Serrano-Gonzalo, I. | Search bioRxiv

bioRxiv2024

Pyruvate from bone marrow mesenchymal stem cells supports myeloma redox homeostasis and anabolism

Multiple myeloma is an incurable cancer of plasma cells that depends on the bone marrow for its survival. Despite its prevalence, the molecular mechanisms underlying this malignancy remain poorly understood. In this study, we aim to bridge this knowledge gap by elucidating the metabolic interplay between myeloma cells and bone marrow mesenchymal stem cells (BMMSCs). BMMSCs are crucial in supporting myeloma cell metabolism, contributing to their proliferation, survival, and resistance to chemotherapy. Through a combination of mathematical modelling and experimental co-cultures, we demonstrate that pyruvate - the end product of glycolysis - plays a key role in myeloma cell metabolism. Our findings reveal that myeloma cells predominantly rely on the uptake of pyruvate produced by neighbouring BMM-SCs via the plasma membrane proton-linked monocarboxylate transporters MCT-1 and MCT-2 encoded by the Slc16a1 and a2 genes, respectively. Furthermore, we show that pharmacological inhibition of the MCT-1/2, with AZD3965, triggers a cascade of compensatory metabolic responses, disrupting redox balance and significantly reducing the proliferation capacity of co-cultured myeloma cells.

cancer biology↗

bioRxiv2022

Mathematical reconstruction of the metabolic network in an in-vitro multiple myeloma model.

It is increasingly apparent that cancer cells, in addition to remodelling their metabolism to survive and proliferate, adapt and manipulate the metabolism of other cells. This property may be a telling sign that pre-clinical tumour metabolism studies that exclusively utilise in-vitro mono-culture models could prove to be limited for uncovering novel metabolic targets that can translate into clinical therapies. Although this is increasingly recognised, and work addressing this is becoming routinary in a rapidly emerging field, much remains unknown. This study employs an interdisciplinary approach that leverages the predictive power of mathematical modelling to enrich experimental findings. We develop a functional multicellular in-silico model that facilitates the qualitative and quantitative analysis of the metabolic network spawned by an in-vitro co-culture model of bone marrow mesenchymal stem- and myeloma cell lines. To procure this model, we devised a bespoke human genome constraint-based reconstruction workflow that combines aspects from the legacy mCADRE & Metabotools algorithms, the novel redHuman algorithm, along with 13C-metabolic flux analysis. Our workflow transforms the latest human metabolic network matrix (Recon3D) into two cell-specific models coupled with a metabolic network spanning a shared growth medium. When cross-validating our in-silico model against the in-vitro model, we found that the in-silico model successfully reproduces vital metabolic behaviours of its in-vitro counterpart; results include cell growth predictions, respiration rates, as well as support for observations which suggest cross-shuttling of redox-active metabolites between cells. Together, our methodology and its results provide yet another step toward the relevance of studies of this type in the field.

bioengineering↗