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Polygenic risk scores, radiation treatment exposures and subsequent cancer risk in childhood cancer survivors

Nature Medicine volume 30, pages 690–698 (2024)Cite this article

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Abstract

Survivors of childhood cancer are at increased risk for subsequent cancers attributable to the late effects of radiotherapy and other treatment exposures; thus, further understanding of the impact of genetic predisposition on risk is needed. Combining genotype data for 11,220 5-year survivors from the Childhood Cancer Survivor Study and the St Jude Lifetime Cohort, we found that cancer-specific polygenic risk scores (PRSs) derived from general population, genome-wide association study, cancer loci identified survivors of European ancestry at increased risk of subsequent basal cell carcinoma (odds ratio per s.d. of the PRS: OR = 1.37, 95% confidence interval (CI) = 1.29–1.46), female breast cancer (OR = 1.42, 95% CI = 1.27–1.58), thyroid cancer (OR = 1.48, 95% CI = 1.31–1.67), squamous cell carcinoma (OR = 1.20, 95% CI = 1.00–1.44) and melanoma (OR = 1.60, 95% CI = 1.31–1.96); however, the association for colorectal cancer was not significant (OR = 1.19, 95% CI = 0.94–1.52). An investigation of joint associations between PRSs and radiotherapy found more than additive increased risks of basal cell carcinoma, and breast and thyroid cancers. For survivors with radiotherapy exposure, the cumulative incidence of subsequent cancer by age 50 years was increased for those with high versus low PRS. These findings suggest a degree of shared genetic etiology for these malignancy types in the general population and survivors, which remains evident in the context of strong radiotherapy-related risk.

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Fig. 1: Associations between cancer-specific PRSs and risk of specific subsequent cancer type among survivors of childhood cancer of European ancestry.
Fig. 2: Joint associations between radiation exposure and PRSs.
Fig. 3: Cumulative incidence of subsequent cancers among survivors of childhood cancer of European ancestry with follow-up starting at age 21 years.

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Data availability

Genotype data from the CCSS for survivors diagnosed in 1970–1986, as well as relevant phenotype data for survivors diagnosed in 1970–1999, are accessible via dbGaP (accession. no. phs001327.v1.p1). Genotype and phenotype data from the SJLIFE (accession no. SJC-DS-1002) and genotype data from the CCSS (accession no. SJC-DS-1005) for survivors diagnosed in 1987–1999 are accessible through the St Jude Cloud Survivorship Portal (https://stjude.cloud).

Code availability

The SAS and R codes for the main statistical analyses are available at https://github.com/gibsontm/PRSandRT-secondcancer.git.

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Acknowledgements

This analysis and the CCSS GWAS were supported by the Intramural Research Program of the National Cancer Institute, the National Institutes of Health and the US Department of Health and Human Services. A portion of the CCSS genotyping was supported by the Leukemia & Lymphoma Society (K. Kamdar, principal investigator). CCSS is supported by the National Cancer Institute (no. CA55727 to G.T.A., principal investigator). The SJLIFE is supported by the National Cancer Institute (U01 CA195547, M. M. Hudson and K. K. Ness, principal investigators; Cancer Center Support (CORE) grant no. CA21765, C. Roberts, principal investigator) and the American Lebanese Syrian Associated Charities. The opinions expressed by the authors are their own and this material should not be interpreted as representing the official viewpoint of the US Department of Health and Human Services, the National Institutes of Health or the National Cancer Institute.

Author information

Authors and Affiliations

  1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    Todd M. Gibson, Danielle M. Karyadi, Stephen W. Hartley, Vidushi Kapoor, Joshua N. Sampson, Stephen J. Chanock & Lindsay M. Morton

  2. Department of Pathology, Children’s Hospital of Colorado, University of Colorado, Denver, CO, USA

    Michael A. Arnold

  3. Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK

    Amy Berrington de Gonzalez

  4. Department of Pathology and Laboratory Medicine, Nationwide Children’s Hospital, Columbus, OH, USA

    Miriam R. Conces

  5. Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Rebecca M. Howell

  6. Cancer Prevention and Clinical Statistics Programs, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Wendy M. Leisenring

  7. Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA

    Joseph P. Neglia & Lucie M. Turcotte

  8. Department of Epidemiology and Cancer Control, St Jude Children’s Research Hospital, Memphis, TN, USA

    Gregory T. Armstrong

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Contributions

T.M.G., D.M.K., S.J.C. and L.M.M. conceived and designed the study. M.A.A., M.R.C., R.M.H., W.M.L., J.P.N., L.M.T. and G.T.A. contributed to data collection, exposure assessment and outcome ascertainment. T.M.G., D.M.K., S.W.H., V.K., J.N.S. and L.M.M. contributed to the data analysis. T.M.G. and L.M.M. drafted the manuscript. A.B.G. and all other authors contributed to data interpretation and critically reviewed and revised the manuscript. All authors approved the final version of the manuscript for publication.

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Correspondence to Todd M. Gibson.

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Nature Medicine thanks Alanna Church, Michael Hauptmann and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Ming Yang, in collaboration with the Nature Medicine team.

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Extended data

Extended Data Fig. 1 Associations between cancer-specific polygenic risk score (PRS) and risk of specific subsequent neoplasm type among European ancestry survivors of childhood cancer.

Associations between cancer-specific polygenic risk score (PRS) and risk of specific subsequent neoplasm type among European ancestry survivors of childhood cancer with a categorical PRS variable based on deciles of PRS among unique controls, where odds ratio indicates relative risk compared to the lowest PRS decile (decile 1). Cases were matched to 2–100 controls based on study, sex, age at childhood cancer diagnosis, and follow-up time. Multivariable conditional logistic regression models included childhood cancer diagnosis type, ancestry, age at childhood cancer diagnosis, radiation dose to the body region of the subsequent cancer, and chemotherapy exposure. Data are presented as odds ratio with 95% confidence interval. Numbers of cases and controls and odds ratios for each decile are provided in Supplementary Table 3.

Extended Data Fig. 2 Associations between cancer-specific polygenic risk score (PRS) and risk of specific subsequent neoplasm type among European ancestry survivors of childhood cancer by cohort.

Associations between cancer-specific polygenic risk score (PRS) and risk of specific subsequent neoplasm type among European ancestry survivors of childhood cancer by cohort (CCSS: Childhood Cancer Survivor Study; SJLIFE: St. Jude Lifetime Cohort Study), with a continuous, standardized PRS (mean = 0, standard deviation = 1), where odds ratio indicates relative risk per one standard deviation change in PRS. Cases were matched to 2–100 controls based on study, sex, age at childhood cancer diagnosis, and follow-up time. Multivariable conditional logistic regression models included childhood cancer diagnosis type, ancestry, age at childhood cancer diagnosis, radiation dose to the body region of the subsequent cancer, and chemotherapy exposure. Data are presented as odds ratio with 95% confidence interval.

Extended Data Fig. 3 Associations between cancer-specific polygenic risk score (PRS) and risk of specific subsequent neoplasm type among European ancestry and non-European ancestry survivors of childhood cancer.

Associations between cancer-specific polygenic risk score (PRS) and risk of specific subsequent neoplasm type among survivors of childhood cancer with a continuous, standardized PRS (mean = 0, standard deviation = 1), where odds ratio indicates relative risk per one standard deviation change in PRS. Cases were matched to 2–100 controls based on study, sex, age at childhood cancer diagnosis, and follow-up time. Multivariable models included adjustment for age at childhood cancer diagnosis, type of childhood cancer diagnosis, radiation dose to the body region of the subsequent cancer, and receipt of chemotherapy. Blue diamonds represent the association for survivors of European ancestry, and black circles represent the associations for survivors of non-European ancestry. Data are presented as odds ratio with 95% confidence interval.

Extended Data Fig. 4 Cumulative incidence of subsequent cancer among European ancestry childhood cancer survivors categorized by joint categories of binary PRS and more detailed radiotherapy (RT).

Cumulative incidence of subsequent cancer among European ancestry childhood cancer survivors with follow-up starting at age 21 years. Joint categories were defined by binary PRS (low PRS: PRS < median among controls; high PRS: ≥ median) and more detailed radiotherapy (RT) categories. For basal cell carcinoma (Panel A), RT was categorized (RT < 1 Gray; RT 1 to <10 Gray; RT ≥ 10 Gray) based on maximum skin RT dose (maximum delivered dose to any body region divided by two). For breast cancer (Panel B), RT was categorized (RT < 10 Gray; RT 10 to <30 Gray; RT ≥ 30 Gray) based on maximum delivered chest RT dose. Lines represent the cumulative incidence and shaded areas around each cumulative incidence curve represent the 95% confidence bands. Gray’s test was used to test for heterogeneity among the cumulative incidence curves for joint PRS-radiotherapy categories, with statistical significance defined as p < 0.05 in two-sided tests. The table beneath each figure shows the number of survivors at risk by joint category group at age 21 and at successive age decades.

Extended Data Fig. 5 Cumulative incidence of subsequent basal cell carcinoma among European ancestry childhood cancer survivors categorized by joint categories of PRS quintiles and binary radiotherapy (RT).

Cumulative incidence of subsequent basal cell carcinoma among European ancestry childhood cancer survivors with follow-up starting at age 21 years. Joint categories were defined by quintiles of PRS among controls and binary RT categories. RT was categorized (RT low: RT < 1 Gray; RT high: RT ≥ 1 Gray) based on maximum skin RT dose (maximum delivered dose to any body region divided by two). Lines represent the cumulative incidence and shaded areas around each cumulative incidence curve represent the 95% confidence bands. Gray’s test was used to test for heterogeneity among the cumulative incidence curves for joint PRS-radiotherapy categories, with statistical significance defined as p < 0.05 in two-sided tests. The table beneath the figure shows the number of survivors at risk by joint category group at age 21 and at successive age decades.

Extended Data Fig. 6 Cumulative incidence of subsequent breast cancer among European ancestry female childhood cancer survivors categorized by joint categories of PRS quintiles and binary radiotherapy (RT).

Cumulative incidence of subsequent breast cancer among European ancestry female childhood cancer survivors with follow-up starting at age 21 years. Joint categories were defined by quintiles of PRS among controls and binary RT categories. RT was categorized (RT low: RT < 10 Gray; RT high: RT ≥ 10 Gray) based on maximum RT dose delivered to the chest. Lines represent the cumulative incidence and shaded areas around each cumulative incidence curve represent the 95% confidence bands. Gray’s test was used to test for heterogeneity among the cumulative incidence curves for joint PRS-radiotherapy categories, with statistical significance defined as p < 0.05 in two-sided tests. The table beneath the figure shows the number of survivors at risk by joint category group at age 21 and at successive age decades.

Extended Data Fig. 7 Cumulative incidence of subsequent thyroid cancer among European ancestry childhood cancer survivors categorized by joint categories of PRS quintiles and binary radiotherapy (RT).

Cumulative incidence of subsequent thyroid cancer among European ancestry childhood cancer survivors with follow-up starting at age 21 years. Joint categories were defined by quintiles of PRS among controls and binary RT categories. RT was categorized (RT low: RT < 10 Gray; RT high: RT ≥ 10 Gray) based on maximum RT dose delivered to the neck. Lines represent the cumulative incidence and shaded areas around each cumulative incidence curve represent the 95% confidence bands. Gray’s test was used to test for heterogeneity among the cumulative incidence curves for joint PRS-radiotherapy categories, with statistical significance defined as p < 0.05 in two-sided tests. The table beneath the figure shows the number of survivors at risk by joint category group at age 21 and at successive age decades.

Extended Data Fig. 8 Cumulative incidence of subsequent squamous cell carcinoma and melanoma among European ancestry childhood cancer survivors categorized by joint categories of binary PRS and binary radiotherapy (RT).

Cumulative incidence of subsequent squamous cell carcinoma and melanoma among European ancestry childhood cancer survivors with follow-up starting at age 21 years. Groups were defined by joint categories of PRS (low PRS: PRS < median among controls; high PRS: PRS ≥ median) and RT dose. For squamous cell carcinoma (Panel A) and melanoma (Panel B), RT was categorized (low RT: RT < 1 Gray; high RT: RT ≥ 1 Gray) based on maximum skin RT dose (maximum delivered dose to any body region divided by two). Lines represent the cumulative incidence and shaded areas around each cumulative incidence curve represent the 95% confidence bands. Gray’s test was used to test for heterogeneity among the cumulative incidence curves for joint PRS-radiotherapy categories, with statistical significance defined as p < 0.05 in two-sided tests. The table beneath each figure shows the number of survivors at risk by joint category group at age 21 and at successive age decades.

Extended Data Table 1 Joint associations between detailed radiation dose categories and binary polygenic risk score (PRS) for risk of subsequent neoplasms among European ancestry survivors of childhood cancer
Full size table
Extended Data Table 2 Joint associations between binary radiation exposure and quintiles of polygenic risk score (PRS) for risk of subsequent neoplasms among European ancestry survivors of childhood cancer
Full size table

Supplementary information

Reporting Summary

Supplementary Table 1

Selected characteristics of survivors of childhood cancer of predominantly European ancestry with high-quality genotype data used to create the case-control sets.

Supplementary Table 2

Associations between cancer-specific PRS categorized based on quintiles among unique controls and risk of specific subsequent cancer type among survivors of childhood cancer.

Supplementary Table 3

Associations between cancer-specific PRS categorized based on deciles among unique controls and risk of specific subsequent cancer type among survivors of childhood cancer.

Supplementary Tables 4 and 5

Supplementary Table 4 Previous studies used for PRS construction. Supplementary Table 5 Germline variants that included the six PRS interrogated in the CCSS and SJLIFE cohorts.

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Gibson, T.M., Karyadi, D.M., Hartley, S.W. et al. Polygenic risk scores, radiation treatment exposures and subsequent cancer risk in childhood cancer survivors. Nat Med 30, 690–698 (2024). https://doi.org/10.1038/s41591-024-02837-7

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