[HTML][HTML] Clinical and genetic risk prediction of subsequent CNS tumors in survivors of childhood cancer: a report from the COG ALTE03N1 study

X Wang, CL Sun, L Hageman, K Smith… - Journal of Clinical …, 2017 - ncbi.nlm.nih.gov
X Wang, CL Sun, L Hageman, K Smith, P Singh, S Desai, DS Hawkins, MM Hudson…
Journal of Clinical Oncology, 2017ncbi.nlm.nih.gov
Purpose Survivors of childhood cancer treated with cranial radiation therapy are at risk for
subsequent CNS tumors. However, significant interindividual variability in risk suggests a
role for genetic susceptibility and provides an opportunity to identify survivors of childhood
cancer at increased risk for these tumors. Methods We curated candidate genetic variants
from previously published studies in adult-onset primary CNS tumors and replicated these in
survivors of childhood cancer with and without subsequent CNS tumors (82 participants and …
Abstract
Purpose
Survivors of childhood cancer treated with cranial radiation therapy are at risk for subsequent CNS tumors. However, significant interindividual variability in risk suggests a role for genetic susceptibility and provides an opportunity to identify survivors of childhood cancer at increased risk for these tumors.
Methods
We curated candidate genetic variants from previously published studies in adult-onset primary CNS tumors and replicated these in survivors of childhood cancer with and without subsequent CNS tumors (82 participants and 228 matched controls). We developed prediction models to identify survivors at high or low risk for subsequent CNS tumors and validated these models in an independent matched case-control sample (25 participants and 54 controls).
Results
We demonstrated an association between six previously published single nucleotide polymorphisms (rs15869 [BRCA2], rs1805389 [LIG4], rs8079544 [TP53], rs25489 [XRCC1], rs1673041 [POLD1], and rs11615 [ERCC1]) and subsequent CNS tumors in survivors of childhood cancer. Including genetic variants in a Final Model containing age at primary cancer, sex, and cranial radiation therapy dose yielded an area under the curve of 0.81 (95% CI, 0.76 to 0.86), which was superior (P=. 002) to the Clinical Model (area under the curve, 0.73; 95% CI, 0.66 to 0.80). The prediction model was successfully validated. The sensitivity and specificity of predicting survivors of childhood cancer at highest or lowest risk of subsequent CNS tumors was 87.5% and 83.5%, respectively.
Conclusion
It is possible to identify survivors of childhood cancer at high or low risk for subsequent CNS tumors on the basis of genetic and clinical information. This information can be used to inform surveillance for early detection of subsequent CNS tumors.
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