Replication Stress Induces Hyper-Apobec Mutagenesis in Multiple Myeloma
Bibliographic record
Abstract
Introduction APOBEC mutational signatures are prominent in newly diagnosed multiple myeloma (NDMM), driven primarily by the enzymes APOBEC3A (A3A) and APOBEC3B (A3B). The activity of these enzymes varies significantly among patients, with some exhibiting no detectable mutations while others show high levels of APOBEC-induced mutations, termed hyper-APOBEC. This study aims to investigate the underlying causes of hyper-APOBEC activity in multiple myeloma (MM) patients. Methods We analyzed 752 whole genomes from NDMM patients in the CoMMpass study. Within the CoMMpass study, 723 patients had whole exome sequencing (WES) data available, and 767 had RNA sequencing (RNA-Seq) data. Lentiviral knockdown (KD) and overexpression (OE) of A3B were performed in human MM cell lines, followed by RNA-seq and pathway analysis to identify key regulatory pathways associated with APOBEC activity. We further validated the functional impact of A3B on DNA replication, proliferation, and DNA damage. Results APOBEC activity was identified in 57% of patients via WES, with 11% classified as hyper-APOBEC. Differential expression analysis revealed 696 genes associated with hyper-APOBEC independently of MAF/MAFB translocations. Notably, A3A and A3B mRNA expression levels were significantly higher in hyper-APOBEC cases. Further analysis using Spearman's correlation identified 50 genes significantly correlated with A3B (r-squared > 0.18; p < 0.01), primarily involved in cell cycle and DNA replication pathways. To validate these findings, we compared our results with ICGC breast cancer data, revealing that 35 of the 50 correlated genes exhibited similar patterns. Many of these genes were negatively regulated by E2F4 as part of the DREAM complex and positively regulated by E2F1 and FOXM1, suggesting that suppression of the DREAM complex increases A3B expression. Using the ICGC breast WGS dataset, hyper-APOBEC correlated with homologous recombination deficiency (p < 0.05). Further analysis of the CoMMpass dataset showed that higher A3B expression was associated with increased chromothripsis (p < 0.01), APOBEC mutagenesis (p < 0.02), 1q gains/amps (p < 0.02), 13q deletions (p < 0.05), and high-risk transcriptional profiles (GEP70) and worse prognosis. These findings underscore the significant impact of A3B on genomic instability, cell proliferation, and patient outcomes in MM. Importantly, pharmacological inhibition of FOXM1 (FDI6, 20uM) and E2F4/6 (HLM00074, 20uM) in MM cell lines such as 8226, U266 and MM1.S, confirmed increased A3B levels following E2F4/6 inhibition and decreased A3B levels after FOXM1 inhibition upon 72h of treatment. Genetic ablation through a CRISPR CAS9 APOBEC3B approach confirmed the interplay between A3B and the DREAM complex observed in vitro. To functionally validate these findings, we created RNA-seq data of A3B KD in human L363/LP1 and A3B OE in OPM2 MM cell lines. Significant correlations were observed between A3B expression levels and genes associated with the cell cycle, G1 to S phase transition, and DNA replication. These results were validated in vitro using BrdU/7AAD assays, which demonstrated G1 to S phase arrest and decreased DNA double-strand break levels (γH2AX) in A3B KD cells, with the opposite pattern in A3B OE cells. Furthermore, replication stress induced by hydroxyurea (HU) treatment led to increased A3B expression, single-stranded DNA (pS4/8-RPA2), and double-stranded DNA breaks (γH2AX) levels, supporting our in silico findings. Conclusion Our study shows that high APOBEC mRNA expression is associated with hyper-APOBEC mutations and occurs predominantly in MM cells with high replication stress and genomic instability. Combining our genomic and functional data, we can draw a model where replication stress in the context of genomic instability leads to more single-stranded DNA and increased A3B expression, creating a feed-forward loop of mutagenesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".