Germline Risk Contribution to Genomic Instability in Multiple Myeloma

Abstract

Genomic instability, a well-established hallmark of human cancer, is also a driving force in the natural history of multiple myeloma (MM) – a difficult to treat and in most cases fatal neoplasm of immunoglobulin producing plasma cells that reside in the hematopoietic bone marrow. Long recognized manifestations of genomic instability in myeloma at the cytogenetic level include abnormal chromosome numbers (aneuploidy) caused by trisomy of odd-numbered chromosomes; recurrent oncogene-activating chromosomal translocations that involve immunoglobulin loci; and large-scale amplifications, inversions, and insertions/deletions (indels) of genetic material. Catastrophic genetic rearrangements that either shatter and illegitimately reassemble a single chromosome (chromotripsis) or lead to disordered segmental rearrangements of multiple chromosomes (chromoplexy) also occur. Genomic instability at the nucleotide level results in base substitution mutations and small indels that affect both the coding and non-coding genome. Sometimes this generates a distinctive signature of somatic mutations that can be attributed to defects in DNA repair pathways, the DNA damage response (DDR) or aberrant activity of mutator genes including members of the APOBEC family. In addition to myeloma development and progression, genomic instability promotes acquisition of drug resistance in patients with myeloma. Here we review recent findings on the genetic predisposition to myeloma, including newly identified candidate genes suggesting linkage of germline risk and compromised genomic stability control. The role of ethnic and familial risk factors for myeloma is highlighted. We address current research gaps that concern the lack of studies on the mechanism by which germline risk alleles promote genomic instability in myeloma, including the open question whether genetic modifiers of myeloma development act in tumor cells, the tumor microenvironment (TME), or in both. We conclude with a brief proposition for future research directions, which concentrate on the biological function of myeloma risk and genetic instability alleles, the potential links between the germline genome and somatic changes in myeloma, and the need to elucidate genetic modifiers in the TME.

Revealing the impact of recurrent and rare structural variants in multiple myeloma

“…Consistent with recent findings in breast cancer 37 , in our series, SV hotspots showed seven-fold enrichment for multiple myeloma germline predisposition SNPs as compared with the remaining mappable genome (6 SNPs in 125 Mb of hotspots vs 17 in the remaining genome, Poisson test p = 0.0002; Figure S6 ) 48,49 . The involved SNPs were on 3q26.2 (SV hotspot involving SEC62/SAMD7 ), 6p21.3 (unknown SV target), 6q21 ( ATG5/PRDM1 ), 9p21.3 ( CDKN2A/CDKN2B ), 19p13.11 ( KLF2 ) and 2q31.1 ( SP3 ) ( Table S8 ).…”

“…Germline predisposition SNPs for multiple myeloma were obtained from a recent meta-analysis of GWAS-studies 48,49 . Poisson test for enrichment in hotspots was performed as for super-enhancers.…”

Targeting BCL‐2 with venetoclax and dexamethasone in patients with relapsed/refractory t(11;14) multiple myeloma

“…The mutational landscape analyses demonstrated that more patients with high TMB were in the phase two cohort compared to phase one. This finding is consistent with greater tumor genomic instability in a more heavily pre‐treated R/R MM population 36,37 . Similarly, more patients with del(17p) and gain(1q) were in the phase two cohort compared to phase one.…”

Clonal Evolution of Multiple Myeloma—Clinical and Diagnostic Implications

“…Genomic instability, a hallmark of all neoplastic diseases, is the source of genetic heterogeneity of MM not only at the individual patient level (intrapatient genetic heterogeneity), but also between patients with the same diagnosis (interpatient heterogeneity) [35,70,71]. Therefore, the molecular landscape of newly diagnosed MM is heterogeneous as there is no universal mutation pattern typical for MM [16][17][18][19][72][73][74].…”