then fixed to a chip, which was read by the nCounter machine, giving counts based on recorded fluorescence intensities. This allows for a molecule-by-molecule resolution of the relative abundance of the miRNA in a sample.

The nCounter-reported raw counts were normalised according to the top 100 miRNAs using nSolver 4.0 software, and the normalised data were then analysed with BRBArray Tools, an open-source analysis extension used by the National Cancer Institute [50]. Dose correlation analysis and heat maps were also generated using BRBArray Tools. Statistical relevance was tested with DIANA Tools, mirExTra2.0. [51], using the LIMMA statistical method. The *p*-value threshold for relevance was set at 0.05.

cDNA synthesis and miRNA analysis by RT-qPCR were carried out by using the miRCURY™ LNA™ miRNA PCR System (Qiagen). cDNA was prepared from 2 µL RNA with a concentration of 40 ng/µL in a 10 µL reaction volume. The cDNA was diluted 20-fold and assayed in a 10 µL PCR reaction volume. The amplification was performed in a Rotor-Gene Q real-time PCR cycler (Qiagen). The following PCR primers (all purchased from Qiagen) were used: miR-669d-5p (YP00205051), miR-93-5p (YP00204715), miR-504-5p (YP00204396), miR-467h (YP00205922), miR-706 (YP00205976), miR-709 (YP00205463), miR-1961 (YP00205381), miR-1933-5p (YP00205351), miR-181c-5p (YP00204683), miR-338-5p (YP00204114), miR-34b-5p (YP00205075), miR-761 (YP00205475), miR-129-5p (YP00204534) and miR-708-5p (YP00204490). The amplification curves were analysed using the Rotor-Gene Q Series software (software version 2.1.0.9) both for the determination of quantification cycles and for the melting curve (T<sub>m</sub>) analysis. In order for the data to be considered for further analysis, the following criteria had to be met: appropriate melting curves, T<sub>m</sub> had to be within known specifications for the assay and the Cq value had to be ≤37. The relative concentration of each miRNA was calculated by the Rotor-Gene Q software, where sham-irradiated (0 Gy) samples were used as controls. To achieve optimal relative expression results, mmu-miR-423-3p was used as a normaliser, since mmu-miR-423-3p was present in a constant and well-detectable concentration in BM-derived EVs, which did not change due to 0.1 Gy or 3 Gy irradiation.

4.6. *Western Blot Analysis of EV and BMC Proteins*

BMCs and BM-derived EVs were isolated as described above. After the EV isolation protein content was measured by the Bradford protein assay kit (Thermo Fisher Scientific, Waltham, MA, USA) using a Synergy HT (Biotek, Winooski, VT, USA) plate reader, EVs with a 60 µg protein content and 2.6 × 10⁶ BMCs were lysed with radioimmunoprecipiation assay (RIPA) lysis buffer containing 2% protease inhibitor (Protease Inhibitor Cocktail (P8340), Kenilworth, NJ, USA); then, the protein concentration was determined by the bichinchoninic acid (BCA) assay kit (Pierce™ BCA Protein Assay Kit, Thermo Fisher Scientific, Waltham, MA, USA). For further steps, 40 µg protein was precipitated by trichloroacetic acid (TCA) solution (one part of the TCA was added to three parts of the protein solution), incubated on ice for 5 min and pelleted at 3800× g and 4 °C for 5 min. The pellet was washed with ice-cold acetone twice, and the protein samples were diluted 1:2 in 2× Laemmli buffer (Bio-Rad Hercules, CA, USA) supplemented with β-mercaptoetanol, boiled at 95 °C for 5 min and cooled on ice for 5 min before loading on the gel. A total of 40 µg of the protein was loaded and electrophoresed on 4–20% sodium dodecyl sulphate-polyacrylamide (SDS-PAGE) gel (4–20% Mini-PROTEAN® TGX™ Precast Protein Gels, Bio-Rad Hercules, CA, USA) and transferred to a polyvinylidene fluoride (PVDF) membrane. After blotting, the PVDF membrane was blocked with blocking buffer (containing 3% bovine serum albumin (BSA) in Tris Buffered Saline, with Tween 20) at room temperature (RT) for 30 min. The blocked membrane was incubated with the primary antibodies: recombinant Anti-ATG4B (ab154843), H2AFV Polyclonal Antibody (PA5109802) and beta Actin Polyclonal Antibody (PA1-183) (Thermo Fisher Scientific, Waltham, MA, USA) at RT for 2 h, followed by 1 h of incubation with horseradish peroxidase-conjugated goat anti-rabbit secondary antibody (Goat Anti-Rabbit IgG H&L (HRP), (ab6721 Abcam). Antibodies were diluted in the blocking buffer according to the manufacturer's instructions. As a
protein standard, the Spectra™ Multicolor Broad Range Protein Ladder was used (Thermo Fisher Scientific). The membrane was washed in Tris-buffered saline-tween buffer three times, and protein bands were visualised using 3,3'-diaminobenzidine substrate (Pierce™ DAB Substrate Kit, Thermo Fisher Scientific) by the chromogenic method. The density of each protein band was recorded and analysed by ImageJ software (Image Processing and Analysis in Java, National Institutes of Health, Bethesda, MD, USA). The measured density values were normalised to the density value of the loading control, β-actin.

### 4.7. *Mass Spectrometry (MS) Sample Preparation and Measurement*

BMCs from directly irradiated mice (n = 3 for 0 Gy BM, n = 4 for 0.1 Gy and 3 Gy BM) as well as BMCs co-cultured with BM-derived EVs from irradiated mice (n = 4 for 0 Gy BM + EV, n = 5 for 0.1 Gy BM + EV, 3 Gy BM + EV) were placed in 100 µL RIPA buffer (Thermo Fisher Scientific) that contained 25 mM Tris.HCl ph 7.6, 150 mM NaCl, 1% NP-40, 1% sodium deoxycholate and 0.1% SDS and incubated at 4 °C for 30 min [52]. They were then subjected to an ice-cold sonication bath for 30 s and another incubation (4 °C, 15 min). The protein concentration of the individual samples was determined using a BCA assay following the instruction manual (Thermo Fisher Scientific) on an Infinite M200 Spectrophotometer (Tecan GmbH, Crailsheim, Germany). BSA was used as an internal standard.

A total of 10 µg of the sample was enzymatically digested using a modified filter-aided sample preparation (FASP) protocol, as described in [53,54]. Peptides were stored at -20 °C until the MS measurement.

The MS measurement was performed in the data-dependent (DDA) mode. MS data were acquired on a Q Exactive (QE) high-field (HF) mass spectrometer (Thermo Fisher Scientific Inc.), as described in [55].

### 4.8. *MS Data Processing and Protein Identification*

Proteome Discoverer 2.4 software (Thermo Fisher Scientific; version 2.4.1.15) was used for peptide and protein identification via a database search (Sequest HT search engine) against the Swissprot mouse database (Release 2020_02, 17061 sequences), considering full tryptic specificity and allowing for up to one missed tryptic cleavage site, a precursor mass tolerance of 10 ppm and a fragment mass tolerance of 0.02 Da. Carbamidomethylation of cysteine was set as a static modification. Dynamic modifications included the deamidation of asparagine and glutamine, the oxidation of methionine and a combination of methionine loss with acetylation on protein N-terminus. The percolator was used for validating peptide spectrum matches and peptides, accepting only the top-scoring hit for each spectrum and satisfying the cut-off values for FDR < 1% and a posterior error probability < 0.01. The final list of proteins complied with the strict parsimony principle.

A schematic illustration of the workflow used for MS data processing and protein identification can be seen in Supplementary Figure S3.

### 4.9. *Data Processing and Label-Free Quantification*

The quantification of proteins was based on the area value of the abundance values for unique plus razor peptides. Abundance values were normalised in a retention time-dependent manner to account for sample loading errors. The protein abundances were calculated by summing up the abundance values for admissible peptides. The final protein ratio was calculated using the median abundance values of three replicate analyses each. The statistical significance of the ratio change was ascertained by employing the *t*-test approach described in [56], which is based on the presumption that we look for expression changes for proteins that are just a few in number in comparison to the number of total proteins being quantified. The quantification variability of the non-changing "background" proteins can be used to infer which proteins change their expression in a statistically significant manner.
The T-test was solely used for pairwise comparisons of two conditions. The following pairwise conditions were compared: (0.1 Gy BM)/(0 Gy BM); (3 Gy BM)/(0 Gy BM); (0.1 Gy BM + EV)/(0 Gy BM + EV); (3 Gy BM + EV)/(0 Gy BM + EV).

Proteins identified with an FDR <1% and a fold change above ±1.33 in treated samples, along with a Benjamini–Hochberg adjusted *p*-value < 0.05, were considered deregulated.

### 4.10. Pathway Analysis of Significantly Altered EV-Derived miRNAs and BMC Proteins

Statistically significant miRNAs differentially expressed in the EVs from irradiated mice were used in the miRNA functional KEGG pathway analysis, which was performed with DIANA mirPath v.3. Experimentally validated interactions from TarBase v.8 (http://www.microrna.gr/tarbase (accessed on 20 September 2022)) [57] were used primarily, and data generated by the microT-CDS algorithm [58] were used only if no experimentally validated interaction was found for the miRNA. The *p*-value threshold was set at <0.05.

For protein analysis, all four treatment groups (0.1 Gy or 3 Gy directly irradiated BMCs, and BMCs treated with 0.1 Gy- or 3 Gy-irradiated EVs) were considered separately, and the results were compared to their respective controls (either 0 Gy sham-irradiated or treated with BM-derived EVs from 0 Gy-irradiated mice) and to each other. Only significantly deregulated proteins based on MS analysis were included in the analysis, where the official gene symbol of the proteins was used in the query data. To calculate the number of protein–protein interactions (PPI) and form protein clusters, the STRING database version 11.0 (https://string-db.org/ (accessed on 12 September 2022)) was used. In the analysis, all interaction sources (text mining, experiments, databases, co-expression, neighbourhood, gene fusion, co-occurrence) were used, and the minimum required interaction score was 0.4 (medium confidence); protein clustering was performed using the MCL clustering algorithm within STRING. Pathway annotations and enrichment analysis were performed with the pathDIP database, version 4.0.7.0 (http://ophid.utoronto.ca/pathDIP/ (accessed on 19 September 2022)), which is an annotated database integrating data from several pathway databases. The advantage of using PathDIP was that it gave a greater protein coverage by using both literature-curated (core), orthologue and extended pathways. Extended pathways integrate core pathways with experimentally detected and orthologous PPIs. PPIs are either experimentally detected or high-confidence computationally predicted. Due to the pathway extension method, more than 36,000 pathway orphans (proteins with no annotations available in curated or orthologue pathways) could be annotated in sixteen non-human organisms, which led to a 9.56 times increase in the protein coverage in model organisms [59]. In our PathDIP analysis, we only considered data originating from the KEGG database in order to use similar conditions as in the microRNA pathway analysis. We used extended pathway associations, where core pathways were integrated with experimentally detected and orthologous PPIs with a minimum confidence level of protein–pathway association predictions of 0.95. Only significant pathways (*p* < 0.05) were considered.

To detect possible interactions between the significantly altered proteins and microRNAs, two databases were used: Tarbase for experimentally validated interactions and miRDB (http://mirdb.org/ (accessed on 20 September 2022)) [60] for predicted interactions.

### 4.11. Statistical Analysis

Data are presented as the mean ± standard deviation (SD). If no other method was indicated, then Students's *t*-test was applied to determine statistical significance using GraphPad Prism version 6.00 for Windows (GraphPad Software, La Jolla, CA, USA). Data were considered statistically significant if the *p*-value was lower than 0.05. For the dose correlation calculation, Pearson Correlation was used. To identify significantly altered miRNAs, the LIMMA method was used in DIANA mirExTra 2.0.
**5. Conclusions**

In this study, we identified differentially expressed miRNAs in the BM-derived EVs from mice irradiated with low- or high-dose IR. We showed that miRNAs regulated pathways related to the IR response and to normal and malignant BM functioning. The miRNA profile of the EVs was only moderately affected by low-dose irradiation, but the deregulated miRNAs were involved in pathways that are important for a healthy bone marrow, such as signalling pathways regulating the pluripotency of stem cells and mitochondria-related biological processes. These data indicate that oxidative stress after low-dose irradiation can be transferred by EV-derived miRNAs to non-irradiated bone marrow cells in a bystander manner.

We performed detailed proteomic analysis of either directly irradiated BMCs or those treated with EVs from irradiated mice. Several proteins, protein clusters and protein pathways were in common between directly irradiated and EV-treated BMCs, most probably representing biological processes transmitted via EVs in a bystander manner. One such important common process was the induction of oxidative stress after low-dose direct irradiation and treatment with EVs from low-dose irradiated mice. While pathways related to the DNA damage response were altered in both high-dose-irradiated BMCs and in BMCs treated with 3 Gy EVs, there was an important difference at the protein level. In directly irradiated cells, protein clusters indicated alterations in processes directly involved in DNA damage recognition, repair and processes linked to the epigenetic control of the IR response such as chromatin remodelling or histone methylation. In the EV-treated cells, only protein clusters involved in biological processes related to chromatin remodelling and histone modifications were present, which we think indicates that EVs can transmit factors influencing the DNA damage response pathway only via epigenetic mechanisms. We are not aware of other studies comparing direct and EV-induced changes in the proteomic profile of BMCs after irradiation. Since EV-derived miRNAs have important roles in regulating cellular processes in EV acceptor cells, pathways regulated by differentially expressed miRNAs in the EVs and altered protein pathways in BMCs treated with BM-derived EVs were compared. Certain important pathways altered in BMCs treated with 3 Gy EVs were identified as also regulated by miRNAs differentially expressed in 3 Gy EVs such as the cell cycle and myeloid leukaemia. Within these common pathways, direct interactions were shown between six miRNAs (mmu-miR-706, mmu-miR-709, mmu-miR-761, mmu-miR-669g, mmu-miR-129-5p and mmu-miR-1942) and eleven proteins (Atg4b, Calu, H2afv, Krt16, Rtf1, Snca, Tgm2, Ube2c, Clic4, Dnajb6 and Eif2b1), which might represent potential biomarkers indicative of EV-mediated effects. The existence of such common pathways indicates that miRNAs can induce functional changes in EV acceptor cells, strengthening the possible regulatory role of EV-derived miRNAs. Nevertheless, the majority of altered protein pathways could not be linked with miRNA-regulated pathways, indicating that miRNAs are involved in the regulation of certain but not all EV-mediated bystander effects, and other molecules comprising the EV cargo also have their role. In order to understand IR-induced bystander signals mediated by EVs, it is important to perform the complex characterisation of EV cargo changes after IR and to link them to biological processes in the EV acceptor cells. Since bystander responses are very important modulators of radiation damage, a better knowledge of these processes helps in an improved understanding of tissue responses to IR and in the estimation of long-term risks after radiation exposure.

**Supplementary Materials:** The supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24108607/s1.

**Author Contributions:** Conceptualisation: K.L., C.B. and S.T.; methodology: K.L., S.T., C.B., I.B.C., E.A.R., P.S. and B.J.; software: I.B.C., E.A.R., P.S. and C.v.T.; validation: T.S., I.B.C., K.L. and G.S.; formal analysis: I.B.C.; investigation: I.B.C., E.A.R., P.S., L.C.-G., C.v.T., D.K. and M.F.; resources: K.L., S.T. and C.B.; data curation: P.S., E.A.R. and K.L.; writing—original draft preparation: K.L., I.B.C. and E.A.R.; writing—review and editing: I.B.C., C.v.T., K.L. and G.S.; visualisation: I.B.C. and E.A.R.;
supervision: K.L., C.B. and S.T.; project administration: K.L.; funding acquisition: K.L., C.B. and S.T.
All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Euratom research and training programme 2014–2018 under the grant agreement No 662287.

**Institutional Review Board Statement:** The animal study protocol was approved by the Budapest and Pest County Administration Office Food Chain Safety and Animal Health Board (ethical permission: PE/EA/392-7/2017).

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Raw proteomic and miRNA profiling data have been uploaded to the Store<sup>db</sup> database (www.storedb.org, accessed on 30 January 2023). Study ID: https://www.storedb.org/?STOREDB:STUDY1176 (accessed on 30 January 2023), DOI: http://dx.doi.org/10.20348/STOREDB/1176 (accessed on 30 January 2023).

**Acknowledgments:** We wish to acknowledge the expert technical assistance of Károly Haller and Mariann Csabádi in the experimental animal care and handling.

**Conflicts of Interest:** The authors declare no conflict of interest.

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<figure><img src="image_39.png" /></figure>

Article

# Differential Expression of ATM, NF-KB, PINK1 and Foxo3a in Radiation-Induced Basal Cell Carcinoma

Rim Jenni<fnref n="1" />, Asma Chikhaoui<fnref n="1" />, Imen Nabouli<fnref n="1" />, Anissa Zaouak<fnref n="2" /> ID, Fatma Khanchel<fnref n="3" />, Houda Hammami-Ghorbel<fnref n="2" /> and Houda Yacoub-Youssef <fnref n="1" />,* ID

<figure><img src="image_40.png" /></figure>

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**Citation:** Jenni, R.; Chikhaoui, A.; Nabouli, I.; Zaouak, A.; Khanchel, F.; Hammami-Ghorbel, H.; Yacoub-Youssef, H. Differential Expression of ATM, NF-KB, PINK1 and Foxo3a in Radiation-Induced Basal Cell Carcinoma. *Int. J. Mol. Sci.* **2023**, *24*, 7181. https://doi.org/10.3390/ijms24087181

Academic Editor: François Chevalier

Received: 22 February 2023

Revised: 22 March 2023

Accepted: 27 March 2023

Published: 13 April 2023

<figure><img src="image_41.png" /></figure>

**Copyright:** © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
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Attribution (CC BY) license (https://
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**Abstract:** Research in normal tissue radiobiology is in continuous progress to assess cellular response following ionizing radiation exposure especially linked to carcinogenesis risk. This was observed among patients with a history of radiotherapy of the scalp for ringworm who developed basal cell carcinoma (BCC). However, the involved mechanisms remain largely undefined. We performed a gene expression analysis of tumor biopsies and blood of radiation-induced BCC and sporadic patients using reverse transcription-quantitative PCR. Differences across groups were assessed by statistical analysis. Bioinformatic analyses were conducted using miRNet. We showed a significant overexpression of the *FOXO3a*, *ATM*, *P65*, *TNF-α* and *PINK1* genes among radiation-induced BCCs compared to BCCs in sporadic patients. *ATM* expression level was correlated with *FOXO3a*. Based on receiver-operating characteristic curves, the differentially expressed genes could significantly discriminate between the two groups. Nevertheless, *TNF-α* and *PINK1* blood expression showed no statistical differences between BCC groups. Bioinformatic analysis revealed that the candidate genes may represent putative targets for microRNAs in the skin. Our findings may yield clues as to the molecular mechanism involved in radiation-induced BCC, suggesting that deregulation of ATM-NF-kB signaling and *PINK1* gene expression may contribute to BCC radiation carcinogenesis and that the analyzed genes could represent candidate radiation biomarkers associated with radiation-induced BCC.

**Keywords:** radiotherapy; radiation-induced BCC; low-dose effects; DNA repair; ATM-NF-kb signaling; *PINK1* gene; microRNA; biomarkers

## 1. Introduction

Basal cell carcinoma (BCC) is the most frequent skin cancer, accounting for 90% of cutaneous cancer, and the most common human malignancy worldwide, characterized by an increasing incidence [1]. According to the Global Cancer Observatory (GLOBOCAN) database,1,198,073 new cases of non-melanoma skin cancer, including BCC, were reported in 2020 [2]. While ultraviolet radiation (UV) is the most known carcinogen involved in skin malignancy, ionizing radiation (IR) exposure is an established etiological risk factor. In fact, radiotherapy is a standard treatment regimen for numerous solid tumors, and it was adopted for the treatment of some benign lesions of the skin, notably ringworm of the scalp (tinea capitis) [3]. Indeed, epidemiological studies have reported that previous depilatory radiotherapy is associated with a fourfold increased risk of cutaneous malignancy in irradiated skin, primarily BCC [4]. BCC occurs after a long period, up to decades after exposure, as a late effect of irradiation, with an inverse correlation between carcinogenesis risk and age at radiation exposure [5,6].

<footnote n="1">¹ Laboratory of Biomedical Genomics and Oncogenetics (LR16IPT05), Institut Pasteur de Tunis, University Tunis El Manar, Tunis 1002, Tunisia</footnote>

<footnote n="2">² Department of Dermatology, Habib Thameur Hospital (LR12SP03), Medicine Faculty, University Tunis El Manar, Tunis 1008, Tunisia</footnote>

<footnote n="3">³ Anatomopathology Department, Habib Thameur Hospital (LR12SP03), Medicine Faculty, University Tunis El Manar, Tunis 1008, Tunisia</footnote>

<footnote>* Correspondence: houda.yacoub@pasteur.utm.tn</footnote>
In addition, conflicting data exist concerning the clinical profile and the prognosis of radio-induced BCC compared to BCC in sporadic cases. Although some studies have reported a similar clinical course independently of radiotherapy history, other reports have described a more aggressive response associated with higher recurrence rates and difficult-to-treat radiation-induced BCC [7–9].

Aberrant activation of Hedgehog signaling is defined as a key common driver of BCC development. Moreover, high-throughput analyses have highlighted the potential contribution of other signaling pathways in BCC tumorigenesis, notably the WNT, Hippo, NOTCH, and mTOR pathways [10,11]. Nevertheless, little attention has been paid to the underlying molecular mechanisms involved in radiation-induced BCC, and studies that were conducted to identify molecular signatures unique to these tumors are controversial [12,13]. It was suggested that identifying the molecular link between the DDR pathway and Hedgehog signaling could unveil the pathogenesis of BCC developed post-radiotherapy [14].

Furthermore, studies based on genomic and transcriptomic profiling are ongoing to decipher the molecular mechanisms of radiogenic cancer and to identify molecular signatures that are discriminatory between radio-induced cancer and its sporadic counterpart. These were explored notably in radiation-induced hematological malignancies [15], sarcoma [16] and thyroid cancer [17]. While some reports have revealed molecular patterns unique to radiation-induced cancer with a lack of consistency, others have failed to identify these signatures, and the mechanisms underlying radiation-induced carcinogenesis are still largely misunderstood [18–20]. In fact, IR induces double-strand DNA breaks (DSBs) which activate ATM protein, a master regulator of the DNA damage response (DDR) pathway, leading subsequently to a cascade of cellular responses that may ultimately contribute to different cell fates [21]. It was reported that different signaling pathways are activated in response to IR in normal and tumor cells, including cellular senescence [22], mitochondrial signaling [23], inflammation [24], oxidative stress response [25], autophagy [26] and microRNA signaling [27–29]. Indeed, it was suggested that tumor recurrence following radiotherapy may be explained by radiation-induced cellular senescence of adjacent normal cells surrounding the tumor [22,30,31].

In this study, we aimed to decipher the molecular mechanism(s) of radiation-induced BCC tumorigenesis by investigating the expression patterns of genes of interest in radio-induced BCC and exploring their potential usefulness as candidate biomarkers specific to this tumoral entity. Moreover, we aimed to study the microRNA-mRNA regulatory network to understand the potential contribution of microRNA regulators in this pathogenesis. Our results identified differential gene expression between radiation-induced and non-radiation-induced BCC, suggesting that the deregulation of ATM-NF-kB signaling and *PINK1* expression could be involved in the pathogenesis of radiation-induced BCC.

## 2. Results

### 2.1. *Clinical Features of BCC Patients*

Patients were separated into two groups depending on history of radiotherapy of the scalp for tinea capitis during their childhood: radiation-induced (radio-induced) BCC and non-radiation-induced (non-radio-induced) BCC developed in sporadic patients.

According to the experience of the referral center, the "Dermatology department of Habib Thameur Hospital", the majority of patients treated with radiotherapy for tinea capitis develop nodular BCC on the scalp.

To avoid any bias due to patient selection that may have affected gene expression levels, the patients enrolled in both groups were selected to match different parameters (age at BCC diagnosis, UV exposure, etc.) as closely as possible. All collected tumors were localized on the face (six cases) and on the scalp (two cases). All tumors were primary BCCs. Mean age at diagnosis was 66.25 and 65.5 for the radio-induced and non-radio-induced groups, respectively. The tumors were of nodular or adenoid histology independently of radiation etiology. The majority of patients, especially radio-BCC patients, showed multiple lesions. Adenoid tumors coexisted with basosquamous carcinoma at the same anatomical
site or with morphea form BCC ata nearby site in the cases of BCC2 and BCC5, respectively. Basosquamous carcinoma and morphea form BCC are aggressive BCC subtypes. Within our cohort, BCC patients presented different clinical phenotypes (according to the numbers and sites of lesions and histopathological subtypes) independently of IR exposure. Clinical and anatomopathological parameters were obtained from medical records and are summarized in Table 1. Different clinical and histopathological BCC subtypes are presented in Figures 1 and 2 respectively.

<table><caption>**Table 1.** Patients' characteristics.</caption><thead><tr><th>Patient</th><th>Gender</th><th>Ethnicity</th><th>Age</th><th>History of Radiotherapy</th><th>Histology</th><th>Tumor Size</th><th>Multifocality</th><th>Tumor Location</th></tr></thead><tbody><tr><td>BCC2</td><td>M</td><td>Tunisia</td><td>60</td><td>Yes</td><td>Adenoid</td><td>3 cm</td><td>Yes (n = 7)</td><td>Temporal region of the face</td></tr><tr><td>BCC4</td><td>M</td><td>Tunisia</td><td>60</td><td>Yes</td><td>Adenoid</td><td>3 cm</td><td>Yes (n = 2)</td><td>Temporal region of the face</td></tr><tr><td>BCC5</td><td>M</td><td>Tunisia</td><td>79</td><td>No</td><td>Adenoid</td><td>1 cm</td><td>Yes (n = 3)</td><td>Temporal region of the face</td></tr><tr><td>BCC8</td><td>M</td><td>Tunisia</td><td>85</td><td>Yes</td><td>Nodular</td><td>2.5 cm</td><td>No</td><td>Scalp</td></tr><tr><td>BCC12</td><td>F</td><td>Tunisia</td><td>63</td><td>No</td><td>Nodular</td><td>3 cm</td><td>Yes (n = 2)</td><td>Ala of nose</td></tr><tr><td>BCC16</td><td>M</td><td>Tunisia</td><td>40</td><td>No</td><td>Nodular</td><td>3 cm</td><td>No</td><td>Ala of nose</td></tr><tr><td>BCC19</td><td>M</td><td>Tunisia</td><td>80</td><td>No</td><td>Nodular</td><td>3 cm</td><td>No</td><td>Cheek</td></tr><tr><td>BCC22</td><td>M</td><td>Tunisia</td><td>60</td><td>Yes</td><td>Nodular</td><td>2 cm</td><td>Yes (n = 2)</td><td>Scalp</td></tr></tbody></table>

<figure><img src="image_42.png" /><figcaption>**Figure 1.** Radio-induced and non-radio-induced BCC patients. 1-corresponds to a non-radio-induced BCC patient. 2,3-correspond to two radio-induced patients: 2-presents one small malignant lesion; 3-presents multiple lesions on the scalp. The aggressive form of BCC is independent of radiation etiology in this cohort.</figcaption></figure>
<figure><img src="image_43.png" /><figcaption>**Figure 2.** Hematoxylin-and-eosin-stained section of BCC tumor tissues representative of different histopathological subtypes of BCC. (A) Adenoid basal cell carcinoma with pseudo-glandular appearance. The stroma is fibrous (×100). (B) Nodular subtype of basal cell carcinoma with melanin deposit (×100). (C) Morphea form basal cell carcinoma with narrow cords of basaloid cells which are compressed by abundant sclerotic collagenous stroma (×100). (D) Basosquamous basal cell carcinoma (×100). (E) A focal squamous differentiation (×200). Scale bars = 200 µm for (A–D) and 50 µm for (E).</figcaption></figure>

## 2.2. *Molecular Analysis*

All tumors located on the head was selected as an inclusion criterion. This decision was made in order to exclude any differential gene expression associated with molecular signatures linked to UV exposure. First, we investigated *FOXO3a*, *ATM*, *P65*, *PINK1* and *TNF-α* expression in radio-induced BCC and non-radio-induced BCC and in age-matched healthy controls using the rt-qPCR technique. Our data revealed significant upregulation of *FOXO3a*, *ATM*, *P65*, *PINK1* and *TNF-α* genes among the radio-induced BCC patients compared to the non-radio-induced BCC group (*p* = 0.021 for each of the *ATM*, *P65*, *PINK1* and *TNF-α* genes; *p* = 0.043 for *FOXO3a*) (Figure 3).

Furthermore, a significant strong positive correlation was observed between *ATM* and *FOXO3a'* expression among BCC patients using the Pearson correlation test (r = 0.951, *p* = 0.000289) (Figure 4). A positive correlation was also observed between *ATM* and *P65* (r = 0.984, *p* = 0.000009) and between *ATM* and *TNF-α* (r = 0.976, *p* = 0.000036).
<figure><img src="image_44.png" /><figcaption>**Figure 3.** Differential gene expression profiles for radio-induced and non-radio-induced BCC biopsies. Blue box plot: non-radio-induced BCC (NR); green box plot: radio-induced BCC (R). (* = *p* < 0.05).</figcaption></figure>

<figure><img src="image_45.png" /><figcaption>**Figure 4.** Correlation between *FOXO3a* and *ATM* expression in BCC patients’ biopsies. Pearson correlation of *FOXO3a* and *ATM* gene expression fold changes among BCC patients revealed a strong positive correlation of these genes with a Pearson correlation coefficient (r) = 0.951 (p = 0.00289). Each circle represents the expression levels of both genes for each patient.</figcaption></figure>
We further examined the potential of *FOXO3a*, *ATM*, *P65*, *PINK1* and *TNF-α* genes to discriminate between radio-induced and non-radio-induced BCC using ROC curve analysis. We defined cut-off values of 0.179, 7.956, 7.09, 16.78 and 0.46 for *FOXO3a*, *ATM*, *P65*, *PINK1* and *TNF-α*, respectively, based on the Youden index method. Our results revealed that the gene expression levels could significantly differentiate between BCC groups (area under the curve (AUC) = 1, *p* = 0.021, for the *ATM*, *P65*, *PINK1* and *TNF-α* genes, with 100% specificity and 100% sensitivity, and AUC = 0.938, *p* = 0.043, with 100% sensitivity and 75% specificity, for *FOXO3a*) (Figure 5). In fact, these genes showed an excellent diagnostic performance, which suggests their usefulness as potential diagnostic biomarkers for radio-induced BCC.

<figure><img src="image_46.png" /></figure>

**Figure 5.** ROC curve analysis of differentially expressed genes between radio-induced and non-radio-induced BCC. ROC analysis for the *FOXO3a*, *ATM*, *P65*, *PINK1* and *TNF-α* genes in different plots. The *p*-value is the probability that the observed sample AUC-ROC is found when the true AUC-ROC is 0.5 (null hypothesis: the variable cannot distinguish between the two groups; area = 0.5 if the ROC coincides with the reference line). We found that the area under the curve is significantly different from 0.5. *ATM*, *P65*, *PINK1* and *TNF-α* have excellent discrimination performance, with AUCs = 1 (100%specificity and 100% sensitivity). The ROC curve foreach of them passes through the upper left corner of the plot, while *FOXO3a* has an ROC curve close to the upper left corner, with an AUC = 0.938 that represents an excellent diagnostic value.

Subsequently, the expression levels of the *TNF-α* and *PINK1* genes were analyzed in the blood of patients with BCC to assess their potential as non-invasive biomarkers for radio-induced BCC. Our data showed a similar expression profile for *TNF-α* among BCC patients in both groups (*p* > 0.05). Inaddition, *PINK1* analysis revealed upregulation among radio-induced BCC compared to non-radio-induced BCC, which was in accordance with the *PINK1* expressionin patients´ biopsies. However, this differential expression failed to reach statistical significance (*p* > 0.05) (Figure 6).
<figure><img src="image_47.png" /><figcaption>**Figure 6.** Differential gene expression profiles between radio-induced and non-radio-induced BCC in patients' blood. Blue box plot: non-radio-induced BCC NR; green box plot: radio-induced BCC R.</figcaption></figure>

## 2.3. *Bioinformatic Analysis*

We examined putative interactions between the differentially expressed genes and microRNAs (miRNAs) in the skin using the miRNet database. An miRNA-target interaction network was created that included several upstream miRNAs that interact directly with FOXO3a, ATM, P65, TNF-α and PINK1 mRNAs, representing a complex landscape of functional associations. Each node represents an mRNA or miRNA (Figure 7). In fact, miRNAs are intricately involved in the DDR pathway by targeting ATM in the skin. FOXO3a and ATM had the highest interaction (highest connectivity degree) and hence were the most important hubs in this network analysis. miR-24-3p was the most important miRNA regulating the network based on its having the highest node degree (Table 2). According to the Reactome database, cellular senescence was the most enriched pathway (*p* = 0.0026, adj. *p* < 0.05).

<figure><img src="image_48.png" /><figcaption>**Figure 7.** miRNA-mRNA interaction network with differentially expressed genes in the skin, constructed using miRNet database data.</figcaption></figure>
<table><caption>**Table 2.** Top miRNAs and targeted mRNAs in the network interactions determined via miRNet.</caption><thead><tr><td>Node</td><td>Degree</td></tr></thead><tbody><tr><td>FOXO3a</td><td>13</td></tr><tr><td>ATM</td><td>9</td></tr><tr><td>RELA</td><td>6</td></tr><tr><td>TNF</td><td>5</td></tr><tr><td>hsa-mir-24-3p</td><td>4</td></tr><tr><td>PINK1</td><td>4</td></tr><tr><td>hsa-mir-124-3p</td><td>3</td></tr><tr><td>hsa-mir-155-5p</td><td>3</td></tr><tr><td>hsa-mir-26a-5p</td><td>2</td></tr><tr><td>hsa-mir218-5p</td><td>2</td></tr><tr><td>hsa-mir-27b-3p</td><td>2</td></tr><tr><td>hsa-mir-22b-3p</td><td>2</td></tr><tr><td>hsa-mir-22b</td><td>2</td></tr><tr><td>hsa-mir-let-7b-5p</td><td>3</td></tr></tbody></table>

The majority of these miRNAs are described in the literature as IR-responsive and are primarily involved in cellular senescence (this will be discussed below). Hence, we suggest that deregulation of these miRNAs in response to IR may affect skin cells' response to irradiation, notably linked to the analyzed pathways, which may be associated with the carcinogenesis process.

### 3. Discussion

In our study, we aimed to identify differentially expressed genes between radio-induced and non-radio-induced BCC which may provide insights into the molecular contributors to or the under pinning sofradio-induced carcinogenesis. To the best of our knowledge, our study was the first to explore the ATM-NF-kB pathway and *PINK1* expression in radio-induced BCC. In addition, we suggest that miRNA regulation of these pathways may shed light on radio-induced BCC.

BCC represents a significant health and socio-economic burden given its high frequency and incidence [32]. BCC is rarely invasive or metastatic and is usually associated with a good prognosis. However, it may lead to significant morbidity due to its locally destructive potential and its relatively high recurrence rate [33]. In addition, different BCC entities exist, though the genetic basis of the carcinogenic process and clinical differences are not fully elucidated [34]. Moreover, it is unclear whether mechanisms of BCC carcinogenesis differ according to etiological factors.

IR is a well-known risk factor for skin malignancies. Clinical and epidemiological studies have reported a high rate of BCC cancer following IR exposure, which has primarily been described in the context of treatment for tinea capitis during childhood [4]. It was suggested that cancer risk may persist throughout the life of exposed individuals [35]. Conflicting data exist concerning the prognosis of radio-induced BCC.

#### - Clinical features of radio-induced BCC and non-radio-induced BCC

In the present study, patients were characterized by different clinical profiles independently of radiation etiology, presenting adenoid or nodular subtypes. Although nodular BCC is the most frequent subtype, adenoid tumors are very rare histopathological variants that are considered low-grade BCCs [36]. Adenoid tumors were isolated or associated with other subtypes, notably basosquamous and morphea form BCC, for BCC2 and 5, respectively, which are aggressive BCC subtypes [37,38]. Nodular BCC was classified as a low-risk tumor according to the WHO classification. According to BCC risk stratification, BCC8 and BCC19 are associated with an intermediate prognosis, as they are characterized as nodular subtypes, with sizes> 2 cm, and are located in low-risk areas [39]. Based on the new BCC classification, tumors may be classified as "easy-to-treat" or "difficult-to-treat", which classifications are associated with different clinical outcomes [40,41]. Although some
tumors included in our study were “easy-to-treat” BCCs, some of them presented specific features that may pose treatment difficulties, which may be linked to tumor location, as with BCC12 and BCC16 sporadic cases (located in patients’ noses). These tumors have a high risk of recurrence. In fact, our data are consistent with a study which reported that IR exposure does not affect clinical and histopathological features or even patient prognosis [42]. However, other studies have reported a more aggressive phenotype among radio-induced BCC [9]. Herein, prognosis was assessed based on clinical prognostic factors.

- Gene expression analysis to decipher radio-induced BCC carcinogenesis mechanisms

Despite radiation exposure being a known carcinogenic factor for BCC, the underlying molecular mechanisms are not yet fully understood. Although those studies have reported the absence of molecular signatures that could discriminate between radio-induced and non-radio-induced BCC, particularly linked to the *PTCH* and *TP53* genes [13,43], it was suggested that the Hh signaling pathway could be linked to susceptibility to BCC radiation carcinogenesis and that *PTCH* could contribute to this process [43]. In fact, it was reported that the genetic background of Ptch-mutated mice may affect susceptibility to BCC development after IR exposure [44,45]. Furthermore, it was suggested that genomic instability could explain genetic susceptibility to radio-induced BCC carcinogenesis [46], which may predispose to mitochondrial DNA mutations [47]. Recently, a genomic characterization of radio-induced BCC versus sporadic cases has revealed specific chromosomal rearrangements that could discriminate between both groups [12].

- ATM-NF-kB signaling and PINK1-mediated mitophagy in response to irradiation

In our study, we report differentially expressed genes between BCC groups that are radiation-responsive and mainly involved in IR-driven BCC carcinogenesis. *ATM* and *FOXO3a* expression were significantly increased in BCC biopsies from irradiated patients compared to sporadic cases. In fact, IR induces DSBs which trigger the DDR pathway. *ATM* is a master regulator involved in the coordination of cellular response to radiation-induced DNA damage and a key determinant of radio-sensitivity [48]. In addition, *ATM* expression was significantly correlated with *FOXO3a* expression level in BCC patients. This suggests a potential regulation, at least in part, of *ATM* by *FOXO3a* transcription factors. Indeed, it was reported that in the DDR pathway, *FOXO3a* interacts directly with *ATM*, which is required for ATM autophosphorylation, promoting the ATM response network [49]. However, our findings were in agreement with the fact that *FOXO3a* regulates *ATM* gene expression, which has been reported in hematopoietic stem cells [50]. Nonetheless, it was described that, in response to DNA damage, *FOXO3a* upregulation maintains genomic stability and is mediated by H2AX, a downstream target of ATM [51,52]. However, *FOXO3a* and *ATM* expression levels were not correlated among three radio-induced patients, which may suggest that other factors are involved in *ATM* regulation in BCC radiation carcinogenesis. Moreover, we revealed upregulation of *P65*, which coded for an NF-kB subunit, and of *TNF-α*, which coded for a pro-inflammatory cytokine and a senescence-associated secretory phenotype (SASP) factor, among irradiated patients. A positive correlation was observed between ATM and P65 and between ATM and *TNF-α*, which could suggest a molecular link between ATM and NF-kB. In fact, IR triggers cellular senescence in normal and cancer cells. ATM is a key driver of NF-kB-induced cellular senescence following DNA damage through the secretion of SASP factors, which enhance NF-kB signaling in an autocrine manner via cytokine receptors [22]. Our data suggest an aberrant activation/over-presentation of the ATM-NF-kB signaling pathway in response to IR. Despite this, we did not directly analyze NF-kB signaling activation. The high expression levels of *TNF-α* and *P65* are indicative markers of NF-kB activation. A few studies have been performed to assess the biological effect of IR on human skin cells which revealed the activation of the DDR pathway, an inflammatory response [53–55], and the expression of cellular senescence markers [56]. Moreover, in the context of cancer radiotherapy, IR induced cellular senescence of normal cells adjacent to tumors, leading to either tissue fibrosis and organ dysfunction or to tumorigenesis [22,30,31]. Indeed, it was suggested that
transient senescent cells are associated with an anti-tumoral effect, while their accumulation is linked to a detrimental effect leading to increased cancer susceptibility [57].

Furthermore, ATM plays an important role in mitochondrial responses to irradiation, following recognition of nuclear DNA damage and subsequent damage signal transduction to mitochondria, playing an important role in the crosstalk between these two organelles in irradiated fibroblast cells, which enhance mitochondrial biogenesis and ROS generation [58]. Although nuclear DNA was primarily considered as a main target of IR, the involvement of mitochondria as key targets of IR and as contributors to radio-induced cell impairment is becoming increasingly evident [23,59] and could explain the high risk of carcinogenesis [60]. Despite the role of mitochondrial dysfunction in response to irradiation being well understood, the involvement of mitochondrial integrity and dynamics has been less explored. In fact, ATM can promote selective elimination of defective mitochondria, termed mitophagy, via activation of the PINK1/Parkin pathway; however, the mechanism involved is not fully elucidated. It was described that ATM impacts this pathway via kinase-dependent [61] or -independent mechanisms through the regulation of PINK1 (PTEN-induced putative kinase1) expression or interaction with Parkin [62,63]. In addition, ATM-deficient cells revealed that mitophagy induction following irradiation is ATM-dependent [64]. We analyzed PINK1 gene expression, a key contributor to mitophagy, and observed over expression in radio-induced BCC compared to non-radio-induced cases. In addition, FOXO3a enhances PINK1 gene expression, leading to a pro-survival signal in response to oxidative stress [65]. This was in accordance with another study which suggested that under extensive mitochondrial alterations, mitophagy activation enhances cell survival following irradiation [66]. However, it was suggested that post-irradiation mitophagy induction could maintain cellular redox control and that disruption of this pathway leads to tumorigenesis [60]. Another report has described that mitophagy effect depends on irradiation dose [67].

In summary, our results suggest that the ATM-NF-kB signaling pathway and the *PINK1* gene, related to cellular senescence and mitophagy, are involved in radio-induced BCC carcinogenesis.

- Biomarkers of radio-induced BCC

ROC curve analysis revealed that the differentially expressed genes could significantly discriminate between radio-induced BCC and non-radio-induced BCC and may consequently represent candidate radio-induced BCC biomarkers. This could guide further validation studies aiming to investigate the relevance of these candidate biomarkers with larger cohorts based on independent sets of samples. Such studies could provide straightforward evidence of potential radiation biomarkers and be a step toward understanding radio-susceptibility to BCC. Indeed, accumulating studies are seeking to identify molecular peculiarities unique to radiation-induced cancer compared to sporadic counterparts, as they are often clinically indistinguishable, which may lead to the decipherment of key events involved in radiation carcinogenesis [15]. Conflicting data have been generated, while some reports have identified specific signatures associated with molecular fingerprints of radiation-induced cancer. Others have often described similar molecular patterns independently of radiation etiology, and no accurate molecular signature/biomarker has yet been settled [16,18,68]. Further studies are warranted to untangle the underlying mechanisms. Therefore, we examined whether these biomarkers in particular, *TNF-α* and *PINK1* could serve as non-invasive tools by analyzing their expression profiles in patients' blood. *TNF-α* was under-expressed in BCC patients, with a similar pattern independent of radiation etiology. These data may support that *TNF-α* alteration was tumor-specific. This finding was supported by a loop between radio-induced inflammation, mobilization of immune cells and sustained tissular damage, mediated by DNA damage and SASP factors following irradiation [69]. However, our results were in discordance with previous studies that reported persistent systemic inflammation in individuals with a history of IR exposure [70]. This was explained by possible confounding factors or by the combinatorial effect of patient age and irradiation [71–73]. In fact, the BCC patients included in our study were age-
matched; accordingly, the differences in gene expression probably reflect cellular response to irradiation. In addition, inflammatory systemic response may be explained by blood cell response to irradiation, since these individuals were exposed to whole-body rather than localized irradiation. On the other hand, *PINK1* was differentially expressed between the two BCC groups, with overexpression in irradiated cases; however, this differential expression failed to reach statistical significance. In fact, an increase in *PINK1* expression in rat thyroids was reported following irradiation [74]. Our results point out, at least, that the analyzed genes could not represent non-invasive radio-BCC biomarkers.

- miRNA regulators in BCC radiation carcinogenesis

Our current understanding of cellular response to irradiation has evolved to a more complex network that involves different molecular determinants, such as epigenetic regulators, mainly miRNAs [75]. miRNAs mediate cellular radio-response via regulating components of key signaling pathways involved in this process, specifically DDR signaling [76]. Indeed, it was suggested that gene expression profile alterations following irradiation are largely explained by miRNAs, which play a crucial role in defining cell fates, controlling subsequent radiosensitivity [77]. Moreover, it was described that miRNAs participate in radiation carcinogenesis [78–80]. In this study, miRNAs represented in the network analysis created by miRNet are mostly described as radio-responsive. miR-24-3p represents the most important miRNA in the generated network, targeting the *ATM*, *RELA* (*P65*) and *PINK1* genes. In fact, it was reported that miR-24-3p plays a crucial role in carcinogenesis and therapeutic response associated with radiosensitivity [81]. miR-24 was described as a regulator of cellular response to DNA damage, and its downregulation enhances tumor cell radio-resistance [82]. Furthermore, miR-24 expression decreases with cellular senescence [83], and it was defined as a mitochondrial miR (mitomiR) [84]. It was described that miR-24-3p and miR-124 attenuate the expression of pro-inflammatory mediators via NF-κB signaling [85,86]. miR-124 also increases in senescent skin, while it decreases during tumorigenesis, particularly in squamous cell carcinoma [87]. In addition, it was reported that Let-7 family expression patterns are altered upon irradiation, characterized by ATM-dependent downregulation in skin fibroblasts [88]. miR-26a and miR-100a were described as enhancing tumor cell radio-sensitivity via targeting DNA repair proteins [89,90]. miR-145 is described as a regulator of the DDR pathway and cellular senescence in different cell types [91,92]. Downregulation of miR-145-5p was also reported in basal cell carcinoma [93]. Indeed, it was revealed that senescence-associated miRNAs (SA-miRs) are implicated in radiation-induced premature cellular senescence and that the knockdown of miR-155 stimulates this process [94]. miR-181a/b are involved in keratinocyte replicative senescence and are dysregulated in cancers [95]. According to miRNA transcriptome profiling, miR-222 was repressed in irradiated cells [96]. Moreover, miR-24 is a radiation-responsive miRNA that may represent a potential biomarker of radiation-induced gastric cancer [97]. We suggest that this network may give insights into the regulatory role of microRNAs in radio-induced BCC; some of these miRNAs may contribute to the pathogenesis of BCC through the regulation of ATM-NF-κB signaling and PINK1 expression level in response to irradiation. Experimental studies are warranted to validate these interactions in radio-induced BCC.

Further research in the field of normal tissue radiobiology is of paramount importance to decipher the mechanisms involved in cellular radio-response. In fact, even though depilatory radiotherapy is no longer used, IR is still used as a clinical diagnostic tool and a therapeutic modality, besides being used for occupationally/accidentally exposed individuals, and the incidence of BCC is continuously increasing. Moreover, patients with cancers, including some BCCs amenable to radiotherapy, may develop a second malignancy due to the radiosensitivity of healthy tissues surrounding the tumor, which affects treatment efficiency. The identification of promising biomarkers is an unmet need to improve long-term risk assessment following IR exposure, which may aid clinicians in monitoring exposed individuals. These biomarkers may represent novel targets to prevent or at least minimize cellular radiotoxicity linked to carcinogenesis risk.
To our knowledge, our study represents the first investigation of ATM-NF-kB signaling and *PINK1* gene expression, implicated in cellular senescence and mitophagy in BCC pathogenesis following radiotherapy. Further studies are needed to deeply characterize and explore these processes in a larger cohort of radio-induced BCC patients. Moreover, proteins encoded by the studied genes should be analyzed to further confirm the activation of these pathways. In addition, further studies are mandatory to shed light on the complexity of the interactions between genes of interest and microRNAs in response to irradiation.

# 4. Materials and Methods

## 4.1. Human Specimens and Sample Collection

We conducted a comparative study using patients' fresh frozen skin biospecimens and blood. According to histological evaluation, confirmed by an atomopathologist, a total of eight patients diagnosed with basal cell carcinoma were enrolled in this study. Four of the BCC samples were obtained from sporadic patients and four were obtained from patients with a history of radiotherapy of the scalp for tinea capitis during their childhood and were considered as radio-induced BCC. All tumors being located on the face and scalp area was an inclusion criterion. One healthy skin biopsy from a UV-exposed area from the head of a healthy age- and geographically matched control was included after screening for the absence of any signs of malignancy. Systemic investigation was performed for five of the patients, including three radio-induced BCCs and two BCCs from sporadic cases (or non-radiation-induced BCC), and the sample from the healthy control. BCC and healthy control biopsies were collected from the Dermatology department of "Habib Thameur" Hospital.

All participants included in this study provided written informed consent, and the study was carried out in accordance with the Helsinki principles and approved by the Institute Pasteur Ethics Committee in Tunisia under the ethical accord number (reference PCI/22/2012/v2).

## 4.2. Gene Expression Analysis

### 4.2.1. RNA Extraction and cDNA Synthesis

Total RNA from the tissue and blood samples of patients with BCC and the healthy control were extracted using trizol and the miRNeasy Mini Kit (QIAGEN), following the manufacturer's instructions. The concentration and purity of isolated RNA was assessed using the Nanodrop spectrophotometer DeNovix DS-11 (Thermo Fisher Scientific, Wilmington, DE, USA).

Prior to total isolated RNA reverse transcription (RT), a DNase treatment was carried out in a Qsp of 10 µL, using 1 µg of RNA, 10X DNase Buffer and 1 U/µL of DNase I enzyme. After RNA sample incubation at ambient temperature for 15 min, 25 mM of EDTA was added, and RNA was then placed at 65 °C for 10 min. The cDNA synthesis was performed using the Superscript II RT Kit (Cat. No:18064014 Invitrogen, Carlsbad, CA, USA), starting with 1µg of purified RNA in a total reaction volume of 20 µL, according to the manufacturer's protocol.

### 4.2.2. Quantitative Real-Time PCR

The *ATM*, *FOXO3a*, *P65* (*RELA*), *TNF-α* and *PINK1* genes were investigated by quantitative real-time PCR (qPCR) using the Syber Green kit, according to the manufacturer's protocol. Among genes involved in cellular senescence and mitophagy, this set of genes was selected after exploring gene expression data generated by the GTEx (Genotype-Tissue Expression) database. These genes are expressed in human skin cells and showed no differences between sun-exposed and non-sun-exposed skin areas. Specific primers were used. The qPCR reaction was carried out in a 96-well plate using the Light Cycler L480 (Roche Applied System) with a reaction volume containing Sybr Green Mix (Invitrogen), Quantities of 10 µM of each forward and reverse primer for 17 µL of Mix and 100 ng/µL of cDNA were used. cDNA amplification was performed in a cycling protocol with 35 cycles (at 95 °C for 15 s and for 60 °C for 1 min) preceded by a pre-amplification step at 95 °C
for 10 min. Relative gene expression levels were normalized to the expression of the housekeeping gene *RPLP0*. Experiments were performed in duplicate for each candidate target gene and for each reference gene. Relative fold changes were calculated using the comparative cycle threshold (ct) method ($2^{-\Delta\Delta C_t}$). The sequences of the primers are listed in Table 3.

<table><caption>**Table 3.** Primer sequences used for qPCR.</caption><thead><tr><th>Gene</th><th>Sequence (5'-3')</th><th>Length</th><th>Tm (°C)</th></tr></thead><tbody><tr><td rowspan="2">FOXO3a</td><td>F: CGGACAAACGGCTCACTCT</td><td>19</td><td>61.9</td></tr><tr><td>R: GGACCCGCATGAATCGACTAT</td><td>21</td><td>61.7</td></tr><tr><td rowspan="2">ATM</td><td>F: GCACGAAGTGCCCTCCAATTC</td><td>21</td><td>61.1</td></tr><tr><td>R: ACATTCTGGCACGCTTTGG</td><td>19</td><td>61.4</td></tr><tr><td rowspan="2">TNF-α</td><td>F: CCTCTCTCTAATCAGCCCTCTG</td><td>22</td><td>62.1</td></tr><tr><td>R: GAGGACCTGGGAGTAGATGAG</td><td>21</td><td>62.8</td></tr><tr><td rowspan="2">PINK1</td><td>F: CCCAAGCAACTAGCCCCTC</td><td>19</td><td>64.5</td></tr><tr><td>R: GGCAGCACATCAGGGTAGTC</td><td>20</td><td>63.1</td></tr><tr><td rowspan="2">P65</td><td>F: ATGTGGAGATCATTGAGCAGC</td><td>21</td><td>60</td></tr><tr><td>R: CCTGGTCCTGTGTAGCCATT</td><td>20</td><td>60.2</td></tr></tbody></table>

### 4.3. Statistical Analysis

IBM SPSS version 21.0 was used for statistical analysis. Differences across specimen groups and gene expression correlations were inspected using the Mann-Whitney U and Pearson exact tests, respectively. Area under the curve-receiver operating characteristic (AUC-ROC) analysis was performed to evaluate the potential of candidate genes to discriminate between radio-induced BCC and non-radio-induced BCC groups. An excellent model for a good separation performance was considered when the AUC value was near to 1. Cut-off values were determined according to the Youden index method. Maximizing the Youden index enabled the identification of the cut-off point of the curve with the highest value for the sum of sensitivity and specificity. For all tests, a *p*-value < 0.05 was considered statistically significant.

### 4.4. Bioinformatic Analysis

We explored the miRNet 2.0 database to identify putative upstream microRNAs that target the candidate genes and generate an miRNA-target gene interaction network-based visual analysis of the skin. In fact, node degrees (the numbers of connections with other nodes) indicate important hubs in the generated network. In addition, miRNet offers a functional enrichment analysis, which was performed with the Reactome pathway tool (adjusted *p* < 0.05).

## 5. Conclusions

We suggest that aberrant regulation of ATM-NF-kB signaling and *PINK1* gene expression could be related to BCC radiation carcinogenesis and that biomarkers involved in these pathways may discriminate between BCCs according to their radiation etiologies. Furthermore, we suggest that microRNAs may play an important role as well, highlighting their potential implication in the pathogenesis of radio-induced BCC. Our study highlights the importance of the exploration of radio-induced carcinogenesis and extends our understanding to a more complex network involving different interconnected cellular and molecular components.
**Author Contributions:** R.J. performed the experiments, analyzed the data and drafted the manuscript. A.C. collected the biospecimens, helped with the experiments and reviewed the manuscript draft. I.N. helped with the biospecimen collections. A.Z. performed the skin biopsies. F.K. performed the anatomopathological analysis for tumor biopsies. H.H.-G. undertook the patient recruitment and clinical follow-up of patients. H.Y.-Y. was responsible for the study conception, supervised the study and revised the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** The study was supported by the Tunisian Ministry of Public Health, the Ministry of Higher Education and Scientific Research (LR16IPT05) and the "Project Collaborative Interne" (PCI_Melanoma, IPT).

**Institutional Review Board Statement:** This study was carried out in accordance with the Helsinki principles and approved by the Institute Pasteur Ethics Committee in Tunisia under the ethical accord number (reference PCI/22/2012/v2).

**Informed Consent Statement:** Written informed consent was obtained from all subjects involved in the study for the molecular investigation and publication of the article.

**Data Availability Statement:** All data have been provided in the manuscript. The data generated in this study can be provided by the corresponding author upon reasonable request.

**Acknowledgments:** We would like to thank the patients for their collaboration and trust.

**Conflicts of Interest:** The authors declare no conflict of interest.

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<figure><img src="image_49.png" /></figure>

Review

# High Resolution and Automatable Cytogenetic Biodosimetry Using In Situ Telomere and Centromere Hybridization for the Accurate Detection of DNA Damage: An Overview

Radhia M'Kacher <fnref n="1" />*, Bruno Colicchio <fnref n="2" /> ID, Steffen Junker <fnref n="3" />, Elie El Maalouf <fnref n="1" />, Leonhard Heidingsfelder <fnref n="4" />, Andreas Plesch <fnref n="4" />, Alain Dieterlen <fnref n="2" />, Eric Jeandidier <fnref n="5" /> ID, Patrice Carde <fnref n="6" /> and Philippe Voisin <fnref n="1" />

<figure><img src="image_50.png" /></figure>

check for
updates

**Citation:** M'Kacher, R.; Colicchio, B.; Junker, S.; El Maalouf, E.; Heidingsfelder, L.; Plesch, A.; Dieterlen, A.; Jeandidier, E.; Carde, P.; Voisin, P. High Resolution and Automatable Cytogenetic Biodosimetry Using In Situ Telomere and Centromere Hybridization for the Accurate Detection of DNA Damage: An Overview. *Int. J. Mol. Sci.* **2023**, *24*, 5699. https://doi.org/10.3390/ijms24065699

Academic Editors: François Chevalier
and Ivan Y. Iourov

Received: 16 December 2022

Revised: 7 March 2023

Accepted: 10 March 2023

Published: 16 March 2023

<figure><img src="image_51.png" /></figure>

**Copyright:** © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).

**Abstract:** In the event of a radiological or nuclear accident, or when physical dosimetry is not available, the scoring of radiation-induced chromosomal aberrations in lymphocytes constitutes an essential tool for the estimation of the absorbed dose of the exposed individual and for effective triage. Cytogenetic biodosimetry employs different cytogenetic assays including the scoring of dicentrics, micronuclei, and translocations as well as analyses of induced premature chromosome condensation to define the frequency of chromosome aberrations. However, inherent challenges using these techniques include the considerable time span from sampling to result, the sensitivity and specificity of the various techniques, and the requirement of highly skilled personnel. Thus, techniques that obviate these challenges are needed. The introduction of telomere and centromere (TC) staining have successfully met these challenges and, in addition, greatly improved the efficiency of cytogenetic biodosimetry through the development of automated approaches, thus reducing the need for specialized personnel. Here, we review the role of the various cytogenetic dosimeters and their recent improvements in the management of populations exposed to genotoxic agents such as ionizing radiation. Finally, we discuss the emerging potentials to exploit these techniques in a wider spectrum of medical and biological applications, e.g., in cancer biology to identify prognostic biomarkers for the optimal triage and treatment of patients.

**Keywords:** cytogenetic biodosimetry; radioprotection; telomere; centromere; chromosomal instability

1. Introduction

Biological dosimetry refers to the quantitative estimation of an absorbed dose of radia-
tion in individuals exposed to ionizing radiation [1]. Radiation exposure may occur due
to the geological environment, medical diagnostics and therapy, occupation in radiation
facilities or the nuclear industry, or large-scale incidents such as accidents in nuclear indus-
tries, nuclear tests, fallouts, nuclear terrorism, or dirty bombs [2–4]. Individuals involved
in large-scale incidents often do not have personal dosimeters. In cases of exposures re-
quiring dose reconstruction, regardless of the circumstances, biological dosimetry becomes
a valuable tool in the accurate assessment of the absorbed radiation dose in the shortest
possible time for successful and effective triage and medical management.

The DNA-damaging effects of genotoxic stress such as ionizing radiation may result
in chromosome aberrations that can be used as a biomarker, i.e., a biological endpoint to
indicate an earlier event as a result of exposure [5]. Biological dosimetry based on cytoge-
netic assays, termed cytogenetic biodosimetry, has, for decades, been the most extensively

<footnote n="1">¹ Cell Environment DNA Damage R&D, Genopole, 91000 Evry-Courcouronnes, France</footnote>

<footnote n="2">² IRIMAS, Institut de Recherche en Informatique, Mathématiques, Automatique et Signal, Université de Haute-Alsace, 69093 Mulhouse, France</footnote>

<footnote n="3">³ Institute of Biomedicine, University of Aarhus, DK-8000 Aarhus, Denmark</footnote>

<footnote n="4">⁴ MetaSystems GmbH, Robert-Bosch-Str. 6, D-68804 Altlussheim, Germany</footnote>

<footnote n="5">⁵ Laboratoire de Génétique, Groupe Hospitalier de la Région de Mulhouse Sud-Alsace, 69093 Mulhouse, France</footnote>

<footnote n="6">⁶ Department of Hematology, Institut Gustave Roussy, 94804 Villejuif, France</footnote>

<footnote>* Correspondence: radhia.mkacher@cell-environment.com; Tel.: +33-160878918</footnote>
studied system. The assays are usually performed on peripheral blood lymphocytes (PBL) because they are easily accessible. The assays are based on the quantification of radiation-induced chromosomal aberrations such as chromosome dicentrics (DC), cytokinesis-block micronuclei (CBMN), premature chromosome condensation (PCC), fragments/rings, or fluorescence in situ hybridization (FISH) for chromosome painting to monitor, e.g., translocations. Three of the techniques, i.e., DC assay (DCA), CBMN, and FISH have now been standardized for monitoring and quantifying the resulting chromosome aberrations in PBL. One of the assays, the DCA, is considered the “gold standard” for biological dosimetry in radiation emergency medicine by IAEA and other international agencies due to the radio-specificity of DCs. Of note, DCA has proven its utility in past large-scale nuclear accidents or accidents such as the Chernobyl accident in 1986 [6].

The assessment of individual doses of exposure in a population should be carried out within the shortest possible time for effective triage and medical intervention, especially in the event of a large-scale radiation incident involving a sizable population group. However, cytogenetic assays for scoring chromosome aberrations suffer from methodological limitations because most of them require a cell culture step, followed by cytological preparations of the cells, and finally scoring under microscopes. Therefore, the time required for performing such biodosimetric measurements and obtaining a result becomes longer than desirable (i.e., >50 h) [1,7–9]. The situation is even more challenging when a large number of samples need to be processed, e.g., in a large-scale nuclear incident. Further efforts are thus required to improve methods for scoring radiation-induced chromosome aberrations.

The introduction of peptide nucleic acid (PNA) probes to the scoring of radiation-induced DNA damage has opened new horizons for cytogenetic biodosimetry. Such probes have the advantage of short hybridization times, high specificity, and signal intensity, in addition to low cost [10]. By employing telomere and centromere-specific PNA probes (TC staining), we have obtained significant advances in the scoring of dicentric and ring chromosomes—the best biomarkers of radiation-induced DNA damage—on metaphases from mitosis-induced lymphocytes [10,11] and also on premature chromosome condensation (PCC) in nonstimulated lymphocytes [12,13]. Furthermore, the application of TC staining to the CBMN assay has vastly improved the identification of micronucleus formation, thus increasing the applicability of this assay [14]. Thus, not only have these improvements enhanced the precision of the cytogenetic assays but also obviated the need for personnel with high expertise [15,16].

More recently, as a result of the improvements in these techniques, their applicability has been explored in other fields of biology and their use by other biological non-DNA ionizing radiation assessors have been proposed. Thus, with the advance of cytogenetic techniques, they are not restricted to radiation biology and are not only applicable for the assessment of the effects of any genotoxic agent but also intrinsic defects in maintaining DNA integrity due to pathological gene variants. For instance, chromosomal instability is a prerequisite of ongoing cellular transformation and cancer development. These significantly improved cytogenetic techniques should constitute a valuable tool for the improved characterization of karyotypes in cancer patients, and hence, focused individual treatment and follow-up [17,18].

Here, we present an overview of the advantages of employing TC staining in current techniques used for cytogenetic biodosimetry, i.e., the shorter processing time, higher resolution, accuracy, and automatable recording, and we discuss the clinical utility of these approaches and their great potential in biological dosimetry.

## 2. Cytogenetic Markers of Irradiation

Cytogenetic biodosimetric assays are based on several biological endpoints essentially related to chromosomal aberrations that are consequences of DNA damage in peripheral blood lymphocytes (Figure 1). The markers of irradiation can be classified into three groups:
<figure><img src="image_52.png" /><figcaption>**Figure 1.** Schematic overview of the consequences of DNA repair mechanisms of varying efficiencies, induced after exposure to genotoxic agents. To the right are depicted examples of cytogenetic preparations using assays employed in cytogenetic biodosimetry. PCC: premature chromosome condensation; DCA: dicentric chromosome assay; TR: scoring of translocations; and MN: micronucleus assay.</figcaption></figure>

(1) Direct molecular consequences such as single and double-strand breaks in the DNA molecule detected by fluorochrome-labeled antibodies specific for, e.g., γH2AX, MR11 proteins, or p53-binding protein (53BP1) that are markers of double-strand breaks (DSB) [19,20]. The preparation and analysis of the immunostainings can be automated [4,21]. The proteins are useful markers of DSB (Table 1) in analyses of putative biological effects of low doses of irradiation [22] and for the triage of exposed populations [23,24]. In addition, immunostaining can be used to assess interindividual sensitivity to radiation [25]. However, the specificity of the abovementioned markers to irradiation, the lack of stability of the fluorescent signals over time, the standardization of the technique, and the interindividual variation constitute the main drawbacks for their use in biological dosimetry [26,27].

(2) The kinetics of DNA break repair is monitored in prematurely condensed chromosomes (PCCs) in the form of single-stranded filaments. PCCs can be observed by ordinary light microscopy or by fluorescence microscopy after staining with appropriate DNA dyes [28,29]; however, the techniques are subject to significant constraints and low stability of the acentric breaks over time, which limit their use in particular investigations.

(3) The consequences of DNA misrepair on the integrity of chromosomes at the time of the first postirradiation cell division or during the second interphase. Such failures resulting in more or less stable dicentrics, translocations, acentric fragments, or micronuclei can be visualized microscopically by the employment of relevant cytogenetic techniques of high sensitivity, specificity, and accuracy. Moreover, the techniques are automatable and easy to implement.

The long-term consequences of irradiation on DNA integrity have been investigated in populations exposed to irradiation following nuclear accidents or medical treatments, and also in their offspring [30–36] (Figure 1). Based on the collected data, multiple models of radiation-induced carcinogenesis and the transmission of chromosome aberrations to offspring have been proposed [37].
<table><caption>**Table 1.** Different categories of commonly used cytogenetic biological dosimeters/indicators explored for radiation dose reconstruction and possible accidental exposure situations. The question marks indicate that the validity of the test is not yet recognized.</caption><thead><tr><th rowspan="2">Techniques</th><th colspan="4">Types of Exposure to Ionizing Radiation</th><th rowspan="2">Sensitivity<br>Sensitivity</th></tr><tr><th>Recent and<br>Homogeneous<br>Events</th><th>Recent and<br>Heterogeneous<br>Events</th><th>Past Event</th><th>Large-Scale<br>Event</th></tr></thead><tbody><tr><td>Dicentric and<br>centric rings</td><td>YES</td><td>YES</td><td>NO</td><td>YES</td><td>0.1 Gy</td></tr><tr><td>Micronuclei</td><td>YES</td><td>YES</td><td>NO</td><td>YES</td><td>0.3 Gy</td></tr><tr><td>Translocations</td><td>YES</td><td>YES</td><td>YES</td><td>NO</td><td>0.25–0.3 Gy</td></tr><tr><td>PCC—CHO</td><td>YES</td><td>YES</td><td>NO</td><td>YES</td><td>0.1 Gy</td></tr><tr><td>PCC—ring</td><td>YES</td><td>?</td><td>NO</td><td>?</td><td>?</td></tr></tbody></table>

### 3. TC Staining Allows Insight into Mechanisms of Formation of Chromosome Aberrations

TC staining represents a major advance in not only the sensitivity of detection and classification of complex chromosome aberrations but also in elucidating mechanisms of their formation based on their structural alterations. The staining of telomeres, i.e., the ends of each chromosome, allows a very precise determination of the chromosomal landscape. Centromere staining makes it possible to define the nature of the chromosome aberrations and ultimately predict how sustainable they will be during subsequent cell divisions.

Thus, using TC staining, the accurate nomenclature of chromosomal aberrations can be established: (1) Dicentric chromosome: two centromere signals with four telomere signals; (2) centric ring chromosome: one centromere signal without any telomere signal; (3) acentric ring without telomere and centromere signal; (4) acentric chromosomes with four telomere signals or acentric fusion accompanied by dicentric or ring or translocation formation; (5) acentric chromosome with two telomere signals related to terminal deletion; and (6) acentric chromosome without telomere and centromere signals are related to interstitial deletion (Figure 2).

Moreover, TC staining makes it possible to distinguish between metaphases in the first and second mitotic cell division without any supplementary step related to the cross-hybridization of the centromere signal [11].

Furthermore, the scoring of TC-stained chromosome preparations is fully automatable [11,12,17]. Therefore, we believe that the implementation of TC staining will open new fields of research and diagnosis offering the vastly improved visualization of chromosomes and the identification and definition of their associated aberrations.
<figure><img src="image_53.png" /><figcaption>**Figure 2.** DNA damage and chromosomal aberrations after exposure to ionizing irradiation: (A) DNA damage after one, two, or four DSB. (B) Chromosomal aberrations in the first mitosis are visualized by uniform staining or TC staining. The latter permits the precise identification of chromosomal aberrations. Ace: acentric fragment; Rc: ring chromosome; Dic: dicentric chromosome; inv: inversion; TR: translocation; I: insertion; Gray: centromere; and red: telomere. (C) CBMN assay followed by TC staining for assessing DNA damage permits a distinction between aneugenic and clastogenic exposures. CBMN assay followed by TC staining allows the detection of the mechanisms of the formation of an anaphase bridge: a short anaphase bridge without TC staining related to the presence of a dicentric chromosome with centromere breakpoints and a long anaphase bridge with TC staining related to the presence of dicentric chromosomes with telomere fusions.</figcaption></figure>

**4. Employment of TC Staining Adds Distinctive Value to Commonly Used Cytogenetic Techniques**

Table 1 summarizes the sensitivity of commonly used cytogenetic biological dosimetry techniques and the possible detection of recent or past irradiation as well as the homogeneous and heterogenous exposure (Table 1).

**4.1. The "Gold Standard" Technique**

Among the various assays employed in cytogenetic biodosimetry, the dicentric chromosome assay (DCA) is considered the “gold standard” in radiation emergency medicine.

It is medically and legally recognized [1,7–9] and is approved by the International Atomic Energy Agency (IAEA) because of its proven utility in past large-scale nuclear incidents and accidents [30,38].
A dicentric chromosome is an abnormal chromosome with two centromeres. It is formed through two double-strand breaks (DSB) and followed by the fusion of two chromosome fragments, each with a centromere, resulting in the formation of a dicentric chromosome together with acentric fragments (Figure 2B) [8].

Dicentric chromosomes, together with centric rings, the latter formed by the fusion of sticky chromosome ends (Figure 2B), occur in peripheral lymphocytes of individuals as a consequence of recent exposure to an external source of ionizing radiation. Their frequency is dose-dependent. However, they are unstable aberrations, and hence their frequencies decrease during subsequent cell divisions. The acentric fragments can also provide an aid in dose estimation, e.g., to substantiate the presence of other aberrations or, especially in cases of partial body exposure, to verify information about the incident.

Dicentrics and centric rings are relatively simple to score and enumerate. Moreover, their frequency is dose-dependent. For those reasons their enumeration in peripheral blood lymphocytes, termed the "dicentric chromosome assay" (DCA), constitutes the basis of the "Gold Standard" technique for estimating biological dosimetry.

The abovementioned chromosomal aberrations can be observed after uniform staining (Giemsa or DAPI) of metaphases of lymphocytes from a blood sample after their cultivation for 48 h in the presence of phytohemagglutinin (PHA), a stimulator of mitosis, followed by a 2-4 h colcemid-induced block of metaphase (Figure 3A).

<figure><img src="image_54.png" /></figure>

**Figure 3.** The identification of unstable chromosomal aberrations after the in vitro irradiation of blood lymphocytes (63× magnification) using (A) uniform chromosome staining (Giemsa staining) permits the detection of unstable chromosomal aberrations according to their morphologies; (B) telomere (red) and centromere (green) staining allow the accurate detection of all unstable chromosome aberrations: (i) dicentric chromosome with two green signals and four red signals (top insert), (ii) ring chromosomes with one green signal, but no red signals (2nd insert from the top), and (iii) acentric fragments with four red signals only (bottom insert).

Several studies have shown that frequencies of chromosome aberrations are similar in in vitro and in vivo irradiated blood lymphocytes, respectively. Hence, a calibration curve of the dose-effect relationship obtained after the in vitro irradiation of blood is used to estimate the dose of exposure from an irradiation event in vivo [39,40].

The operating conditions are described in numerous publications such as the IAEA technical guides [1,7–9]. Key points of the technique to validate its quality and reproducibility are defined in several ISO standards [41–43].

By incorporating TC staining into the "gold standard" technique, the identification of normal chromosomes as well as their aberrations has been vastly improved. The visualization of telomere sequences permits the identification of chromosome ends, and visualization of the centromere sequences, the nature of a chromosome, i.e., (i) dicentric: chromosome with two centromere signals (Figure 2B); (ii) centric ring: circular chromosome without telomere signal and with only centromere signal (Figure 2B); (iii) acentric: chromosome
without centromere signal and with or without telomere signal (Figures 2 and 3) [10,11]. Thus, TC staining allows the accurate and reliable detection of all unstable chromosomal aberrations in a single analysis. Importantly, the analysis can be made operator independent [11,44]. Last, but not least, software has been developed that allows the satisfactory automation of chromosomal aberrations scoring [11,12,45–49]. Thus, the technique has significantly reduced the labor-intensive and time-consuming burden of enumerating chromosome aberrations in the classical “gold standard” assay. Moreover, this improved technique should also be applied to studies on the effects of any external genotoxic agent and intrinsic cellular factors affecting chromosome stability.

## 4.2. *Detection of Translocations*

Chromosomal anomalies that are the result of exchanges of genetic material between non-homologous chromosomes are termed translocations (Figure 2B) [50–56]. The frequency of radiation-induced translocations in a cell population depends on the dose of irradiation [57]. Some of the translocations may persist for decades because they remain compatible with cell division, as documented in biodosimetric studies on A-bomb survivors performed decades after exposure, and on patients observed for decades after their treatment with radiotherapy for ankylosing spondylitis [58]. Thus, in contrast to dicentrics, rings, and fragments that are lost progressively in subsequent mitotic divisions, a translocation is a better biomarker for retrospective dose evaluation when there has been a long delay between exposure and blood sampling.

In the past, the identification and analysis of translocations based on banding techniques required highly skilled staff to assess karyotypes. However, the introduction of the FISH technique has revolutionized this analysis by using one or several different chromosome-specific colors to “paint” each pair of chromosomes. Each chromosome-specific DNA probe is labeled with fluorescent molecules allowing each chromosome pair or group to be visualized individually or collectively. Any exchange of non-homologous chromosomal material can therefore be easily identified. The fastest method at present is to ‘paint’ three pairs of chromosomes, each pair being the same or different in color from another pair [54,55]. However, some imprecision in the detection of the nature of aberrations cannot be completely avoided, such as an incomplete translocation or terminal translocation, and the distinction between translocation and a specific configuration of a dicentric chromosome with both centromeres in close proximity [17,18]. However, by combining telomere and centromere staining with chromosome painting, the scoring of chromosomal aberrations becomes considerably simpler and more reliable. A further advantage of combining these techniques is that the nature of more complex aberrations can be established with high accuracy, as demonstrated in Figure 4.

## 4.3. *The Cytokinesis-Blocked Micronucleus Assay (CBMN)*

The scoring of micronuclei has been proposed as an alternative to the conventional quantification of chromosomal aberrations because the assay is faster and also easier. Micronuclei are biomarkers not only of DNA damage but also of genomic instability [59]. However, the high baseline frequency of micronuclei in healthy populations has limited the sensitivity and application of the CBMN assay for the follow-up of exposed populations [60].

Micronuclei containing acentric chromosome fragments or chromatid fragments arise due to non- or misrepaired DNA double-strand breaks as a result of exposure to clastogenic agents, e.g., ionizing radiation [61,62]. Micronuclei can also contain whole chromosomes that lag behind and do not attach to the mitotic spindle during the segregation process in anaphase. Such micronuclei arise as a result of exposure to aneugenic agents (e.g., intra-cellular oxidants and polycyclic aromatic hydrocarbons) [62], and they represent the main fraction (>70%) of spontaneously occurring micronuclei [14,63]. Irrespective of the cause of their origin, these chromosomes or chromosome fragments are subsequently enveloped by a nuclear membrane and appear in the cytoplasm as small nuclei, i.e., micronuclei,
separated from the main nucleus (Figure 2C). The assay is based on peripheral lymphocytes stimulated to undergo mitosis by in vitro stimulation with phytohemagglutinin (PHA). Micronuclei can subsequently be observed in interphase cells.

Ionizing radiation is a strong clastogenic agent and thus a potent inducer of micronuclei, most of which lack centromeres. The CBMN assay has now been established as a reliable technique in radiobiology for the assessment of the radiation exposure of medical, occupational, or accidentally exposed individuals.

The enhanced resolution of the CBMN assay has been obtained by including TC staining or only centromere staining [14,63–65]. The achievements using that approach are significant: (1) The visualization of both the telomere and the centromere sequences enhances the sensitivity and detection of MN. (2) The determination of the nature of the genotoxic exposure: clastogenic effect (i.e., MN–T with only telomere sequences) and aneugenic (i.e., MN–TC with telomere and centromere staining) (cf. Figures 2C and 5). In addition, the introduction of TC staining into the CBMN assay may advance our insight into molecular mechanisms giving rise to dicentric chromosomes due to the improved scoring of long anaphase bridges with TC sequences and short anaphase bridges without any staining (Figure 2C).

<figure><img src="image_55.png" /><figcaption>**Figure 4.** The detection of stable chromosomal aberrations after the in vitro irradiation of blood lymphocytes (63× magnification) using (A) chromosome 1 (red), 4 (yellow), and 11 (green) painting and the identification of a complex rearrangement involving chromosome 1 with a reciprocal translocation and of two other undefined aberrations. (B) By combining telomere and centromere staining with chromosome painting, the two other aberrations can be defined: telomere deletion (1st insert from the top) was detected in chromosome 1 implicated in this reciprocal translocation (2nd insert from the top); the precise detection of an acentric fragment accompanied the formation of this reciprocal aberration (3rd insert from the top); detection of an acentric ring lacking telomere and centromere staining (bottom insert).</figcaption></figure>

### 4.4. Premature Chromosome Condensation (PCC) Assay

Occasionally, it is difficult to obtain sufficient numbers of metaphases in lymphocytes grown in a culture with PHA. An alternative useful method to the gold standard technique is the premature chromosome condensation (PCC) assay that facilitates the visualization of interphase chromatin as a condensed form of chromosomes. Usually, chromosomes condense during mitosis, following a strict order that is under strict cellular controls. However, it is possible to artificially uncouple chromosome condensation from the mitotic sequence, which makes it possible to visualize chromosomes in, e.g., resting PBL. Two different approaches are usually employed to induce PCC: (1) The PCC fusion approach (PCC-CHO), and (2) the chemical induction approach. In the fusion approach, Chinese hamster ovary (CHO) cells in the M-phase of their cell cycle are fused with the target interphase cells using a fusogen-like polyethylene glycol or inactivated Sendai virus. Prior to fusion, mitotic CHO cells have been synchronized and stocks are frozen and stored until used [28,66].
<figure><img src="image_56.png" /><figcaption>**Figure 5.** A combination of telomere (red) and centromere (green) staining in the CBMN assay allows the easy identification of the nature of a genotoxic exposure. (A) The detection of micronuclei after uniform DNA staining. The staining does not allow the identification of their chromosomal contents. (B) Micronuclei with only telomere staining (yellow arrow) as a consequence of exposure to the clastogenic agent, and micronuclei with telomere and centromere staining (green arrow) due to exposure to the aneugenic agent (63× magnification).</figcaption></figure>

Alternatively, PCC can be induced chemically in PBL at any stage of the cell cycle by treatment with okadaic acid or calyculin, which are specific inhibitors of serine/threonine protein phosphatase [13,67,68]. The technique is very easy to practice, simply by substituting colcemid with either of the two chemicals. Incubation times of only 30 min, sometimes only 5–10 min (in contrast to the 2–4 h colcemid block) induce a sufficient number of chromosomes. The PCC index is usually much higher (>10%) than the mitotic index (1–2% at best), which makes chromosome analysis much easier. In addition, the drug-induced PCC has outstanding merit that allows the metaphase chromatin, i.e., G₁-, S-, and G₂-phase chromatin to be visualized as condensed forms of chromosome structure.

The induction of PCC allows the observation of chromosomes with a light microscope not only during mitosis but also in interphase and hence the analysis of (i) chromosome breakage and repair after exposure to ionizing radiation or chemical mutagens; (ii) DNA duplication; (iii) conformational changes during the cell cycle. Thus, PCCs constitute a useful alternative in cases where metaphase analysis may fail [69], e.g., (1) Estimation of a heterogeneous dose when the collected cells are a mixture of unirradiated and highly irradiated cells, delayed by repair mechanisms resulting in a delayed entry into the cell cycle; (2) accidental exposure to high levels of ionizing radiation, which produces a mitotic delay of unknown duration accompanied by significant apoptotic death; or (3) a very low chronic mitotic index, as in some pathological situations or elderly people.

By combining TC staining with the PCC technique for the analysis of DNA damage, the advantages include: (1) The possibility, for the first time, to visualize and score dicentric chromosomes; (2) determining the nature of acentric breaks; and (3) higher precision to monitor the kinetics of formation of chromosomal aberrations (Figure 6). The combination of these two techniques opens new horizons for the PCC technique, not only for the rapid scoring of DNA damage but also in the application of biological dosimetry into radiation emergency medicine and the automation of the analysis [12,68,70].
<figure><img src="image_57.png" /><figcaption>**Figure 6.** The combination of TC staining with the PCC fusion technique allows the reliable scoring of chromosome fragments and the detection of dicentric chromosomes. (A) Conventional DNA staining of PCC permits the scoring of chromosome condensation fragments (63× magnification). (B) Simultaneous telomere (red signals) and centromere (green signals) staining permits the detection of dicentric chromosomes (top inserts) and the accurate and consistent detection of acentric chromosomes (bottom inserts). The large red areas represent telomere signals of CHO chromosomes.</figcaption></figure>

**5. Automation of Biological Dosimetry Methods**

Following considerable development of novel reagents and the standardization of cytogenetic preparations, the quality of cytogenetic slides has increased progressively to levels that make it feasible to automate the search for metaphases and capture slides. The first attempts to automate the scoring of radiation-induced DNA damage began in the 1990s with the automation of the scoring of micronuclei after uniform DNA staining (Giemsa or DAPI) [71]. The first commercially available system was Metafer MNScore from MetaSystems [72].

Spectacular advances have been achieved in recent years in terms of sensitivity and interface after uniform staining using cytogenetic slides or flow cytometers (DAPI) [21,73–75]. However, this automation concerns only the scoring of micronuclei and does not make it possible to differentiate the origin of micronuclei because centromere staining has not yet been implemented. The automation of other DNA damage markers such as anaphase bridges or nuclear buds (NBUDs) is still not relevant despite their crucial importance in biological dosimetry or chromosomal instability fields [76].

The second attempt of automation concerns the scoring of dicentric chromosomes after uniform staining. Reliability had long been hampered by the difficulty of recognizing metaphases by the use of many processors with little software. The first commercially available system was Metafer DCScore from MetaSystems [77–79]. A spectacular improvement was achieved in terms of sensitivity, which is essentially due to the introduction of TC staining [11,80,81] and the marketing of more advanced software.

The automation of PCC-CHO following uniform staining [66] and subsequent TC staining [12] has now been initiated; however, the implementation of this technique and its current use requires further technical development.

The automation of the scoring of translocation has not been undertaken so far. However, ongoing work using machine learning approaches after TC staining followed by M-FISH should make it possible to achieve high efficiency in the automation process.

**6. Application of Cytogenetic Tools in a Wider Spectrum of Fields in Medicine and Biology**

Cytogenetic biodosimetry is not limited to ionizing radiation and the follow-up of exposed populations. It is, in fact, applicable in the assessment of the effect of any genotoxic agent as well as that of inherent spontaneous genome instability in, e.g., cancer patients. The need to improve cytogenetic biodosimetry assays has been driven by the need to
transfer technology to all cytogenetic laboratories to achieve high sample throughput for the processing of large cohorts of exposed populations as well as in medical settings [17,18,82].

The multiplex (M-FISH) technique is the latest evolution of FISH, which stains sex chromosomes and each pair of autosomes with different colors (1986). However, M-FISH has not been used intensively due to the complexity of the analysis. Recently, some studies started to use this technique [83–88]; however, the resolution of chromosomes to identify complex rearrangements can be vastly improved when TC staining with M-FISH [17,18,89].

TC staining followed by multiplex FISH (M-FISH), termed (TC+M-FISH), allows the reliable analysis of both unstable and stable chromosomal aberrations in a single-step analysis (Figure 7). In addition, this approach makes it possible to obtain an accurate karyotype in cases of genome heterogeneity and clonal escape.

<figure><img src="image_58.png" /><figcaption>**Figure 7.** Telomere and centromere staining followed by M-FISH offers the sensitive and accurate detection of all chromosome aberrations, both stable and unstable ones. This approach permits the reliable identification of breakpoints and the assessment of the presence of complex clonal aberrations (63× magnification).</figcaption></figure>

The employment of the TC+M-FISH approach in the analysis of the transmission of unstable chromosomal aberrations through multiple cell divisions has permitted not only the reevaluation of the transmission of dicentric chromosomes but also, for the first time, the documentation of the transmission of an acentric chromosome and the involvement of centromere breakpoints in this transmission [44]. Moreover, we have been able to demonstrate the persistence of specific configurations of dicentric chromosomes with both centromeres in close proximity during cell division [44]. Such dicentric chromosome configurations can easily be mistaken for translocation when only using the M-FISH technique because centromeric regions are not visible in the M-FISH assay.

Recently, we demonstrated the clinical utility of the TC+M-FISH technique for the detection of chromosomal aberrations in cancer patients in general, and of dicentric chromosomes in particular [17]. Today, the latter is considered the best cytological biomarker of chromosomal instability in cancer patients [90].

The TC+M-FISH approach permits the establishment of reliable and accurate karyotypes for cancer diagnosis [17,18]. Thus, the application of TC+M-FISH has revealed a much higher frequency of dicentric chromosomes with a specific configuration (two centromeres in close proximity) than has been observed previously by using conventional and molecular cytogenetics.

Moreover, the TC+M-FISH technique makes it possible to detect both stable and unstable aberrations, allowing accurate identification with high sensitivity of all chromosomal aberrations in addition to the putative progress of clonal escape and chromosomal
instability. This approach will improve our knowledge not only of the biological effects of chemotherapy or low doses of irradiation but also of the underlying mechanisms of the formation of chromosomal aberrations. It could also be applied, with advantage, in the follow-up of exposed populations with a high risk of developing secondary cancer or late complications after exposure to genotoxic agents.

## 7. Advantages and Limitations of Current Cytogenetic Biomarkers of Ionizing Radiation

Most of the cytogenetic markers that have been used routinely for the past 50 years are primarily indicators of structural or functional damage to cellular components. However, despite their well-documented advantages, several challenges remain to be addressed and solved.

### 7.1. Specificity of Cytogenetic Biodosimetry Markers

It should be borne in mind that none of the chromosomal biomarkers described above are specific for monitoring exposure to ionizing radiation. In fact, they may also reflect the combinatory influence of other stressors such as the prior health status of the individual and genotoxic contamination by pollutants or chemicals that may create severe and long-lasting pathophysiological damage. Consequently, these markers constitute valuable indicators of the stress status of an individual (e.g., DNA repair, chromosome instability, and carcinogenesis). At low and medium doses of ionizing radiation, they may also reflect the subtle association between different additive effects of ionizing radiation such as radiation sensitivity, adaptation, and bystander effect, the consequences of which are not fully understood.

### 7.2. Challenges in Dose Estimation

1. The spontaneous rate of chromosomal aberrations in the general population is an important factor in cytogenetic biodosimetry because it can influence the interpretation of data. Thus, DNA damage can also be induced by occupational activities, lifestyle, and environmental factors [91]. Furthermore, there are variations in natural, terrestrial, and cosmic radioactivity, which differ from region to region and from country to country [92]. Finally, the worldwide increase in exposure to magnetic fields such as the use of mobile phones and the multiplicity of the employment of ionizing radiation in industry and medicine may have contributed to significant variations [93]. The latest evaluation of the frequencies of spontaneous chromosome aberrations dates back several decades. Since then, a vast amount of insight has accumulated into the causes and frequencies of chromosome aberrations. Moreover, significant technical improvements in their detection have been achieved. Therefore, the re-examination of the frequency of spontaneous chromosomal aberrations in the general population is urgently needed. For that purpose, an automated TC+M-FISH approach would be most relevant.

2. The distribution of aberrations according to age and sex is not clear and differs from one study to another. Recently, several studies have demonstrated the difference in genotoxic stress response according to sex [94–96]. Notably, the used dose-response curves did not take into account the age or sex of the exposed population.

3. The interpretation of complex chromosomal rearrangements in the estimation of the absorbed dose has always been challenging in biological dosimetry. A significant correlation has been found between the formation of complex chromosomal rearrangements and the clinical outcome of patients treated with radiotherapy [97,98]. The presence of these kinds of aberrations has also been correlated with interindividual radiation sensitivity and genomic instability [99]. The lack of analysis of complex chromosomal rearrangement in a large cohort of an exposed population using a sensitive technique did not make it possible to advance our knowledge regarding their formations and their interpretations.
4. The interpretation of “Rogue cells” in the analysis of chromosomal aberrations and the estimation of the dose after exposure is still unclear. “Rogue cells” are cells with multiple and complex chromosomal aberrations (e.g., dicentric, tricentric, translocations, insertions, deletions, and acentric chromosomes) related to the activation of viral infection [100,101]. A significant increase in induced chromosomal aberrations has been detected in the presence of rogue cells [102–105]. Further studies are needed to investigate the role of viral infection in the formation of radiation-induced chromosomal aberrations.

### 7.3. Relevant Questions for Cytogenetic Biological Dosimetry Assays

Although research over the last 50 years on cytogenetic biomarkers in biodosimetry has sufficiently covered their operational capacities, there still persist some gray areas that need to be addressed and resolved to improve the assessment of potential genotoxic exposures [52,106]:

- How can we validly relate lymphocyte lifetime and (re)circulation to partial exposure and thus introduce useful correction factors in the estimation of an absorbed dose of ionizing radiation?

- What value can be attributed to translocation analysis in the concept of dose, especially decades or years after a potential exposure?

- How do we coordinate all of the biological and biophysical markers available to the dosimetrist into a coherent entity, integrating the concept of multiparameter analyses?

- How do we integrate new developments (genomics, proteomics, and transcriptomics) that, without renovating the current biotechnological landscape, make it possible to associate physiopathology more globally with genomic instability?

- How do we integrate modulation phenomena, such as cellular and tissue radiosensitivity, radiation adaptation, and abscopal or bystander effects, that are still incompletely understood?

### 7.4. Internal Exposure

The internal exposure to ionizing radiation, particularly that due to contamination, is classically considered in three specific contexts: (i) environmental, to which all people are naturally subject; (ii) occupational, concerning certain categories of workers, and finally, (iii) iatrogenic, the consequences of which evolve with the level of health care [107]. Biological indicators could be very useful to characterize the occurrence and type of effects observed, as well as the intracellular and intercellular processes activated in response to internal exposure. The first interest is the clinical and epidemiological study of cancers developed by humans after exposure to a radio-contaminant; the second interest is related to clinical treatment and the histological characterization of treated cancers after induction of vectorized radioimmunotherapy.

## 8. New Challenges for the Use of Biological Dosimetry in Detecting Carcinogenesis Susceptibility

The accurate detection of DNA damage is not restricted to cytogenetic biodosimetry after accidental, professional, or medical exposure to ionizing radiation [108]. Personalized medicine also needs this approach for the development of new biomarkers of DNA repair deficiency in order to propose a specific treatment for individual patients. The clinical utility of these techniques—particularly the need for sensitive and specific biomarkers—is justified by the stratification of patients regarding the deleterious consequence of chromosomal instability [108,109]. The introduction of TC staining in the cytogenetic biological dosimetry approach and the automation of the scoring of all chromosomal aberrations must lead to the creation of databases allowing sensitive and specific stratification of exposed populations and/or patients.

The second challenge is related to the impact of low-dose effects on chromosome instability. Improved detection of DNA damage by introducing TC staining makes it
possible to reveal genetic consequences for doses below 0.1 Gy. Their application, including telomere analysis to the field of low-dose exposures, could add significant advantages to our understanding of such effects.

The third challenge is paradoxically to have the best-standardized response for various types of irradiation, dose rate, and genetic parameters in any laboratory practicing biological dosimetry assessment. This apparently simple feature, although required for better efficiency, is not always obtainable—and the reasons for that are not always obvious. The introduction of TC staining in the automatic scoring of DNA damage has rendered the analysis independent of the level of expertise of the operator. In addition, high reproducibility of the scoring has been achieved. The systematic use of this technique instead of the classical scoring of chromosome aberrations could greatly improve the respective standardizations.

Finally, the possible fusion between the “gold standard” technique (dicentric chromosome), FISH or M-FISH technique (translocation), and CBMN assay (micronuclei) will represent an important technical challenge that will surely lead to wider applications for sensitive and reliable dose estimation [110,111].

While biodosimetry using traditional cytogenetic assays is useful for dose assessments following accidental exposure to ionizing radiation, the field of biodosimetry has advanced significantly with expansion into the fields of genomics, proteomics, metabolomics, and transcriptomics [112–115]. However, advances in the assessment of radiation exposure using those approaches have more relevance to clinical applications for patients undergoing radiation therapy. The information derived from radiation responses may advance personalized care and could help alleviate the damage to normal tissue [116].

## 9. Conclusions

For more than 50 years cytogenetic biodosimetry has been routinely and successfully practiced worldwide by a few specialized laboratories for assessing individual exposure to ionizing radiation, and international networks have been established in preparation for a potential nuclear catastrophe. However, all of the classical techniques applied for these purposes suffer from several limitations: they are unnecessarily time-consuming, their sensitivity and specificity are untimely limited, and they require highly skilled personnel that may be in shortage in the event of a major nuclear catastrophe. By including TC staining together with M-FISH, several of these obstacles may be overcome. Moreover, importantly, the automation of these novel techniques adds to the major achievements provided by the inclusion of TC staining in the current cytogenetic assays. We also propose their use in the general assessment of DNA damage and chromosome instability which are largely underestimated in many diseases. Last but not the least, wider potentials exploiting these techniques are emerging for their application in identifying prognostic biomarkers and guides for the better triage and management of medical patients. The standardization of cytogenetic biological dosimetry approaches permits the use of a unique dose-response curve. The automation of these approaches opens new horizons in the construction of large databases in exposed populations, allowing the precise estimation of risk associated with radiation exposure. This is the role of official instances such as the AIEA and OMS as well as an international research program for the harmonization and standardization of the process such as the RENEB program. We also need companies to manufacture the kits and for standardization and development of analysis software with the overall aim of automating all of the processes.

**Author Contributions:** Conceptualization, R.M. and P.V.; investigation, B.C. and E.E.M.; resources, A.D., A.P., L.H. and E.J.; writing—original draft preparation, R.M., P.V. and S.J.; writing—review and editing, R.M., S.J. and P.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.
**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

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Article

# Transcriptome-Based Traits of Radioresistant Sublines of Non-Small Cell Lung Cancer Cells

Margarita Pustovalova¹, Philipp Malakhov¹, Anastasia Guryanova¹, Maxim Sorokin¹,² ID, Maria Suntsova², Anton Buzdin¹,²,³, Andreyan N. Osipov¹,⁴,⁵,* ID and Sergey Leonov¹,⁶ ID

¹ School of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Russia

² World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, 119435 Moscow, Russia

³ Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia

⁴ State Research Center-Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency (SRC-FMBC), 123098 Moscow, Russia

⁵ N.N. Semenov Research Center of Chemical Physics, Russian Academy of Sciences, 117977 Moscow, Russia

⁶ Institute of Cell Biophysics, Russian Academy of Sciences, 142290 Pushchino, Russia

* Correspondence: aosipov@fmbcfmba.ru

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**Citation:** Pustovalova, M.; Malakhov, P.; Guryanova, A.; Sorokin, M.; Suntsova, M.; Buzdin, A.; Osipov, A.N.; Leonov, S. Transcriptome-Based Traits of Radioresistant Sublines of Non-Small Cell Lung Cancer Cells.
*Int. J. Mol. Sci.* **2023**, *24*, 3042.
https://doi.org/10.3390/ijms24033042

Academic Editors: Anthony Lemarié
and François Chevalier

Received: 28 November 2022

Revised: 30 January 2023

Accepted: 31 January 2023

Published: 3 February 2023

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**Copyright:** © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).

**Abstract:** Radioresistance is a major obstacle for the successful therapy of many cancers, including non-small cell lung cancer (NSCLC). To elucidate the mechanism of radioresistance of NSCLC cells and to identify key molecules conferring radioresistance, the radioresistant subclones of p53 wild-type A549 and p53-deficient H1299 cell cultures were established. The transcriptional changes between parental and radioresistant NSCLC cells were investigated by RNA-seq. In total, expression levels of 36,596 genes were measured. Changes in the activation of intracellular molecular pathways of cells surviving irradiation relative to parental cells were quantified using the Oncobox bioinformatics platform. Following 30 rounds of 2 Gy irradiation, a total of 322 genes were differentially expressed between p53 wild-type radioresistant A549IR and parental A549 cells. For the p53-deficient (H1299) NSCLC cells, the parental and irradiated populations differed in the expression of 1628 genes and 1616 pathways. The expression of genes associated with radioresistance reflects the complex biological processes involved in clinical cancer cell eradication and might serve as a potential biomarker and therapeutic target for NSCLC treatment.

**Keywords:** non-small cell lung cancer; DNA repair; radioresistance; ionizing radiation; transcriptionics; gene expression

## 1. Introduction

Lung cancer is the leading cause of cancer-related deaths worldwide [1], with non-small cell lung cancer (NSCLC) accounting for ~85% of all cases [2]. Radiotherapy is a critical choice in the curative management of patients with inoperable NSCLC; however, the prognosis remains poor due to radioresistance of cancer cells present in heterogeneous tumor populations [3]. Radioresistance is linked to both intrinsic (cancer stem cells, mutational status, epithelial–mesenchymal transition (EMT) process) and extrinsic (hypoxia, tumor microenvironment) mechanisms [4] in which cancer cells accumulate genetic changes allowing them to survive harsh treatment conditions and repopulate. In this case, understanding the changes in gene expression profiles and signal molecular pathways of radioresistant cells is important for the selection of new treatment options and therapeutic schemes for NSCLC patients.

With the development of Next-Generation Sequencing, RNA expression profiles can improve our understanding of the molecular mechanisms responsible for cancer radioresistance. In addition, combining expression data of single gene products with a molecular
pathway activation level (PAL) can lead to the development of more robust biomarkers, as shown in both experiment [5,6] and theory [7]. Thus, RNA-seq profiles can be used as potent predictors of tumor radioresistance and might serve as potential biomarkers for therapeutic targets.

We previously generated radioresistant sublines of NSCLC from p53 wild-type A549 and p53-deficient H1299 cells [8,9]. We used Illumina NextSeq 550 to sequence the transcriptomes of parental (A549 and H1299) cells and their radioresistant sublines (A549IR and H1299IR) to expand and improve the data.

Here, we present the changes in gene expression profiles and molecular pathway activation levels of radioresistant NSCLC sublines in relation to their p53 status.

## 2. Results

### 2.1. Establishment of the Radioresistant NSCLC Cells

We obtained radioresistant NSCLC sublines using fractionated X-ray irradiation at a total dose of 60 Gy; their survival curves have been previously published [10]. We performed both conventional clonogenic test and the soft agar colony formation assay for assessing cellular radiosensitivity (Figure 1). Both A549IR (wild-type p53) and H1299IR (p53-deficient) cells showed reduced radiosensitivity compared to parental cells growing on a solid surface (Figure 1a). To elucidate further the ability of cells to grow independently of a solid surface, we performed the soft agar colony formation assay (Figure 1b). While A549IR cells showed a statistically significant reduction in radiosensitivity only after exposure to 2 Gy, H1299IR cells showed an overall reduction in radiosensitivity compared to parental H1299 cells (Figure 1b), suggesting their ability to escape from anoikis. Thus, our results demonstrate the overall p53-independent decrease in radiosensitivity of NSCLC cells surviving multifractionated X-ray irradiation.

<figure><img src="image_62.png" /><figcaption>**Figure 1.** Radiosensitivity of parental and radioresistant NSCLC cells growing in (a) anchorage-dependent (solid surface) and in (b) anchorage-independent (soft agar) conditions. \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001. Data are means ± SEM for more than three independent experiments (published previously [10]).</figcaption></figure>

### 2.2. Differential Gene Expression of NSCLC Cells

To evaluate gene expression changes of radioresistant sublines compared to parental ones, we performed RNA sequencing using the Illumina Nextseq 550 System. The results demonstrated differential expression of 322 genes (log10(control) > 1, |log2FC| > 1) in p53 wild-type radioresistant compared to parental A549 cells. Among them, 164 genes were up-regulated, while 158 genes were down-regulated (Supplementary Table S1). In p53-deficient NSCLC cells, 1628 genes were expressed differentially (log10(control) > 1, |log2FC| > 1) in radioresistant vs. parental cells: 808 genes were up-regulated, while 820 genes were down-regulated (Supplementary Table S1). Radioresistant sublines demonstrated seven common up-regulated genes (*ATRNL1*, *CA2*, *CNR1*, *FAM189A1*, *GFRA1*, *RASGRP1*, *RGL3*); however, no statistically significant enrichment was found (Figure 2a). The nine down-
regulated genes that were common between A549IR and H1299IR cells included *ADGRF1*, *EPHA7*, *LOX*, *LY6G5C*, *NSUN7*, *SLC22A31*, *SNAI2*, *TNFRSF11B* and *ZNF233* (*p* = 0.0105) (Figure 2b).

<figure><img src="image_63.png" /><figcaption>**Figure 2.** Differential gene intersection showing: (a) up-regulated genes in A549IR cells ∩ H1299IR cells; (b) down-regulated genes in A549IR cells ∩ H1299IR cells. Red asterisk indicate statistical significance * *p* < 0.05.</figcaption></figure>

Within the obtained gene sets, Gene Ontology (GO)-based functional analysis provides statistically enriched GO terms that show gene relationships according to three ontology categories and described gene products. These categories are biological process, molecular function and cellular component [11]. We then identified significantly enriched GO terms and characterized radioresistant vs. parental A549 and H1299 cells. In total, enriched GO terms were found in 80 subcategories under biological process, three subcategories under cellular component, and seven subcategories under molecular function. In biological process ontology, the results indicated that desmosome organization, regulation of vitamin D biosynthesis and metabolic process, negative regulation of DNA damage response and signal transduction by p53 class mediator, negative regulation of anoikis, apoptosis, regulation of cell adhesion mediated by integrin and regulation of cell morphogenesis were mainly associated with radioresistant A549IR and H1299IR cells. Significant GO enrichment profiles in the biological process (BP) (only the first 30 out of 80 BPs *p*-value less than 0.01) are summarized in Table 1. Enriched GO molecular function terms in radioresistant A549IR and H1299IR cells were oxidoreductase activity, transmembrane-ephrin receptor activity, chemorepellent activity and E-box binding. Through GO analysis, we found that overrepresented GO terms in our radioresponsive gene sets were closely linked to such cellular components as hippocampal mossy fiber to CA3 synapse, integral and intrinsic components of postsynaptic density membrane.

<table><caption>**Table 1.** Differential genes intersection for biological process ontology for common down-regulated genes in A549IR cells ∩ H1299IR cells.</caption><thead><tr><th>ID</th><th>Description</th><th><i>p</i>-Value Adjusted</th><th>Genes</th></tr></thead><tbody><tr><td>GO:0002934</td><td>desmosome organization</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0030656</td><td>regulation of vitamin metabolic process</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0042368</td><td>vitamin D biosynthetic process</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0048251</td><td>elastic fiber assembly</td><td>0.019522</td><td>LOX</td></tr><tr><td>GO:0048755</td><td>branching morphogenesis of a nerve</td><td>0.019522</td><td>EPHA7</td></tr><tr><td>GO:0070561</td><td>vitamin D receptor signaling pathway</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0072178</td><td>nephric duct morphogenesis</td><td>0.019522</td><td>EPHA7</td></tr><tr><td>GO:1905809</td><td>negative regulation of synapse organization</td><td>0.019522</td><td>EPHA7</td></tr></tbody></table>
<table><caption>**Table 1.** *Cont.*</caption><thead><tr><th>ID</th><th>Description</th><th>p-Value Adjusted</th><th>Genes</th></tr></thead><tbody><tr><td>GO:0061314</td><td>Notch signaling involved in heart development</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0033629</td><td>negative regulation of cell adhesion mediated by integrin</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0042362</td><td>fat-soluble vitamin biosynthetic process</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0072176</td><td>nephric duct development</td><td>0.019522</td><td>EPHA7</td></tr><tr><td>GO:0018158</td><td>protein oxidation</td><td>0.019522</td><td>LOX</td></tr><tr><td>GO:0035791</td><td>platelet-derived growth factor receptor-beta signaling pathway</td><td>0.019522</td><td>LOX</td></tr><tr><td>GO:0010839</td><td>negative regulation of keratinocyte proliferation</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0042481</td><td>regulation of odontogenesis</td><td>0.019522</td><td>TNFRSF11B</td></tr><tr><td>GO:0043518</td><td>negative regulation of DNA damage response, signal transduction by p53 class mediator</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0003198</td><td>epithelial to mesenchymal transition involved in endocardial cushion formation</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0045779</td><td>negative regulation of bone resorption</td><td>0.019522</td><td>TNFRSF11B</td></tr><tr><td>GO:0048670</td><td>regulation of collateral sprouting</td><td>0.019522</td><td>EPHA7</td></tr><tr><td>GO:2000811</td><td>negative regulation of anoikis</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0032026</td><td>response to magnesium ion</td><td>0.019522</td><td>TNFRSF11B</td></tr><tr><td>GO:0046851</td><td>negative regulation of bone remodeling cell migration involved in heart development</td><td>0.019522</td><td>TNFRSF11B</td></tr><tr><td>GO:0060973</td><td>vitamin biosynthetic process</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0009110</td><td>retinal ganglion cell axon guidance</td><td>0.019522</td><td>EPHA7</td></tr><tr><td>GO:0031290</td><td>positive regulation of CREB transcription factor activity</td><td>0.019522</td><td>ADGRF1</td></tr><tr><td>GO:0032793</td><td>negative regulation of tissue remodeling</td><td>0.019522</td><td>TNFRSF11B</td></tr><tr><td>GO:0034104</td><td>muscle cell cellular homeostasis</td><td>0.019522</td><td>LOX</td></tr><tr><td>GO:0046716</td><td>cell junction disassembly</td><td>0.019522</td><td>SNAI2</td></tr><tr><td>GO:0150146</td><td></td><td></td><td></td></tr></tbody></table>

## 2.3. Radiation-Induced Transcriptome Alteration in Radioresistant NSCLC Cells through Pathway Activation Level (PAL) Analysis

Pathway Activation Level (PAL) is an integral parameter, which serves as an accurate qualitative measure of pathway activation [12]. The PAL analysis was performed for functional analysis of our radioresponsive gene sets acquired from the RNA-seq of radioresistant sublines relative to their parental cells using data from Reactome [13], NCI Pathway Interaction [14], Biocarta, KEGG Adjusted, Metabolism and Primary databases. As a result, we found 420 differential pathways (Benjamini Hochberg adjusted *p*-value < 0.05) between radioresistant A549IR and parental A549 cells. A total of 230 pathways were up-regulated in radioresistant A549IR cells (PAL > 0) and 190 pathways were down-regulated in A549IR cells (PAL < 0). Here, we present the top 10 up-regulated and down-regulated pathways associated with the radioresistance-related transcriptome alteration in A549IR sublines (*p*-value less than 0.05) (Figure 3a,b). Based on the results of the PAL analysis, we first identified demannosylation ("Progressive trimming of alpha-1,2-linked mannose residues from Man9/8/7GlcNAc2 to produce Man5GlcNAc2"), interleukin 12 biosynthesis, c-Kit pathways and BCR signaling, proposing metabolical, immunological/inflammatory responses, cell migration and actin filament polymerization as pathways that could be meaningfully associated with radiation tolerance of A549IR cells. Among the top 10 down-regulated pathways with lowest PAL-score, Anthrax toxin pathways involving apoptosis, inflammatory responses, necrosis, negative regulation of macrophage activation and phagocytosis were involved in A549IR radioresistance (Figure 3a).

We found 1616 differential pathways (Benjamini Hochberg adjusted *p*-value < 0.05) between radioresistant and parental H1299 cells: 917 pathways were up-regulated (PAL > 0), while 699 pathways were down-regulated (PAL < 0) (Figure 3). The most significantly up-regulated pathways (*p*-value less than 0.001) associated with H1299IR radioresistance are shown in Figure 3b. Significant up-regulation of T cell proliferation and differentiation
points to a link between immunological responses and radiation tolerance in H1299IR cells. In addition, the high-scoring functions in the pathways were the insulin-like growth factor 1 receptor (IGF1R) and the diabetes mellitus pathway with subsequent inhibition of the PI3K/Akt pathway involved in glucose import (Figure 3b). The latter was among the top 10 scoring down-regulated pathways considerably involved in H1299IR radioresistance.

<figure><img src="image_64.png" /><figcaption>**Figure 3.** PAL chart of A549 and H1299 cells: (a) Top 10 up- and down-regulated pathways in A549IR and (b) H1299IR cells, Benjamini Hochberg adjusted *p*-value < 0.05 (only pathways containing 10 and more genes).</figcaption></figure>

The overlap between A549IR and H1299IR up-regulated and down-regulated pathways contained 142 common differential molecular pathways (Supplementary Table S2).