Biologically-based modeling of radiation risk and biomarker prevalence for papillary thyroid cancer in Japanese a-bomb survivors 1958–2005

Abstract

Purpose

Thyroid cancer of papillary histology (PTC) is the dominant type in radio-epidemiological cohorts established after nuclear accidents or warfare. Studies on post-Chernobyl PTC and on thyroid cancer in the life span study (LSS) of Japanese a-bomb survivors consistently revealed high radiation risk after exposure during childhood and adolescence. For post-Chernobyl risk assessment overexpression of the CLIP2 gene was proposed as molecular biomarker to separate radiogenic from sporadic PTC. Based on such binary marker a biologically-based risk model of PTC carcinogenesis has been developed for observational Chernobyl data. The model featured two independent molecular pathways of disease development, of which one was associated with radiation exposure. To gain credibility the concept for a mechanistic risk model must be based on general biological features which transcend findings in a single cohort. The purpose of the present study is therefore to demonstrate portability of the model concept by application to PTC incidence data in the LSS. By exploiting the molecular two-path concept we improve the determination of the probability of radiation causing cancer (POC).

Materials and methods

The current analysis uses thyroid cancer incidence data of the LSS with thyroid cancer diagnoses and papillary histology (n = 292) from the follow-up period between 1958 and 2005. Risk analysis was performed with both descriptive and biologically-based models.

Results

Judged by goodness-of-fit all applied models described the data almost equally well. They yielded similar risk estimates in cohorts post-Chernobyl and LSS. The preferred mechanistic model was selected by biological plausibility. It reflected important features of an imperfect radiation marker which are not easily addressed by descriptive models. Precise model predictions of marker prevalence in strata of epidemiological covariables can be tested by molecular measurements. Application of the radiation-related molecular pathway from our preferred model in retrospective risk assessment decreases the threshold dose for 50% POC from 0.33 (95% confidence interval (CI) 0.18; 0.64) Gy to 0.04 (95% CI 0.01; 0.19) Gy for females and from 0.43 (95% CI 0.17; 1.84) Gy to 0.19 (95% CI 0.05; 1.00) Gy for males. These improvements are still not sufficient to separate radiation-induced from sporadic PTC cases at very low doses <0.015 Gy typical for the Fukushima accident.

Conclusions

Successful application of our preferred mechanistic model to LSS incidence data confirms and improves the biological two-path concept of radiation-induced PTC. Model predictions suggest further molecular validation studies to consolidate the basis of biologically-based risk estimation.

Keywords:

• Papillary thyroid cancer
• radiation risk
• biomarker prevalence
• Japanese a-bomb survivors
• mechanistic modeling of carcinogenesis

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Panels A, B of Figure 1 in Takano (2017) represent PTC development along the MSC pathway.

2 Panel C of Figure 1 in Takano (2017) schematically depicts PTC development along the C2C pathway.

Additional information

Notes on contributors

Jan Christian Kaiser

Dr. Jan Christian Kaiser leads the working group “Integrative Modeling” in the Institute of Radiation Medicine at the Helmholtz Zentrum München, German Research Center for Environmental Health, in Munich, Germany. He holds a doctoral and masters’ degree in statistical physics. His research involves integration of molecular biology and radiation epidemiology in biologically-based risk models.

Munechika Misumi

Dr. Munechika Misumi is the Associate Senior Scientist in the Department of Statistics, Radiation Effects Research Foundation in Hiroshima, Japan. He has a Ph.D. and a Master of Statistics with biomedical concentration. He has been involved in a variety of epidemiological and biological studies based on the cohort of atomic bomb survivors. His research interests include statistical methodologies for radiation epidemiology, measurement errors in the regression analysis, and biological modeling.

Kyoji Furukawa

Dr. Kyoji Furukawa is a professor at Biostatistics Center, Kurume University, Japan. He has been a researcher in biostatistics and radiation research, and his recent interests include methodological development for radiation risk assessment.