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PXD019619

PXD019619 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleDevelopment of novel combination treatments in AML guided by proteomics profiling
DescriptionAcute promyelocytic leukaemia (APL) can be cured by the co-administration of arsenic trioxide (ATO) and all-trans retinoic acid (ATRA). These small molecules relieve the differentiation blockade of the cancerous promyelocytes and trigger their maturation into functional neutrophils, which are physiologically primed for apoptosis. This normalization therapy uses low dose treatments and represents a compelling alternative to cytotoxic anticancer chemotherapy. However, the serendipitous discovery of this combination treatment prevented the establishment of methodologies to screen for novel combination treatments consisting of inducers of differentiation and other metallopharmaceuticals. Here, we present an experimental framework that enables interrogating the suitability, directionality and extent of normalization of novel combination treatments. Since the endpoint of this anticancer treatment is remodelling of cancer phenotypes, this approach requires a mechanism-driven understanding of the drug-induced cellular adaptions along the path to mature neutrophils. For this purpose, label-free quantification proteomics is used to probe the proteome changes upon differentiation and metal(-loid) treatment on the molecular level in a panel of ATRA-responsive and ATRA-non-responsive acute myeloid leukaemia (AML) cell lines, including APL. The induction of differentiation was confirmed by the up-regulation of canonical surface markers (e.g. CD11β) and validated by flow cytometry. The regulation of key transcription factors in this panel of AML cell lines reflects their position in the myeloid differentiation cascade (e.g. SPI1, GFI-1 and CEBPE). The additive/synergistic contributions of ATO to the combination treatment were thoroughly characterized and include changes in metabolic activities, as well as protein signatures related to management of reactive oxygen species and an integrated stress response. The latter two are also characteristic for the organoruthenium-based drug candidate plecstatin-1, which was recently shown to modulate the scaffold protein plectin. The combination of differentiation-induction and plecstatin-1 treatment featured a striking similarity in the responsiveness of the AML cancer cells compared to ATO+ATRA. It turned out to be at least equivalent in the regulation of key processes underlying normalization therapy in AML with granulocytic maturation. By exploiting response patterns of AML cancer cells induced by the ATO+ATRA combination treatment, this approach may allow identifying novel small molecule combinations, which may have the potential to achieve normalization and thus therapeutic benefit beyond APL.
HostingRepositoryPRIDE
AnnounceDate2024-10-08
AnnouncementXMLSubmission_2024-10-08_11:40:06.814.xml
DigitalObjectIdentifierhttps://dx.doi.org/10.6019/PXD019619
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportSupported dataset by repository
PrimarySubmitterChristopher Gerner
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationListOxidation; Acetyl; Carbamidomethyl; iodoacetamide derivatized residue
InstrumentQ Exactive
Dataset History
RevisionDatetimeStatusChangeLog Entry
02020-06-06 15:01:44ID requested
12024-10-08 11:40:07announced
Publication List
Meier-Menches SM, Neuditschko B, Janker L, Gerner MC, Schmetterer KG, Reichle A, Gerner C, . Front Chem, 10():826346(2022) [pubmed]
10.6019/PXD019619;
10.3389/fchem.2022.826346;
Keyword List
submitter keyword: AML, arsenic trioxide, cancer, APL, proteomics, differentiation, normalization, metal, plecstatin-1, ruthenium
Contact List
Christopher Gerner
contact affiliationDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria. Joint Metabolome Facility, University of Vienna and Medical University of Vienna, Vienna, Austria.
contact emailchristopher.gerner@univie.ac.at
lab head
Christopher Gerner
contact affiliationUniversity of Vienna
contact emailchristopher.gerner@univie.ac.at
dataset submitter
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