| Literature DB >> 29467487 |
Charlotte Pawlyn1, Andrea Loehr2, Cody Ashby3, Ruslana Tytarenko3, Shayu Deshpande3, James Sun4, Kyle Fedorchak4, Tariq Mughal4, Faith E Davies3, Brian A Walker3, Gareth J Morgan5.
Abstract
PARP inhibitors can induce synthetic lethality in tumors characterized by homologous recombination deficiency (HRD), which can be detected by evaluating genome-wide loss of heterozygosity (LOH). Multiple myeloma (MM) is a genetically unstable tumor and we hypothesized that HRD-related LOH (HRD-LOH) could be detected in patient samples, supporting a potential role for PARP inhibition in MM. Using results from targeted next-generation sequencing studies (FoundationOne® Heme), we analyzed HRD-LOH in patients at all disease stages (MGUS (n = 7), smoldering MM (SMM, n = 30), newly diagnosed MM (NDMM, n = 71), treated MM (TRMM, n = 64), and relapsed MM (RLMM, n = 234)) using an algorithm to identify HRD-LOH segments. We demonstrated HRD-LOH in MM samples, increasing as disease progresses. The extent of genomic HRD-LOH correlated with high-risk disease markers. Outcome of RLMM patients, the biggest clinical group, was analyzed and patients with HRD-LOH above the third quartile (≥5% HRD-LOH) had significantly worse progression-free and overall survival than those with lower levels (p < 0.001). Mutations in key homologous recombination genes account for some, but not all, of the cases with an excess of HRD-LOH. These data support the further evaluation of PARP inhibitors in MM patients, particularly in the relapsed setting with a high unmet need for new treatments.Entities:
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Year: 2018 PMID: 29467487 PMCID: PMC6035152 DOI: 10.1038/s41375-018-0017-0
Source DB: PubMed Journal: Leukemia ISSN: 0887-6924 Impact factor: 11.528
Fig. 1a Percentage of genomic HRD-LOH by disease stage. b Percentage of genomic HRD-LOH by UAMS molecular subgroup. The raw data points and the median and inter-quartile range for each data set are shown. c Distribution of HRD-LOH shown as the percentage of patients with HRD-LOH >1% at each genomic locus across the autosomal chromosomes. For the acrocentric chromosomes, 13, 14, 15, 21, and 22, only the q arm was considered as estimates of HRD-LOH in the p arm would be unreliable
Fig. 2a Event-free survival by genomic HRD-LOH. Kaplan–Meier plots demonstrating the probability of survival for those patients with genomic HRD-LOH <5% (n = 150, median 0.512 years) vs. ≥5% (n = 65, median 0.197 years). Hazard ratio 1.79 (1.3, 2.5); p = 0.00065. b Overall survival by genomic HRD-LOH. Kaplan–Meier plots demonstrating the probability of survival for those patients with genomic HRD-LOH <5% (n = 150, median 1.266 years) vs. ≥5% (n = 65, median 0.939 years). Hazard ratio 2.18 (1.5, 3.2); p = 8.23e−05
Multivariate Cox regression analysis of event-free and overall survival
| Event-free survival | Wald interaction | |
|---|---|---|
| HRD-LOH*PR | <0.0001 | 0.01 |
| HRD-LOH*GEP70 | <0.0001 | 0.08 |
| HRD-LOH*PI | <0.0001 | 0.02 |
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| HRD-LOH*PR | <0.0001 | 0.002 |
| HRD-LOH*GEP70 | <0.0001 | 0.39 |
| HRD-LOH*PI | <0.0001 | 0.04 |
Fig. 3a Genomic HRD-LOH across all myeloma samples with those carrying a mutation in a gene associated with homologous recombination indicated in black (HRmut). b Genomic HRD-LOH by presence of HRmut or wild type (HRwt). Wilcoxon test for difference between groups, p = 0.056. c Genomic HRD-LOH by presence of a BRCA1/2 mutation. Wilcoxon test for difference between groups, p = 0.383. The raw data points and the median and inter-quartile range for each data set are shown. The number and percentage of patients with a mutation identified in each of the genes indicated is shown in the table below the figure