A substantial increase in papillary thyroid carcinoma (PTC) among children exposed to the radioiodine fallout has been one of the main consequences of the Chernobyl reactor accident. Recently, the investigation of PTCs from a cohort of young patients exposed to the post-Chernobyl radioiodine fallout at very young age and a matched nonexposed control group revealed a radiation-specific DNA copy number gain on chromosomal band 7q11.23 and the radiation-associated mRNA overexpression of CLIP2. In this study, we investigated the potential role of CLIP2 as a radiation marker to be used for the individual classification of PTCs into CLIP2-positive and -negative cases-a prerequisite for the integration of CLIP2 into epidemiological modelling of the risk of radiation-induced PTC. We were able to validate the radiation-associated CLIP2 overexpression at the protein level by immunohistochemistry (IHC) followed by relative quantification using digital image analysis software (P=0.0149). Furthermore, we developed a standardized workflow for the determination of CLIP2-positive and -negative cases that combines visual CLIP2 IHC scoring and CLIP2 genomic copy number status. In addition to the discovery cohort (n=33), two independent validation cohorts of PTCs (n=115) were investigated. High sensitivity and specificity rates for all three investigated cohorts were obtained, demonstrating robustness of the developed workflow. To analyse the function of CLIP2 in radiation-associated PTC, the CLIP2 gene regulatory network was reconstructed using global mRNA expression data from PTC patient samples. The genes comprising the first neighbourhood of CLIP2 (BAG2, CHST3, KIF3C, NEURL1, PPIL3 and RGS4) suggest the involvement of CLIP2 in the fundamental carcinogenic processes including apoptosis, mitogen-activated protein kinase signalling and genomic instability. In our study, we successfully developed and independently validated a workflow for the typing of PTC clinical samples into CLIP2-positive and CLIP2-negative and provided first insights into the CLIP2 interactome in the context of radiation-associated PTC.

Gene expression time-course experiments allow to study the dynamics of transcriptomic changes in cells exposed to different stimuli. However, most approaches for the reconstruction of gene association networks (GANs) do not propose prior-selection approaches tailored to time-course transcriptome data. Here, we present a workflow for the identification of GANs from time-course data using prior selection of genes differentially expressed over time identified by natural cubic spline regression modeling (NCSRM). The workflow comprises three major steps: 1) the identification of differentially expressed genes from time-course expression data by employing NCSRM, 2) the use of regularized dynamic partial correlation as implemented in GeneNet to infer GANs from differentially expressed genes and 3) the identification and functional characterization of the key nodes in the reconstructed networks. The approach was applied on a time-resolved transcriptome data set of radiation-perturbed cell culture models of non-tumor cells with normal and increased radiation sensitivity. NCSRM detected significantly more genes than another commonly used method for time-course transcriptome analysis (BETR). While most genes detected with BETR were also detected with NCSRM the false-detection rate of NCSRM was low (3%). The GANs reconstructed from genes detected with NCSRM showed a better overlap with the interactome network Reactome compared to GANs derived from BETR detected genes. After exposure to 1 Gy the normal sensitive cells showed only sparse response compared to cells with increased sensitivity, which exhibited a strong response mainly of genes related to the senescence pathway. After exposure to 10 Gy the response of the normal sensitive cells was mainly associated with senescence and that of cells with increased sensitivity with apoptosis. We discuss these results in a clinical context and underline the impact of senescence-associated pathways in acute radiation response of normal cells. The workflow of this novel approach is implemented in the open-source Bioconductor R-package splineTimeR.

BackgroundAcquired and inherent radioresistance of tumor cells is related to tumor relapse and poor prognosis – not only in head and neck squamous cell carcinoma (HNSCC). The underlying molecular mechanisms are largely unknown. Therefore, systemic in-depth analyses are needed to identify key regulators of radioresistance. In the present study, subclones of the CAL-33 HNSCC cell line with different radiosensitivity were analyzed to identify signaling pathways related to the different phenotypes.MethodsSubclones with altered radiosensitivity were generated by fractionated irradiation of the parental CAL-33 cells. Differences in radiosensitivity were confirmed in colony formation assays. Selected subclones were characterized at the genomic and transcriptomic level by SKY, array CGH, and mRNA-microarray analyses. Time-course gene expression analyses upon irradiation using a natural cubic spline regression model identified temporally differentially expressed genes. Moreover, early and late responding genes were identified. Gene association networks were reconstructed using partial correlation. The Reactome pathway database was employed to conduct pathway enrichment analyses.ResultsThe characterization of two subclones with enhanced radiation resistance (RP) and enhanced radiosensitivity (SP) revealed distinct genomic and transcriptomic changes compared to the parental cells. Differentially expressed genes after irradiation shared by both subclones pointed to important pathways of the early and late radiation response, including senescence, apoptosis, DNA repair, Wnt, PI3K/AKT, and Rho GTPase signaling. The analysis of the most important nodes of the gene association networks revealed pathways specific to the radiation response in different phenotypes of radiosensitivity. Exemplarily, for the RP subclone the senescence-associated secretory phenotype (SASP) together with GPCR ligand binding were considered as crucial. Also, the expression of endogenous retrovirus ERV3-1in response to irradiation has been observed, and the related gene association networks have been identified.ConclusionsOur study presents comprehensive gene expression data of CAL-33 subclones with different radiation sensitivity. The resulting networks and pathways associated with the resistant phenotype are of special interest and include the SASP. The radiation-associated expression of ERV3-1 also appears highly attractive for further studies of the molecular mechanisms underlying acquired radioresistance. The identified pathways may represent key players of radioresistance, which could serve as potential targets for molecularly designed, therapeutical intervention.Electronic supplementary materialThe online version of this article (doi:10.1186/s13014-016-0672-0) contains supplementary material, which is available to authorized users.

SummaryThis study showed a clear dose-response relationship for the CLIP2 radiation marker in post-Chernobyl papillary thyroid carcinoma cohorts for young patients and hints to different molecular mechanisms in tumors induced at low doses compared to moderate/high doses.

Strong evidence for the statistical association between radiation exposure and disease has been produced for thyroid cancer by epidemiological studies after the Chernobyl accident. However, limitations of the epidemiological approach in order to explore health risks especially at low doses of radiation appear obvious. Statistical fluctuations due to small case numbers dominate the uncertainty of risk estimates. Molecular radiation markers have been searched extensively to separate radiation-induced cancer cases from sporadic cases. The overexpression of the CLIP2 gene is the most promising of these markers. It was found in the majority of papillary thyroid cancers (PTCs) from young patients included in the Chernobyl tissue bank. Motivated by the CLIP2 findings we propose a mechanistic model which describes PTC development as a sequence of rate-limiting events in two distinct paths of CLIP2-associated and multistage carcinogenesis. It integrates molecular measurements of the dichotomous CLIP2 marker from 141 patients into the epidemiological risk analysis for about 13 000 subjects from the Ukrainian-American cohort which were exposed below age 19 years and were put under enhanced medical surveillance since 1998. For the first time, a radiation risk has been estimated solely from marker measurements. Cross checking with epidemiological estimates and model validation suggests that CLIP2 is a marker of high precision. CLIP2 leaves an imprint in the epidemiological incidence data which is typical for a driver gene. With the mechanistic model, we explore the impact of radiation on the molecular landscape of PTC. The model constitutes a unique interface between molecular biology and radiation epidemiology.