Effects of cyclophosphamide and mitomycin C on radiation-induced transcriptional biomarkers in human lymphoblastoid cells

Abstract Purpose Ionizing radiation (IR)-induced transcriptional changes are considered a potential biodosimetry for dose evaluation and health risk monitoring of acute or chronic radiation exposure. It is crucial to understand the impact of confounding factors on the radiation-responsive gene expressions for accurate and reproducible dose assessment. This study aims to explore the potential influence of exposures to chemotherapeutic agents such as cyclophosphamide (CP) and mitomycin C (MMC) on IR-induced transcriptional biomarkers. Methods The human B lymphoblastoid cells (AHH-1) were exposed to 0, 20, 50, 100, 200 and 500 μg/ml CP or 0, 0.025, 0.05, 0.1 and 1 μg/ml MMC, respectively. The appropriate concentrations of CP and MMC were added for 1 h before irradiation with 0, 2, 4 and 6 Gy of 60Co γ-rays at a dose rate of 1 Gy/min. Cell viability was evaluated by CCK-8 assay. The gene expression responses of 18 radiation-induced transcriptional biomarkers were examined at 24 h after exposures to CP and MMC, respectively. The expression levels of five crucial DNA interstrand crosslinks (ICLs) repair genes were also evaluated. The biodosimetry models were established based on the specific radiation-responsive gene combinations. Results The baseline transcriptional levels of the 18 selected genes were slightly affected by CP treatment in the absence of IR, while the transcript responses to IR could be inhibited as the concentration of CP up to 50 μg/ml. MMC treatment up-regulated the background levels in most radiation-responsive gene expressions. Of 18 genes, only the relative mRNA expression levels of CDKN1A and BBC3 were repressed after treatment with IR and MMC in combination. The relative mRNA level of RAD51 was significantly up-regulated after exposure to CP, while the expression of FANCD2, RAD51 and BLM showed an overall increase in response to MMC treatment. After irradiation, the relative mRNA expression levels of FANCD2, BRCA2 and RAD51 exhibited dose-dependent increases in IR alone and MMC treatment groups. In addition, the biodosimetry models were established using 2-4 radiation-responsive genes based on different radiation exposure scenarios. Conclusion Our findings suggested that IR-induced gene expression changes were slightly affected after exposure to a relatively low concentration of CP and MMC. Gene expression combinations might improve the broad applicability of transcriptional biodosimetry across diverse radiation exposures.


Introduction
With the widespread application of nuclear devices and radiological sources, there is a risk of unintentional partialbody or total-body irradiation.Moreover, there is the life threat of large-scale nuclear or radiological accidents with numerous exposed populations (Chopra et al. 2021;Satyamitra et al. 2022).Ionizing radiation (IR) exposure might bring about serious health consequences.Therefore, it is critical to evaluate the extent of exposure for providing applicable medical countermeasures in the case of radiological emergency events (Kabacik et al. 2011;Kultova et al. 2020;Ostheim et al. 2022).Biodosimetry assays based on the assessment of molecular biomarkers are considered surrogate measurements or supplements to physical dosimetry after IR exposure (Wathen et al. 2021).Current approaches applied for dose estimation include the dicentric chromosome assay (DCA), micronucleus (MN), c-H2AX foci, and "omics" methods, such as genomics, transcriptomics, metabolomics, and lipidomics (Sullivan et al. 2013;Sproull and Camphausen 2016;Ainsbury et al. 2022).Recent studies have reported that exposure to IR resulted in damage to cellular components, activating genes that participated in the DNA damage response and repair functions, such as cell cycle regulation (CDKN1A, MDM2, PCNA and CCNG1), apoptosis (BAX,BBC3 and GDF15) and DNA repair (DDB2, XPC and POLH) (Budworth et al. 2012;Tucker et al. 2014;Li et al. 2017;Lacombe et al. 2018).IR-induced specific gene expression changes could be examined within hours and days following radiation exposure using microarray and quantitative real-time PCR (Ostheim et al. 2022).Many laboratories worldwide developed the signatures for dose assessment based on combinations of radiation-responsive transcriptional biomarkers in cells (Warters et al. 2009;Chauhan and Howland 2014;Weissmann et al. 2016), mice (Broustas et al. 2017;Shuryak et al. 2020), rats (Saberi et al. 2015), tissues (Keam et al. 2018;Sagkrioti et al. 2022), nonhuman primates (Park et al. 2017;Balog et al. 2020;Port et al. 2021) and human peripheral blood models (Biolatti et al. 2021;Ostheim, Coker, et al. 2021;Ostheim, Don Mallawaratchy, et al. 2021).Several inter-comparison exercises have shown that this approach has the capability to be served as a robust and promising radiation biodosimetry for medical triage, dose estimation and prediction of outcome (Manning et al. 2017;Satyamitra et al. 2022).However, there is an ongoing debate on the influence of inter-individual variation and confounding factors when using transcriptional markers for dose evaluation, which may reduce the radiation specificity of IR-induced gene expression alterations (Manning et al. 2013;Kultova et al. 2020).It has been proven that variations in IR-induced gene expressions widely existed among different individuals.Particularly, sex and age may contribute to the inter-individual variance and influence the gene expression-based biodosimetry (O'Brien et al. 2018).Our previous studies demonstrated that the establishment of sex-specific gene combinations could improve the precision of dose estimation in irradiated human peripheral blood samples (Li et al. 2019).Additionally, it has been confirmed that smoking, infection or chronic inflammation status may affect the response to IR (Budworth et al. 2012;Soltani et al. 2016;Cruz-Garcia et al. 2018).However, little is known about the impacts of IR and chemicals or medicines co-exposure on the utilization of transcriptional biomarkers as radiation biodosimetry in various radiation scenarios.
Exposure to IR and chemical agents is an extremely complex biological process that may activate a range of genes producing interactions involving DNA damage response, cell cycle modulation, signal transduction, apoptosis and oncogenesis (Sakamoto-Hojo et al. 2003).It is important to assess the specific transcriptional responses independent of environmental and chemical factors for the development and application of radiological biodosimetry (Kultova et al. 2020;Satyamitra et al. 2022).In clinical medicine, IR combined with DNA interstrand crosslink (ICL) agents such as nitrogen mustards and mitomycin C (MMC) is widely utilized in cancer treatments because of their DNA-damaging properties (Roos et al. 2016;Liu et al. 2022).Generally, IR induces DNA double-strand breaks by releasing energy and increasing reactive oxygen species (ROS) accumulation (Kulkarni et al. 2009).Nitrogen mustard such as cyclophosphamide (CP) could cause the cross-linking of DNA and RNA strands, and the activation of apoptosis (Liu et al. 2022), while MMC played a vital role in the formation of monomeric adducts and ICL through activating reductive enzymes (Kulkarni et al. 2009;Chang et al. 2017).It has been reported that the inductions of chromosome aberrations and MN in lymphoblastoid cells increased after treatment with IR and MMC in combination (Iijima and Morimoto 1991;Asur et al. 2009).Therefore, there is needed to investigate the effects of chemicals exposure on the specificity of IR-induced transcriptional biomarkers.
In this study, a panel of eighteen radiation-responsive genes identified by our previous studies was utilized to systematically explore the impact of exposures to CP and MMC on the changes in baseline and IR-induced relative expression levels of these transcriptional biomarkers in the human B lymphoblastoid cells (AHH-1) (Li et al. 2019).The five transcriptional biomarkers of ICLs induced by chemicals were also evaluated.The biodosimetry models were established based on the specific radiation-responsive gene combinations after exposure to CP and MMC, respectively.

Irradiation
The 60 Co c-rays irradiation was carried out at the Beijing Radiation Center.The absorbed doses were calibrated using an ionizing chamber.AHH-1 cells were placed in a homogenous radiation field with 30 Â 30 cm and irradiated with 0 (control), 2, 4 and 6 Gy of 60 Co c-rays at a dose rate of 1 Gy/min.After irradiation, the cells were cultured in the incubator for 24 h.Three independent experiments were performed.

Cell viability assay
The cell viability was determined by CCK-8 kit (Dojindo, Tokyo, Japan).Briefly, a total of 1 Â 10 4 cells were seeded in 96-well plates and treated with CP and MMC in six wells for 24, 48 and 72 h at 37 C, respectively.After adding 10 ll of CCK-8 solution, the cells were maintained at 37 C for 1 h.The absorbance was detected using spectrophotometrically at 450 nm.

Candidate genes
The eighteen genes in our previous study were used for evaluating the effects of CP and MMC on the transcriptional biomarkers in response to IR (Li et al. 2019).In addition, the transcript levels of five genes (FANCD2, BRCA1, BRCA2, RAD51 and BLM) were also measured for determining the formation of ICLs induced by chemotherapeutic agents (Nikolova et al. 2017;Zhao et al. 2022).

RNA isolation and qRT-PCR analysis
Total RNA was extracted from cultured cells using Trizol reagent (Thermo Fisher Scientific Inc, Waltham, USA).The single-strand cDNA was generated utilizing High-Capacity cDNA Reverse transcription kit (Thermo Fisher Scientific Inc, Waltham, MA, USA) following the manufacturer's protocol with 1 lg of total RNA.For qRT-PCR quantification, the amplification reactions for candidate genes were conducted with SYBR Green PCR Master Mix (Thermo Fisher Scientific Inc, Waltham, MA, USA) and ran on the ABI 7500 fast Real-Time PCR System as described previously (Li et al. 2019).The specific primer sequences were presented in Supplementary Table 1.The relative mRNA levels over control were calculated using ACTB and B2M as reference genes.

Statistical analysis
SPSS version 25.0 (SPSS Inc, Chicago, IL) and GraphPad Prism 8.0.2 (GraphPad Inc, San Diego, CA, USA) were applied to perform statistical analyses and graphs.All quantitative data were described as the mean ± standard deviation (SD) in at least three independent experiments.The statistical significances in cell viability and gene expression change between the different groups were analyzed using One way ANOVA followed by LSD and S-N-K post hoc tests.The dose-effect curves for single genes were established by linear regression analysis.The dosimetry models based on gene expression alterations were constructed utilizing the stepwise regression method.P < .05 was considered statistically significant.
Based on the cell viability, the optimal chemical concentrations in this study were determined as 20 lg/ml CP, 50 lg/ml CP and 0.025 lg/ml MMC.The effects of IR and chemical treatments in combination on cell viability were also evaluated.Following treatments with IR (0-6 Gy) and CP (20 and 50 lg/ml) or MMC (0.025 lg/ml) for 24 h, there were significant differences in cell viabilities among the groups after exposure to 4-6 Gy (P < .01).Compared to IR alone, cells treated with IR and MMC showed a significant decrease in cell viability (P < .01)(Figure 1 (D and E)).

Effects of CP and MMC treatments on the baseline transcript levels of radiation-responsive genes
To test the effects of CP and MMC treatments on the radiation-responsive genes in the absence of IR exposure, the baseline transcript level responses of 18 genes in our panel were measured at 24 h after CP and MMC treatments with respect to transcript levels in untreated AHH-1 cells, respectively.DDB2 and PPM1D were strongly upregulated (2-fold and 1.8-fold, respectively) by 50 lg/ml CP treatment (P < .05,0.01) (Figure 2(A and B)).TNFRSF10B and PCNA expression were downregulated (1.5-fold) by 50 lg/ml CP treatment (Figure 2(D ad F)).CCNG1 and PCNA expressions were slightly increased (1.4-fold) by 20 lg/ml CP treatment (P < .05)(Figure 2(E and F)).Significant decreases in GDF15 gene expression were observed with increasing concentrations of CP treatment (1.6-and 2-fold, respectively) (P < .01)(Figure 2(G)).CP treatment showed no significant changes in baseline levels of other genes (fold-change < 1.5).

Changes in the transcript levels of radiationresponsive genes after co-exposure to IR and CP
The expression changes of 18 genes were evaluated at 24 h in response to IR and co-treated with CP (20 and 50 lg/ml).
In the absence of CP, IR-induced gene expression changes showed significant up-regulation in a dose-dependent manner (Figure 3).Co-exposure to 20 lg/ml CP with IR, no significant change was shown in the transcript levels of radiation-induced CDKN1A, BAX, XPC, FDXR, TNFSF4, PHPT1, GADD45A, TNFRSF10B, MDM2, PPM1D, BBC3, POLH and PCNA genes in contrast to IR alone at each dose point (P > .05)(Figure 3(A-L, Q-R)).The DDB2 expression increased 1.2-1.3folds in response to 4-6 Gy irradiation and treatment with 20 lg/ml CP when compared to IR alone (Figure 3(E)).After co-exposure to 20 lg/ml CP and 2 Gy irradiation, the relative expression levels of RPS27L, GDF15, ASTN2, CCNG1 were lower than that of an IR alone (P < .05 and 0.01) (Figure 3(M-P)).Following the co-treatment with 50 lg/ml CP and IR, the majority of radiationinduced gene transcriptional changes were significantly down-regulated when compared to IR alone, and combined with 20 lg/ml CP (P < .05 and 0.01).In the presence of CP, radiation-induced RPS27L and CCNG1 expression changes gradually decreased with the increasing concentration of CP (P < .05)(Figure 3(M and P)).

Changes in the transcript levels of radiationresponsive genes after co-exposure to IR and MMC
To examine the influence of MMC on the radiation-responsive genes, the relative mRNA levels of 18 genes were assessed at 24 h following exposure to IR alone and combined with 0.025 lg/ml MMC.Compared with the IR alone, the relative mRNA levels of radiation-induced CDKN1A and BBC3 were evidently decreased (1.4-fold and 1.5-fold, respectively) at each dose point after co-exposure to MMC (P < .05)(Figure 4(A and C)).The alterations on the relative transcript levels of FDXR, ASTN2 and RPS27L in the presence of MMC treatment and 4 Gy radiation exposure were much lower than that of in IR group (1.4-, 1.3-and 1.5-fold, respectively) (P < .05)(Figure 4(B, D and E)).MMC treatment did not show any modulated influence on the relative mRNA levels of other radiation-responsive gene expressions (P > .05).

Effects of CP and MMC treatment on the transcriptional levels of ICLs-related biomarkers
To verify whether CP and MMC could induce the formation of ICLs in AHH-1 cells, the changes in the expression levels of five crucial ICLs repair genes were examined, including FANCD2, BRCA1, BRCA2, RAD51 and BLM.After being exposed to 20 lg/ml CP, 50 lg/ml CP and 0.025 lg/ml MMC, the mRNA levels of RAD51 significantly increased higher than that in the control group, respectively (P < .01)(Figure 5).Compared with other groups, the transcript level of FANCD2 significantly increased after exposure to MMC (P < .01).In addition, the alterations in the BLM gene expressions induced by CP were lower than those in the control and MMC treatment groups (P < .01).The relative mRNA levels of BRCA1 and BRCA2 didn't show significant modulations after treatment with CP and MMC (P > .05).
To further understand whether IR could influence the changes of ICLs-related biomarkers, the transcriptional levels of five critical genes induced by CP and MMC were also evaluated after co-exposure to 0-6 Gy c-rays irradiation.The   relative mRNA expression levels of FANCD2, BRCA2 and RAD51 significantly increased with radiation doses in the two groups without or with MMC, but the magnitude in expression levels of FANCD2 and RAD51 in MMC treatment group were lower than those in IR alone (P < .05,0.01) (Figure 6(A, C and D)).In the presence of CP, compared with 0 Gy, the alterations in the expression levels of FANCD2 and BRCA2 were up-regulated after exposure to 4 Gy irradiation and then gradually down-regulated in response to 6 Gy (Figure 6(A and C)).The transcript level of BLM reached the peak after 4 Gy irradiation among four treatment groups, but there was no significant difference between the groups (Figure 6(E)).The transcript levels of BRCA1 weren't affected by the treatment of IR, CP and MMC, respectively (Figure 6(B)).

Dose-response curves of IR-induced transcriptional biomarkers
To determine the effects of CP and MMC on the doseresponse relationships of transcriptional biomarkers induced by IR, the dose-response curves were constructed by linear regression analysis, respectively (Table 1).For IR alone exposure, there were strong statistical correlations between the fold change of 18 genes in our panel and radiation doses (R 2 ¼ 0.87-0.99).Following co-exposure to 20 lg/ml CP and 0.025 lg/ml MMC, the R 2 values of the regression equations for 18 genes were all greater than 0.9, indicating that these genes had good dose-effect relationships (P < .05 and .01).It had shown that the transcript level of some genes could be affected by 50 lg/ml CP treatment.The linear  equations of CDKN1A, XPC, FDXR, PHPT1, GADD45A, PPM1D, BBC3, RPS27L, GDF15 and POLH showed the best goodness of fit with R 2 of 0.93-0.98.

Establishment of radiation-responsive gene expression-based biodosimetry models
The gene expression biodosimetry utilizing a panel of radiation-sensitive genes may enhance the accuracy of dose assessment.In the current study, the specific dosimetry models based on the treatments of IR alone, and co-exposure to CP and MMC were developed using the stepwise regression analysis, respectively.The variable selection and statistical coefficients of regression models were presented in Table 2.Each gene set contained 2-4 genes and the R 2 value reached above 0.97, which was much better than that of equations for most individual genes.Exposure to IR alone, CDKN1A, TNFSF4, MDM2 and BAX were included in the dosimetry model, which could explain 0.99 of the total variances.After co-exposure to 20 and 50 lg/ml CP, CDKN1A was incorporated into two models, respectively.In the combined IR and MMC group, GADD45A, GDF15, ASTN2 and BAX were selected to produce the best regression fit with an R 2 of 0.99.

Discussion
Humans are frequently exposed to IR both in environmental and medical settings.Radiation can cause serious acute or chronic health hazards at higher levels of dose exposure (Cheung et al. 2003;Meadows et al. 2008).Given the limitations of current approaches available to evaluate radiation Stepwise regression analysis was used to establish gene expression dosimetry models.Dosimetry modeling was conducted using P < .05for variable entry and the R 2 value was used to determine the goodness fit of all models.Tolerance and VIF were employed to test the multi-collinearity of models.If tolerance !0.1 or variance inflation factor VIF 10, there is no significant degree of collinearity among independent variables.
exposure, IR-induced gene expression changes provide an ideal model for rapid and high-throughput individual dosimetric assessment.Although studies have shown that the development of radiation dosimetry based on gene expressions combination could strengthen the robustness and accuracy of dose evaluation in case of radiological emergency or clinical medicine (Lacombe et al. 2018;Schule et al. 2022), the impact of potential confounders on the specificity of gene expression alterations induced by IR should be considered (Amundson 2023).Previous studies have focused on several factors such as gender, age, smoking, inflammation and immune system response (Manning et al. 2017;Cruz-Garcia et al. 2018), but there is still needed to explore the influence of chemicals on radiation-responsive gene expressions.In this study, two ICL-inducing chemotherapeutic agents, CP and MMC, were used to investigate the impact on a panel of IR-induced transcriptional biomarkers from our previous studies.The transcriptional responses of five pivotal biomarkers for ICLs induced by CP and MMC were also examined for elucidating the difference in DNA repair between different chemicals.To further improve the wide application of gene expression-based biodosimetry, specific dosimetry models were constructed depending on the chemical exposures.
In our previous studies, 18 radiation-responsive genes were identified and validated in human peripheral blood, showing evident up-regulation in a dose-dependent manner following IR exposure (Li et al. 2019).It is well known that IR could cause complex changes in transcript patterns by activating multiple cellular signal transduction pathways.The bioinformatics analysis demonstrated that most genes took part in response to stimulus and signalling.12 genes, including CDKN1A, BAX, FDXR, DDB2, GADD45A, TNFRSR10B, MDM2, BBC3, RPS27L, GDF15, CCNG1 and PCNA, were enriched in p53 downstream pathway (Supplementary Table 2).Accumulating evidence has shown that the IR-induced DNA replication arrest and DNA double-strand breaks (DSBs) triggered the activation of transcription factor p53 through the ATM/ATR pathway and further caused the transcriptional changes of p53 downstream target genes (Christmann and Kaina 2013).Generally, the genes in our panel mainly took part in biological processes such as cell cycle regulation (CDKN1A, GADD45A, MDM2, PCNA, PPM1D, TNFSF4 and CCNG1), apoptosis (BBC3, BAX, TNFRSF10B and GDF15), DNA repair (DDB2, XPC and POLH and RPS27L), cell metabolism (FDXR and PHPT1) and immune response (TNFSF4 and TNFRSF10B).
Exposures of cells to genotoxic agents, including IR and chemical agents, could cause DNA damage.Assessment of the radiation specificity of gene expression-based biodosimetry in individuals who may expose to chemicals would be helpful to promote the broad utility of radiation biodosimetry.Since there were pieces of evidence that the alterations of IR-induced certain gene expression in human peripheral blood could be influenced by some confounders (Ostheim et al. 2022).Therefore, AHH-1 cells were used to observe the effects of CP and MMC on transcript levels of 18 radiation-responsive genes in this study.The results revealed that CP and MMC concentration-and time-dependently inhibited cell viability in AHH-1 cells.Previous studies revealed that the cells treated with MMC displayed concentration-dependent elevation in the incidences of sister-chromatid exchanges (SCE) and MN (Iijima and Morimoto 1991;Asur et al. 2009).These findings indicated that exposure to a relatively high concentration of chemicals could bring about serious DNA damage or cell death.After the treatments by the optimal concentration of CP and MMC for 24 h, the baseline levels of the selected 18 genes were examined.Current results demonstrated that CP and MMC treatment modulated the baseline transcription of genes in different manners.Exposure to 50 lg/ml CP treatment showed significant changes in basal DDB2 and GDF15 expression levels (fold change > 2-fold), while the baseline transcript expressions of other genes were not affected by treatment with different concentrations of CP (fold change < 1.5-fold).On the other hand, MMC treatment induced a 1.5-2.4-foldincrease in the background transcript levels of most genes.A similar consequence was found that chromosome aberrations and MN could be detected in cells treated with 0.05 lg/ml MMC (Asur et al. 2009;Kulkarni et al. 2009).In order to explain the differences between CP and MMC in DNA damage-response mechanisms, the transcriptional responses of five biomarkers (FANCD2, BRCA1, BRCA2, RAD51 and BLM) were determined in AHH-1 cells, which played important roles in recognition and activation of ICL repairs (Deans and West 2011;Zhao et al. 2022).After CP exposure, only the relative mRNA level of RAD51 was significantly up-regulated, while the expression levels of FANCD2, RAD51 and BLM showed overall increases in response to MMC treatment.These results indicated that exposure to MMC could rapidly activate the ICL repair system and further modulated the transcription levels of p53 downstream target genes, which was consistence with the findings in the previous study (Martinez et al. 2008).
The effects of CP and MMC as potential confounders on the IR-induced gene expression alterations were examined in AHH-1 cells.In the absence of chemicals, the transcriptional levels of 18 genes displayed significant up-regulations in a dose-dependent manner after irradiation, which was consistent with our previous findings (Li et al. 2019).However, it was also noted that the magnitudes of transcriptional variations induced by IR in human peripheral blood were higher than that in AHH-1 cells.These differences could be contributed to the various cell types.In the presence of CP, the transcript responses of most genes in cells treated with 20 lg/ml CP and IR in combination showed no significant difference when compared to IR alone.After being co-treated with 50 lg/ml CP and 6 Gy radiation exposure, CP modified the relative mRNA levels of 18 genes by an additional average 1.5-fold decrease over the effects of IR alone or IR combined 20 lg/ml CP.Since CP had little influence on the background levels of these genes, the down-regulation in radiation-responsive gene expression changes could be related to the decline in cell viability after exposure to a relatively high concentration of CP.To elucidate the interplay of CP and IR on DNA damage response, gene expression changes associated with ICL sensitivity were also assessed following IR.It was shown that the expression levels of FANCD2, BRCA2 and RAD51 significantly increased after exposure to 0-6 Gy irradiation alone, suggesting IR-induced DNA damages might elicit the activation of critical key genes involved in homologous recombination (HR) for error-free repairing the DSBs (Michl et al. 2016).After co-exposure to CP and IR, the mRNA levels of FANCD2 and RAD51 were much lower than those in IR alone, while the BRCA2 and BLM expression changes reached the peak at the dose point of 4 Gy and then drastically decreased.These results revealed that IR and CP could interact with each other in the formation of ICLs.
Unlike CP treatment, the present study indicated that exposure to MMC led to increases in most genes' baseline transcript levels in the absence of IR.It was very important to assess the promising of these genes as radiation biodosimetry in the context of MMC exposures.The findings suggested that the relative mRNA levels of 16 transcriptional biomarkers induced by IR were similar with or without MMC treatment, which indicated that exposure to MMC could not affect the changes in the transcript levels of IRinduced gene expressions.In addition, compared with exposure to IR alone, the transcriptional biomarkers of ICL had consistent changes after co-exposure to IR and MMC.The cytogenetic study in another study pointed out that MMC was an S-dependent agent and mainly induced the formation of SCE, while IR was an S-independent and produced the dicentric and rings (Iijima and Morimoto 1991).These findings suggested that IR and MMC might result in DNA damage through different molecular mechanisms.Several publications confirmed that CDKN1A and BBC3 were considered critical biomarkers for predicting radiation exposure (Amundson et al. 2004;Li et al. 2011).However, it was observed that the IR-induced CDKN1A and BBC3 expressions in ex vivo experiments were confounded by LPS-induced inflammation and curcumin (an anti-inflammatory agent) (Budworth et al. 2012;Soltani et al. 2016).Our study also revealed that co-exposure with MMC and IR significantly declined CDKN1A and BBC3 transcript responses compare to IR alone, suggesting that CDKN1A and BBC3 transcriptional responses to IR could be modulated by several confounding factors such as inflammation and chemicals.Studies have proven that CDKN1A is a cyclin-dependent kinase inhibitor, mediating multiple biological processes such as cell cycle regulation, differentiation, migration, cytoskeletal dynamics, apoptosis, DNA repair, autophagy and senescence through p53-dependent or p53independent pathways (Kreis et al. 2019), while BBC3 is a direct up-regulated target of p53 that regulates the intrinsic and extrinsic apoptotic pathways, including p53-dependent pathways, JAK-STAT, PI3K-AKT-FOXO1/3a, MAPK, WNT and TGF-b signalling (Li 2021).This could be explained why the changes in certain single gene expressions were altered by multiple exposures.
Due to the impact of CP and MMC exposure on the alterations in expression levels of radiation-sensitive genes, it was crucial to appraise the feasibility of these biomarkers for radiation dose estimation after co-exposure to IR and chemicals.In this study, the dose-response curves for each single gene showed the linear models with or without CP (20 lg/ml) and MMC treatments, which were comparable to IR alone.Although most genes expression were repressed after radiation in the presence of a relatively high concentration CP (50 lg/ml), there were 10 genes (CDKN1A, XPC, FDXR, PHPT1, GADD45A, PPM1D, BBC3, RPS27L, GDF15 and POLH) with good dose-response relationships (R 2 > 0.93).Several publications demonstrated that using single gene biomarkers could cause the inaccuracy of dose evaluation due to the influence of confounding factors (Abend et al. 2022), while gene expression combinations might be particularly reliable and stable in diverse radiation scenarios (Paul et al. 2011;Jacobs et al. 2020).Therefore, the optimal stepwise regression models for dose estimation were obtained based on different chemical treatments in this study.Each model incorporated 2-4 specific genes, which could improve the accuracy of gene expression biodosimetry to some extent.Further research would be needed to validate the impacts of chemicals on the transcript levels of radiation-sensitive genes in human peripheral blood samples and to evaluate the specificity and reliability of gene expression dosimetry models obtained in this study for dose estimation in patients combined with chemotherapy and radiotherapy.
In summary, this study demonstrated that exposure to CP had little impact on the basal expression levels of transcriptional biomarkers induced by IR, while a relatively high concentration of CP could inhibit the relative mRNA expression of certain genes after radiation exposures.On the other hand, although MMC could increase the baseline levels in genes in our panel, it did not affect the changes in the transcript levels of IR-induced gene expressions.Our findings indicated that the establishment of dosimetry models based on a panel of specific IR-induced transcriptional biomarkers may promote the broad application of transcriptional biodosimetry across diverse radiation exposures.

Figure 1 .
Figure 1.Effects of CP, MMC and IR on the cell viability in AHH-1 cells.Cell viabilities were assessed by CCK-8 assay after exposure to different concentrations or doses of CP (A), MMC (B) and IR (C), respectively.The impacts of optimal concentrations of CP (20 and 50 mg/ml) (C) and MMC (0.025 mg/ml) (D) on cell viability were also evaluated at 24 h after 0-6 Gy irradiation.Data were presented as mean ± standard deviation (SD), n ¼ 6 per group.

Figure 5 .
Figure5.The expression levels of five critical genes for ICLs in AHH-1 cells after exposure to CP (20 and 50 mg/ml) and MMC (0.025 mg/ml).The transcriptional expressions of FANCD2, BRCA1, BRCA2, RAD51 and BLM were assessed at 24 h after treatment using qRT-PCR.ACTB and B2M were used to normalize gene expression.Data represented the mean ± SD of three independent experiments.One-way ANOVA was used to analyze the statistical differences among the groups.P < .05indicates statistically significant ( ÃÃ P < .01).

Figure 6 .
Figure 6.Effects of IR on the transcriptional biomarkers of ICLs induced by CP (20 and 50 mg/ml) and MMC (0.025 mg/ml) treatments.The relative mRNA expression levels of FANCD2 (a), BRCA1 (B), BRCA2 (C), RAD51 (D) and BLM (E) were measured at 24 h after co-exposure to IR and CP or MMC.Fold changes in gene expression relative to sham-irradiated control (0 Gy) were measured.Statistical analysis was used by One-way ANOVA.Data are expressed as the mean ± SD of three independent experiments.P < .05indicates statistically significant ( Ã P < .05,ÃÃ P < .01 and ÃÃÃ P < .001).

Table 1 .
The dose-response curves of radiation-responsive genes after exposure to IR alone, combined IR and CP, and combined IR and MMC.represents the relative quantitative mRNA level (fold change); x represents the absorbed dose in Gy.

Table 2 .
Stepwise regression coefficients of gene expression-based dosimetry models after exposure to IR alone, combined IR and CP, and combined IR and MMC.
a Dependent variable: dose.