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. 2016 Dec 20;12(12):e1006501.
doi: 10.1371/journal.pgen.1006501. eCollection 2016 Dec.

Enrichment of Targetable Mutations in the Relapsed Neuroblastoma Genome

Affiliations

Enrichment of Targetable Mutations in the Relapsed Neuroblastoma Genome

Olivia M Padovan-Merhar et al. PLoS Genet. .

Abstract

Neuroblastoma is characterized by a relative paucity of recurrent somatic mutations at diagnosis. However, recent studies have shown that the mutational burden increases at relapse, likely as a result of clonal evolution of mutation-carrying cells during primary treatment. To inform the development of personalized therapies, we sought to further define the frequency of potentially actionable mutations in neuroblastoma, both at diagnosis and after chemotherapy. We performed a retrospective study to determine mutation frequency, the only inclusion criterion being availability of cancer gene panel sequencing data from Foundation Medicine. We analyzed 151 neuroblastoma tumor samples: 44 obtained at diagnosis, 42 at second look surgery or biopsy for stable disease after chemotherapy, and 59 at relapse (6 were obtained at unknown time points). Nine patients had multiple tumor biopsies. ALK was the most commonly mutated gene in this cohort, and we observed a higher frequency of suspected oncogenic ALK mutations in relapsed disease than at diagnosis. Patients with relapsed disease had, on average, a greater number of mutations reported to be recurrent in cancer, and a greater number of mutations in genes that are potentially targetable with available therapeutics. We also observed an enrichment of reported recurrent RAS/MAPK pathway mutations in tumors obtained after chemotherapy. Our data support recent evidence suggesting that neuroblastomas undergo substantial mutational evolution during therapy, and that relapsed disease is more likely to be driven by a targetable oncogenic pathway, highlighting that it is critical to base treatment decisions on the molecular profile of the tumor at the time of treatment. However, it will be necessary to conduct prospective clinical trials that match sequencing results to targeted therapeutic intervention to determine if cancer genomic profiling improves patient outcomes.

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Conflict of interest statement

SMA and VAM are employees of Foundation Medicine and have an equity interest in Foundation Medicine.

Figures

Fig 1
Fig 1
Study cohort overview A) Tabulation of Children’s Oncology Group (COG) risk classification and treatment time points of biopsy for 151 samples. (Intermed. = intermediate risk group) B) Number of samples taken at each treatment time point for nine patients with serial biopsies. (HR = high risk, IR = intermediate risk, LR = low risk at time of biopsy; further information in S2 Table) C) Tabulation of all variants identified (VUS: variants of unknown significance) D) Total number of variants identified per sample, stratified by COG risk group. Inset shows a similar calculation for suspected driver variants only. Heavy line represents the median of the data. “n” indicates the number of patients in each risk group. E) Total number of variants in each sample. Each bar represents an individual sample; color corresponds to risk group (red = high, blue = intermediate, green = low).
Fig 2
Fig 2
Suspected driver variants in diagnostic, treated, and relapsed neuroblastomas A) Frequency of all suspected driver short variants (single nucleotide variants, insertions, deletions) per gene in the entire cohort. Bars represent the number of patients with at least one lesion in a given gene, normalized to the total number of patients at each time point. Patients with multiple lesions in the same gene were only counted once per gene. B) All suspected driver amplification events with copy number >10. Bars represent the number of patients at each time point with a given gene amplification, normalized to the total number of patients at that treatment time point. C) All suspected driver homozygous deletion events. Bars represent the number of patients at each time point with a given gene loss, normalized to the total number of patients at that treatment time point. D) All suspected driver gene rearrangements and fusions. Bars represent the number of patients at each time point with a given genomic rearrangement, normalized to the total number of patients at that treatment time point. E) Number of variants in each sample, stratified by type of variant (“All variants” includes suspected driver variants as well as VUSs; “Suspected” includes suspected driver variants only; “Actionable” are suspected driver variants that have FDA approved or investigational therapy matches) and disease time point (blue, diagnosis; yellow, post-treatment; red, relapse). P values calculated using Welch’s T-test. F) Fraction of samples containing at least one variant of each type (variant types as described in (E)), stratified by disease time point. P values calculated using Fisher’s exact test.
Fig 3
Fig 3
Mutation frequencies in MYCN amplified and non-amplified tumors, and in the MAPK pathway A) Frequency of suspected driver genomic alterations (short variants, copy number changes, and genomic rearrangements and fusions; MYCN amplification events excluded) in patients with and without MYCN amplification. Bars represent number of patients with at least one lesion in a given gene, normalized by the number of patients in each category. B) Percentage of patients with any suspected driver variant in the MAPK pathway at diagnosis, after treatment, and at relapse. Patients with multiple mutations in the same gene are only counted once.

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