Intra-individual variation in G2 chromosomal radiosensitivity

A 4-Gene Signature of CDKN1, FDXR, SESN1 and PCNA Radiation Biomarkers for Prediction of Patient Radiosensitivity

The quest for the discovery and validation of radiosensitivity biomarkers is ongoing and while conventional bioassays are well established as biomarkers, molecular advances have unveiled new emerging biomarkers. Herein, we present the validation of a new 4-gene signature panel of CDKN1, FDXR, SESN1 and PCNA previously reported to be radiation-responsive genes, using the conventional G2 chromosomal radiosensitivity assay. Radiation-induced G2 chromosomal radiosensitivity at 0.05 Gy and 0.5 Gy IR is presented for a healthy control (n = 45) and a prostate cancer (n = 14) donor cohort. For the prostate cancer cohort, data from two sampling time points (baseline and Androgen Deprivation Therapy (ADT)) is provided, and a significant difference (p > 0.001) between 0.05 Gy and 0.5 Gy was evident for all donor cohorts. Selected donor samples from each cohort also exposed to 0.05 Gy and 0.5 Gy IR were analysed for relative gene expression of the 4-gene signature. In the healthy donor cohort, there was a significant difference in gene expression between IR dose for CDKN1, FXDR and SESN1 but not PCNA and no significant difference found between all prostate cancer donors, unless they were classified as radiation-induced G2 chromosomal radiosensitive. Interestingly, ADT had an effect on radiation response for some donors highlighting intra-individual heterogeneity of prostate cancer donors.

Prediction of the Acute or Late Radiation Toxicity Effects in Radiotherapy Patients Using Ex Vivo Induced Biodosimetric Markers: A Review

A search for effective methods for the assessment of patients' individual response to radiation is one of the important tasks of clinical radiobiology. This review summarizes available data on the use of ex vivo cytogenetic markers, typically used for biodosimetry, for the prediction of individual clinical radiosensitivity (normal tissue toxicity, NTT) in cells of cancer patients undergoing therapeutic irradiation. In approximately 50% of the relevant reports, selected for the analysis in peer-reviewed international journals, the average ex vivo induced yield of these biodosimetric markers was higher in patients with severe reactions than in patients with a lower grade of NTT. Also, a significant correlation was sometimes found between the biodosimetric marker yield and the severity of acute or late NTT reactions at an individual level, but this observation was not unequivocally proven. A similar controversy of published results was found regarding the attempts to apply G2- and γH2AX foci assays for NTT prediction. A correlation between ex vivo cytogenetic biomarker yields and NTT occurred most frequently when chromosome aberrations (not micronuclei) were measured in lymphocytes (not fibroblasts) irradiated to relatively high doses (4-6 Gy, not 2 Gy) in patients with various grades of late (not early) radiotherapy (RT) morbidity. The limitations of existing approaches are discussed, and recommendations on the improvement of the ex vivo cytogenetic testing for NTT prediction are provided. However, the efficiency of these methods still needs to be validated in properly organized clinical trials involving large and verified patient cohorts.

Seeking genetic signature of radiosensitivity--a novel method for data analysis in case of small sample sizes

Background

The identification of polymorphisms and/or genes responsible for an organism's radiosensitivity increases the knowledge about the cell cycle and the mechanism of the phenomena themselves, possibly providing the researchers with a better understanding of the process of carcinogenesis.

Aim

The aim of the study was to develop a data analysis strategy capable of discovering the genetic background of radiosensitivity in the case of small sample size studies.

Results

Among many indirect measures of radiosensitivity known, the level of radiation-induced chromosomal aberrations was used in the study. Mathematical modelling allowed the transformation of the yield-time curve of radiation-induced chromosomal aberrations into the exponential curve with limited number of parameters, while Gaussian mixture models applied to the distributions of these parameters provided the criteria for mouse strain classification. A detailed comparative analysis of genotypes between the obtained subpopulations of mice followed by functional validation provided a set of candidate polymorphisms that might be related to radiosensitivity. Among 1857 candidate relevant SNPs, that cluster in 28 genes, eight SNPs were detected nonsynonymous (nsSNP) on protein function. Two of them, rs48840878 (gene Msh3) and rs5144199 (gene Cc2d2a), were predicted as having increased probability of a deleterious effect. Additionally, rs48840878 is capable of disordering phosphorylation with 14 PKs. In silico analysis of candidate relevant SNP similarity score distribution among 60 CGD mouse strains allowed for the identification of SEA/GnJ and ZALENDE/EiJ mouse strains (95.26% and 86.53% genetic consistency respectively) as the most similar to radiosensitive subpopulation

Conclusions

A complete step-by-step strategy for seeking the genetic signature of radiosensitivity in the case of small sample size studies conducted on mouse models was proposed. It is shown that the strategy, which is a combination of mathematical modelling, statistical analysis and data mining methodology, allows for the discovery of candidate polymorphisms which might be responsible for radiosensitivity phenomena.