Multiple myeloma (MM) is best understood as a dynamically evolving genomic ecosystem shaped by inherited susceptibility, early oncogenic events, and continuous selective pressures. We propose an evolutionary genomics framework integrating germline risk, disease initiation, clonal diversification, and therapeutic adaptation into a unified model of MM biology. Polygenic risk burden, rare predisposing variants, and alterations in DNA repair and telomere pathways create a permissive background that influences precursor states and immune interactions. Primary cytogenetic events, particularly immunoglobulin heavy chain (IgH) translocations and hyperdiploidy, establish biologically distinct founding clones and constrain subsequent evolutionary trajectories. Disease progression is driven by secondary chromosomal alterations, copy number changes, MYC activation, TP53 loss, and structural rearrangements, promoting genomic instability and transcriptional plasticity. Longitudinal studies reveal branching clonal architectures shaped by treatment-driven selection. Integrating germline and somatic landscapes within an evolution-aware precision framework may improve risk stratification, anticipate high-risk trajectories, and support adaptive strategies to achieve more durable disease control. While polygenic risk scores (PRS) provide insight into inherited susceptibility, they are not yet clinically actionable for risk stratification or screening in MM and currently remain research tools. This framework provides a clinically oriented basis for applying genomic biomarkers to risk stratification, treatment selection, and longitudinal monitoring.
Carretero‐Fernández et al. (Fri,) studied this question.