Jonathan Hofmann

Ph.D., M.P.H.

National Cancer Institute

Investigator

PLCO (Learn more about this study)

2016-0009

May 23, 2017

A metabolomic analysis of multiple myeloma development and progression

Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS), an asymptomatic pre-malignant condition characterized by the presence of monoclonal protein in blood and/or urine. Molecular epidemiologic studies of MGUS and MM have the potential to identify novel etiologic pathways and elucidate the biological mechanisms underlying associations with obesity and other MM risk factors. Furthermore, while some clinical features of MGUS (e.g., amount of monoclonal protein, immunoglobulin type) have been associated with progression from MGUS to MM, there is considerable interest in identifying novel markers associated with progression to clinically manifest disease. We propose to use a metabolomics approach to identify metabolites associated with future MM risk and with progression from MGUS to MM. Assays will be performed using an established metabolomics platform that is capable of measuring >1,000 metabolites with demonstrated high reproducibility (median CV of 8%). Our investigation will take advantage of the information on baseline MGUS status that will be available for over 8,000 PLCO subjects, including those with MGUS who did and did not progress to MM during follow-up. From among this subset, we plan to select approximately 220 MM cases, 350 subjects with MGUS who did not progress to MM, and 350 MGUS-free controls. As part of this effort, we will assess whether incorporating selected metabolites into current risk stratification models can improve our ability to identify MGUS-positive subjects at high risk of progression to MM. Findings from the proposed study could provide new insight into our understanding of the etiology of MM. In addition, the results could have important implications for the clinical management of MGUS patients; improvements in risk stratification modeling could lead to opportunities for secondary prevention of MM, with early therapeutic intervention for MGUS patients at high risk of progression to frank MM.

The specific aims of this study are:

1. To identify metabolomic profiles associated with future MM risk and progression from MGUS to MM; and

2. To evaluate whether incorporating selected metabolites into existing risk stratification models can improve our ability to identify MGUS-positive subjects at high risk of progression to clinically manifest disease.