT Ferroptosis is a form of regulated cell death that is characterized by iron‐dependent lipid peroxidation. This process is regulated by specific metabolites, the lipid composition of the cells, redox‐active iron, and antioxidant mechanisms. Although numerous regulators have been identified over the past decade, exploring other mechanisms, particularly from non‐coding genomic regions, can build a thorough understanding of the multifaceted regulatory processes underlying ferroptosis. MicroRNAs (miRNAs) play a crucial role in gene regulation and cellular functions. Through a CRISPR KO screen, we identified miR‐940 as a negative regulator of ferroptosis. Overexpression of miR‐940 in several cell lines consistently suppressed ferroptosis induced by system x c − inhibition. Notably, multiple cancer patient cohorts with elevated miR‐940 levels exhibit reduced survival. Integrated bioinformatic, transcriptomic, and proteomic analyses revealed that miR‐940 decreases the expression of ACSL4, LPCAT3, DMT1, and NCOA4, and simultaneously increases levels of GPX4. Pharmacological inhibition of GPX4 attenuated the protective effect of miR‐940, indicating that its primary anti‐ferroptotic activity is mediated through GPX4. Overall, these mechanistic insights link gene rewiring to reduced levels of redox‐active iron and diminished lipid peroxidation, mediating ferroptosis suppression. These findings provide a defined regulatory network, presenting a novel target for therapeutic exploration in susceptible cancers.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Ferroptosis and cancer prognosis · MicroRNA in disease regulation · Cancer-related molecular mechanisms research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Cell Signaling and Chemical Biology, Research Unit Signaling and Translation Helmholtz Zentrum München Neuherberg Germany

Institute of Virology Helmholtz Zentrum München Neuherberg Germany

Computational Health Center Helmholtz Zentrum München Neuherberg Germany

Department of Biological Sciences Columbia University New York New York USA

Gene Editing & Screening Core Facility Memorial Sloan Kettering Cancer Center New York New York USA

Metabolomics and Proteomics Core Helmholtz Zentrum München Neuherberg Germany

Chair of Analytical Food Chemistry, TUM School of Life Sciences Technical University of Munich Freising‐Weihenstephan Germany

Institute of Molecular Toxicology and Pharmacology Helmholtz Zentrum München Neuherberg Germany

Institute of Toxicology and Environmental Hygiene School of Medicine and Health Technical University Munich Munich Germany

Genetics and Cellular Engineering Group, Research Unit Signaling and Translation Helmholtz Zentrum Munich Neuherberg Germany

Department of Biochemistry and Pharmacology Bio21 Molecular Science and Biotechnology Institute The University of Melbourne Parkville Victoria Australia

Institute of Virology School of Medicine and Health Technical University Munich Germany

Department of Chemistry Department of Pathology and Cell Biology Herbert Irving Comprehensive Cancer Center Irving Institute for Cancer Dynamics Data Science Institute Digestive and Liver Disease Research Center Columbia University New York New York USA

Funding

Deutsche Forschungsgemeinschaft · National Science Foundation

References (54)

Show source-provided references
1. 10.1038/s41573‐023‐00749‐810.1038/s41573‐023‐00749‐8 ↗
2. 10.1016/j.cell.2012.03.04210.1016/j.cell.2012.03.042 ↗
3. 10.1016/j.cell.2020.04.03910.1016/j.cell.2020.04.039 ↗
4. 10.1016/j.cell.2022.06.00310.1016/j.cell.2022.06.003 ↗
5. The Metabolic Code Of Ferroptosis: Nutritional Regulators Of Cell Death10.1016/j.tibs.2025.04.007 ↗
6. 10.1016/j.redox.2024.10321110.1016/j.redox.2024.103211 ↗
7. 10.1016/j.celrep.2020.02.04910.1016/j.celrep.2020.02.049 ↗
8. 10.1021/acschembio.1c0095310.1021/acschembio.1c00953 ↗
9. 10.1038/s41586‐019‐1705‐210.1038/s41586‐019‐1705‐2 ↗
10. 10.1038/s41586‐019‐1707‐010.1038/s41586‐019‐1707‐0 ↗
11. 10.1038/s41586‐022‐05022‐310.1038/s41586‐022‐05022‐3 ↗
12. 10.1021/acscentsci.9b0106310.1021/acscentsci.9b01063 ↗
13. 10.1038/s41589‐020‐0613‐y10.1038/s41589‐020‐0613‐y ↗
14. 10.1038/s41419‐024‐07251‐y10.1038/s41419‐024‐07251‐y ↗
15. 10.1038/s41467‐023‐42702‐810.1038/s41467‐023‐42702‐8 ↗
16. 10.1038/s41467‐024‐51996‐110.1038/s41467‐024‐51996‐1 ↗
17. 10.1016/j.cell.2023.05.00310.1016/j.cell.2023.05.003 ↗
18. 10.1038/s41586‐025‐09389‐x10.1038/s41586‐025‐09389‐x ↗
19. 10.1055/s‐0034‐139734410.1055/s‐0034‐1397344 ↗
20. 10.1038/s41418‐022‐00998‐x10.1038/s41418‐022‐00998‐x ↗
21. 10.1016/j.omtn.2021.05.00310.1016/j.omtn.2021.05.003 ↗
22. 10.1111/jcmm.1412110.1111/jcmm.14121 ↗
23. 10.7150/jca.3180010.7150/jca.31800 ↗
24. 10.18632/oncotarget.445610.18632/oncotarget.4456 ↗
25. 10.3892/ijo.2017.389710.3892/ijo.2017.3897 ↗
26. 10.1038/s41388‐019‐1093‐y10.1038/s41388‐019‐1093‐y ↗
27. MicroRNA‐940 Inhibits Epithelial‐Mesenchymal Transition Of Glioma Cells Via Targeting ZEB2
28. 10.2147/OTT.S23730710.2147/OTT.S237307 ↗
29. 10.1002/1873‐3468.1298510.1002/1873‐3468.12985 ↗
30. 10.1038/cddis.2014.29310.1038/cddis.2014.293 ↗
31. MicroRNA‐940 Inhibits Glioma Progression By Blocking Mitochondrial Folate Metabolism Through Targeting of MTHFD2
32. 10.1126/science.124700510.1126/science.1247005 ↗
33. 10.1016/j.chembiol.2019.01.00810.1016/j.chembiol.2019.01.008 ↗
34. miR940 Inhibits Cell Proliferation And Promotes Apoptosis In Esophageal Squamous Cell Carcinoma Cells And Is Associated With PostOperative Prognosis
35. MicroRNA‐940 induces Apoptosisof HTR8‐S/Vneo Cells in Intrahepatic Cholestasis of Pregnancy by Regulating RhoA10.1620/tjem.2025.J104 ↗
36. 10.1016/j.yexcr.2018.10.01110.1016/j.yexcr.2018.10.011 ↗
37. 10.1111/bph.1625710.1111/bph.16257 ↗
38. Integrated Analysis Of Public Datasets For The Discovery And Validation Of Survival‐Associated Genes In Solid Tumor
39. 10.2196/2763310.2196/27633 ↗
40. 10.1186/gb‐2013‐14‐5‐r4510.1186/gb‐2013‐14‐5‐r45 ↗
41. 10.1038/nchembio.223910.1038/nchembio.2239 ↗
42. 10.1038/s41589‐021‐00853‐z10.1038/s41589‐021‐00853‐z ↗
43. 10.1186/s12864‐017‐4285‐210.1186/s12864‐017‐4285‐2 ↗
44. 10.1093/nar/gkab107910.1093/nar/gkab1079 ↗
45. The Biochemical Basis of microRNA Targeting Efficacy10.1126/science.aav1741 ↗
46. 10.1038/nmeth.132210.1038/nmeth.1322 ↗
47. 10.1038/nprot.2016.13610.1038/nprot.2016.136 ↗
48. 10.1074/mcp.M113.03159110.1074/mcp.M113.031591 ↗
49. 10.1021/pr101065j10.1021/pr101065j ↗
50. 10.1038/nmeth.390110.1038/nmeth.3901 ↗
51. 10.1007/s11306‐016‐1104‐810.1007/s11306‐016‐1104‐8 ↗
52. 10.1016/j.chroma.2014.07.02110.1016/j.chroma.2014.07.021 ↗
53. 10.1038/s41587‐023‐01690‐210.1038/s41587‐023‐01690‐2 ↗
54. Notame′: Workflow for Non‐Targeted LC–MS Metabolic Profiling10.3390/metabo10040135 ↗