Dataset Information

Clinical Impact of Tumor Mutational Burden in Neuroblastoma.

ABSTRACT:

Background

Neuroblastoma is the most common pediatric extracranial solid tumor. Within conventional risk groups, there is considerable heterogeneity in outcomes, indicating the need for improved risk stratification.

Methods

In this study we analyzed the somatic mutational burden of 515 primary, untreated neuroblastoma tumors from three independent cohorts. Mutations in coding regions were determined by whole-exome/genome sequencing of tumor samples compared to matched blood leukocytes. Survival data for 459 patients were available for analysis of 5-year overall survival using the Kaplan-Meier method and log-rank test. All statistical tests were two-sided.

Results

Despite a low overall somatic mutational burden (mean = 3, range = 0-56), 107 patients were considered to have high mutational burden (>3 mutations). Unfavorable histology and age 18?months and older were associated with high mutational burden. Patients with high mutational burden had inferior 5-year overall survival (29.0%, 95% confidence interval [CI] = 17.2 to 41.8%) vs those with three or fewer somatic mutations (76.2%, 95% CI = 71.5 to 80.3%) (log-rank P?ConclusionsThis study demonstrates that mutational burden of primary neuroblastoma may be useful in combination with conventional risk factors to optimize risk stratification and guide treatment decisions, pending prospective validation.

SUBMITTER: Hwang WL

PROVIDER: S-EPMC6624164 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Publications

Clinical Impact of Tumor Mutational Burden in Neuroblastoma.

Hwang William L WL Wolfson Rachel L RL Niemierko Andrzej A Marcus Karen J KJ DuBois Steven G SG Haas-Kogan Daphne D

Journal of the National Cancer Institute 20190701 7

<h4>Background</h4>Neuroblastoma is the most common pediatric extracranial solid tumor. Within conventional risk groups, there is considerable heterogeneity in outcomes, indicating the need for improved risk stratification.<h4>Methods</h4>In this study we analyzed the somatic mutational burden of 515 primary, untreated neuroblastoma tumors from three independent cohorts. Mutations in coding regions were determined by whole-exome/genome sequencing of tumor samples compared to matched blood leukoc ...[more]

PMID: 30307503

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Project description:BACKGROUND:Tumor mutational burden (TMB) measurement is limited by low tumor purity of samples, which can influence prediction of the immunotherapy response, particularly when using whole-exome sequencing-based TMB (wTMB). This issue could be overcome by targeted panel sequencing-based TMB (pTMB) with higher depth of coverage, which remains unexplored. METHODS:We comprehensively reanalyzed four public datasets of immune checkpoint inhibitor (ICI)-treated cohorts (adopting pTMB or wTMB) to test each biomarker's predictive ability for low purity samples (cut-off: 30%). For validation, paired genomic profiling with the same tumor specimens was performed to directly compare wTMB and pTMB in patients with breast cancer (paired-BRCA, n=165) and ICI-treated patients with advanced non-small-cell lung cancer (paired-NSCLC, n=156). RESULTS:Low tumor purity was common (range 30%-45%) in real-world samples from ICI-treated patients. In the survival analyzes of public cohorts, wTMB could not predict the clinical benefit of immunotherapy when tumor purity was low (log-rank p=0.874), whereas pTMB could effectively stratify the survival outcome (log-rank p=0.020). In the paired-BRCA and paired-NSCLC cohorts, pTMB was less affected by tumor purity, with significantly more somatic variants identified at low allele frequency (p<0.001). We found that wTMB was significantly underestimated in low purity samples with a large proportion of clonal variants undetected by whole-exome sequencing. Interestingly, pTMB more accurately predicted progression-free survival (PFS) after immunotherapy than wTMB owing to its superior performance in the low tumor purity subgroup (p=0.054 vs p=0.358). Multivariate analysis revealed pTMB (p=0.016), but not wTMB (p=0.32), as an independent predictor of PFS even in low-purity samples. The net reclassification index using pTMB was 21.7% in the low-purity subgroup (p=0.016). CONCLUSIONS:Our data suggest that TMB characterization with targeted deep sequencing might have potential strength in predicting ICI responsiveness due to its enhanced sensitivity for hard-to-detect variants at low-allele fraction. Therefore, pTMB could act as an invaluable biomarker in the setting of both clinical trials and practice outside of trials based on its reliable performance in mitigating the purity-related bias.

Dataset Information

Clinical Impact of Tumor Mutational Burden in Neuroblastoma.

Background

Methods

Results

Publications

Clinical Impact of Tumor Mutational Burden in Neuroblastoma.

Similar Datasets

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