Biology subjects

Griessinger, E.

Publications and source records attributed to Griessinger, E..

3 recordsLinked to original sources

bioRxiv2023

FAO-supported OxPhos leukemic stem cells are sensitive to cold.

Targeting mitochondrial oxidative phosphorylation (OxPhos) metabolism has revealed a potential weakness for leukemic stem cells (LSCs) that can be exploited for therapeutic purposes. Fatty acids oxidation (FAO) is a crucial OxPhos-fueling catabolic pathway for some AML and for chemotherapy-resistant AML cells. Here, we identified cold sensitivity at 4{degrees}C (cold killing challenge: CKC4), as a novel vulnerability that selectively kills FAO-supported OxPhos LSCs in Acute Myeloid Leukemia while sparing normal hematopoietic stem cells (HSCs). Cell death of OxPhos leukemic cells was induced by membrane permeabilization at 4{degrees}C while by sharp contrast, leukemic cells relying on glycolysis were resistant. Forcing glycolytic cells into OxPhos metabolism sensitized them to CKC4. We show using lipidomic and proteomic analyzes that OxPhos shapes the composition of the plasma membrane and introduce variation of 22 lipid subfamilies between cold-sensitive and cold-resistant cells. Cold sensitivity is a potential OxPhos biomarker. SignificanceThis study reveals that mitochondrial energetics fueled by FAO metabolism introduces membrane fragility upon cold exposure in OxPhos-driven AMLs and in LSCs. This novel physical property of Leukemic cells and LSCs opens new avenues for biomarker and diagnostics as well as for anti-OxPhos drug screening and LSCs targeting. One Sentence SummaryOxPhos leukemic cells die at 4{degrees}C

cancer biology↗

bioRxiv2022

The PIP4K2 inhibitor THZ-P1-2 exhibits antileukemia activity by disruption of mitochondrial homeostasis and autophagy

Treatment of acute leukemia is challenging due to genetic heterogeneity between and even within patients. Leukemic stem cells (LSCs) are relatively drug-resistant and frequently lead to relapse. Their plasticity and capacity to adapt to extracellular stress, in which mitochondrial metabolism and autophagy play important roles, further complicates treatment. Genetic models of phosphatidylinositol-5-phosphate 4-kinase type 2 proteins (PIP4K2s) inhibition demonstrated the relevance of these enzymes in mitochondrial homeostasis and autophagic flux. Here, we uncover the cellular and molecular effects of THZ-P1-2, a pan-inhibitor of PIP4K2s, in acute leukemia cells. THZ-P1-2 reduced cell viability and induced DNA damage, apoptosis, loss of mitochondrial membrane potential, and accumulation of acidic vesicular organelles. Protein expression analysis revealed that THZ-P1-2 impaired autophagy flux. In addition, THZ-P1-2 induced cell differentiation and showed synergistic effects with venetoclax in resistant leukemic models. In primary leukemia cells, LC-MS/MS-based proteome analysis revealed that sensitivity to THZ-P1-2 was associated with mitochondrial metabolism, cell cycle, cell-of-origin, and the TP53 pathway. Minimal effects of THZ-P1-2 observed in healthy CD34+ cells suggested a favorable therapeutic window. Our study provides insight into pharmacological inhibition of PIP4Ks targeting mitochondrial homeostasis and autophagy shedding light on a new class of drugs for acute leukemias.

pharmacology and toxicology↗

bioRxiv2022

Identifying predictors of survival in patients with leukemia using single-cell mass cytometry and machine learning

Mass cytometry by time-of-flight (CyTOF) is an emerging technology allowing for in-depth characterisation of cellular heterogeneity in cancer and other diseases. However, computational identification of cell populations from CyTOF, and utilisation of single cell data for biomarker discoveries faces several technical limitations, and although some computational approaches are available, high-dimensional analyses of single cell data remains quite demanding. Here, we deploy a bioinformatics framework that tackles two fundamental problems in CyTOF analyses namely: a) automated annotation of cell populations guided by a reference dataset, and b) systematic utilisation of single cell data for more effective patient stratification. By applying this framework on several publicly available datasets, we demonstrate that the Scaffold approach achieves good tradeoff between sensitivity and specificity for automated cell type annotation. Additionally, a case study focusing on a cohort of 43 leukemia patients, reported salient interactions between signalling proteins that are sufficient to predict short-term survival at time of diagnosis using the XGBoost algorithm. Our work introduces an automated and versatile analysis framework for CyTOF data with many applications in future precision medicine projects. Datasets and codes are publicly available at: https://github.com/dkleftogi/singleCellClassification

cancer biology↗