Screening radiation-differentially expressed circular RNAs and establishing dose classification models in the human lymphoblastoid cell line AHH-1

Abstract

Purpose

In the event of a large-scale radiological accident, rapid and high-throughput biodosimetry is the most vital basis in medical resource allocation for the prompt treatment of victims. However, the current biodosimeter is yet to be rapid and high-throughput. Studies have shown that ionizing radiation modulates expressions of circular RNAs (circRNAs) in healthy human cell lines and tumor tissue. circRNA expressions can be quantified rapidly and high-throughput. However, whether circRNAs are suitable for early radiation dose classification remains unclear.

Methods

We employed transcriptome sequencing and bioinformatics analysis to screen for radiation-differentially expressed circRNAs in the human lymphoblastoid cell line AHH-1 at 4 h following exposure to 0, 2, and 5 Gy ⁶⁰Co γ-rays. The dose–response relationships between differentially expressed circRNA expressions and absorbed doses were investigated using real-time polymerase chain reaction and linear regression analysis at 4 h, 24 h, and 48 h post-exposure to 0, 2, 4, 6, and 8 Gy. Six distinct dose classification models of circRNA panels were established and validated by receiver operating characteristic (ROC) curve analysis.

Results

A total of 11 radiation-differentially expressed circRNAs were identified and validated. Based on dose–response effects, those circRNAs changed in a dose-responsive or dose-dependent manner were combined into panels A through F at 4 h, 24 h, and 48 h post-irradiation. ROC curve analysis showed that panels A through C had the potential to effectively classify exposed and non-exposed conditions, which area under the curve (AUC) of these three panels were all 1.000, and the associate p values were .009. Panels D through F excellently distinguished between different dose groups (AUC = 0.963–1.000, p < .05). The validation assay showed that panels A through F demonstrated consistent excellence in sensitivity and specificity in dose classification.

Conclusions

Ionizing radiation can indeed modulate the circRNA expression profile in the human lymphoblastoid cell line AHH-1. The differentially expressed circRNAs exhibit the potential for rapid and high-throughput dose classification.

Keywords:

• CircRNAs
• dose classification
• biomarker
• transcriptomics
• ionizing radiation

Acknowledgements

All authors wish to thank Dr. Ling Gao for her important suggestions.

Author contributions

X.L.T. and Q.J.L. designed the study. T.T.Z. and T.J.C. performed the cell culture and cell irradiation. X.L.T. performed all the molecular biology assays, the data collection, and the data analysis. X.L.T. drafted the manuscript. Q.J.L. and M.T. commented on previous versions of the manuscript. All authors have read and approved the final manuscript.

Disclosure statement

The authors report there are no competing interests to declare.

Data availability statement

All the transcriptomic data generated and analyzed during the current study are available in the GEO repository under the accession GSE218844 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE218844). All the other data generated and analyzed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant No. 82173463 to Q. J. L.

Notes on contributors

Xue-Lei Tian

Xue-Lei Tian, Ph.D., is an associate research fellow at the China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention.

Ting-Ting Zhang

Ting-Ting Zhang, Ph.D. candidate, is a student at the China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention.

Tian-Jing Cai

Tian-Jing Cai, M.D., is an associate research fellow at the China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention.

Mei Tian

Mei Tian, Ph.D., is a professor at the China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention.

Qing-Jie Liu

Qing-Jie Liu, Ph.D., is a professor at the China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention.