Rising Prevalence of Low-Frequency PPM1D Gene Mutations after Second HDCT in Multiple Myeloma.
Katja SeipelNuria Z VeglioHenning NiliusBarbara JekerVera Ulrike BacherThomas PabstPublished in: Current issues in molecular biology (2024)
Multiple myeloma (MM) first-line treatment algorithms include immuno-chemotherapy (ICT) induction, high-dose chemotherapy (HDCT) and autologous stem cell transplant (ASCT) consolidation, followed by lenalidomide maintenance. After these initial therapies, most patients suffer a disease relapse and require subsequent treatment lines including ICT, additional HDCT and ASCT, or novel immunotherapies. The presence of somatic mutations in peripheral blood cells has been associated with adverse outcomes in a variety of hematological malignancies. Nonsense and frameshift mutations in the PPM1D gene, a frequent driver alteration in clonal hematopoiesis (CH), lead to the gain-of-function of Wip1 phosphatase, which may impair the p53-dependent G1 checkpoint and promote cell proliferation. Here, we determined the presence of PPM1D gene mutations in peripheral blood cells of 75 subsequent myeloma patients in remission after first or second HDCT/ASCT. The prevalence of truncating PPM1D gene mutations emerged at 1.3% after first HDCT/ASCT, and 7.3% after second HDCT/ASCT, with variant allele frequencies (VAF) of 0.01 to 0.05. Clinical outcomes were inferior in the PPM1D -mutated ( PPM1D mut) subset with median progression-free survival (PFS) of 15 vs. 37 months ( p = 0.0002) and median overall survival (OS) of 36 vs. 156 months ( p = 0.001) for the PPM1D mut and PPM1D wt population, respectively. Our data suggest that the occurrence of PPM1D gene mutations in peripheral blood cells correlates with inferior outcomes after ASCT in patients with multiple myeloma.
Keyphrases
- multiple myeloma
- peripheral blood
- induced apoptosis
- newly diagnosed
- free survival
- end stage renal disease
- stem cells
- cell proliferation
- ejection fraction
- cell cycle arrest
- chronic kidney disease
- high dose
- risk factors
- risk assessment
- low dose
- machine learning
- squamous cell carcinoma
- rheumatoid arthritis
- cell cycle
- oxidative stress
- deep learning
- gene expression
- electronic health record
- copy number
- signaling pathway
- stem cell transplantation
- artificial intelligence
- locally advanced
- dna methylation
- bone marrow
- cell death
- data analysis