OA-22: TiMMing: Developing an Innovative Suite of Bioinformatic Tools to Harmonize and Track the Origin of Copy Number Alterations in the Evolutionary History of Multiple Myeloma

Introduction: Multiple Myeloma (MM) is a hematologic cancer with heterogeneous and complex genomic landscape, where Copy Number Alterations (CNAs) play a key role in the disease's pathogenesis and prognosis. It is of biological and clinical interest to study the temporal occurrence of early alterations, as they play a disease "driver" function by deregulating key tumor pathways.

Methods: This study presents an innovative bioinformatic suite consisting of five bioinformatics tools (BOBaFit, RemasterCNA, RAPH, ComphyNumber and TestClonality) created for the purpose of harmonizing Copy Number data across different genomic platforms and tracing the origin of CNAs throughout the evolutionary history of MM. To this aim, large cohorts of newly-diagnosed MM (NDMM, N=1582) and Smoldering-MM (SMM, N=282) were aggregated.

Results: The tools developed in this study enabled the harmonization of CNAs as obtained from different genomic platforms (i.e. WGS, ULP-WGS, WES, SNP array) in order to obtain the highest statistical power. Therefore, the high numerosity of these cohorts was harnessed for both 1) the identification of novel genes characterized as MM focal "driver" alterations through the optimized use of GISTIC tool (including NFKB2, NOTCH2, MAX and EVI5 and MYC-ME2-enhancer genes), and 2) the generation of an innovative timing model based on Bradley-Terry approach and implemented with the introduction of a statistical method aimed at introducing statistical confidence intervals for CNAs analysis.
By applying this model on both NDMM and SMM cohorts, it has been possible to identify specific CNAs (1q(CKS1B)amp, 13q(RB1)del, 11q(CCND1)amp and 14q(MAX)del) that were categorized as "early/driver" events. A high level of precision was guaranteed by the narrow confidence intervals in the timing estimates. These CNAs were proposed as critical MM alterations, playing a critical role in the evolutionary history of both SMM and NDMM. Importantly, among the identified events, CKS1B amp and RB1 del were previously poorly characterized from an evolutionary point of view and uncertainly classified between primary and secondary events, while MAX del represents a completely new discovered MM driver alteration.
Finally, a stepwise backward-forward Cox Regression survival model was employed to identify all the independent genomic alterations having the greatest effect on patients’ outcomes (i.e. Progression Free and Overall Survival), named deletion of RB1, amplification of CKS1B, amplification of MYC, amplification NOTCH2 and deletion-mutation of TRAF3.

Conclusions: In conclusion, the study highlighted the existence of previously unrecognized "early-drivers” MM CNAs, whose impact on patients’ survival has been demonstrated. These CNAs might improve MM patients’ stratification and contribute to precisely assess patients’ prognosis.

Acknowledgements: BolognAIL ONLUS, AIRC19-IG22059