Identification of genes encoding targets associated with adverse events in multiple myeloma.

Abstract

1556 Background: Despite novel therapeutic options, understanding the toxicity profile of anti multiple myeloma (MM) drug regimens (AMDR) is vital. Data suggests adverse event (AE) profile is orchestrated by certain associated genes. The purpose of this study is to explore the interplay of genes, regimens, AEs and provide genetic evidence for a linkage between regimens and the presence of AEs. Methods: We examined a group of AMDRs retrieved from the FDA Adverse Event Reporting System. Drug-associated genes were obtained from the Drug Gene Interaction Database, DGIdb. Then, genes were imported to the Online Mendelian Inheritance in Man (OMIM) to search for the existing clinical synopses (features) in the peer reviewed biomedical material, or phenotypes when no data was available. Clinical synopses were then linked to MedDRA. Gene gene interaction was also determined through the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). We then constructed a detailed large MM pharmacogenetic network to illustrate the linkage among drugs, genes and MM via various expert integrated resources. AMDR responses were then assessed at the DNA and protein levels by modularizing genetic causation into different scenarios i) a direct drug effect on gene expression; ii) the secondary or tertiary effect of drug(s) on subsequent drug metabolism or disposition altering gene expression pathways; iii) modulation of another biological network that disturbs drug effect on gene expression resulting in exacerbating AE occurrence. Results: We found multiple genes including CTLA4, NFKB1, PSMB8, CCND1 and HLAA were complicit/associated with different AEs including cardiac or hepatobiliary disorders or other serious events. Our results suggested the expression of CTLA4 was influenced by multiple AMDRs from combinations of bortezomib (V), lenalidomide (R), melphalan (M), or dexamethasone (d). When AMDRs involve these agents, the occurrence of pericardial disorders due to the treatment exhibited high confidence. We also found carfilzomib (K) combinations (Kd or KRd) were associated with PSMB8 which was likely to be the genetic factor concomitant with heart failures, cardiac arrhythmias, or hepatobiliary toxicities. Furthermore, our findings suggested NFKB1, thalidomide associated gene interacting with PSMB8, may present the same toxicity events in hepatobiliary disorders. Conclusions: Understanding the genomic basis of specific drug-AE combinations could reveal molecular mechanisms underlying drug-gene-AE associations and recognize the causality of AEs. When considering alternative agents in MM, our study offers insights for predicting treatment responses such as PSMB8 which could potentially cause an off target effect of K on cardiomyocyte 20S beyond MM cells. Our plan is to integrate this novel computational biology approach with translational medicine to further investigate our observation.