Activated stromal cells transfer mitochondria to rescue acute lymphoblastic leukemia cells from oxidative stress
Open Access
- 9 September 2019
- journal article
- research article
- Published by American Society of Hematology in Blood
- Vol. 134 (17), 1415-1429
- https://doi.org/10.1182/blood.2019001398
Abstract
We investigated and modeled the mesenchymal stromal cell (MSC) niche in adult acute lymphoblastic leukemia (ALL). We used gene expression profiling, cytokine/chemokine quantification, flow cytometry, and a variety of imaging techniques to show that MSCs, directly isolated from the primary bone marrow specimens of patients with ALL, frequently adopted an activated, cancer-associated fibroblast phenotype. Normal, primary human MSCs and the MSC cell line HS27a both were activated de novo, when exposed to the reactive oxygen species (ROS)–inducing chemotherapy agents cytarabine (AraC) and daunorubicin (DNR), a phenomenon blocked by the antioxidant N-acetyl cysteine. Chemotherapy-activated HS27a cells were functionally evaluated in a coculture model with ALL targets. Activated MSCs prevented therapy-induced apoptosis and death in ALL targets, via mitochondrial transfer through tunneling nanotubes (TNTs). Reduction of mitochondrial transfer by selective mitochondrial depletion or interference with TNT formation by microtubule inhibitors, such as vincristine (VCR), prevented the “rescue” function of activated MSCs. Corticosteroids, also a mainstay of ALL therapy, prevented the activation of MSCs. We also demonstrated that AraC (but not VCR) induced activation of MSCs, mitochondrial transfer, and mitochondrial mass increase in a murine NSG model of disseminated SEM cell–derived ALL, wherein CD19+ cells closely associated with nestin+ MSCs after AraC, but not in the other conditions. Our data propose a readily clinically exploitable mechanism for improving treatment of ALL, in which traditional ROS-inducing chemotherapies are often ineffective at eradicating residual disease, despite efficiently killing the bulk population.Keywords
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