Despite recent improvements in childhood cancer survival, survivors remain at increased risk for late effects such as subsequent malignant neoplasms (SMNs). Thyroid SMN is among the most prevalent SMNs in childhood cancer survivors, and advanced disease is associated with significant treatment-related morbidities. A current risk prediction model for thyroid SMN, developed for the Childhood Cancer Survivor Study (CCSS) cohort, includes only non-genetic risk factors, such as female gender, age at diagnosis, and therapeutic radiation exposure. Short telomeres are a genetic risk factor for primary cancer risk, but the impact of telomere length upon SMN is just emerging. The PI has conducted one of the first studies addressing this question, with recently published results showing short telomeres associated with thyroid SMN in the CCSS cohort. Because radiation contributes to telomere shortening, we hypothesize that radiation-exposed childhood cancer survivors with underlying genetic defects in telomere maintenance are at highest risk for developing thyroid SMN. Our goal is to elucidate telomere biology defects underlying risk for thyroid SMN using CCSS genotyping data and biorepository samples. We will use our results to improve the existing thyroid SMN risk prediction model in the CCSS cohort, and then test our model for reproducibility in a distinct Children's Oncology Group (COG) study. We will test our hypothesis in three Specific Aims (SA). SA1 leverages existing CCSS genotyping data to determine if single nucleotide polymorphisms (SNPs) associated with impaired telomere maintenance distinguish survivors with thyroid SMN compared with survivors without SMN, and contribute to telomere length as estimated by qPCR. SA2 asks if rare and deleterious mutations in telomere maintenance genes are enriched in survivors with thyroid SMN as compared with survivors without SMN and cancer-naive controls. Mutations identified will be tested for functional impact in vitro, using established telomerase activity assays and flow FISH for telomere length in lymphocyte subsets. SA3 will extend a previously validated risk prediction model for thyroid SMN, measuring the added impact of genetic factors including (1) top telomere maintenance SNPs associated with SMN in the CCSS, (2) top telomere maintenance SNPs found in SA1, and (3) SNPs previously associated with telomere length. The model will then be tested in a distinct COG survivor study. We expect a risk prediction model inclusive of genetic factors to improve our ability to identify childhood cancer survivors at highest risk for thyroid SMN. At-risk survivors are now screened for thyroid SMN by thyroid gland palpation, a technique that is relatively insensitive. We expect our model to justify use of more sensitive screening modalities, such as ultrasound, in targeted populations, thereby substantially reducing the impact of a prevalent SMN upon non-relapse related morbidities. By establishing a role for genetic risk factors such as telomere maintenance defects in predicting late effects such as thyroid SMN, this study has the potential to transform how we approach risk determination for late effects common to childhood cancer survivors.

Public Health Relevance

Although survival from childhood cancer has improved significantly, survivors continue to be at risk for numerous serious late effects of cancer therapy such as subsequent malignant neoplasms (SMNs). We have recently shown that a specific genetic marker is predictive of risk for thyroid SMN, one of the most prevalent SMNs in the childhood cancer survivor population. The goal of this proposal is to further explore the biology behind this association, and to develop an effective tool for screening childhood cancer survivors that will facilitate implementation of preventive measures for those at highest risk for thyroid SMN.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA194473-03
Application #
9339623
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Shelburne, Nonniekaye F
Project Start
2015-09-01
Project End
2019-08-31
Budget Start
2017-09-01
Budget End
2018-08-31
Support Year
3
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Baylor College of Medicine
Department
Pediatrics
Type
Schools of Medicine
DUNS #
051113330
City
Houston
State
TX
Country
United States
Zip Code
77030