FISH and GEP Based Prediction of Chromosomal Translocation Identifies Myeloma Patients Who Do Not Benefit From Bortezomib
Authors: Tian Erming , Zhang Qing , Heuck Christoph , Chavan Shweta S. , Sawyer Jeffrey , Usmani Saad Z , Epstein Joshua , Barlogie Bart 
Published: October 2019

Abstract 1814

Gene expression profiling (GEP) provides valuable information on molecular subclass and prognostic risk of multiple myeloma (MM). In addition to subclass designation, GEP also predicts many cytogenetic aberrations in MM (Zhou, Blood 119:e148). We re-examined GEP derived assignments of translocation-related molecular subgroups (CD1, CD2 MF, and MS) in correlation to FISH data. Focusing on 14q32 translocation, we used FISH probes to MMSET/FGFR3, CCND3, CCND1, MAF, and MAFB in combinations with probes specific to the immunoglobulin heavy chain (IGH) constant and viable regions (IGHC and IGHV) to identify translocations in myeloma cells from Total Therapy (TT) 4 and TT5 patients at baseline. Combining our FISH data with GEP expression of probe sets specific to the IgH translocation partners, we identified threshold expression levels; above this threshold the expression level was clearly indicative of genomic translocations of t(4;14)(p16;q32), t(6;14)(p21;q32), t(11;14)(q13;32), t(14;16)(q32;q23), or t(14;20)(q32;q11). Below these thresholds, increased signals reflected gene copy numbers. Overall, 42.2% (113/268) of patients were predicted and confirmed to have 14q translocations: 14.9% had t(4;14), 3.4% t(6;14), 19.4% t(11;14), 3.4% t(14;16), and 1.1% t(14;20). In cases of GEP indicated simultaneous spikes of several 14q translocation partners, we discovered that 14q translocation were indeed mutually exclusive - one 14q translocation per clone. The spikes of the other 14q partner gene(s) shown by GEP, reflected copy number driven increases, or in a few cases, the co-existence of distinct clones, each with a unique 14q translocation. Using threshold expression levels equivalent to those developed in the TT4 and TT5 training set, we predicted that 42.3% (335/792) of patients treated on TT2 and TT3 protocols had 14q translocations at baseline, as follows; 14.9% t(4;14), 1.4% t(6;14), 19.8% t(11;14), 4.4% (14;16), and 1.8% t(14;20). Next, we correlated the effects of 14q translocations with overall survival of patients treated with TT2 and TT3. Patients whose GEP spikes predicted MMSET/FGFR3 and CCND3 translocations significantly benefited from the inclusion of Bortezomib in TT3; and patients with CCND1 and MAFB translocations had improved median survivals comparing 8 years follow-ups of TT2 and TT3. In contrast, patients with high MAF expression clearly did not benefit from the inclusion of the proteasome inhibitor in TT3. In conclusion, by combining interphase FISH and GEP we established predictive threshold expression levels of 14q translocations in MM and identified a group of patients who do not benefit from Bortezomib. This single-gene approach to define molecular subgroups is expedient and provides important information of prognostic significance.

Disclosures:

Tian: University of Arkansas for Medical Sciences: Employment, under pending process, under pending process Patents & Royalties. Sawyer:University of Arkansas for Medical Sciences: Employment, under panding process, under panding process Patents & Royalties. Epstein:University of Arkansas for Medical Sciences: Employment, under pending process, under pending process Patents & Royalties. Barlogie:University of Arkansas for Medical Sciences: Employment, under pending process, under pending process Patents & Royalties.