Multiple myeloma is a malignancy of plasma cells, which grows at multiple foci in the bone marrow, secretes monoclonal immunoglobulins, and typically induces skeletal destruction, hypercalcemia, anemia, and renal failure. Although it remains an incurable cancer, novel therapeutic regimens have improved overall survival in the last decade. Multiple myeloma originates from post germinal center, terminally differentiated B lymphocytes through a multi-step process involving early and late genetic changes. Multiple myeloma is preceded by monoclonal gammopathy of undetermined significance (MGUS), a frequent age-progressive premalignant expansion of bone marrow plasma cells that behave benignly despite the presence of most myeloma-specific genetic abnormalities. Indeed, development and progression of multiple myeloma are believed to rely on vicious interactions with the bone marrow environment, offering a paradigm to investigate the bone-cancer relationship. In particular, bone and stromal cells are known to be diverted by cancer cells through altered cytokine circuitry. The resulting enhanced osteoclastogenesis and neoangiogenesis, and reduced osteoblast differentiation and activity sustain cancer cell survival, proliferation, migration and chemoresistance. Such crucial interactions, however, have only partially been elucidated in their complexity, dynamics and exact role in disease evolution. A better knowledge of this interplay, still elusive, could help identify prognostic markers, pathomechanisms, and therapeutic targets for future validation.
Aiming to achieve an unbiased, comprehensive assessment of the extracellular milieu during multiple myeloma genesis and progression, we performed a metabolomic analysis of patient-derived peripheral and bone marrow plasma by ultra high performance liquid and gas chromatography followed by mass spectrometry.
By feature transformation-based multivariate analyses, metabolic profiling of both peripheral and bone marrow plasma successfully discriminated active disease from control conditions (health, MGUS or remission). Moreover, both central and peripheral metabolic scores significantly correlated with bone marrow plasma cell counts. Significant changes in the peripheral metabolome were found to be associated with abnormal renal function in the subset of myeloma patients. Noteworthy, however, renal dysfunction-associated features failed to independently predict disease load, while non-overlapping disease vs. control analyses consistently identified a number of metabolites associated with disease. Among these, increased levels of the C3f-derived peptide, HWESASLL, and loss of circulating lysophosphocholines emerged as hallmarks of active disease. In vitro tests on myeloma cell lines and primary patient-derived cells revealed a previously unsuspected direct trophic role exerted by lysophosphocholines on malignant plasma cells.
Altogether, our data demonstrate that metabolomics is a powerful approach suitable for studying the complex interactions of multiple myeloma with the bone marrow environment and general metabolism. This novel strategy holds potential to identify unanticipated markers and pathways involved in development and progression of multiple myeloma.
No relevant conflicts of interest to declare.
Asterisk with author names denotes non-ASH members.