Project 2: Multi-Omics of high-risk MM

PROJECT SUMMARY/ABSTRACT
While our own extensive studies have confirmed the significant role of the disrupted genome in Multiple
Myeloma (MM), they have also re-emphasized the gaps in understanding, and the importance of immune
regulation and gene-environment interaction. It is indeed likely that the evolution of MM, both before or during
therapy, is the result of a complex interplay of biological perturbations driven by genetic changes and
environmental influences. Our past work has also demonstrated that studying small numbers of patients at
great depth can be as rewarding for scientific understanding as studies of superficial genomic events in
thousands of patients. Thus we will strive to generate the first, longitudinal, translational clinical trial and
comprehensive data resource of environmental genetic interactions for the highest-risk MM population. It is
these patients who continue to rapidly fail highly effective therapeutics for reasons which are still completely
opaque. New and bold approaches using state-of-the-art technology are required to reverse this decades-old
lack of progress.
Our hypothesis is that analysis of data capturing gene-environment interactions at high resolution will reveal
insights into biological pathways influencing MM responsiveness to therapy and subsequent outcomes. First,
we will leverage a carefully studied and homogeneously treated high-risk group of “double hit” patients in a
Phase 2 clinical trial with large control clinical databases and bio-repositories to derive, for each patient, a
detailed map of environmental gene interactions linked to clinical outcome over time. Second, we will perform a
series of complex analyses to identify MM-associated changes in and across the genome, transcriptome,
epigenome, immune environment, proteome, lipidome and metabolome. Third, we will study these samples at
the highest resolution technically feasible today, and seek to define gene-environment interaction changes
over time that associate with response to therapy. Finally, high resolution data capturing these interaction
changes and clinical response data will be linked to improve our understanding of the mechanisms underlying
MM variability among patients in regards to disease outcomes. This comprehensive resource will enable a
more individualized approach to clinical surveillance and therapy for MM.

Grant Number: 5P50CA186781-10
NIH Institute/Center: NIH
Principal Investigator: Esteban Braggio