Proteomic Profiling of Multiple Myeloma Using iTRAQ Labeling Followed by Multidimensional Liquid Chromatography and Tandem Mass Spectrometry.
Authors: Dytfeld Dominik , Hari Malathi , Strahler John , Mellacheruvu Dattatreya , Subramani Suchitra , Nesvizhskii Alexey , Sreekumar Arun , Jakubowiak Andrzej J 
Published: October 2019

Abstract
Abstract 4865

Introduction
Despite an increased number of new treatments, multiple myeloma (MM) remains mostly incurable. There is emerging evidence that achieving at least 90% disease reduction (very good partial response, VGPR) is associated with improved control of disease (Jakubowiak et al, JCO, in press). However, even with the most active regimens, 40-60% of patients (pts) with newly diagnosed MM and the majority of pts with relapsed/refractory MM do not achieve VGPR. The objective of this study is to establish predictors of response and drug resistance by applying proteomic profiling of MM. Here we present the preliminary analysis of differential proteomic profiling of plasma cells (PC) from pts with MM.

Methods
We have performed proteomic analysis of PC from 5 pts with previously untreated MM enrolled in the frontline VDD study (combination treatment with bortezomib, pegylated doxorubicin, and dexamethasone) using iTRAQ (Isobaric Tags for Relative and Absolute Quantitation) technique in 8-plex variant. With regards to samples analyzed two pts showed at least VGPR (≥VGPR) and the rest exhibited less than VGPR (<VGPR) to the regimen. PCs were acquired from bone marrow aspiration, and were thereafter enriched with use of a negative selection kit (RossetteSep, StemCell Technologies). To enable comparison across experiments, proteins from the myeloma cell line MM1.S were used as an internal reference. Proteins were processed with iTRAQ reagents according to the manufacturer's protocol (Applied Biosystems). The pooled samples were SCX fractionated before MS analysis (Applied Biosystems 4800 Proteomics Analyzer TOFTOF). The data were analyzed using ProteinPilot software. The resulting enrichment was processed through a clustering algorithm to identify commonalities and differences in protein expression.

Results
We identified 426 proteins, of which 399 were quantified. Using a 2 fold expression threshold, 18 proteins were elevated in samples from pts ≥VGPR to VDD while 102 proteins were down regulated compared to the <VGPR group. The upregulated proteins were analyzed for their biological nuance using Oncomine Concept Map (www.oncomine.org). Interestingly, the top concept that was enriched in this analysis described the gain of chromosome 1q multiple myeloma (p = 3.6E-6). Notably, this concept was enriched by 7 proteins: namely adenylate kinase 2, rho/rac guanine nucleotide exchange factor (GEF) 2, hepatoma-derived growth factor (high-mobility group protein 1-like), pre-B-cell leukemia homeobox interacting protein 1, sperm associated antigen 9, tropomyosin 3 and vimentin, all of which were elevated in patients responsive to VDD.

Conclusions
We showed patient-derived proteomic characteristics in MM using 8-plex iTRAQ methodology. As a proof of concept, preliminary analysis of samples obtained from pts enrolled in frontline VDD shows differential expression of 120 proteins in patients who achieved ≥VGPR vs <VGPR. The updated results of proteomic profiling of PCs from newly diagnosed patients will be presented at the meeting.
This study was supported by a grant from the Multiple Myeloma Research Foundation.

Disclosures
No relevant conflicts of interest to declare.