Eighty-two pathways were activated and 59 were inhibited. This suggests non-random overlap between the differential pathways in both comparisons, *p* < 0.05 (Figure 4).

<figure><img src="image_65.png" /><figcaption>**Figure 4.** Overlap between differentially regulated molecular pathways between A549IR and H1299IR cells. Overlap of significantly (a) up-regulated (PAL > 0) and (b) down-regulated (PAL < 0) molecular pathways between A549IR and H1299IR cells are shown; * denotes significance at *p* < 0.05 for the overlaps obtained in perturbation.</figcaption></figure>

## 2.4. *Differential Pathway Changes in NSCLC Cells*

A main factor related to radioresistance is the presence of cancer stem cells (CSC) inside tumors, which are responsible for metastases, relapses, radiation therapy failure, and a poor prognosis in cancer patients. The Wnt signaling is one of the key cascades regulating maintenance of CSCs, metastasis and immune control of many cancers including NSCLC [15]. We further analyzed the expression of key signaling pathways involved in cancer radioresistance, including Wnt, p53, Hippo, NF-κB, Akt, FOXO, etc. (22 pathways in total) (Figure 5). Heatmap analysis revealed slight up-regulation of beta1 integrin (Alpha9 beta1 integrin signaling events), Wnt (Wnt ligand biogenesis and trafficking, WNT5A-dependent internalization of FZD4) and NF-κB signaling for both A549IR and H1299IR cells (Figure 5, red rectangle). Among pathways of interest, p53, HSF, Cyclin D1, and FOXO almost did not show any change in radioresistant cells over their parental cell lines.

Interestingly, H1299IR cells demonstrated a significant increase in Wnt signaling over parental level, compared to A549IR subline. “NCI Wnt signaling network Main Pathway” and “NCI FOXA2 and FOXA3 transcription factor networks Main Pathway” were almost 50-fold up-regulated in H1299IR over parental cells, suggesting their role in radioresistance of p53-deficient NSCLC. The level of the main Wnt signaling pathway and Wnt target genes, as well as the “Regulation of HSF1-mediated heat shock response”, “Regulation of retinoblastoma protein” and “FOXM1 transcription factor network”, were significantly up-regulated in H1299IR compared to A549IR cells (Figure 5), suggesting the role of genotype in radioresistance-associated pathway profiles. In contrast, the down-regulation of “Inactivation of Gsk-3 by Akt Causes Accumulation of B-Catenin in Alveolar Macrophages”, “KEGG Hippo signaling pathway” and “Akt phosphorylates targets in the cytosol” were more significantly down-regulated pathways in H1299IR than in A549IR subline.
<figure><img src="image_66.png" /><figcaption>**Figure 5.** Heat map of RNA-Seq transcriptome analysis for 22 selected pathways in A549IR and H1299IR cells. The most significant differences between H1299IR and A549IR sublines are highlighted in red. Benjamini Hochberg adjusted *p*-value < 0.05.</figcaption></figure>

## 2.5. Characteristics of Senescence-Associated Radioresistance in NSCLC Cells

It is becoming increasingly clear that acute and chronic senescence are characterized by distinct senescence-associated secretory phenotype (SASP) factors involved in tumor progression. A positive correlation between radioresistance and early induction of head-and-neck squamous cell carcinoma (HNSCC) cell senescence accompanied by NF-κB-dependent production of distinct senescence-associated cytokines was identified by Schoetz et al. [16]. Hence, despite the subtle up-regulation of NF-κB signalling (Figure 5), we attempted to further elucidate the transcription of NF-κB-regulated genes encoding key secretory proteins of SASP. Based on the Chien analysis [17] of 263 genes involved in H-RasV12-induced senescence in IMR-90 normal lung fibroblasts, a well-characterized system of cellular senescence, we analyzed changes in the expression of select NF-κB-regulated genes that encode secretory proteins in our radioresistant sublines. In total, we analyzed the expression of 13 genes (Table 2). Only H1299IR showed significant up-regulation of CXCL8, a gene coding IL8, a ligand for the chemokine receptor CXCR2, and TGFB2, the gene encoding a secreted ligand of the TGF-β (transforming growth factor-beta) superfamily of proteins. Both A549IR and H1299IR sublines demonstrated significant increase in the expression of IL6.

<table><caption>**Table 2.** Differential gene expression of NF-κB-regulated secretory proteins in A549IR and H1299IR cells (statistically significantly up-regulated genes shown in green, down-regulated genes shown in red).</caption><thead><tr><th>Genes</th><th>A549IR LFC</th><th>A549IR <i>p</i>-Value</th><th>H1299IR LFC</th><th>H1299IR <i>p</i>-Value</th></tr></thead><tbody><tr><td>CCL20</td><td>-1.325</td><td>0.246</td><td>-0.085</td><td>0.791</td></tr><tr><td>CCL3</td><td>0.079</td><td>0.810</td><td>-0.085</td><td>0.791</td></tr><tr><td>CXCL1</td><td>0.043</td><td>0.895</td><td>0.739</td><td>0.134</td></tr><tr><td>CXCL2</td><td>-0.448</td><td>0.348</td><td>-0.037</td><td>0.917</td></tr></tbody></table>
<table><caption>**Table 2. Cont.**</caption><thead><tr><th>Genes</th><th>A549IR LFC</th><th>A549IR p-Value</th><th>H1299IR LFC</th><th>H1299IR p-Value</th></tr></thead><tbody><tr><td>CXCL3</td><td>-0.247</td><td>0.348</td><td>0.054</td><td>0.924</td></tr><tr><td>CXCL5</td><td>0.513</td><td>0.119</td><td>-0.085</td><td>0.791</td></tr><tr><td>CXCL8</td><td>-0.299</td><td>0.424</td><td>3.544</td><td>0.000</td></tr><tr><td>FGF2</td><td>-0.066</td><td>0.760</td><td>-0.194</td><td>0.560</td></tr><tr><td>IL1A</td><td>0.773</td><td>0.354</td><td>-0.085</td><td>0.791</td></tr><tr><td>IL1B</td><td>0.299</td><td>0.582</td><td>0.283</td><td>0.738</td></tr><tr><td>IL6</td><td>1.494</td><td>0.006</td><td>1.500</td><td>0.004</td></tr><tr><td>NRG1</td><td>-0.322</td><td>0.212</td><td>-2.212</td><td>0.009</td></tr><tr><td>TGFB2</td><td>-0.037</td><td>0.863</td><td>1.579</td><td>0.003</td></tr></tbody></table>

However, the expression of *IL6* alone was not accompanied by the increase in the proportion of SA-β-Gal positive cells in A549IR vs. A549 (Figure 6). In contrast, H1299IR cells had a significantly higher (**** *p* < 0.001) fraction of SA-β-Gal positive cells compared to the parental subline. Collectively, our findings emphasize the emerging role of secreted factors (IL8, IL6, TGF-β and Neuregulin 1) in regulating senescence through paracrine and/or autocrine mechanisms conferring radioresistance in NSCLC cell lines.

<figure><img src="image_67.png" /><figcaption>**Figure 6.** Changes in the proportion of SA-β-Gal positive cells in A549IR and H1299IR. Data are means ± SEM for more than three independent experiments. **** *p* < 0.0001.</figcaption></figure>

### 3. Discussion

The present study used whole-genome expression profiles to characterize the radioresistance of A549IR and H1299IR NSCLC cells. The integrative analysis of the expression RNA profiles revealed deregulated biological processes or pathways that may serve as predictors of radiosensitivity and future prospective therapeutic targets. To investigate the gene expression profiles and molecular pathway activation levels, two NSCLC radioresistant sublines (A549IR and H1299IR) with different p53 status were established by fractionated irradiation in a total dose of 60 Gy. We previously reported the activation of pro-survival signaling DNA repair pathways in A549IR and H1299IR cells, including G2/M cell cycle progression, BRCA1 pathway, ATR and DNA double-strand breaks repair by homologous recombination and non-homologous end joining [10]. The key molecular and cellular characteristics of radioresistant cells, including DNA repair, proliferation, epithelial-to-mesenchymal transition, etc., were confirmed and characterized in our previous studies [8,9,18,19].

Recent studies using transcriptomic analysis suggested the role of lncRNAs, such as H19 [20], circRNAs, such as ZNF208 [21], whole-genome miRNA and mRNA [22] in
determining NSCLC radioresistance. This demonstrates that transcriptomics is a valuable readout for evaluating outcomes in NSCLC patients undergoing radiotherapy [23]. Here, we interrogated the gene expression profiles obtained by sequencing of total RNA isolated from parental (A549 and H1299) and radioresistant (A549IR and H1299IR) NSCLC cells differing in their p53 status.

We observed up-regulation of 164 and 808 genes in radioresistant A549IR and H1299IR cells, respectively. Aiming to identify potent common biomarkers of NSCLC radioresistance, we observed seven common up-regulated genes (*ATRNL1*, *CA2*, *CNR1*, *FAM189A1*, *GFRA1*, *RASGRP1*, *RGL3*) and nine common down-regulated genes (*ADGRF1*, *EPHA7*, *LOX*, *LY6G5C*, *NSUN7*, *SLC22A31*, *SNAI2*, *TNFRSF11B* and *ZNF233*) between the two cell lines. Among them, several up-regulated genes are known to be involved in the formation of tumor microenvironments (Carbonic anhydrase 2 (*CA2*)) [24,25], cancer chemoresistance (Cannabinoid receptor 1 (*CNR1*)) [26], *GFRA1* [27]) and cancer recurrence after therapy (*RGL3*) [27,28]. Interestingly, some of the common down-regulated genes, such as *EPHA7* and *NSUN7*, are known for both their tumor suppressing and promoting roles, or are associated with overall survival (OS) (*SLC22A31*) [29–32], while others have clear pro-tumorigenic roles (*ADGRF1*, *LOX*, *LY6G5C*, *SNAI2*, *TNFRSF11B*, *ZNF233*) [30,33–36]. This may suggest a differential role of many potent pro-tumorigenic genes in cancer aggressiveness and in sustaining radioresistant phenotypes of NSCLC cells during normal culture conditions. However, this notion warrants further investigation and the role of each up-regulated and down-regulated gene in NSCLC radioresistance must be confirmed individually.

High-throughput gene expression data allows calculating pathway activity levels (PAL) associated with cancer radioresistance. In A549IR cells, one of the most activated pathways included progressive trimming of alpha-1,2-linked mannose residues from Man9/8/7GlcNAc2 to produce Man5GlcNAc2 (Figure 4a). N-glycan demannosylation is a highly conserved mechanism allowing cells to avoid protein misfolding and subsequent functional deficiency and cellular toxicity [37]. This process occurs in the Golgi apparatus and forces irreparable misfolded glycoproteins into the Endoplasmic Reticulum-Associated Degradation (ERAD) pathway, where they can be destroyed [38]. Our results demonstrate for the first time the association of the Man-trimming pathway with NSCLC radioresistance.

Surprisingly, we observed the NO2-dependent IL-12 Pathway in NK cells (Figure 4a) as the second most activated pathway in A549IR cells. The IL-12 is a cytokine that activates the large granular lymphocytes or natural killer cells (NK) and is considered a strong candidate for immunotherapy-based tumor cell killing [39]. At the same time, Single Nucleotide Polymorphisms (SNPs) in the IL-12 gene have been associated with the risk of NSCLC [40,41] and breast cancer [42].

The overall effect of senescence on cancer progression and cancer cell resistance to X-ray radiation is still not fully understood and remains controversial. Senescence is a state where cells neither function normally nor die. Cells that are damaged or old may enter this suspended state. In this state, they do not reproduce, but are able to communicate with the tumor microenvironment (TME) through senescence-associated secretory phenotype (SASP) in a paracrine fashion [43]. Albeit stress-induced senescence is generally considered to be a tumor-suppressive mechanism [44], long-term treatment-induced senescence of cells may be harmful. Long-term induction of senescence will produce TME that promotes inflammation and immunosuppression [45]. Hence, induction of cancer cell senescence as a recently suggested new therapeutic strategy against cancer [46–49] should be context-dependent and evaluated carefully based on the cancer stage. Additionally, it seems to be possible to develop new therapeutic strategies to combine priming (immunization) with IR-induced senescent patient-derived cancer cells with IR treatments. In this regard, our study provides new add-in transcriptomic information about activation of SASP-related genes and signaling pathways in response to certain IR stress-inducing insults of different duration.

Interleukins as secretory proteins are involved in SASP-related radioresistance [50]. Previously reported positive correlation between radioresistance of human HNSCC cell senescence accompanied by NF-κB-dependent production of distinct senescence-associated
cytokines [16], together with the up-regulation of NF-κB signaling observed in our study, allowed us to assume their potent role in NSCLC radioresistance. The results of the differential gene expression analysis of NF-κB-regulated secretory proteins revealed the association of *CXCL8*, *IL6* and *TGFB2* up-regulation and *NRG1* down-regulation with the increase in the proportion of SA-β-Gal positive cells in H1299IR subline (Table 2). Notably, *CXCR2/IL8* activation is associated with both NSCLC lymph node metastasis and unfavorable prognosis for patients with NSCLC [51]. TGF-β1 causes a switch from cohesive to single cell motility and intravasation that are essential for blood-borne metastasis in breast cancer [52]. It also mediated neutrophil recruitment that drives NOTCH1 signaling-mediated metastasis in colorectal cancer [53]. In H1299IR cells, *NRG1*, Neuregulin 1 coding gene, was significantly down-regulated (Table 2). Importantly, *MUC1* and *NRG1* are controlled by the Eukaryotic Translation Initiation Factor 4 Gamma 1 (EIF4G1) for NSCLC survival and tumorigenesis with clinical relevance [54], while *NRG1* is the major tumor suppressor gene postulated to be on 8p: it is in the correct location, is antiproliferative and is silenced in many breast cancers [55]. Last, but not least, the up-regulation of *IL6* alone seemed to be insufficient to induce senescence, as can be seen by the low SA-β-Gal-positive fraction of A549IR cell subline (Figure 6). Our findings suggest that the *CXCR2/ligand-axis* activation can be pivotal in driving radiotherapy-induced senescence in NSCLC.

Among other pathways involved in cell migration, proliferation and survival, we observed the up-regulation of anandamide degradation pathways in the A549IR subline. Anandamide is an endocannabinoid, part of a family of biologically active lipids that bind to and activate cannabinoid receptors and play a role in biological activities of both the central and periphery nervous systems [56,57]. Anandamide can be transported into the cell where it is metabolized by cyclooxygenase 2 (COX-2) to prostaglandin-ethanolamides (PG-EAs) [58]. The PGs, for example PGE2, are likely to mediate some of the tumour-promoting effects of COX-2, such as immune response, angiogenesis and cell proliferation [59,60]. An IR-induced increase in COX-2 expression was previously observed in radioresistant A549 cells [61]. Moreover, targeting COX-2 inhibited malignant proliferation of A549 cells in vivo and in vitro [62]. Thus, our results support previously published data on anandamide degradation pathways in radioresistance.

Most of the down-regulated pathways in A549IR cells contained the Anthrax toxin (Figure 4a). Tumor endothelial marker 8 (TEM8), also known as anthrax toxin receptor 1 (ANTXR1), is highly expressed in cancers. Its expression level was associated with tumor size, primary tumor stage and a poor prognosis in patients with lung adenocarcinoma [63]. The ANTXR1 is expressed on metastatic breast cancer stem cells (CSCs) and functions in collagen signaling, as well as Wnt signaling, ZEB1 expression, and CSC self-renewal, invasion, tumorigenicity, and metastasis [64]. The ANTXR1 was identified as a functional biomarker of triple-negative breast CSCs, and pancreatic ductal adenocarcinoma (PDAC) patients stratified based on the ANTXR1 expression level showed increased mortality and enrichment of pathways known to be necessary for CSC biology, including TGF-β, NOTCH, Wnt/β-catenin, and IL-6/JAK/STAT3 signaling and epithelial to mesenchymal transition, suggesting that ANTXR1 may represent a putative CSC marker [65]. However, based on our data, the ANTXR1 pathway does not play a role in NSCLC radioresistance.

In H1299IR cells, radioresistance was associated with deregulation of metabolism including PI3K/Akt signaling pathway involved in the development of obesity and type 2 diabetes mellitus (DM) [66]. The DM has been shown to be associated with NSCLC progression, suggesting that pre-existing diabetes is an independent prognostic factor for overall survival (OS) among patients with both diabetes and lung squamous cell lung carcinoma who receive standard treatments [67–69]. Women with lung cancer and diabetes had significantly increased risk of overall mortality (HR = 1.27, 95% CI: 1.07–1.50) compared to those without diabetes [70]. However, it is still unclear whether the DM is a risk factor for developing NSCLC or vice versa. Here we demonstrate significant up-regulation of Type 2 diabetes mellitus pathways in H1299IR cells through overexpression of IGF-1R and down-regulation of the PI3K/Akt signaling pathway (Figure 3b). The IGF-1R may activate
two major signaling pathways, the PI3K/Akt and MAPK pathways [71]. The activated form of Akt, phosphorylated Akt (p-Akt), may inhibit several proapoptotic factors including glycogen synthase kinase-3 beta (GSK3β) [72], which in turn mediates insulin resistance and human type 2 diabetes [73]. Thus, it is tempting to speculate that up-regulation of DM pathways in H1299IR cells serve as a prognostic biomarker of DM in patients with NSCLC, suggesting that pre-existing NSCLC is a potent inducer of DM leading to a worse prognosis. However, this notion warrants further investigation.

Unlike A549IR, H1299IR cells demonstrated significant up-regulation of the IL-4 signaling pathway (Figure 3b). The IL-4 plays a role in T cell activation, differentiation, proliferation, and survival [74] and, together with its receptor complex (IL4R), has been studied for their role in epithelial cancer progression, including enhanced migration, invasion, survival, and proliferation [75]. Recently, T cell marker genes were proposed as novel prognostic signatures for lung squamous cell carcinoma (LUSC) patients [76].

We observed significant 50-fold up-regulation of Wnt signaling in H1299IR cells. Wnt proteins are secreted glyco-lipoproteins that participate in cell fate determination, proliferation and the control of asymmetric cell division during lung development [77]. It has been suggested that Wnt signaling is also involved in the regulation of cancer stem cells [78] and thus, plays an important role in lung carcinogenesis [79]. The major (canonical) Wnt pathway signals through β-catenin [80]. In the absence of Wnt, β-catenin undergoes proteolytic degradation by β-catenin destruction complex consisting of axis inhibition protein (AX-IN), adenomatous polyposis coli (APC), and glycogen synthase kinase 3 beta (GSK3β) phosphorylates β-catenin [78]. In the presence of Wnt, cytoplasmic levels of β-catenin rise and it migrates to the nucleus where it activates the expression of various target genes, including cyclin D1 [81], c-Myc [82] and survivin [83].

To elucidate whether Wnt pathway contributes to radioresistance in NSCLC, we further evaluated the Wnt pathway activation. We observed significant up-regulation of canonical (Wnt/β-catenin) pathway in radioresistant H1299IR cells, but not in A549IR cells (Figure 5). Moreover, this process was accompanied by down-regulation of inactivation of GSK3β by Akt, which can cause accumulation of β-catenin in alveolar macrophages pathway. A GSK3β inactivation influences β-catenin, leading to increases in cell motility and migration. The phosphorylation of GSK3β by Akt results in its inactivation. The down-regulation of this process leads to the presence of activated, non-phosphorylated GSK3β, which in turn can phosphorylate β-catenin at Ser33/37. This results in the proteasomal degradation of β-catenin. In colon cancer cells with hyperactivated canonical Wnt signaling, pharmacological inhibition of the PI3K-Akt signaling leads to a nuclear accumulation of β-catenin and FOXO3α, and subsequently increased cell scattering and metastasis [84]. The FOXA2 and FOXA3 transcription factor networks were also up-regulated in H1299IR cells (Figure 5). In A549IR cells, down-regulation of the Wnt signaling pathway might be associated with upregulation of the MCC gene which can suppress cell proliferation and the Wnt/β-catenin pathway in colorectal cancer cells (Supplementary Table S1) [85].

The genes and signaling pathways identified in this study provide new important insights into the mechanisms underlying radioresistance in NSCLC cells. The observed whole genome expression profiles can be linked to molecular and cellular characteristics of radioresistant cells, including decreased radiosensitivity, resistance to cell death, enhanced cell proliferation and migration, and raise interest as potential biomarkers and therapeutic targets for NSCLC treatment.

# 4. Materials and Methods

## 4.1. *Cell Cultures and Irradiation*

The A549 (p53 wild-type) and H1299 (p53-deficient cells) cell cultures and their isogenic radioresistant sublines A549IR and H1299IR were cultured in RPMI-1640 medium (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) containing 10% fetal bovine serum (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with L-glutamine and antibiotics under standard conditions (37 °C, 5% CO₂).
The radioresistant sublines were established after 30 fractions of 2 Gy X-ray exposure using 200 kV X-ray RUB RUST-M1 X-irradiator facility (0.85 Gy/min, 2 × 5 mA, 1.5 mm Al filter, JSC "Ruselectronics", Moscow, Russia). Cells were irradiated five days a week at room temperature. After reaching a total dose of 60 Gy, cells were cultured at 37 °C in a humidified atmosphere with 5% CO₂ for up to 3 weeks to recover. The radioresistance was previously confirmed using clonogenic assay [19].

## 4.2. Clonogenic Test and Soft Agar Colony Formation

The A549, A549IR, H1299, and H1299IR cells were subjected to single X-ray irradiation at doses of 2 Gy, 4 Gy, and 6 Gy, removed from the plastic surface immediately after irradiation, and plated on Petri dishes 60 mm in diameter in the amount of 150, 500, 1000, and 2000 cells/well, respectively. Petri dishes were incubated at 37 °C in a humid atmosphere with 5% CO₂ for two weeks to form colonies. After that, the cells were fixed with 100% methanol for 15 min at room temperature, followed by Giemsa staining for 15 min. Only colonies containing more than 50 cells were counted. Seeding efficiency (PE) and survival rate (SF) were calculated using the following equations:

$$PE = \text{number of colonies formed}/\text{number of cells seeded} \times 100\% \quad (1)$$

$$SF = \text{number of colonies formed}/(\text{number of cells seeded} \times PE) \quad (2)$$

The anchorage-independent soft agar colony formation assay was performed according to the procedure described Borowicz et al. [86]. Exponentially growing A549, A549IR, H1299, and H1299IR cells were X-rayed at doses of 0 Gy, 2 Gy, 4 Gy, and 6 Gy. Collected by trypsin treatment, cells were mixed with 0.6% purified agar. Cell/agar mixtures were added to 6 well plates pre-coated with 1.0% purified agar in complete medium (1.5 mL agar per well) and allowed to solidify for 30 min at room temperature before being placed in a humidified cell culture incubator at 37 °C. Twice a week, 100 µL of culture medium was added to the wells to prevent the agar from desiccation. After colonies formed (~21 days), they were stained with 0.05% crystal violet and counted manually.

## 4.3. Transcriptomic Analysis

The gene expression level was evaluated by RNA-seq analyses of three biological replicates of each cell line. The InnuPREP RNA Mini Kit 2.0 together with innuPREP DNase I Digest (Analytik Jena, Berlin, Germany) were used to isolate total RNA. To measure RNA concentration, we used the Qubit 4 Fluorometer with Qubit RNA Assay kit. The RNA integrity number (RIN) was measured by TapeStation with RNA ScreenTape reagents (Agilent, Santa Clara, CA, USA). For depletion of ribosomal RNA and library construction, the KAPA RNA HyperPrep Kit with the RiboErase (HMR) kit were used. The KAPA UDI Primer Mixes were used for sample barcoding to allow their multiplexing in a single sequencing run. Library concentrations were measured using the Qubit 4 Fluorometer with the Qubit dsDNA HS Assay kit (Life Technologies, Waltham, MA, USA) and TapeStation with High Sensitivity D1000 reagents (Agilent). The RNA sequencing was performed on the Illumina Nextseq 550 System with reagents for single-end sequencing and read length of 75 bp.

## 4.4. Bioinformatics Analysis

FASTQ read files were analyzed using the STAR software [87] in "GeneCounts" mode using transcriptome annotation from Ensembl (GRCh38 genome assembly and GRCh38.89 transcriptome annotation). In total, expression levels of 36,596 genes were measured. The data was normalized using DESeq2 [88].

Changes in the activation of intracellular molecular pathways of IR-survived cells compared to parental cells were quantified using the Oncobox bioinformatics platform [89]. A total of 38 molecular pathways associated with DNA repair were used for analysis [90].
Pathway activation level (PAL) for each molecular pathway was calculated using the formula:

$$ \mathrm{PAL}_p = \sum_n ARR_{np} \times \ln CNR_n \div \sum_n |ARR_n|, \quad (3) $$

where PALp is the level of activation of the molecular pathway p; CNRn (case-to-normal ratio)—the ratio of gene n expression level in a tumor sample under study to an average level for the control group; 'ln' is the natural logarithm; the discrete ARRnp value (role of activator/repressor) of gene n product in the p pathway is determined as follows: ARRnp is -1 if gene product n inhibits pathway p; 1 if n activates pathway p; 0 if n has ambiguous or unclear role in a pathway p; 0.5 or -0.5 if n is rather an activator of a pathway or its inhibitor, respectively.

### 4.5. Gene Ontology (GO) Analysis

The GO analysis is a commonly applied method for functional studies of large-scale genomic or transcriptomic data [11]. Function enrichGO from the clusterProfiler package was used to identify significantly enriched GO terms among the given list of genes that are differentially expressed in radioresistant and parental cells [PMID: 22455463]. Statistically overrepresented GO categories with *p*-value < 0.05 were considered significant.

### 4.6. Analysis of Senescence-Associated β-Galactosidase (SA-β-Gal) Positive Cells

The “Cellular Senescence Assay” commercial kit (EMD Millipore, Burlington, MA, USA, Catalog Number: KAA002) was used for quantification of senescence-associated β-galactosidase (SA-β-Gal) positive cells. The cells were stained according to the manufacturer’s protocol. The stained cells were visualized using EVOS® FL Auto Imaging System (Fisher Scientific, Pittsburgh, PA, USA) with 20× objective. The proportion of SA-β-Gal positive cells was calculated manually.

### 4.7. Statistics

Statistics were performed using GraphPad Prism 9.0.2.161 software (GraphPad Software, San Diego, CA, USA). Statistical significance was tested using the Student *t*-test. The results are represented as means ± SEM of more than three independent experiments. Significance levels were denoted by asterisks: * *p* < 0.05, ** *p* < 0.01, *** *p* < 0.001, **** *p* < 0.0001.

## 5. Conclusions

For the first time, we investigated the transcriptome profile of radioresistant NSCLC sublines of A549 and H1299 cells through RNA-seq and bioinformatic functional analysis. Our research with this new methodological approach may provide a useful guideline for the experimental design of gene expression studies and for exploring novel routes to uncover the complete regulatory network involved in radioresistance. In the present study, we used only two radioresistant NSCLC cell sublines derived from parental A549 and H1299 cells. However, it will be worth investigating the differences of the same set of differentially expressed genes in other tumor cell lines and primary cells isolated from lung tumor tissue. Some of the identified novel targets could be potentially interesting in further studies for sensitization of tumor cells to improve radiation effects. Our research could help to interpret the complicated molecular mechanisms leading to radioresistance. Furthermore, it might contribute to the identification of other target genes for predictive biomarkers, improving radiotherapy.

**Supplementary Materials:** The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24033042/s1.

**Author Contributions:** Conceptualization, M.P., S.L. and A.N.O.; software, M.S. (Maxim Sorokin); formal analysis, M.S. (Maxim Sorokin); research, M.S. (Maria Suntsova), A.G. and P.M.; writing—original draft preparation, M.P.; writing—review and editing, S.L., A.N.O. and A.B.; visualization,
M.S. (Maxim Sorokin) and M.P.; project administration, M.P.; funding acquisition, M.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the strategic academic leadership program 'Priority 2030' (Agreement 075-02-2021-1316, 30 September 2021).

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The materials and data are available from the corresponding authors.

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

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Article

# Long-Term Cultured Human Glioblastoma Multiforme Cells Demonstrate Increased Radiosensitivity and Senescence-Associated Secretory Phenotype in Response to Irradiation

Lina Alhaddad <fnref n="1" />,<fnref n="2" />,† ID, Zain Nofal <fnref n="1" />,† ID, Margarita Pustovalova <fnref n="1" />,<fnref n="3" />, Andreyan N. Osipov <fnref n="1" />,<fnref n="3" />,<fnref n="4" />,* ID
and Sergey Leonov <fnref n="1" />,<fnref n="5" /> ID

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**Citation:** Alhaddad, L.; Nofal, Z.; Pustovalova, M.; Osipov, A.N.; Leonov, S. Long-Term Cultured Human Glioblastoma Multiforme Cells Demonstrate Increased Radiosensitivity and Senescence-Associated Secretory Phenotype in Response to Irradiation. *Int. J. Mol. Sci.* **2023**, *24*, 2002. https://doi.org/10.3390/ijms24032002

Academic Editor: François Chevalier

Received: 15 December 2022

Revised: 14 January 2023

Accepted: 17 January 2023

Published: 19 January 2023

<figure><img src="image_70.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:** The overall effect of senescence on cancer progression and cancer cell resistance to X-ray radiation (IR) is still not fully understood and remains controversial. How to induce tumor cell senescence and which senescent cell characteristics will ensure the safest therapeutic strategy for cancer treatment are under extensive investigation. While the evidence for passage number-related effects on malignant primary cells or cell lines is compelling, much less is known about how the changes affect safety and Senescence-Associated Secretory Phenotype (SASP), both of which are needed for the senescence cell-based vaccine to be effective against cancer. The present study aimed to investigate the effects of repeated passaging on the biological (self-renewal capacity and radioresistance) and functional (senescence) characteristics of the different populations of short- and long-term passaging glioblastoma multiforme (GBM) cells responding to senescence-inducing DNA-damaging IR stress. For this purpose, we compared radiobiological effects of X-ray exposure on two isogenic human U87 cell lines: U87L, minimally cultured cells (<15 passages after obtaining from the ATCC) and U87H, long-term cultured cells (>3 years of continuous culturing after obtaining from the ATCC). U87L cells displayed IR dose-related changes in the signs of IR stress-induced premature senescence. These included an increase in the proportion of senescence-associated β-galactosidase (SA-β-Gal)-positive cells, and concomitant decrease in the proportion of Ki67-positive cells and metabolically active cells. However, reproductive survival of irradiated short-term cultured U87L cells was higher compared to long-term cultured U87H cells, as the clonogenic activity results demonstrated. In contrast, the irradiated long-term cultured U87H cells possessed dose-related increases in the proportion of multinucleated giant cancer cells (MGCCs), while demonstrating higher radiosensitivity (lower self-renewal) and a significantly reduced fraction of DNA-replicating cells compared to short-term cultured U87L cells. Conditioned culture medium from U87H cells induced a significant rise of SA-β-Gal staining in U87L cells in a paracrine manner suggesting inherent SASP. Our data suggested that low-dose irradiated long-term cultured GBM cells might be a safer candidate for a recently proposed senescence cell-based vaccine against cancer.

**Keywords:** glioblastoma multiforme; multinucleated giant cancer cell; senescent tumor cells (STC); stress-induced premature senescence (SIPS); senescence-associated secretory phenotype (SASP)

<footnote n="1">¹ School of Biological and Medical Physics, Moscow Institute of Physics and Technology (National Research University), 141701 Dolgoprudny, Russia</footnote>

<footnote n="2">² Department of Environmental Sciences, Faculty of Sciences, Damascus University, Damascus P.O. Box 30621, Syria</footnote>

<footnote n="3">³ State Research Center—Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency (SRC-FMBC), 123098 Moscow, Russia</footnote>

<footnote n="4">⁴ N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119991 Moscow, Russia</footnote>

<footnote n="5">⁵ Institute of Cell Biophysics, Russian Academy of Sciences, 142290 Pushchino, Russia</footnote>

<footnote>* Correspondence: aosipov@fmbcfmba.ru</footnote>

<footnote>† These authors contributed equally to this work.</footnote>
# 1. Introduction

Glioblastoma multiforme (GBM) is one of the most aggressive and most common malignant primary brain tumors in adults and often occurs in patients over 65 years of age [1,2]. Radiotherapy is still a treatment of choice for patients with GBM. However, its efficacy is limited by the dose that can be safely administered without eliciting serious side-effects, especially in elderly and debilitated patients, as well as the fact that recurrence, metastasis and radioresistance are common in GBM [3]. Radiotherapy can cause cancer cells to enter a state of stress-induced premature senescence (SIPS), thereby slowing down the cell cycle and further proliferation and allowing cancer cells to escape the DNA-damaging effects of X-rays. It is believed that SIPS rather than apoptosis, is preferentially induced in GBM cells after radio-and chemotherapy. Cancer cell senescence inhibits cancer growth by halting massive proliferation and increasing chances of immune clearance [4].

While the evidence for passage number-related effects on malignant primary cells or cell lines is compelling, much less is known about how the changes affect safety and SASP, both of which are needed for a recently proposed senescence cell-based vaccine to be effective against cancer. Indeed, it was discovered that senescent tumor cells induce a bigger immune response than dead cancer cells [5]. Inducing tumor formation in mice previously injected with senescent tumor cells led to the development of fewer tumors, with some developing none. Albeit the injection was less effective against pre-existing tumors, this research suggests that a potential senescent cell cancer vaccine could show promise.

The quality and the reproducibility of anti-cancer effects of senescence cell-based vaccines depends on the quality and safety of the tumor cells used to make the vaccine. In turn, these characteristics of tumor cells seem to depend not least on the degree of subcultivation of cancer cells. The effects of passage number are usually long lasting. Transformed and diseased cell lines are of special concern, since they represent abnormal starting populations. Over time, they may change both their genotypic and their phenotypic traits. In these cell types, one or all of the typical cellular checkpoint genes, such as p16/INK4a, pRB and p53, have been altered whereby the cells have become "eternal". These alterations are often in parallel with other cellular mutations, and the continual subculture of these cell lines exacerbates genomic and phenotypic instability [6]. For example, reduced cancer stem cell characteristics in a side population (SP) of late-passage non-small cell lung cancer (NSCLC) cells was reported. These include increased frequency of tumor-initiating and self-renewal capacity, and resistance to DNA-damaging agent doxorubicin and ionizing radiation [7]. The discovery that the SP from long-term passage NSCLC cells was not consistently enriched for stem cell-like cancer cells in the cancer stem cell research field leads to the recommendation to use only low-passage cell lines.

Further complicating matters is that a passage level considered "high" for one cell line may not give rise to any significant passage effects in another. To prevent passage-related effects from affecting experiments, it is important to know how many experiments can be performed in a given set of cells at the same time, and how many there are.

How to induce tumor cell senescence to serve as a therapeutic strategy for cancer treatment is under extensive investigation. Thus, studies of the molecular mechanisms of cancer cell senescence and cancer cells' escape from senescence will provide a new perspective on how cancer can be treated safely.

The overall effect of senescence on cancer progression and cancer cell resistance to X-ray radiation (IR) is still not fully understood and remains controversial. Senescence is a state where cells neither function normally nor die. Cells that are damaged or old may enter this suspended state. In this state, they do not reproduce, but they still communicate with the tumor microenvironment through SASP in a paracrine fashion [8]. Albeit stress-induced senescence is generally considered to be a tumor-suppressive mechanism [9], long-term treatment-induced senescence of cells may be harmful. Long-term induction of senescence will produce a tumor microenvironment that promotes inflammation and immunosuppression [10]. Hence, induction of cancer cell senescence as a recently suggested new therapeutic strategies against cancer [5,11–13] should be context-dependent and evaluated
carefully based on the cancer age. Additionally, it is possible to develop new therapeutic strategies to combine priming (immunization) with IR-induced senescent patient-derived cancer cells with IR treatments [14].

Based on all these findings, we thought be worth investigating the effects of repeated passaging on the biological (self-renewal capacity and radioresistance) and functional (senescence) characteristics of different populations of short- and long-term cultivated GBM cells responding to senescence-inducing DNA-damaging IR stress. We compared U87 cell lines that differ significantly in the culture duration after receiving from the ATCC: low passage number U87 cell lines (U87L) that have undergone up to 15 passages and high passage number U87 cell lines (U87H) that have undergone more than 3 years of continuous passaging. Our results demonstrate that long-term cultivation may sensitize GBM cells to IR, while possessing the safest phenotype, including constitutive highest SASP and lowest self-renewal capacities. In contrast, the short-term cultivated GBM cells sustained higher reproductive survival possibly through an IR dose-related increase in the proportion of SA-β-Gal-positive cells (both MGCCs and non-MGCCs) that might ultimately lead to GBM radioresistance.

## 2. Results

### 2.1. Long-Term Cultivation Leads to a Decrease in Clonogenic Growth of GBM Cell Line after Irradiation

Clonogenic assay or colony formation assay is an in vitro cell survival assay based on the ability of a single adherent cell to grow into a colony and is a "gold standard" for assessing cancer cells' radiosensitivity [15]. The number of colonies originating from single cells is expressed by plating efficiency (PE), an index which has emerged for normalization of surviving fractions based on the major premise that under untreated conditions the relation between the number of seeded cells and the number of resulting colonies is linear. PE is often used for determining the effects of growth factors and toxicity testing. We aimed to evaluate PE alteration of IR exposed minimally cultured (U87L) and long-term cultured (U87H) GBM cells. We observed that 2 Gy IR significantly increases PE of U87L cells (by 1.45 times, *p* < 0.01) and decreases its value after 6 Gy exposure (by 2.71 times, *p* < 0.001) compared to non-irradiated cells (Figure 1a). In contrast, U87H cells displayed a dose-dependent decrease in the PE by 1.55 times (*p* < 0.01) and by 3.67 times (*p* < 0.001) after irradiation at doses of 2 and 6 Gy, respectively (Figure 1b). Despite the PE results, U87L cells had higher survival fractions (SF) compared to U87H after irradiation at a dose of 6 Gy (*p* < 0.01) (Figure 1c), indicating their higher radioresistance growing under anchorage-dependent conditions.

<figure><img src="image_71.png" /><figcaption>Figure 1. *Cont.*</figcaption></figure>
<figure><img src="image_72.png" /><figcaption>**Figure 1.** Plating efficiency of U87L (a) and U87H (b) cells after exposure to 2 and 6 Gy IR. Colony formation efficiency in soft agar of U87L (d) and U87H (e) cells after exposure to the same doses of IR. Reproductive survival of GBM cell lines was analyzed using survival fraction of cells grown under both anchorage-dependent (c) and anchorage-independent conditions (f). \* *p* < 0.05; \*\* *p* < 0.01; \*\*\* *p* < 0.001; \*\*\*\* *p* < 0.0001; \*\*\*\*\* *p* < 0.00001.</figcaption></figure>

Anchorage-independent growth is the ability of transformed cells to grow indepen-
dently of the attachment to a solid surface, and is a hallmark of carcinogenesis, anoikis
resistance and propensity to tumor metastasis [16]. To evaluate whether the long-term
culturing affects the anoikis resistance of two isogenic U87 cell sublines, we assessed
their reproductive survival using anchorage-independent soft agar colony formation assay.
Whereas U87L cells demonstrated increased ability to grow and to form colonies under
non-adherent conditions (Figure 1d), the long-term cultured U87H cells had a significantly
reduced ability (Figure 1e) both with and without IR exposure. Consequently, the survival
fraction of U87L cells significantly exceeded that of U87H cells (Figure 1f) supporting the
notion that long-term culturing leads to decreases in reproductive survival of the GBM
U87H cell subline in response to IR-induced stress.

## 2.2. Influence of Preceding Cultivation Length on Metabolism of GBM Cells after Irradiation

To understand the underlying mechanisms of the discovered clonogenic effect of
long culturing of malignant cells, we evaluated the metabolic changes in cells of two U87
sublines forming the colonies in soft agar. Alamar Blue test has been widely used for
cytotoxicity and viability assays based on the ability of NADPH oxidoreductases to reduce
the oxidized, non-fluorescent, blue state of the compound to a fluorescent, pink state [17].
The significant increase (by 1.25 times, *p* < 0.01) and decrease by 2.83 times (*p* < 0.00001) in
metabolic activity of U87L cells in response to IR at 2 and 6 Gy, respectively (Figure 2a),
correlates well with the dynamics in their colony formation efficacy (Figure 1d) after IR
exposure at the same doses. At the same time, irradiation did not lead to a change in
metabolic activity of colony-forming long-term cultured cells of U87H subline (Figure 2b).
Taken together, our results demonstrate that the retained ability of the U87L cell subline to
modulate its own activity of NADPH oxidoreductases may underlie the high reproductive
survival in response to IR-induced stress.
<figure><img src="image_73.png" /><figcaption>**Figure 2.** Assessment of the metabolic activity of U87L (a) and U87H (b) cells 7 days after irradiation at doses of 2 and 6 Gy using the Alamar Blue test in soft agar. **p** < 0.01; ****p** < 0.00001.</figcaption></figure>

## 2.3. IR Increases the Proportion of Senescent MGCCs in the Short-Term, but Not in the Long-Term Cultivated GBM Cell Line

Advanced age is a major risk factor for the development of GBM [18]. At the same time, MGCCs arise in response to ionizing radiation in many tumors and contribute to cancer relapse by first entering a state of dormancy which is often accompanied by the stress-induced premature senescence (SIPS) phenotype and ultimately giving rise to cell progeny with stem-like properties [19]. We found that the proportion of MGCCs in response to irradiation at single therapeutically relevant doses of 2 and 6 Gy differs for U87 cell sublines depending on the duration of their preceding cultivation. We observed an increase in the proportion of MGCCs in U87L cells by 1.5 times (from 7.2% in non-irradiated cells to 10.5%, *p* = 0.006) 24 h after irradiation at a dose of 6 Gy (Figure 3b). For U87H cells, this effect was more pronounced: there was a statistically significant increase in the proportion of MGCCs by 2.2 times (from 5% in non-irradiated cells up to 11.2%, *p* = 0.0095) and 3.77 times (up to 18.8%, *p* = 0.0002) at 24 h after irradiation at doses of 2 and 6 Gy, respectively (Figure 3c).

As the stress-induced premature senescence (SIPS) phenotype is typically identified by senescence-associated β-galactosidase (SA-β-Gal) staining, we further aimed to compare the proportion of SA-β-Gal+ cells in the MGCCs and non-MGCCs populations of two GBM cell lines.

The basal proportion of SA-β-Gal+ cells in the non-MNGCs population of non-irradiated U87H cells (27.9%) was almost the same as in the U87L cell line (28.5%) (Figure 3d,e). Ionizing irradiation of U87L cell lines caused significant increase in SA-β-Gal+ cells up to 31.3% (*p* = 0.07) and 42% (*p* = 0.0008) at 2 Gy and 6 Gy, respectively (Figure 3d). In contrast, the same populations of irradiated U87H cells did not change significantly, reaching 27.2% (*p* = 0.6) and 29.7% (*p* = 0, 7) at 2 Gy and 6 Gy, respectively (Figure 3e).

The proportion of SA-β-Gal+ MGCC population in U87L cell lines increased up to 3% (*p* = 0.2) and 4.5% (*p* = 0.014) in response to irradiation doses of 2 and 6 Gy (Figure 3d), while the proportion of SA-β-Gal+ MGCCs in the U87H cell line was statistically indistinguishable (Figure 3e). Consequently, the proportion of SA-β-Gal+ MGCCs in the U87L cell lines after irradiation increased from 31.5% (non-irradiated cells) up to 45% and 43% of total MGCC population irradiated at 2 Gy and 6 Gy, respectively. The SA-β-Gal+ MGCC proportion in U87H cell lines decreased from 52% (non-irradiated cells) down to 23% of total MGCC population after irradiation at doses of 2 and 6 Gy.

Thus, irradiation triggered an increase in the proportion of both SA-β-Gal-positive MGCCs and non-MGCC populations in U87L cell lines, leaving unchanged the level of this senescence marker in the U87H cell line.
<figure><img src="image_74.png" /><figcaption>**Figure 3.** MGCCs formation in minimally-cultured and long-term cultivated GBM upon irradiation. Representative picture of MGCCs (indicated by arrows) (a). Change in the proportion (%) of MGCCs in U87L (b) and in U87H (c) cell lines 24 h after irradiation. Changes in the proportion (%) of SA-β-Gal+ populations in U87L (d) and U87H (e) cell lines 24 h after exposure to IR at doses of 2 and 6 Gy.
\* *p* < 0.05; \*\* *p* < 0.01; \*\*\* *p* < 0.001.</figcaption></figure>

## 2.4. Proliferative Activity of GBM Cells in Response to a Single Dose Irradiation

While eliminating tumor cells, cancer therapies could also induce a sustained proliferation arrest (treatment-induced dormancy) allowing a significant proportion of dormant cells to remain viable and metabolically active for long times post-treatment. We compared the level of EdU-positive (DNA replicating) cells between U87L and U87H lines using conventional Click-IT™ EdU Alexa Fluor 488 cell proliferation assay. The irradiation did not affect the fraction of DNA-replicating (EdU+) U87L cells (Figure 4a), while it reduced the fraction of proliferating U87H cells (Figure 4b) after 6 Gy by 1.8 times (p < 0.001) compared to non-irradiated cells.

The Ki-67 protein is not required for cancer cell proliferation, but is required for all stages of carcinogenesis [20]. As seen from our data, 6 Gy irradiation caused completely opposite changes in Ki-67 expression: there was a more than 3 times increase (p < 0.0001) and almost 3 times decrease (p < 0.0001) in U87H (Figure 4d) and U87L (Figure 4c) cells, respectively. Thus, increased levels of Ki-67 expression led to an almost 2-fold decrease in the amount of DNA-replicating minimally-cultured U87H cells (Figure 4a), indicating inhibition of proliferation caused by an excess of Ki-67, which is in good agreement with the previous investigations [21]. On the other hand, a significant decrease in the percentage of Ki-67 in U87L cells may evidence a slowdown in their cell cycle without a significant change in the fraction of DNA-replicating cells (Figure 4a).
<figure><img src="image_75.png" /><figcaption>**Figure 4.** Assessment of the proliferative activity of minimally cultured U87L (a,c) and long-term cultured U87H cells (b,d). Change in the percentage of EdU+ cells (a,b), as well as change in the Ki-67 fluorescence intensity (%) (c,d) was measured 24 h after irradiation at doses of 2 and 6 Gy.
*** *p* < 0.001; **** *p* < 0.00001.</figcaption></figure>

## 2.5. Long-Term Cultured U87H Cells Demonstrate Senescence-Associated Secretory Phenotype

To elucidate whether the changes in long-term cultivated U87H line are associated with Senescence-Associated Secretory Phenotype (SASP), we cultivated U87L cells with the condition medium (CM) obtained from U87H cells (Figure 5a). CM obtained from high passaged U87H cells increased the proportion of SA-β-Gal+ U87L cells by 1.6 times compared to control after incubation for 3 days (Figure 5b).

<figure><img src="image_76.png" /><figcaption>**Figure 5.** Assessment of the formation of SA-β-Gal positive cells in U87L line cultured in conditioned medium (CM) obtained from U87H cells. Schematic representation of the experiment (a). Percentage of SA-b-Gal positive cells formed in U87L cells cultured in CM and in the medium from U87L cell line (control) (b). ** *p* < 0.01.</figcaption></figure>
### 3. Discussion

Cellular senescence emerges in response to multiple extracellular or intracellular stress stimuli, such as telomeric dysfunction resulting from repeated cell division, mitochondrial impairment, oxidative stress, severe or irreparable DNA damage and chromatin disruption, and the expression of certain oncogenes. The senescence program causes permanent cell-cycle arrest, preventing the spread of damage to the next cell generation and precludes potential malignant transformation, which makes it a plausible anticancer mechanism during radiotherapy. However, this state of stable proliferative arrest is accompanied by the Senescence-Associated Secretory Phenotype (SASP), which entails the abundant secretion of pro-inflammatory molecules in the tissue microenvironment and contributes to age-related diseases, including GBM [22]. GBM is a primary brain tumor with a median age of diagnosis of 68–70 years [23]. The incidence rate of GBM increases with age from 1.25 per 100,000 people in adults of 35–44 years of age to 15.13 among older people of 75–84 years of age [24]. The basis for the increased incidence of GBM among elderly people remains poorly understood [18].

In the present study, we demonstrate the comparative analysis of X-ray irradiation exposure on two isogenic GBM cell lines: U87L, minimally cultured cells (<15 passages after obtaining from the ATCC) and U87H, long-term cultured cells (>3 years of continuous culturing after obtaining from the ATCC). During the cultivation period, U87H cells underwent several episodes of neosis—one of the forms of cell division, characterized by atypical karyokinesis through nuclear membrane budding, followed by asymmetric intracellular cytokinesis, producing various amounts of small mononuclear cells called Raju cells, which have an extended mitotic lifespan [25].

Short-term cultured U87L cells further demonstrated reduced radiosensitivity based on the resistance to anoikis assessed by soft agar assay (Figure 1f). Anoikis is the type of apoptotic cell death arising upon loss of attachment to the extracellular matrix and neighboring cells. Cancer cells may acquire resistance to anoikis, which allows them to survive after detachment from the primary sites, disseminate throughout the body and repopulate in secondary sites giving metastases [26]. Recent study demonstrated that clusters of circulating tumor cells were mostly large (≥5 µm), exhibited polyploidy and were associated with worse outcomes in non-small cell lung cancer (NSCLC) patients [27]. Here we demonstrate that the radioresistance of short-term cultured GBM cells may be associated with an increase in MGCC formation (Figure 3).

Is the increase solely enough to confer radioresistance of short-term cultivated GBM cell lines? Corroborating the notion that MGCC formation in GBM induces senescence upon irradiation to sustain survival [28], we observed the increase of SA-β-Gal positive cells in U87L cell line. Surprisingly, despite the isogenic U87H cell line producing more MGCC (Figure 3c,b), there was no change in the fraction of SA-β-Gal+ cells in response to IR-induced stress (Figure 3d,e).

To investigate the source of this discrepancy we analyzed the proportion of SA-β-gal-positive cells among MGCC and non-MGCC populations of both isogenic cell lines. In contrast to observations by Kaur et al. [28], we found almost the same significant amount of preexisting MGCC cells, while radiation-induced MGCC formation and senescent marker expression (SA-β-Gal) were different between isogenic cell lines (Figure 3). Indeed, we found for the first time that long-term cultivated cells lost the ability to produce significant amounts of SA-β-Gal+ cells within both MGCC and non-MGCC populations respectively to the doses of IR-induced stress. Thus, sustainably increased SA-β-Gal activity rather than a rise in total MGCC production might play a pivotal role in maintenance of the reproductive survival of the short-term cultivated U87L cell line in response to IR-induced stress.

There are two phenotypes of cell dormancy: senescent cells (SIPS phenotype), in which cell cycle arrest is often irreversible, and resting cells (quiescence phenotype), which can be both non-proliferating, and slowly cycling [29]. While U87L cells demonstrated no change in DNA replication and decreased Ki-67 expression upon 6 Gy irradiation, U87H cells showed decreased DNA replicating activity accompanied by significant increase of
Ki-67 expression (Figure 4). It is important to note that Ki-67 protein is not required for
cancer cell proliferation, but rather required for all stages of carcinogenesis. The variability
in Ki-67 expression is explained by its regulation through the cell cycle and is linked
to heterochromatin packing density [20]. Our data corroborate previous findings that
significant up-regulation of Ki-67 expression often down-regulates the DNA-replication in
cancer cells [21]. Cancer treatment selects for Ki67− dormant cells, and at the same time,
induces both apoptosis and tumor dormancy in Ki67+ tumor cells, resulting in an increased
number of Ki67− and Ki67 low dormant cells [30]. Since SA-β-Gal activity can be found in
both senescent and quiescent cells, in the present study we could not specify the precise
dormancy phenotype of our GBM cell lines, albeit it warrants further investigation.

One of the hallmarks of the activation of cellular senescence is the secretion of a
plethora of cytokines, chemokines, and growth factors, which is referred to as SASP [31].
It was demonstrated that oncogene-induced senescence acted to induce senescence in
human primary melanocytes through an autocrine/paracrine fashion primarily by the
secretion of IGFBP7 [32]. A senescent cell bystander effect was illustrated by Nelson et al.,
in which replicative senescent fibroblasts induce senescence in young fibroblasts in vitro
through junction-mediated cell-cell contact [33]. Later on, it was shown that the senescence
phenotype can be transmitted in a paracrine manner from fibroblasts undergoing oncogene-
induced senescence to normal human fibroblasts and that the transmitted phenotype is
stable [34]. In the present study, we observed that long-term culturing of cells alleviates
SASP phenotype enabling induction of senescence marker in short-term cultured U87L cells
(Figure 5b). The last, not least, our findings might have important clinical implications. The
recent discovery that senescent tumor cells induce a bigger immune response than dead
cancer cells [5] suggests that a potential senescent cell cancer vaccine could show promise.
It is possible to develop new therapeutic strategies to combine priming (immunization)
with IR-induced senescent patient-derived cancer cells with IR treatments [14].

Moreover, other recent studies have also shown that in situ-induced senescent cancer
cells cause the adaptive immune system to become active. These cells can be caused
by either GATA6 [35] or ZNF24 [12,13] ectopic expressions. Alternatively, cancer cell
senescence can be alleviated by HMGCR inhibitor statins [36]. This offers a new strategy
for the treatment of pancreatic cancer by suppression of up-stream TFCP2 signaling and
induction of senescence.

Now, the question of how senescent cells interact with the adaptive immune system
has become a subject of intensive studies. The immune system activation includes dendritic
cells and CD8 T-cells recruited by senescent cancer cells producing SASP [37]. These effects
were supplemented by inducing the processing and presentation of MHC-I antigens elicited
by either X-ray irradiation [38] or doxorubicin [5]. Moreover, senescence related-genes
controlling immune cell infiltration of senescence will produce a tumor microenvironment
and responses to immune checkpoint blockage (ICB) as a lung cancer therapy [11].

While the evidence for passage number-related effects on malignant primary cells
or cell lines is compelling, much less is known about how the changes affect safety and
SASP, both of which are needed for the senescence cell-based vaccine to be effective against
cancer. In this regard, with some assumptions and reservations, it is possible to consider
the U87H cell line as an “aging” subline of U87L cells. Then, short-term cultured U87L cells
demonstrated higher reproductive survival compared to their isogenic “aged” counterpart
after X-ray radiation exposure. Thus, long-term cultivated GBM cells possess the safest
phenotype: highest sensitivity to IR and constitutive highest SASP, while having the lowest
self-renewal capacities. Our data provides novel molecular insights into a multistep process
of post-radiation reproductive survival in GBM and can be exploited for age-related anti-
cancer interventions in the treatment of GBM.
# 4. Materials and Methods

## 4.1. Cell Culture

The ATCC human U87 GBM cell lines were used in our study. U87 cell lines were cultured in DMEM (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% FBS (BioloT, Saint Petersburg, Russia), 1% L-glutamine (Gibco, Grand Island, NY, USA), and 1% antibiotics (100 U/mL penicillin, 100 µg/mL streptomycin) (Sigma-Aldrich, St. Louis, MO, USA). U87L cell lines, which have undergone (up to 15 passages) after thawing and culturing of the original ampoule from ATCC, and the U87H cell lines, which have undergone long-term continuous cultivation (more than 3 years) were used. Cell lines were kept in a humidified atmosphere with 5% CO₂.

## 4.2. Irradiation

Cells were irradiated at room temperature in doses of 2 and 6 Gy using a 200 kV X-ray RUB RUST-M1 biological unit (Ruselectronics, Moscow, Russia). The dose rate was 0.85 Gy/min ± 10%.

## 4.3. Anchorage-Dependent Growth Assay

After reaching 70–80% confluence, the cells were exposed to X-ray radiation at doses of 2 and 6 Gy. Immediately after irradiation, control cells and cells irradiated at doses of 2 and 6 Gy were harvested using a 0.05% solution of trypsin-EDTA (PanEco, Moscow, Russia) and seeded on Petri dishes (60 mm in diameter) at concentrations of 5 × 10², 8 × 10² and 1 × 10³ cells/dish, respectively. Then, Petri dishes were incubated at 37 °C in a humidified atmosphere with 5% CO₂ for 14 days to form colonies. After that, the culture medium was removed by aspiration from each dish, the cells were fixed with 100% methanol for 15 min at room temperature, followed by Giemsa staining for 15 min. Only colonies containing ≥50 individual cells were counted manually.

Plating Efficiency (PE) and Fraction of Cells, which form Colonies (FCC), were calculated using the following equations:

$$PE = \# \text{ of colonies formed} / \# \text{ of cells seeded} \times 100\% \quad (1)$$

$$FCC = \# \text{ of colonies formed after irradiation} / [\# \text{ of cells seeded} \times PE] \quad (2)$$

## 4.4. Soft Agar Clonogenic Assay

6-well plates were coated with 0.6% agar-agar (Sigma-Aldrich, St. Louis, MO, USA) pre-warmed to 43 °C in complete medium. Immediately after irradiation, cells were collected and cell concentrations were adjusted to 5 × 10², 8 × 10² and 1 × 10³ cells/mL. Cell/0.3% noble agar mixtures were added into each well and allowed to solidify for another 30 min at room temperature before placing into a 37 °C humidified cell culture incubator. Three weeks later, colonies were stained with 5% Crystal Violet solution and their number was counted manually.

## 4.5. AlamarBlue Cell Viability Assay in Soft Agar

100 µL of 0.3% agar-agar in growth medium was added to a 96-well microculture plate (Sigma-Aldrich, TPP Zellkultur. Testplatte, Trazadingen, Switzerland) and left to solidify at room temperature for 30 min. Immediately after irradiation, cell suspensions were gently mixed with 0.2% agar-agar preheated on water at 43 °C. The final concentration of cells per well was 6 × 10² cells/100 µL. Immediately after solidification, 50 µL of 0.3% agar-agar in growth medium was added to each well as a feeding layer and allowed to solidify for 30 min at room temperature. Cells were incubated under standard CO₂ incubator conditions (5% CO₂, 37 °C) for 7 days, after which 10% AlamarBlue reagent (Invitrogen, Frederick, MD, USA) was added to each well and cells were incubated for 2 h at 5% CO₂ and 37 °C. The fluorescence of the AlamarBlue reagent was determined using a CLARIOstar instrument (BMG LABTECH, Ortenberg, Germany) at excitation/emission wavelengths of
530/590 nm. The obtained data were processed using the MARS data analysis software (BMG LABTECH, Ortenberg, Germany).

### 4.6. Wright-Giemsa Staining and Analysis of MGCCs

Cells were cultured in a 96-well plate (Sigma-Aldrich, TPP Zellkultur. Testplatte, Trazadingen, Switzerland) at a concentration of 5 × 10³ cells/0.32 cm². 24 h after irradiation, the cells were fixed with absolute methanol for 5 min, after which they were stained using Wright-Giemsa solution diluted 1:10 in 1X PBS (pH 6.6) for 1 h, followed by washing with 1X PBS (pH 6.6) and distilled water. The average number of MGCCs was calculated in five microscopic fields of view at ×100 magnification.

### 4.7. Senescence Associated β Galactosidase Assay (SA-β-Gal)

Detection of the activity of aging-associated beta-galactosidase (SA-β-Gal) (a marker of the cellular senescence phenotype) was performed using a commercial cell senescence assay kit (EMD Millipore KAA002, CA, USA). The presence of the β-Gal enzyme in cells is determined by the characteristic green staining of the cytoplasm. The cells were stained according to supplemented manufacturer protocol with the following modification: at the final 1X PBS washing step, the cell nuclei were stained with 1 µg/mL Hoechst 33342 (Thermo Scientific, Rockford, IL, USA). Such modification significantly improves the quality of counting of SA-β-Gal-negative cells [39,40]. The stained cells were visualized using an EVOS® FL Auto Imaging System (Fisher Scientific, Pittsburgh, PA, USA) with 20× objective. The proportion of SA-β-Gal-positive cells was calculated manually.

### 4.8. Click-iT™ EdU Alexa Fluor 488 (Cell Proliferation Assay)

The Click-iTTM EdU Alexa Fluor 488 Imaging kit (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) was used to assess cell proliferation. Cells were visualized using an ImageXpress Micro XL automated digital imaging and High Content imaging and Analysis system (Molecular Devices LLC, San Jose, CA, USA).

### 4.9. Immunofluorescence Analysis of Ki-67

Cells (at a concentration of 2 × 10³ cells/0.05 cm²) were seeded in a 384-well plate for 24 h. Then, cells were washed briefly in 1X PBS (pH 7.4) and fixed with 4% formaldehyde for 15 min, followed by 3 rinses in 1X PBS (pH 7.4). After blocking cells with 6% BSA (bovine serum albumin) in 1X PBS (pH 7.4) for 1 h at room temperature, cells were incubated with mouse monoclonal Ki-67 antibody (5 µg/mL, clone Ki-S5, Sigma-Aldrich, Darmstadt, Germany) diluted in 1X PBS with 1% BSA and 0.3% TritonX-100 for 1 h at room temperature. After 3 rinses in PBS, cells were incubated for 1 h at room temperature with Alexa Fluor 555 goat Anti-mouse secondary antibody (1:500, Merck-Millipore, Burlington, VT, USA) diluted in 1X PBS with 1% BSA and 0.3% Triton X-100. Nuclei were counterstained with Hoechst 33342 Solution (dilution 6 µg/mL, Thermo Scientific, Rockford, IL, USA). Cells were imaged and inner integrated fluorescence intensities of cells were calculated using the ImageXpress XL fluorescence microscopy (Molecular Devices LLC, San Jose, CA, USA).

### 4.10. Conditioned Medium Experiment

U87H and U87L cells were cultured in T25 flasks with 2 × 10⁶ cells in each and incubated at 37 °C and 5% CO₂. The conditioned medium from each flask was collected on the 4th day of incubation and centrifuged at 3000× g for 10 min; then, without collecting any debris from the bottom of the tubes, the conditioned medium from each flask was filtered through 0.22 mm filter and diluted in 1:4 ratio with fresh DMEM medium. U87L cells were later cultured in 6 repeats with the conditioned medium from U87H cells and 6 repeats with the conditioned medium from U87L cells into 96-well plate with seeding density of 3125 cell/cm². After 3 days of incubation SA-β-Gal assay was performed.
4.11. Statistical Analysis

Statistical data processing was carried out using statistical software GraphPad Prism 9.02.161 (GraphPad Software, San Diego, CA, USA) and EXCEL 2010 Software (Microsoft, Redmond, WA, USA). Data presented as means ± SEM. Significance levels are marked with asterisks: \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001, \*\*\*\* *p* < 0.0001.

**Author Contributions:** Conceptualization, S.L.; methodology, S.L. and A.N.O.; formal analysis, L.A. and Z.N.; irradiation, clonogenic tests, AlamarBlue test, EdU test and ki-67 test, L.A.; MGCCs test and SA-β-Gal test, L.A. and Z.N.; conditioned medium experiment, Z.N.; visualization, L.A. and Z.N.; writing—original draft preparation, L.A.; writing—review and editing, S.L., M.P. and A.N.O.; supervision, S.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** The studies were supported by Priority 2030 Strategic Academic Leadership Program project # 075-02-2021-1316.

**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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<figure><img src="image_77.png" /></figure>

Article

Clustered DNA Damage Patterns after Proton Therapy Beam
Irradiation Using Plasmid DNA

Maria P. Souli 1,2,✉, Zacharenia Nikitaki 1,2,✉, Monika Puchalska 1, Kateřina Pachnerová Brabcová 3,✉,
Ellas Spyratou 4,✉, Panagiotis Kote 2, Efstathios P. Efstathopoulos 4,✉, Megumi Hada 5,✉,
Alexandros G. Georgakilas 2,*,✉ and Lembit Sihver 1,3,*

<figure><img src="image_78.png" /></figure>

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updates

**Citation:** Souli, M.P.; Nikitaki, Z.; Puchalska, M.; Brabcová, K.P.; Spyratou, E.; Kote, P.; Efstathopoulos, E.P.; Hada, M.; Georgakilas, A.G.; Sihver, L. Clustered DNA Damage Patterns after Proton Therapy Beam Irradiation Using Plasmid DNA. *Int. J. Mol. Sci.* **2022**, *23*, 15606. https://doi.org/10.3390/ijms232415606

Academic Editor: François Chevalier

Received: 13 October 2022

Accepted: 6 December 2022

Published: 9 December 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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**Copyright:** © 2022 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:** Modeling ionizing radiation interaction with biological matter is a major scientific challenge, especially for protons that are nowadays widely used in cancer treatment. That presupposes a sound understanding of the mechanisms that take place from the early events of the induction of DNA damage. Herein, we present results of irradiation-induced complex DNA damage measurements using plasmid pBR322 along a typical Proton Treatment Plan at the MedAustron proton and carbon beam therapy facility (energy 137–198 MeV and Linear Energy Transfer (LET) range 1–9 keV/µm), by means of Agarose Gel Electrophoresis and DNA fragmentation using Atomic Force Microscopy (AFM). The induction rate $Mbp^{-1} Gy^{-1}$ for each type of damage, single strand breaks (SSBs), double-strand breaks (DSBs), base lesions and non-DSB clusters was measured after irradiations in solutions with varying scavenging capacity containing 2-amino-2-(hydroxymethyl)propane-1,3-diol (Tris) and coumarin-3-carboxylic acid (C3CA) as scavengers. Our combined results reveal the determining role of LET and Reactive Oxygen Species (ROS) in DNA fragmentation. Furthermore, AFM used to measure apparent DNA lengths provided us with insights into the role of increasing LET in the induction of highly complex DNA damage.

**Keywords:** proton therapy beam; clustered DNA damage; linear energy transfer (LET); Agarose Gel Electrophoresis (AGE); Atomic Force Microscopy (AFM); damage biomarkers; scavenging capacity; biodosimetry

# 1. Introduction

The radiobiological and physical advantages of highly energetic proton beam therapy result in a ground-gaining field over several types of photon radiotherapy, with many proton treatment facilities—in operation or under construction—around the world. Proton beams transverse biological matter depositing a small amount of energy along the track with a low entrance dose but releasing most of their energy just before they stop at a well-defined space range called Bragg Peak. At the distal fall-off of this peak, the energy deposition stops rapidly. This property is employed in treatment planning systems to design different beam combinations that produce wider peaks, called Spread-Out Bragg Peaks (SOBP), with the desired geometrical characteristics of the tumor volume to be treated. This allows the irradiation of cancers with complicated volumes and/or close to radiosensitive organs while minimizing normal tissue complications and dose to organs at risk.

<footnote n="1">1 Atominstitut, Technische Universität Wien, 1020 Vienna, Austria</footnote>

<footnote n="2">2 DNA Damage Laboratory, Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens, 15780 Athens, Greece</footnote>

<footnote n="3">3 Nuclear Physics Institute, Czech Academy of Sciences, Na Truhlářce 39/64, 180 86 Prague, Czech Republic</footnote>

<footnote n="4">4 2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, 11517 Athens, Greece</footnote>

<footnote n="5">5 Radiation Institute for Science & Engineering, Prairie View A&M University, Prairie View, TX 77446, USA</footnote>

<footnote>* Correspondence: alexg@mail.ntua.gr (A.G.G.); lembit.sihver@tuwien.ac.at (L.S.)</footnote>
The excellent dose distribution is the utmost asset of proton beam therapy compared to photon-based modalities, with relative biological effectiveness (RBE) values slightly higher than 1 (1.1–1.4) [1]. For many tumor types, this can reduce radiation-induced long- and short-term side effects in the patients. This is important, especially in reducing the risks of secondary cancer in pediatric cancer treatment.

The most critical target for radiation-induced damage inside a cell is DNA. Ionizing radiation (IR) is known to cause many different lesions in the DNA molecule: single-strand breaks (SSB), double-strand breaks (DSB), base oxidations, abasic sites and DNA protein crosslinks [2]. When these lesions are not randomly distributed along the DNA helix within the cell nucleus volume but are located within an area of 10–20 base pairs of DNA length (few nm), it is defined as complex or clustered DNA damage, which is more complicated and difficult to repair than SSB. These clustered lesions are considered to be responsible for cell death and mutations [3,4]. The DNA repair efficiency in such cases depends on the location, types and number of lesions accumulated in close proximity [5,6]. Although clustered damages are linked to higher cell lethality and mutagenic potential [7], the stochastic formation perplexes its investigation.

Results in experimental radiobiology underline the direct relationship between clus-
tered DNA damage and the interactions of IR with biological matter, especially the ion-
ization cascades created along the tracks inside the target. Linear Energy Transfer (LET)-
oriented studies shows, in most cases, an increased amount of clustered damage with
increasing LET, leading to increased DNA fragmentation [8–13]. Monte Carlo simulations
and multiscale mathematical approaches also agree with these results and suggest that LET
(or, more exactly, the ionization density) plays a major role in determining the biological
effects [6,14–16]. Therefore, there is a great need for DNA damage biomarkers for a better
understanding of the normal tissue damage in proton and particle therapy beams and a
deeper understanding of the mechanisms leading to either cell death or other effects [17].
RBE greater than unity is generally accepted to reflect the increased complexity of DNA
damage induced by charged particles [1,18]. Several published studies underline the im-
portance of DNA damage experiments using a variety of biological systems (plasmids,
mammalian DNA and cells) to help us better understand the intriguing biological responses
triggered by particles like protons or carbons [19].

The energy of the IR can either be deposited on the DNA macromolecule or the
aqueous environment that surrounds DNA. As a result, DNA damage may occur either
due to direct ionization or excitation of the molecule or due to indirect interaction with
energetic electrons and products like Reactive Oxygen Species (ROS), created by radiolysis
of water, which in their turn react directly/indirectly with the DNA [20,21]. This oxidative
environment enhances the probability of induction of non-DSB clusters, often called OCDLs
(Oxidative Clustered DNA Lesions) [22]. By adding scavengers in the aqueous environment
before irradiation, the production of some of the reactants is eliminated, blocking the
subsequent chain reaction and deactivating ROS. The type and the induction rate of DNA
damage also depend on the free radical generation, scavenger concentration and DNA
characteristics [20,23]. In the presence of radiation, the probability of radiolysis is quite
high since water is the most abundant cell component.

The present work is a bottom-up approach to studying DNA damage, primarily
induced by proton therapy beams, by employing a system of plasmid DNA in an aqueous
solution. This is a simplified model, excluding cell response factors and when irradiated,
it becomes a radiation damage detector. DNA molecules of full and known length in
supercoiled (SC) form are vitiated by irradiation to a different extent according to radiation
parameters and turn to circular (C), linear (L) and fragmented (F) forms. These forms
can be detected by rapid electrophoretic methods, easily quantified and translated into
a number of strand breaks. On the contrary, the number of short fragments of DNA is
more arduous to define and leads to an apparent complex damage decrease, probably
due to underestimation. The number of short fragments can either be estimated through
mathematical models or by employing more radical molecule visualization methods. The
first method used in this study was Agarose Gel Electrophoresis (AGE) combined with the Cowan Model, a “traditional” estimation created to describe plasmid forms transitions and DNA breaks formation, while a second supplementary method used Atomic Force Microscopy (AFM), which could be a powerful but demanding method to detect fragments down to 20 nm long (60 bps) [24–26].

Indirect damage through free radicals has been investigated by the addition of Tris and C3CA ROS-scavengers in the initial plasmid solution before irradiation as a radioprotectant. Tris is a common buffer scavenging solution that generally protects from DNA denaturation and free radical attack. C3CA is a coumarin derivative, and coumarins show high biological activity and low toxicity and are commonly used components in cancer treatment (prostate and renal cancer and leukemia) since they have the ability to counteract the side effects of radiotherapy [27].

**2. Results and Discussion**

**2.1. AGE**

The DNA electrophoresis adaptation in this study reveals an easily identified transition between SC, C and L forms of DNA which follows the dose increment and increased fragmentation (Figure 1a). In general, one expects that as the dose increases, the intact SC form is dramatically reduced, i.e., within the first 10 Gy. Of course, this phenomenon is also dependent on the scavenging capacity of the solution, plasmid type and water content, radiation quality and energies of the particles [28]. Simultaneously, the increasing dose of IR produces more breaks recorded as C and L bands (top and middle bands equivalently inside the gel). C is dominant for the first 10 Gy, while the linear DNA production rate (DSB formation) increases after the saturation point of the circular (Figure 1b). For doses higher than 10 Gy, the presence of the SC form is less than 1% and what we detect is the further breakage of C and L plasmid, producing gradually smaller fragments, leading to the formation of smear in the Agarose Gel Electrophoresis (AGE) gels.

<figure><img src="image_80.png" /><figcaption>**Figure 1.** Electrophoretic plasmid analysis: (a) gel image of plasmid form transition for 10 different doses from 0 to 50 Gy with DNA ladder also included (right column). The original image has been slightly enhanced by increasing intensity in order to reveal low-intensity bands (small fragments) but not altered in other editing ways; SC, C and L are separated as expected due to their different DNA molecule mobility in the field. The image presented was oversaturated in order to visualize the fragments (smear in the last lanes). (b) Three plasmid forms transition with increasing dose as quantified according to gel band intensity.</figcaption></figure>

The above pattern is also followed for samples containing the ROS radioprotectants (scavengers) Tris and C3CA. As shown in Figure 2, an increase in scavengers’ concentration results in an overall decrease in SSB formation (which is mainly due to ROS attack). Figure 2a presents proton (entrance)-induced damage detected as the decrease of SC fraction with a dose for different Tris scavenging capacities, from no scavenging (10⁵ s⁻¹ of residual Tris) to 10⁸ s⁻¹, revealing radioprotection of the plasmid integrity up to 90%.
This also proves that a significant amount of the DNA damage is not caused by the initial particle-target interactions, as the most amount of breaks on SC is caused by water radiolysis products. In Figure 2b, the SSB Mbp⁻¹ Gy⁻¹ versus scavenging capacity for Tris and C3CA for protons 198 MeV at the entrance of the beam proves that both scavengers protect DNA from ROS-mediated fragmentation in a concentration-dependent manner from 55% to 98%.

<table><caption>**Table 1.** Irradiation parameters along the therapeutic proton SOBP.</caption><thead><tr><td>Irradiation Position</td><td>Depth in PMMA (cm)</td><td>LET (keV/µm)</td><td>Energy Range (MeV)</td></tr></thead><tbody><tr><td>A—beam entrance</td><td>2</td><td>1</td><td>198</td></tr><tr><td>B—plateau of SOBP</td><td>15</td><td>3</td><td>137–167</td></tr><tr><td>C—tail of SOBP</td><td>16.8</td><td>9</td><td>137–167</td></tr></tbody></table>

<figure><img src="image_81.png" /></figure>

**Figure 2.** Proton (p) and X-rays-induced DNA damage. (a) Proton (entrance)-induced damage revealed as the decrease of SC plasmid with dose for Tris scavenging capacity ranging from no scavenging (10⁵ s⁻¹ of residual Tris) to 10⁸ s⁻¹, revealing the radioprotectant shielding of the plasmid integrity (up to 90%) the highest Tris concentration. (b) SSB Mbp⁻¹ Gy⁻¹ versus scavenging capacity for Tris and C3CA for 198 MeV protons at the entrance of the beam proves concentration-dependent manner. (c) Average number of SSB and single base lesions produced along the Proton Treatment Plan or X-rays, respectively. (d) Average number of DSB and non-DSB clustered damage produced along the Proton Treatment Plan or X-rays. The positions are the entrance of the beam, the middle of the SOBP plateau (midSOBP) and SOBP fall-off, as seen in Figure 3 and Table 1.

The different positions along the treatment plan (Figure 3), and the subsequent relatively slight difference in LET values (Table 1), are also presented in Figure 2. Both strand breaks and base lesions (breaks deliberately created during post-irradiation treatment by restriction enzymes on sites of oxidized purines and pyrimidines) for protons and X-rays are grouped in SSB (Figure 2c) and DSB (Figure 2d) histograms. SSB is accompanied by a number of single base lesions (Figure 2c) that are 2.7 and 1.1 times the SSB value at beam entrance and SOBP fall-off. This no remarkably different pattern recorded in SSB along the beamline is overturned at the middle of the SOBP position, with base lesions being 0.5 times the SSB. Furthermore, SSB is 29–88 times more than DSB in each case, with the difference
between entrance and SOBP within the error range for both SSB and DSB, probably due to similar LET values. Specifically, the mean rates of damage induction at the entrance of the proton beam are:

<figure><img src="image_82.png" /><figcaption>**Figure 3.** General treatment plan dose distribution: the % dose (dashed line) deposited when irradiating a volume of a hypothetical tumor of 4 cm thickness and approximately 13 cm under the skin (grey tumor area), as exported by TPS and the equivalent LET change over depth in water (solid line). The three positions of DNA irradiation (×) along the treatment plan are also marked: the beam entrance (A), the middle of SOBP plateau (B) and the SOBP fall-off (C).</figcaption></figure>

101.101 ± 16.868 SSB Mbp⁻¹Gy⁻¹, 1.914 ± 0.247 DSB Mbp⁻¹Gy⁻¹, 275.852 ± 114.295 Base Lesions Mbp⁻¹Gy⁻¹, 10.908 ± 1.778 non-DSB Clusters Mbp⁻¹Gy⁻¹, and for the irradiation with X-rays at the same position we record 89.559 ± 4.490 SSB Mbp⁻¹Gy⁻¹, 3.147 ± 0.141 DSB Mbp⁻¹Gy⁻¹, 191.102 ± 10.867 Base Lesions Mbp⁻¹Gy⁻¹, 14.723 ± 0.856 non-DSB Clusters Mbp⁻¹Gy⁻¹. Figure 2d shows that clustered DNA damages produced by X-rays outnumber those created by proton beams at the entrance. This may originate from the very low LET for the protons in the entrance that is similar to that of X-rays (~1 keV/µm); therefore, no major differences are expected in general. Furthermore, the contribution of non-DSB oxidative damages in the clusters measured in the case of X-rays is expected to be high, translated into higher levels of clustered damage. Interestingly enough, previous studies [29–31] support the prevalence of oxidized base damages in the case of low-LET radiations such as X-rays. Considering that a percentage of these non-DSB lesions may almost instantly be converted to DSBs through the lyase/endonuclease enzymatic activity used in the present assays, then this may lead to higher levels of clusters as measured in the electrophoresis. Although clustering induced by X-rays appears to numerically exceed clustering produced by protons at the entrance of the beam, proton radiation is more efficient than X-rays, as evidenced by the ratio of non-DSB clusters to DSB for X-rays (4.7) being higher than that for protons (5.7).

At the middle of the SOBP plateau, the mean damage induction rate recorded is 96.012 ± 27.211 SSB Mbp⁻¹Gy⁻¹, 1.529 ± 0.169 DSB Mbp⁻¹Gy⁻¹, 52.085 ± 2.365 Base Lesions Mbp⁻¹Gy⁻¹, 10.415 ± 1.666 non-DSB Clusters Mbp⁻¹Gy⁻¹. At the fall-off of SOBP, where we expect to have higher LET values, the recorded damages were not greater as estimated by simulations for increased LET values but were not always verified by experimental studies [9]. This may have two interpretations. Considering the steep slope shift in LET and the dose distribution at the end of the beam trajectory (Figure 3), where LET increases abruptly but not critically, lower levels of DNA damage is an astounding proof of the successful use of protons for patient treatment since the healthy tissue area in very close proximity (within a few millimeters) of the tumor is only mildly stressed. Especially the low DSB and clustered damage levels, which are potentially lethal for a cell, imply a relatively safe cell environment. On the other hand, the apparent lower level of DSB and clustered damage recorded at the SOBP fall-off might be a result of
underestimation of the damage due to the highly complex and fragmented DNA molecules, as also arises by AFM results. This is probably due to the limitations of the method since, in agarose gel electrophoresis, shorter DNA fragments may escape due to their higher mobility. The values of the mean damage induction rate recorded at the SOBP fall-off are 51.069 ± 6.923 SSB Mbp⁻¹Gy⁻¹, 0.579 ± 0.060 DSB Mbp⁻¹Gy⁻¹, 54.453 ± 6.350 Base Lesions Mbp⁻¹Gy⁻¹, 3.255 ± 0.092 non-DSB Clusters Mbp⁻¹Gy⁻¹.

Experimental results for different scavenging conditions are presented in Figure 4 and for all irradiation positions along the Proton Treatment Plan: proton beam entrance (LET = 1 keV/µm), middle of SOBP plateau (LET = 3 keV/µm) and SOBP fall-off (LET = 9 keV/µm), for Tris and C3CA radioprotectants in all three different values of scavenging capacity (10⁶ s⁻¹, 10⁷ s⁻¹, 10⁸ s⁻¹) and 10⁵ s⁻¹ of residual TRIS (no scavenger). Overall, we detect a decrease in the induction of proton-induced DNA damage with increasing scavenging capacity of the solutions. Comparing reduction in damage levels, the general trend is that with increasing LET (from the entrance to mid-SOBP and fall-off), the dependency on the antioxidant concentration is reduced.

Figure 5a–d shows our experimental values together with the comparable literature data on the plasmid model. The numerical values of the present radiation conditions and the comparable literature data of the plasmid model can be found in Table 1 (Appendix A), accompanied by all critical radiation and sample parameters. For example, for DSBs in, the entrance reduction between ‘no scavenger’ to C3CA is ~76% falling to ~65% for the SOBP. Similarly, for non-DSB (base) clusters, from ~75% reduction (entrance), we go to ~60% for the SOBP region.

<figure><img src="image_83.png" /><figcaption>**Figure 4.** *Cont.*</figcaption></figure>
<figure><img src="image_84.png" /><figcaption>**Figure 4.** Proton-induced DNA damage: (a) Average number of SSB (SSB Mbp⁻¹ Gy⁻¹), (b) DSB (DSB Mbp⁻¹ Gy⁻¹), (c) Base Lesion and (d) non-DSB Clustered DNA damage induction rate versus increasing the scavenging capacity of Tris and C3CA scavengers (from 10⁻⁶ to 10⁻⁸ s⁻¹) for the three irradiation positions: the entrance of the beam (entrance), the middle of the SOBP plateau (midSOBP) and SOBP fall-off (fall-off).</figcaption></figure>

<figure><img src="image_85.png" /><figcaption>**Figure 5.** *Cont.*</figcaption></figure>
<figure><img src="image_86.png" /><figcaption>(c)</figcaption></figure>

<figure><img src="image_87.png" /><figcaption>(d)</figcaption></figure>

**Figure 5.** Proton (p)-induced damage yield (Mbp⁻¹ Gy⁻¹) versus scavenging capacity (s⁻¹) as calculated in the present study for Tris and C3CA (lines are used as guides to the eyes) and literature values from studies using plasmid models with comparable proton energies and solution scavenging capacity. (a) SSB, (b) DSB, (c) Base Lesion, (d) Clustered DNA damage induction rates result from a variety of irradiation conditions, e.g., plasmid in solution or dried, different plasmid concentration and proton energy, details that can be found in Table 1. (see Refs. [28,32–34]).

In Figure 5, we have included cumulative data from different studies using protons of different energies and under different scavenging capacities. Closed circles correspond to the data from the present study, which are in good agreement with the literature data. One general comment is that when reviewing the data from other studies (Table 1), it can be seen that there is a great variety of values and, in some cases, disharmony between our experimental output and the others’ data. Of course, as already explained above, these type of irradiation experiments depends on several physical and chemical parameters that may change the overall interaction of protons with DNA. A comparison with results within the scavenging range of the present study (Figure 5a–d) confirms the strong DNA damages
elimination by scavengers depicted in Figure 4a–d. Although it is generally believed that 60–70% of the biological effects of low LET IR in mammalian cells are caused by indirect action [35,36], plasmid studies show larger proportions of indirect damage through more efficient scavenging. Plasmid studies testing scavenging high LET carbon ion-induced damage also report results implying 96% of the total SSB amount is attributed to indirect damage [37,38]. The aqueous nature of the plasmid solutions probably enhances such findings due to the high radiolysis probability.

By using the mean rate of DSB induction for protons and dividing by the DSB induction rate for X-rays at the entrance of the beam, we estimated an apparent RBE value of 0.61 at the entrance, 0.49 in the middle of the SOBP plateau and 0.18 at the SOBP fall-off. The reported [39] average RBE values for cell survival are 1.1 at the entrance, 1.15 in the center, 1.35 at the distal edge and up to 1.7 in the distal fall-off of the SOBP. These values are calculated with clonogenic cell survival as an endpoint. It is generally accepted that endpoints other than clonogenic survival produce such diverse results that do not allow to avoid the general statement that the RBE is, on average, in line with a value of ~1.1 [40]. RBE values of the present study are based on a simple DNA system of plasmid in an aqueous solution, which excludes the cell response and their repair mechanisms. This model serves well when the focus is on damage (excluding cell response and repair), and the presented RBE values should be considered as damage-calculated. Comparison with the literature values from cell survival would be unfair, first due to the different complexity of the systems and calculation methods, but also due to the fact that the generally accepted RBE values are under question, given the diversity of the results from different irradiation conditions like cell lines, dose and LET.

## 2.2. AFM

The results from the AFM length measurements are organized into histograms presenting length distributions in 50-nm-wide bins in the range of 0 to 1550 nm. The relative frequency of calibrated-from-pixel-to-length plasmid sizes was chosen to present and evaluate, and not show the apparent length, because of the variance in the number of evaluable molecules (N) on mica surfaces for each experimental condition. Figure 6 presents a typical topographic AFM image of plasmid on mica (see more in Figure 1 in Appendix A) and the relative frequency distribution of the lengths of 0 Gy (control) and 10 Gy. The 0 Gy distribution shows the detection of tight-binding DNA conformations of total length mostly of ~200–300 nm, underestimating the length of the supercoiled fraction due to the adsorption of the 3D molecules on the 2D mica surface. On the other hand, 10 Gy distribution reveals the segmentation of the initially supercoiled plasmid into one-stranded unfolded DNA pieces by recording molecules along the whole distribution range.

With increasing dose (Figure 7), there is a shift to smaller plasmid lengths revealed as increased DNA fragmentation due to multiple breaks. The same trend seems to follow the LET increase, since even in the case of small increment as in our experiment (Figure 7a corresponds to proton beam entrance and LET = 1 keV/µm, while Figure 7b to SOBP fall-off plasmid position with LET = 9 keV/µm) the fragment distribution shifts to smaller linear recorded DNA forms.
<figure><img src="image_88.png" /><figcaption>**Figure 6.** Atomic Force Microscopy (AFM) measurements: The relative frequency distribution of apparent molecule lengths for control sample (0 Gy) and irradiated with 10 Gy (proton beams) together with AFM images of DNA molecules of different forms. A representative AFM image (5 µm × 5 µm) of plasmid pBR322 on freshly cleaved mica surface, revealing the DNA macromolecule conformations. Such images are used as input for length evaluation and spread-out full-length circular molecules are utilized as calibration rulers for pixel-to-nm conversion. The length of the super-twisted supercoiled fraction is underestimated due to its adsorption on the mica surface. As a result, the apparent length of control plasmid is recorded smaller, while plasmid irradiated with plasmid is distributed along the whole range of lengths.</figcaption></figure>

<figure><img src="image_89.png" /><figcaption>**Figure 7.** Relative frequency distributions of apparent molecule lengths measured using AFM for plasmid pBR322 irradiated with doses of 20, 30 and 50 Gy at (a) the entrance of proton beam (LET = 1 keV/µm) and (b) SOBP fall-off (LET = 9 keV/µm).</figcaption></figure>
### 3. Materials and Methods

#### 3.1. *Sample Preparation*

Plasmid pBR322, a vector of 4361 base pairs, dissolved in 10 mM Tris-Hcl, 1 mM EDTA (New England BioLabs Inc., Ipswich, MA, USA), was purified from salts via dialysis in ultrapure water (Pur-A-Lyzer dialysis kit from Sigma-Aldrich, St. Louis, MO, USA). Our study included two types of scavengers: coumarin-3-carboxylic acid (C3CA) (a water-soluble coumarin derivative) and 2-amino-2-(hydroxymethyl)propane-1,3-diol (Tris) with hydroxyl radicals (●OH) reaction rate constant $k_{C3CA} = 6.8 \times 10^9 M^{-1} s^{-1}$ [41] and $k_{Tris} = 1.5 \times 10^9 M^{-1} s^{-1}$ [42]. Three forms of plasmid samples were prepared: plasmid without scavenger, plasmid with C3CA and plasmid with Tris in total scavenging capacity of $10^6 s^{-1}$, $10^7 s^{-1}$ and $10^8 s^{-1}$ for each compound. Scavenging capacity equals the product $k \times S$, where S is the scavenger concentration. Every sample contained 10 ng/µL of the plasmid in 20 mM potassium phosphate buffer, pH 7, ultrapure water and scavenger solution in a total volume of 160 µL irradiated in a polypropylene microtube (0.5 mL) with 0.85-mm-thick walls.

#### 3.2. *Irradiation and Dosimetry*

Samples were irradiated at MedAustron Ion Beam Therapy Center in Wiener Neustadt, Austria, with doses up to 50 Gy at room temperature and kept on ice before and after irradiation.

##### 3.2.1. Set-Up

The set-up that held all sample tubes consisted of a Teflon frame holder that allowed positioning of a removable plastic base at different heights. This frame was always placed vertically in the metal base of the solid water RW3 slab phantom, which was also used for a standard dosimetric quality assurance procedure by means of UNIDOSwebline with the ionization chamber ROOS (PTW, Freiburg, Germany).

##### 3.2.2. Proton Irradiation

Treatment planning and dose calculations were performed with the RayStation TPS V5.99 (RaySearch, Stockholm, Sweden) for a hypothetical scenario of an existing tumor, 4 cm thick and 13 cm behind the skin. The set-up was placed on a robotic table (KUKA robot, Reutlingen BEC GmbH, Pfullingen, Germany), and then the table was placed in front of the beam, in a position that was calculated during the treatment planning. The proton beams were of energy range 137–198 MeV with the corresponding LET values 1–10 keV/µm along the clinical SOBP (Figure 3), a LET range that is important to cell killing [43]. The samples were irradiated in order of minutes under room temperature, and they were otherwise kept on ice. Doses of 0, 1, 2, 4, 8, 10, 15, 20, 30 and 50 Gy were delivered in different positions along the proton treatment plan, and an ionization chamber was used for dose monitoring. The chosen positions were achieved by interfering with polymethyl methacrylate (PMMA) plates of calculated thicknesses in front of the samples (Table 1).

##### 3.2.3. X-rays

A YXLON X-ray unit (Yxon International X-ray GmbH, Hamburg, Germany) was employed for plasmid irradiation. The X-ray tube was adjusted to 200 kV, 20 mA, and the dose rate was found to be constant at 1.25 Gy/min. Since the source tube was horizontal and the ROOS chamber set-up prerequisites 1 mm PMMA plate to position the plane parallel chamber vertically to the irradiation axis, all samples were exposed and taped on the back side of that PMMA plate and kept on ice before and after irradiation.

### 3.3. *Post-Irradiation Treatment—DNA Damage Detection*

#### 3.3.1. Agarose Gel Electrophoresis in Tris-Acetate-EDTA (TAE) Buffer

Three subsamples of 5 µL, derived from each sample, were incubated at 37 °C for 1 h without or with enzymes: Formamidopyrimidine DNA glycosylase (Fpg) or Endonuclease III (Nth) in specific complementary reaction buffers (New England BioLabs Inc.).
Both enzymes are E. coli base excision repair enzymes and catalyze cleavage of oxidized nitrogenous bases. Fpg catalyzes lesions in purines, while Nth in pyrimidines and, due to associated lyase activity, they convert both existing and resulting abasic sites and oxidized bases into DNA strand breaks [44]. The optimal enzyme concentration was found by titration of each enzyme to succeed maximum specific along with minimum non-specific cutting activity and by comparing irradiated with non-irradiated samples treated with different enzyme concentrations. Enzymatic reactions were quenched by adding 2 µL of DNA loading dye (MassRuler, ThermoFisher, Waltham, MA, USA) containing bromophenol blue, 3.3 mM Tris-HCl and 11 mM EDTA. The different forms of plasmid DNA were separated and then visualized by employing agarose gel electrophoresis on 1% agarose gel stained with fluorescent dye SYBR Green I (Sigma-Aldrich) under electric field of 100 V in 0.5 × TAE.

At this stage and under the presence of single- and double-strand breaks, plasmid DNA is separated into bands-fractions of different conformations: supercoiled (SC), circular (C) and linear (L) and fragments (F), with the last one being non-detectable due to method limitations (Figure 8). These patterns were visualized with green filter on an MYECL Imager, and band analysis was performed with the image processing program MYImageAnalysis™ v2.0 Software (Thermo Scientific, Waltham, MA, USA). The full-length molecule bands of SC, R and L were identified and integrated. The attempt to include F in the analysis was not always possible, as shorter-than-linear plasmid lengths have greater mobility in the electric field, appearing as a smear under L and SC bands that were not always countable. Averaged SC, C and L relative fractions are quantified by gel luminosity and translated into DNA breaks using Cowan model [45,46] (Equations in Figure 8).

<figure><img src="image_90.png" /><figcaption>**Figure 8.** The electrophoresis concept: Each plasmid sample is added in a well (cathode side), electric field is applied at the gel edges and under the electric potential difference, the negatively charged DNA migrates to the anode side through the gel net. Due to the net-like agarose gel, different DNA forms are separated according to the size of each form that created three clearly distinguishable bands. Supercoiled (SC) plasmid (small-sized twisted DNA) is moving easier and faster, crossing a larger pathway inside the gel and appearing as a more distant band. The large circular (C) and linear (L) molecules have lower mobility than SC, and they are trapped in areas closer to the well. Therefore, the unfolded C appears as higher band in the gel, and L forms a band in between. Additionally, smaller DNA fragments (F) of higher mobility appear as a smear inside the gel. SC is the compact initial DNA with no break; C is caused by the cleavage of one DNA strand (SSB) and L by the cleavage of two strands (DSB). F results from further nicking cannot be safely measured via AGE and is excluded from present analysis. By defining the amount of SC, C and L and employing Cowan model [45] (equations above), we translate it into number of SSB and DSB.</figcaption></figure>
The slope of SSB and DSB vs. dose plots converts results into the useful quantity of G-values (breaks per Gy per Mbp). To improve the statistics, AGE was performed twice for each irradiation condition, and image analysis was performed twice for each gel. The irradiation was only repeated for the middle of SOBP. Results are the mean values accompanied by the error of the mean.

Base lesions and non-DSB clustered damage are calculated via the difference between enzymatic cleavage and strand breaks. Base lesions correspond to the excessive SSB, and non-DSB clustered damage is the excessive DSB that is produced by Nth and Fpg enzymes.

### 3.3.2. AFM Analysis

Samples were also analyzed with an atomic force microscope. A part of the dialyzed (or/and also irradiated) plasmid sample was diluted to 1 ng/µL pBR322 in 1 mM MgCl₂. Mg²⁺ cations of such a concentration stabilize double-stranded DNA, prevents complete denaturation of the DNA and enhances adsorption (via a weak electrostatic attachment) of the molecule onto mica substrate [28,47]. AFM images (Figure 1) were acquired with Nanoscope diInnova device (Veeco Metrology, Santa Barbara, CA, USA) with an Innova scanner possessing a maximum range of 100 µm × 100 µm in tapping mode. Antimony (n) doped silicon tips with a nominal constant 3 N/m and 42 N/m (Bruker, Billerica, MA, USA) were used to acquire several high-resolution DNA topographies of 5 × 5 µm² at a scanning speed 1 Hz and with lateral resolution 512 × 512 pixels. The images were processed with the AFM apparatus software (SPMLab 5.01, Sunnyvale, CA, USA), they were flattened, and a histogram equalization was applied for the background noise subtraction and image contrast increase.

Images were input into the semi-automatic algorithm "lemeDNA" (Length Measurement of DNA) [48]. This algorithm uses 8-connected Freeman chain code to compute the pixel lengths and estimate the length of each molecule in pixels. Since the length of an intact plasmid pBR322 molecule is known to be 4361 base pairs, with each base pair 0.34 nm long (X-ray crystallography studies), calibration from pixels to nm is feasible and arbitrary fragments of DNA can be organized in length distributions.

## 4. Conclusions

The damage induction rate that follows the increasing capacity was found to decrease, underlining dominant indirect effects and the leading role of ROS in proton irradiation treatment. Enzyme analysis reveals that base lesions and non-DSB clusters are increased compared to SSB and DSB, respectively, with base lesions being the leading type of damage. Different positioning along the proton treatment plan shows no remarkable difference between DNA damage recorded at the beam entrance and at the middle of the SOBP position, probably due to very similar LET values. The fact that there is no higher damage induction rate at the distal fall-off of SOBP, as hypothesized for increasing LET, is raising the question about possible underestimation of highly complex damage and if there is multifragmented DNA that is not detectable with AGE and/or other types of interactions between DNA and protons that we do not fully comprehend.

Comparison with the literature suggests a great variety of results since one finds experiments with different beam energy, irradiation conditions and set-ups. Furthermore, although there are studies that invoke the plasmid model, the systems are finally different because there is strong dependence on plasmid type and geometry, scavenging capacity and plasmid hydration level. All these parameters blend together, complicating result interpretation.

AFM provides impressive images of DNA conformations and visualizes fragments as short as 42 bp (equal to 14 nm). The present analysis with the LemeDNA algorithm qualitatively records the shift of the relative frequency distribution of the apparent DNA length towards shorter lengths following the dose increment. On the other hand, quantitatively, there is not enough to contribute since there is no discrimination between different DNA forms, and only the apparent size is recorded. In order to reproduce results comparable to
that of AGE, there is a need for an algorithm that also distinguishes and counts the SC and C and separates the L conformations into categories according to their measured length. This way, users will have the option to perform a similar but stronger analysis than this of traditional AGE.

Proton therapy-induced DNA damage in vitro studies employing biological models like plasmid DNA or cells using real therapeutic beams and exposure conditions are always challenging and quite limited. The cost of proton irradiations is high, and irradiation time is distributed on a priority basis, with patients being the first concern, with clinical research and applied and basic research activities following. At the same time, each ion facility is developed using different technologies (beam physical characteristics, dose delivery system, irradiation set-up, etc.), producing results that are not always repeatable from another beam facility. Therefore, non-clinical studies are difficult to perform and repeat in ion therapy facilities, with the available proton DNA damage data sourcing from the not plentiful literature of different parameters.

Consequently, the present study provides results from experiments performed in a cutting-edge ion therapy facility and analyzed with updated methods. The current results constitute a fresh input for early physical-chemical events of DNA damage induction. At the same time, this work strengthens the challenging attempt toward the modeling and deeper understanding of IR therapeutic modalities' effects on biological systems that may discharge research from demanding experiments in the future. Last but not least, DNA-based systems have been recently used as reliable dosimeters in therapy beam set-up. More specifically, recent independent studies on DNA double-strand breaks measurement were performed using a DNA dosimeter, consisting of magnetic streptavidin beads attached to a properly labeled four kbp DNA molecule suspended in phosphate-buffered saline (PBS) and utilized as a method of radiation measurements for therapeutic beams and high doses > 25 Gy where cellular systems are very difficult to be utilized [49]. Based on all the above, our results may also prove useful in the development of more accurate bio-dosimetry in proton or carbon-therapy treatment planning incorporating the biological signature of radiation and aid reduce damage to normal tissues and toxicity.

**Author Contributions:** Conceptualization, L.S. and A.G.G.; methodology, M.P.S., Z.N., M.P., K.P.B., and E.S.; formal analysis, M.P.S., Z.N., and E.S.; investigation, M.P.S., A.G.G., and L.S.; writing—original draft preparation, M.P.S. and A.G.G.; writing—review and editing, M.P.S., M.P., K.P.B., E.S., P.K., E.P.E., M.H., A.G.G., and L.S.; supervision, L.S. and A.G.G.; project administration, L.S.; funding acquisition, L.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by TU Wien, Austria and MedAustron, Wiener Neustadt, Austria and the project '21GRD02 BIOSPHERE', which has received funding from the European Partnership on Metrology, co-financed by the European Union's Horizon Europe Research and Innovation Programme and by the Participating States.

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** All data will be provided by corresponding authors upon logical request.

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

<table><caption>Table 1. IR (protons, ions and electromagnetic radiation) damage induction rate on plasmod systems: results from the present study and reported in the literature.</caption><thead><tr><th></th><th>Type Rad/Proton Energy (MeV)</th><th>LET (keV/μm)</th><th>Scavenger</th><th>Plasmid</th><th>Plasmid Concentration (ng/μL)</th><th>Scav. Capacity (s<sup>-1</sup>)</th><th>SSB Mbp<sup>-1</sup> Gy<sup>-1</sup></th><th>Error</th><th>DSB Mbp<sup>-1</sup> Gy<sup>-1</sup></th><th>Error</th><th>Base Lesions Mbp<sup>-1</sup> Gy<sup>-1</sup></th><th>Error</th><th>Non-DSB Clusters Mbp<sup>-1</sup> Gy<sup>-1</sup></th><th>Error</th></tr></thead><tbody><tr><td>this study</td><td>X-rays</td><td></td><td>no scav (residual TRIS)</td><td>pBR322 in solution</td><td>10</td><td>10<sup>5</sup></td><td>89.559</td><td>4.490</td><td>3.147</td><td>0.141</td><td>191.102</td><td>10.867</td><td>14.723</td><td>0.856</td></tr><tr><td></td><td></td><td></td><td>TRIS</td><td></td><td></td><td>10<sup>6</sup></td><td>30.232</td><td>1.094</td><td>0.532</td><td>0.215</td><td>65.596</td><td>3.163</td><td>3.919</td><td>0.836</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>10<sup>7</sup></td><td>4.551</td><td>0.746</td><td>0.103</td><td>0.010</td><td>18.656</td><td>3.415</td><td>0.631</td><td>0.036</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>10<sup>8</sup></td><td>1.135</td><td>0.300</td><td>0.108</td><td>0.077</td><td>4.654</td><td>1.005</td><td>0.263</td><td>0.026</td></tr><tr><td></td><td></td><td></td><td>C3CA</td><td></td><td></td><td>10<sup>6</sup></td><td>24.306</td><td>1.194</td><td>0.606</td><td>0.109</td><td>61.223</td><td>6.884</td><td>3.991</td><td>-0.054</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>10<sup>7</sup></td><td>4.921</td><td>0.108</td><td>0.117</td><td>0.011</td><td>9.562</td><td>0.111</td><td>0.726</td><td>0.037</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>10<sup>8</sup></td><td>1.370</td><td>0.054</td><td>0.121</td><td>0.077</td><td>2.139</td><td>0.133</td><td>0.137</td><td>0.032</td></tr><tr><td>this study</td><td>p 198 MeV</td><td>1</td><td>no scav (residual TRIS)</td><td>pBR322 in solution</td><td>10</td><td>10<sup>5</sup></td><td>101.101</td><td>16.868</td><td>1.914</td><td>0.247</td><td>275.852</td><td>114.295</td><td>10.908</td><td>1.778</td></tr><tr><td></td><td></td><td>1</td><td>TRIS</td><td></td><td></td><td>10<sup>6</sup></td><td>45.848</td><td>5.031</td><td>1.534</td><td>0.247</td><td>130.510</td><td>40.667</td><td>13.270</td><td>1.411</td></tr><tr><td></td><td></td><td>1</td><td></td><td></td><td></td><td>10<sup>7</sup></td><td>11.609</td><td>4.668</td><td>0.092</td><td>0.047</td><td>30.405</td><td>-0.222</td><td>0.426</td><td>-0.015</td></tr><tr><td></td><td></td><td>1</td><td></td><td></td><td></td><td>10<sup>8</sup></td><td>2.083</td><td>1.355</td><td>0.025</td><td>0.015</td><td>5.103</td><td>0.227</td><td>0.078</td><td>-0.011</td></tr><tr><td></td><td></td><td>1</td><td>C3CA</td><td></td><td></td><td>10<sup>6</sup></td><td>34.349</td><td>4.683</td><td>0.458</td><td>0.044</td><td>75.715</td><td>16.431</td><td>3.175</td><td>-0.042</td></tr><tr><td></td><td></td><td>1</td><td></td><td></td><td></td><td>10<sup>7</sup></td><td>9.434</td><td>1.499</td><td>0.163</td><td>0.022</td><td>32.678</td><td>8.270</td><td>0.658</td><td>0.023</td></tr><tr><td></td><td></td><td>1</td><td></td><td></td><td></td><td>10<sup>8</sup></td><td>4.141</td><td>0.861</td><td>0.041</td><td>0.014</td><td>10.709</td><td>3.961</td><td>0.052</td><td>-0.013</td></tr><tr><td>p 167-137 MeV</td><td>4</td><td>no scav (residual TRIS)</td><td>pBR322 in solution</td><td>10</td><td>10<sup>5</sup></td><td>96.012</td><td>27.211</td><td>1.529</td><td>0.169</td><td>52.085</td><td>2.365</td><td>10.415</td><td>1.666</td></tr><tr><td></td><td></td><td>4</td><td>TRIS</td><td></td><td></td><td>10<sup>6</sup></td><td>39.171</td><td>0.754</td><td>0.473</td><td>0.048</td><td>74.808</td><td>5.202</td><td>2.912</td><td>0.305</td></tr><tr><td></td><td></td><td>4</td><td></td><td></td><td></td><td>10<sup>7</sup></td><td>12.888</td><td>2.234</td><td>0.096</td><td>0.035</td><td>25.294</td><td>4.359</td><td>0.509</td><td>0.039</td></tr><tr><td></td><td></td><td>4</td><td></td><td></td><td></td><td>10<sup>8</sup></td><td>2.727</td><td>1.152</td><td>0.028</td><td>0.005</td><td>37.634</td><td>25.479</td><td>1.727</td><td>1.516</td></tr><tr><td></td><td></td><td>4</td><td>C3CA</td><td></td><td></td><td>10<sup>6</sup></td><td>37.170</td><td>3.826</td><td>0.490</td><td>0.107</td><td>63.820</td><td>-1.111</td><td>4.053</td><td>0.178</td></tr><tr><td></td><td></td><td>4</td><td></td><td></td><td></td><td>10<sup>7</sup></td><td>9.928</td><td>2.765</td><td>0.125</td><td>0.009</td><td>18.926</td><td>0.070</td><td>0.642</td><td>0.003</td></tr><tr><td></td><td></td><td>4</td><td></td><td></td><td></td><td>10<sup>8</sup></td><td>2.220</td><td>0.786</td><td>0.039</td><td>0.006</td><td>4.596</td><td>0.446</td><td>0.081</td><td>0.005</td></tr><tr><td>p 167-137 MeV</td><td>9</td><td>no scav (residual TRIS)</td><td>pBR322 in solution</td><td>10</td><td>10<sup>5</sup></td><td>51.069</td><td>6.923</td><td>0.579</td><td>0.060</td><td>54.453</td><td>6.350</td><td>3.255</td><td>0.092</td></tr><tr><td></td><td></td><td>9</td><td>TRIS</td><td></td><td></td><td>10<sup>6</sup></td><td>9.581</td><td>0.945</td><td>0.138</td><td>0.052</td><td>17.400</td><td>8.311</td><td>0.671</td><td>0.338</td></tr><tr><td></td><td></td><td>9</td><td></td><td></td><td></td><td>10<sup>7</sup></td><td>2.274</td><td>0.235</td><td>0.032</td><td>0.001</td><td>3.745</td><td>1.864</td><td>0.106</td><td>0.085</td></tr><tr><td></td><td></td><td>9</td><td></td><td></td><td></td><td>10<sup>8</sup></td><td>0.299</td><td>0.089</td><td>0.005</td><td>0.009</td><td>1.269</td><td>0.619</td><td>0.115</td><td>0.121</td></tr><tr><td></td><td></td><td>9</td><td>C3CA</td><td></td><td></td><td>10<sup>6</sup></td><td>11.545</td><td>2.456</td><td>0.172</td><td>0.036</td><td>12.770</td><td>5.628</td><td>0.716</td><td>0.481</td></tr><tr><td></td><td></td><td>9</td><td></td><td></td><td></td><td>10<sup>7</sup></td><td>3.085</td><td>0.691</td><td>0.055</td><td>0.004</td><td>4.010</td><td>1.940</td><td>0.157</td><td>1.495</td></tr><tr><td></td><td></td><td>9</td><td></td><td></td><td></td><td>10<sup>8</sup></td><td>0.717</td><td>0.237</td><td>0.032</td><td>0.016</td><td>0.867</td><td>0.253</td><td>0.009</td><td>0.018</td></tr><tr><td>p 30 MeV</td><td>1.9</td><td>TE buffer</td><td>pBR322 in solution</td><td></td><td></td><td>1.5 × 10<sup>3</sup></td><td>113.760</td><td>17.064</td><td>3.990</td><td></td><td>113.090</td><td></td><td>14.580</td><td></td></tr><tr><td></td><td></td><td></td><td>C3CA</td><td></td><td></td><td>6.8 × 10<sup>5</sup></td><td>24.790</td><td>3.718</td><td>1.930</td><td></td><td>18.020</td><td></td><td>1.540</td><td></td></tr><tr><td></td><td></td><td></td><td>C3CA</td><td></td><td></td><td>6.8 × 10<sup>6</sup></td><td>9.170</td><td>1.376</td><td>0.890</td><td></td><td>13.320</td><td></td><td>0.410</td><td></td></tr><tr><td></td><td></td><td></td><td>C3CA</td><td></td><td></td><td>6.8 × 10<sup>7</sup></td><td>1.220</td><td>0.182</td><td>0.760</td><td></td><td>3.390</td><td></td><td>0.000</td><td></td></tr><tr><td>Sui 2013 [33]</td><td>p 15 MeV</td><td>3.6</td><td>TRIS-HCl</td><td>pUC19 in solution</td><td>100</td><td>3 × 10<sup>8</sup></td><td>9.950</td><td>0.790</td><td>0.064</td><td>0.009</td><td>16.560</td><td>1.400</td><td>0.100</td><td>0.016</td></tr></tbody></table>
<table><caption>Table 1. *Cont.*</caption><thead><tr><th></th><th>Type Rad/Proton Energy (MeV)</th><th>LET (keV/μm)</th><th>Scavenger</th><th>Plasmid</th><th>Plasmid Concentration (ng/μL)</th><th>Scav. Capacity (s<sup>-1</sup>)</th><th>SSB Mbp<sup>-1</sup> Gy<sup>-1</sup></th><th>Error</th><th>DSB Mbp<sup>-1</sup> Gy<sup>-1</sup></th><th>Error</th><th>Base Lesions Mbp<sup>-1</sup> Gy<sup>-1</sup></th><th>Error</th><th>Non-DSB Clusters Mbp<sup>-1</sup> Gy<sup>-1</sup></th><th>Error</th></tr></thead><tbody><tr><td rowspan="4">Leloup 2005 [34]</td><td>p 249 MeV</td><td>0.39</td><td>glycerol</td><td>pHAZE liquid film</td><td></td><td>3.8 × 10<sup>6</sup></td><td>18.850</td><td>3.900</td><td>0.338</td><td>0.039</td><td></td><td></td><td>1.495</td><td>0.260</td></tr><tr><td>p 19.3 MeV</td><td>2.7</td><td></td><td></td><td></td><td>3.8 × 10<sup>6</sup></td><td>5.005</td><td>1.950</td><td>0.104</td><td>0.026</td><td></td><td></td><td>0.377</td><td>0.163</td></tr><tr><td>p 1.03 MeV</td><td>25.5</td><td></td><td></td><td></td><td>3.8 × 10<sup>6</sup></td><td>1.690</td><td>0.260</td><td>0.163</td><td>0.020</td><td></td><td></td><td>0.533</td><td>0.130</td></tr><tr><td>p 249 MeV</td><td>0.39</td><td>glycerol</td><td></td><td></td><td>3.8 × 10<sup>8</sup></td><td>0.917</td><td>0.195</td><td>0.029</td><td>0.006</td><td></td><td></td><td>0.176</td><td>0.026</td></tr><tr><td rowspan="4">Vyšín 2015 [50]</td><td>p 19.3 MeV</td><td>2.7</td><td></td><td></td><td></td><td>3.8 × 10<sup>8</sup></td><td>0.397</td><td>0.091</td><td>0.011</td><td>0.004</td><td></td><td></td><td>0.037</td><td>0.020</td></tr><tr><td>p 1.03 MeV</td><td>25.5</td><td></td><td></td><td></td><td>3.8 × 10<sup>8</sup></td><td>0.384</td><td>0.059</td><td>0.018</td><td>0.002</td><td></td><td></td><td>0.085</td><td>0.020</td></tr><tr><td>p 10 MeV</td><td>6.39</td><td>TE buffer</td><td>pBR322 dry</td><td>30</td><td></td><td>0.009</td><td>0.007</td><td>0.003</td><td>0.001</td><td>0.082</td><td></td><td>0.001</td><td>0.006</td></tr><tr><td>p 20 MeV</td><td>3.64</td><td></td><td></td><td></td><td></td><td>0.053</td><td>0.000</td><td>0.001</td><td>0.001</td><td>0.088</td><td></td><td>0.085</td><td>0.004</td></tr><tr><td rowspan="4">Ohsawa 2021 [51]</td><td>p 30 MeV</td><td>2.61</td><td></td><td></td><td></td><td></td><td>0.044</td><td>0.006</td><td>0.001</td><td>0.000</td><td>0.088</td><td></td><td>0.001</td><td>0.004</td></tr><tr><td>p 20 MeV</td><td>3.1–6.95</td><td>TE buffer</td><td>pBR322 liquid</td><td></td><td></td><td>58.900</td><td>2.600</td><td>2.000</td><td>0.200</td><td>45.800</td><td></td><td>4.500</td><td></td></tr><tr><td>p 30 MeV</td><td>1.96–2.34</td><td></td><td></td><td></td><td></td><td>39.700</td><td>8.200</td><td>1.500</td><td>0.800</td><td>45.900</td><td></td><td>3.900</td><td></td></tr><tr><td>p 27.5 MeV</td><td>2.3</td><td>TE buffer</td><td>pBR322 in solution</td><td>50</td><td></td><td>2.476</td><td>0.032</td><td>0.027</td><td>0.005</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4">Small 2021 [52]</td><td>p 27.5 MeV FLASH</td><td>2.3</td><td></td><td></td><td></td><td></td><td>2.016</td><td>0.156</td><td>0.025</td><td>0.004</td><td></td><td></td><td></td><td></td></tr><tr><td>e 100 MeV</td><td></td><td>no scav</td><td>pBR322 in solution</td><td></td><td></td><td>15.420</td><td>0.860</td><td>0.350</td><td>0.020</td><td></td><td></td><td></td><td></td></tr><tr><td>e 100 MeV FLASH</td><td></td><td></td><td></td><td></td><td></td><td>20.310</td><td>0.200</td><td>0.370</td><td>0.030</td><td></td><td></td><td></td><td></td></tr><tr><td>e 150 MeV</td><td></td><td></td><td></td><td></td><td></td><td>17.630</td><td>0.570</td><td>0.350</td><td>0.030</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4">Small 2019 [53]</td><td>e 150 MeV FLASH</td><td></td><td></td><td></td><td></td><td></td><td>18.740</td><td>0.520</td><td>0.370</td><td>0.040</td><td></td><td></td><td></td><td></td></tr><tr><td>e 200 MeV</td><td></td><td></td><td></td><td></td><td></td><td>20.190</td><td>0.560</td><td>0.380</td><td>0.020</td><td></td><td></td><td></td><td></td></tr><tr><td>e 200 MeV FLASH</td><td></td><td></td><td></td><td></td><td></td><td>21.220</td><td>0.380</td><td>0.380</td><td>0.020</td><td></td><td></td><td></td><td></td></tr><tr><td>e 100 MeV</td><td>0.22</td><td></td><td>pBR322 dry</td><td></td><td></td><td>69.810</td><td>8.720</td><td>3.660</td><td>0.430</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4">Pachnerová 2019 [28]</td><td>e 150 MeV</td><td>0.22</td><td></td><td></td><td></td><td></td><td>80.300</td><td>3.060</td><td>3.710</td><td>0.110</td><td></td><td></td><td></td><td></td></tr><tr><td>e 200 MeV</td><td>0.23</td><td></td><td></td><td></td><td></td><td>50.270</td><td>4.190</td><td>3.830</td><td>0.450</td><td></td><td></td><td></td><td></td></tr><tr><td>60–Co – 6 MeV</td><td>0.19</td><td>no scav</td><td>pBR322</td><td></td><td></td><td>7.940</td><td>0.140</td><td>0.970</td><td>0.100</td><td></td><td></td><td></td><td></td></tr><tr><td>60–Co – 10 MeV</td><td>0.20</td><td></td><td></td><td></td><td></td><td>11.000</td><td>0.660</td><td>1.130</td><td>0.080</td><td></td><td></td><td></td><td></td></tr><tr><td>Součík 2016 [54]</td><td>Carbon ions 400 MeV/u</td><td>11</td><td>TE buffer</td><td>pBR322</td><td>10</td><td>1.5 × 10<sup>3</sup></td><td>128.600</td><td>1.900</td><td>4.800</td><td>0.400</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4"></td><td>Ultra Soft X-rays 1.5 keV</td><td></td><td>TRIS</td><td>pBR322</td><td>5</td><td>1.5 × 10<sup>6</sup></td><td>2.477</td><td>0.130</td><td>0.228</td><td>0.026</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.5 × 10<sup>7</sup></td><td>0.780</td><td>0.059</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.5 × 10<sup>8</sup></td><td>0.163</td><td>0.072</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.5 × 10<sup>8</sup></td><td>2.386</td><td>0.052</td><td>0.208</td><td>0.020</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4"></td><td></td><td></td><td></td><td></td><td></td><td>1.5 × 10<sup>7</sup></td><td>0.845</td><td>0.013</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.5 × 10<sup>8</sup></td><td>0.182</td><td>0.020</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.5 × 10<sup>6</sup></td><td>2.106</td><td>0.091</td><td>0.137</td><td>0.013</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>1.5 × 10<sup>7</sup></td><td>0.800</td><td>0.039</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4"></td><td></td><td></td><td></td><td></td><td></td><td>1.5 × 10<sup>8</sup></td><td>0.228</td><td>0.026</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<figure><img src="image_91.png" /><figcaption>**Figure 1.** AFM topographic images of plasmid pBR322 on mica substrate irradiated with protons: (a) 20 Gy and (b) 30 Gy. AFM reveals the different conformations of DNA from simple linear to complex twisted loops. The difference in plasmid concentration between the two doses is incidental.</figcaption></figure>

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Review

# The Molecular and Cellular Strategies of Glioblastoma and Non-Small-Cell Lung Cancer Cells Conferring Radioresistance

Lina Alhaddad <fnref n="1" />,<fnref n="2" />, Andreyan N. Osipov <fnref n="1" />,<fnref n="3" />,<fnref n="4" />,* and Sergey Leonov <fnref n="1" />,<fnref n="5" />

**Abstract:** Ionizing radiation (IR) has been shown to play a crucial role in the treatment of glioblastoma (GBM; grade IV) and non-small-cell lung cancer (NSCLC). Nevertheless, recent studies have indicated that radiotherapy can offer only palliation owing to the radioresistance of GBM and NSCLC. Therefore, delineating the major radioresistance mechanisms may provide novel therapeutic approaches to sensitize these diseases to IR and improve patient outcomes. This review provides insights into the molecular and cellular mechanisms underlying GBM and NSCLC radioresistance, where it sheds light on the role played by cancer stem cells (CSCs), as well as discusses comprehensively how the cellular dormancy/non-proliferating state and polyploidy impact on their survival and relapse post-IR exposure.

**Keywords:** ionizing radiation; radioresistance; radiosensitivity; cancer stem cells; epithelial mesenchymal transition; polyploid/multinucleated giant cancer cells

## 1. Introduction

Glioblastoma (GBM; grade IV) is classified as the most aggressive, heterogeneous, and invasive primary brain tumor [1] in adults and often occurs in patients over 65 years of age [2]. GBM accounts for 15% of all brain tumors [3–5]. Non-small-cell lung cancer (NSCLC), a heterogeneous class of tumors, represents approximately 85% of all lung cancer diagnoses [6]. Radiotherapy represents the mainstay of therapy in patients with inoperable early-stage NSCLC [7] and GBM [8], yet the prognosis of GBM and NSCLC patients still remains poor due to a refractory response to ionizing radiation (IR) [9,10]. Therefore, a high radioresistance of these tumors still limits therapeutic success. The median survival for elderly patients with GBM remains approximately 8 months with RT alone [11], whereas the observed improvement in median survival of NSCLC time is only 5 to 7 months, and radiotherapy does not offer the possibility of a cure [12]. Tumor heterogeneity accounts for therapeutic failure [13]. Tumor recurrence occurs when therapy-surviving residual tumor cells tenaciously propagate and re-establish the tumor. Many studies have suggested that the heterogeneity of tumors can be explained not only with the characteristic of genetic instability and epigenetic changes but also with the help of cancer stem cells (CSCs) supported by antiapoptotic signaling [14–16]. CSCs thwart harmful insults resulting from radiotherapy due to their distinctive inherent properties of self-renewal for unlimited time, increased aggressiveness, resistance to stress, and preferential activation of the DNA damage checkpoint [10,14,17–21] (Figure 1). CSCs are capable of evading cell death, albeit they can become dormant for extended periods of time [22]. Plasticity of CSCs, therapy

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**Citation:** Alhaddad, L.; Osipov, A.N.; Leonov, S. The Molecular and Cellular Strategies of Glioblastoma and Non-Small-Cell Lung Cancer Cells Conferring Radioresistance. *Int. J. Mol. Sci.* **2022**, *23*, 13577. https://doi.org/10.3390/ijms232113577

Academic Editor: François Chevalier

Received: 12 October 2022

Accepted: 3 November 2022

Published: 5 November 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

<figure><img src="image_94.png" /></figure>

**Copyright:** © 2022 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/).

<footnote n="1">¹ School of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Russia</footnote>

<footnote n="2">² Department of Environmental Sciences, Faculty of Science, Damascus University, Damascus P.O. Box 30621, Syria</footnote>

<footnote n="3">³ State Research Center-Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency (SRC-FMBC), 123098 Moscow, Russia</footnote>

<footnote n="4">⁴ N.N. Semenov Research Center of Chemical Physics, Russian Academy of Sciences, 119991 Moscow, Russia</footnote>

<footnote n="5">⁵ Institute of Cell Biophysics, Russian Academy of Sciences, 142290 Pushchino, Russia</footnote>

<footnote>* Correspondence: aosipov@fmbcfmba.ru</footnote>
resistance, and dormancy are substantially interrelated processes [23,24]. It has been suggested that tumor progression depends profoundly on the CSC niche within it [23]. Invasion and metastasis have been known to be the main obstacles to successful therapy and are closely linked to the mortality rate of GBM [25] and NSCLC [26]. Epithelial-to-mesenchymal transition (EMT) is a very complex process regulated by several families of transcriptional factors through many signaling pathways that form a network that allows tumor cells to acquire invasive properties and penetrate the neighboring stroma, leading to the formation of a privileged microenvironment for tumor progression and metastasis [27]. EMT is hallmarked by the combined loss of epithelial cell junction proteins, such as E-cadherin, and the gain of mesenchymal markers, such as vimentin and N-cadherin [28,29]. EMT is an important inducer of the CSCs' plasticity [30]. IR is one of the exogenous genotoxic agents that are capable of eliciting DNA damage [31]. GBM and NSCLC cells have network mechanisms in response to DNA damage, including initiation of DNA repair and, in certain cases, induction of apoptosis to annihilate dysregulated and damaged cells [32,33]. It has been reported that IR can induce proliferation arrest of tumor cells [34], which is often accompanied by senescence and/or quiescence [35,36]. The mechanisms dictating the exit from cycle arrest have considerable implications on cell fate and can thus affect the outcome of DNA damage-based tumor therapies [36]. Rarely dividing/non-proliferating tumor cells are regarded as deeply resistant to these agents, thereby causing therapeutic failure and tumor recurrence [37]. It has been suggested that tumor cells can recuperate from temporary arrest after DNA damage is repaired [36]. It has been demonstrated that IR can result in the development of polyploid tumor cells [38]. These giant cells have been reported to be adequately pliable to meet developmental tumor needs by facilitating the rapid evolution of tumors and the acquisition of therapy resistance in multiple incurable tumors [39]. Moreover, they have been shown to undergo depolyploidization [40] and produce a limited number of para-diploid clones [41,42]. It should also be noted that the radioresistance of GBM and NSCLC may be attributable to the interlink between the tumor cells and their tumor microenvironment (TME) [43,44].

<figure><img src="image_95.png" /><figcaption>**Figure 1.** Targeting of CSCs. CSCs remaining after radiotherapy can then emerge and repopulate.</figcaption></figure>

## 2. Tumor Heterogeneity

One of the most important hallmarks of GBM [45] and NSCLC [46] is cellular heterogeneity. The heterogeneity of tumor cells is a continuous cause of incomplete molecular response to radiotherapy [13,47,48] due to the diversity of tumor cells within the same tumor, leading to different responses to radiotherapy and inevitable repopulation post-IR [49,50]. Tumor heterogeneity arises from subpopulations of cells with marked genomic
and/or epigenetic change and molecular signatures, a phenomenon termed intra-tumor heterogeneity [51]. Intra-tumoral heterogeneity results in the ability of a tumor to harbor anomalies in a variety of signaling pathways and cells with different levels of sensitivity to established antitumor agents [48]. Three models of tumor progression and metastasis have been postulated to explain this phenomenon—the clonal evolution, the classical CSC, and the plastic CSC models [52] (Figure 2).

<figure><img src="image_96.png" /><figcaption>**Figure 2.** Models of tumor heterogeneity and progression of metastatic disease.</figcaption></figure>

The clonal evolution theory was the first model to describe a way in which tumor cells evolve progressively due to genomic instability resulting from an accumulation of successive mutations. These stochastic events generate the raw material for the clonal outgrowth of novel cell populations that can thrive under selective pressures imposed by the TME, dictating more malignant phenotypes [52,53]. Moreover, heritable changes in the epigenome permit the cells to acquire advantageous traits and to be selected in a neo-Darwinian-like evolutionary paradigm [54]. The classical CSC theory hypothesizes that tumors are immortalized by CSCs identified by their ability to initiate tumor growth, sustain self-renewal, and re-establish a heterogeneous tumor cell population [21,55–57]. This model focuses on the internal heterogeneity within individual clonal subsets. According to this theory, most tumorigenic cells within such a clonal population reside at the peak of the hierarchy [52]. A defining feature of this model is its unidirectional nature, whereby CSCs undergo symmetric division to replenish the CSC pool within a tumor or irreversible asymmetric division to generate more differentiated progeny with low metastatic potential. In this case, the divergent cell phenotypes are regulated by endogenous and exogenous stimuli arising in the TME. These stimuli can lead to the induction of specific growth factor and cytokine pathways that, in turn, affect subtle epigenetic changes in CSCs and their non-CSC progeny. The CSC hierarchical model has been extended to many solid human tumors, including GBM and NSCLC [58,59]. The plastic CSCs theory portrays the phenotypic conversion between the CSC and non-CSC compartments as a bidirectional process [52], highlighting an evolving mechanism by which non-CSCs can dynamically move back up the hierarchy and re-enter the CSC state due to dedifferentiation process [52]. Moreover, this model describes the basic aspects of non-CSC-to-CSC bidirectional interconversions. According to this theory, CSCs may be derived by the oncogenic transformation of normal tissue stem cells, by EMT, by mutations in key regulators of differentiation, or by a spontaneous conversion process [52]. Numerous studies have reported that IR can promote non-CSCs to obtain the phenotype and function of CSCs, so-called “awakened” CSCs [60,61].
### 3. Cancer Stem Cells Concept, History, and Properties

Cancer stem (-like) cells (CSCs) or (CSLCs), also referred to as cancer-initiating cells (CICs), are a small subgroup of cancer cells with the capability of self-renewal and differentiation into heterogeneous tumor cells, and they have been believed to be accountable for tumor initiation, growth, and recurrence [62]. Other terms used for these cells are tumor or rescuing units, tumor-progenitor cells, and functional tumor stem cells [63]. Large-scale studies have indicated that the biological characteristics of tumors, including radioresistance, are determined by CSCs [64,65]. It has been demonstrated that CSCs can be enriched both in vitro and in vivo by IR, indicating the possibility of IR-induced generation of CSCs [66,67]. CSCs are considered to have innately higher radioresistance, invasion capability, and metastatic capacity than their differentiated counterparts [61]. Targeting CSCs in tumors may represent an effective antitumor therapeutic strategy and improve the efficacy of radiotherapy. CSCs share some, or all, properties of SCs, that endow these cells with key traits in tumorigenesis, relative quiescence, activation of survival responses, promotion of blood vessel formation, and enhanced motility [10,68]. For example, miR-200 regulates both normal stem/progenitor cells and CSCs by targeting BMI1, which is necessitated for SC self-renewal [69,70]. Among the early investigators of the 1800s, Virchow and Cohnheim postulated the existence of CSCs that arise from what they believed to be the "activation of dormant embryonic tissue remnants" [71]. CSCs were first proposed by Fiala in 1968 [72]. Although the modern concept of SC biology was absent, a CIC was clearly hypothesized to be an SC unable to differentiate. Researchers in the 1970s advanced the theory that tissue-specific SCs might be the cells of origin for specific tumors [71]. Bayard Clarkson and coworkers identified a small subpopulation of slow-cycling cells, which they termed "dormant cells". These cells were able to escape anti-proliferative chemotherapy and were supposed to be responsible for the relapse of lymphoblastic leukemia in adults [73,74]. The tumor colony assay in soft agar medium proposed by Hamburger and Salmon in the late 1970s introduced the concept that only a small proportion of tumor cells, yielding a plating efficiency of 0.001 to 0.1%, are tumorigenic, and the authors identified these cells as the essential target of therapy [75]. Eventually, compelling evidence for the role of CSCs in the metastatic progression of the tumors was first validated in 1997 when Dick and Bonnet isolated a set of stem cells from human acute myeloid leukemia, and the samples were capable of transferring human acute myeloid leukemia to nonobese diabetic/severe combined immunodeficient mice [56]. In this case, it was observed only that CD34+ CD38− subpopulation [56] was able to reconstitute human acute myeloid leukemia that resembled the human disease in nonobese diabetic/severe combined immunodeficient mice [56,76–78]. CD34+ CD38− cell fraction was shown to represent 0.1–1% of the total cells and possess the proliferative, differentiation, and self-renewal capacities expected of normal stem cells [56,76]. The first time the CSCs concept was applied to solid tumors was in 2003 by Al-Hajj and colleagues [78], when they identified that only a small subset of breast cancer cells expressing markers CD44+/CD24− possessed a marked proliferative capacity, differentiation, self-renewal, and in vivo tumor-forming ability, while the remaining bulk of cells from this tumor had none, even when injected at many-fold higher cell doses [79]. Within the same year, Singh et al. purified CD133+ CSCs from human brain tumors of different phenotypes [80]. In 2004, it was also shown that multiple myeloma contains a rare subset of cells, defined by their lack of expression of the plasma cell marker CD138, that are clonogenic in vitro and tumorigenic in vivo [81]. In 2006, a workshop of the American Association for Cancer Research discussed the rapidly emerging CSC model for tumor progression and established the definition of a CSCs as "a small subset of cells within a tumor that possesses the capacity to self-renewal and to generate the heterogeneous lineages of cancer cells that comprise the tumor" [82]. During the last decade, CSCs have been identified in many solid tumors, including lung [83], pancreas [84], prostate [85], colon [86], liver [87], blood [88], skin [89], thyroid [90], cervix [91], ovary [92], and stomach [93], as well as their functional and phenotypic features have been investigated. CSCs have been previously identified through different criteria, including increased glycolysis
and glycine/serine metabolism or low concentrations of reactive oxygen species (ROS) and ATP [94]. The vast majority of studies, such as colony forming unit and marker expression, have been performed to check CSCs' radioresistance [82,95]. CSCs have been found to display enhanced chromosomal instability, possibly highlighting a role in clonal evolution in their propagation [96]. One of the intrinsic properties of CSCs is their ability to grow in a serum-free medium supplemented with growth factors in non-adherent culture plates [97]. In general, CSCs are considered quiescent or at least slow-cycling [98–101]. These cells can stay dormant for extended periods after treatment but eventually re-enter the cell cycle, leading to tumor regrowth [102]. Furthermore, CSCs exhibit certain properties, such as long-term survival, high expression of drug efflux transporters, abnormal cellular metabolism, deregulated self-renewal pathways, acquisition of EMT phenotype [103], more efficient DNA damage repair than bulk tumor cells after IR [104] (Figure 3).

<figure><img src="image_97.png" /><figcaption>**Figure 3.** The defining properties CSCs.</figcaption></figure>

It has been reported that CSCs withstand anoikis and display immune evasion, which may result in tumor metastasis and relapse [105,106]. Complicated cellular and molecular mechanisms, such as stemness maintenance, EMT, and ROS production, are intimately involved in the process of CSC initiation and facilitation of tumor recurrence and metastasis after treatment [107–110]. Metabolic stressors, which result in numerous enlarged, elongated, and interconnected mitochondria and increase oxidative capacity and ATP production in CSCs [111]. CSCs have been reported to overexpress ROS free-radical scavengers in order to reinforce their defense against ROS-induced damage [112–114], leading to tumor radioresistance. Compared to regular stem cells, CSCs are believed to reside predominantly in niches within the TME, including stromal cells, cancer-associated fibroblasts, infiltrating immune/inflammatory cells, and vascular endothelial cells [67,115,116], to retain their unique properties [117,118]. CSCs niche facilitates their metastatic potential and preserves their plasticity [22,23]. Furthermore, a variety of conditions, such as EMT [30], hypoxia [119], inflammatory cytokines, such as IL-1 β, IL-6, C-X-C motif chemokine ligand 12 (CXCL12), and IL-8 generate cells harboring CSCs properties [120]. The acidic TME has been reported to enhance CSCs radioresistance and angiogenesis through the induction of vascular endothelial growth factor (VEGF) [121,122]. Experimental and clinical studies have indicated that CSCs also possess the ability to initiate tumor formation in the host's
body [123]. Interestingly, as few as 100 CSCs have been shown to be able to recreate tumors in nonobese diabetic/severe combined immunodeficient mice [124]. The frequency of CSC varies broadly between different tumor types, spanning from small populations of <1% in human acute myeloid leukemia and liver cancer up to 82% in acute lymphoblastic leukemia [110]. When leukemic cells were transplanted in vivo, only 1–4% of cells could form spleen colonies [67,125]. In vitro data have shown that only 1 in 1000 to 5000 lung cancer cells generates colonies in soft agar assay, indicating that not every lung cancer cell is capable of clonal tumor initiation [126].

### 3.1. Cancer Stem Cells Related Markers

A large panel of highly specific CSCs markers provides molecular targeted therapies for various tumors, using therapeutic antibodies specific to these markers [127]. These markers are categorized according to cellular localization [128–131]. Many CSCs surface membrane markers have been identified, including podocalyxin, stage-specific mouse embryonic antigen, trophoblast cell-surface antigen 2, epithelial cell adhesion molecule (EpCAM), leucine-rich repeat-containing G-protein coupled receptor 5, aldehyde dehydrogenase 1 family member A1 (ALDH1A1), CD13, CD14, CD19, CD20, CD24, CD26, CD27, CD34, CD38, CD44, CD45, CD47, CD66c, CD90, CD166, CD105, CD133, CD138, CD117/c-kit, CD151, CD166 [129], CD 29 [132], CD271 [133], CD 114 [127], CD 73 [134], integrin α6 (CD49), integrin β1(CD29), integrin β3 (CD61) [135,136], Jagged 1–2 [137], ATP-binding cassette sub-family G member (ABC) transporter family [138], neural cell adhesion molecule (NCAM) [139], and to name a few. Cell surface molecules mediate interactions between cells and their microenvironment [129]. Of note, CD44 and CD133 have been published to be the most widely used markers for isolating CSCs [129,140]. CSCs can be phenotyped by certain stemness-related transcription factors, such as (Yamanaka factors; octamer-binding transcription factor 3/4 (Oct3/4), cellular myelocytomatosis oncogene (c-Myc), SRY (sex determining region Y)-box 2 (SOX2), kruppel-like factor 4 (KLF4), Nanog, Spalt like transcription factor 4 [129], special AT-rich sequence-binding protein 2 (SATB2) [141], forkhead box M1 (FOXM1) [142], mouse nucleoside diphosphate kinase B (NME2) [143], and hypoxia-inducible factor 1-alpha (HIF-1) [144]. These transcription factors contribute to the pathologic self-renewal characteristics of CSCs [145]. Additionally, there is a number of stemness-related markers that are neither cell surface proteins nor transcription factors, including B lymphoma Mo-MLV insertion region 1 homolog (BMI1), Nestin, β-catenin, T-cell immunoglobulin and mucin-domain containing-3 (TIM-3), Musashi-1, ALDH, CXC chemokine receptors (CXCRs) [129,146], transcriptional co-activators (e.g., transformation/transcription domain associated protein TRRAP [147], yes-associated protein 1 (YAP), and transcriptional co-activator with PDZ-binding motif (TAZ) [148], and antiapoptotic genes (e.g., B-Cell Leukemia/Lymphoma 2 (BCL-2), Bcl-2-associated X protein (BAX), cellular FLICE-inhibitory protein (c-FLIP) [149,150]), Survivin [151], B-cell lymphoma-extra-large (Bcl-XL), and myeloid leukemia 1 (MCL-1) [152]. The CSCs phenotype can differ essentially between patients [153]. For example, a small subpopulation of cancer cells is present within some human breast cancers that exhibit a CD44 +/CD24 (−/low) phenotype; these tumorigenic cells have been shown to be highly enriched for CICs in xenografts compared to their counterparts [154], and display a mesenchymal phenotype in the invasive front of the tumor [155]. High CD133 expression is linked to multiple tumor recurrence, increased metastatic potential, and radioresistance [156–158]. It has been reported that CD44 overexpression, in particular CD44v, contributes to tumor radioresistance through the protection against ROS by stimulating the synthesis of reduced glutathione (GSH) level, a primary intracellular antioxidant [159,160]. It has been confirmed that HIF-1α inactivates the T-cell factor-4 (Tcf-4) for direct binding to β-catenin [161], indicating a role of β-catenin–HIF-1α interaction in promoting CSC adaptation to hypoxia after IR [161,162]. BMI1 upregulation has been found to confer radioresistance in tumors through stimulating telomerase activity and enhancing ATM recruitment to the chromatin, leading, in turn to tumor perpetuation [163]. Recent studies have confirmed that SATB2
acts as a regulator of stemness and self-renewal by augmenting the expression of pluripo-
tency maintenance-associated transcription factors, such as SOX2, Oct4, c-Myc, KLF4,
and Nanog [141,164]. ABC transporters overexpression has been reported in several tu-
mors [165,166] and more predominantly in CSCs [137]. Multi-drug resistant proteins (MDR)
have been known to mediate the transport of a variety of cytotoxic compounds out of the
cells [137]. It has been shown that members of the ABC transporter superfamily have a
wide range of physiological activity: (a) detoxification, permeability glycoprotein (P-gp,
also known as MDR1 or ABCB1), and multi-drug resistance-associated protein 1 (MRP1,
also known as ABCC1); (b) xenobiotic oxidative stress alleviation (MRPs and ABCCs);
(c) cellular lipid metabolism (MDR3, ABCG, and ABCA families), and antigen presentation
ATP-binding cassette subfamily-B member 2 and 3, antigen peptide transporter 1 and 2
(ABCB2/transporter associated with antigen processing 1 (TAP1) and ABCB3/TAP2) [167].
A drug-resistance characteristic of CSCs has been identified as a side population [168].
The activity of ABC transporters can be gauged by pumping out fluorescent dyes, such
as rhodamine 123 and Hoechst 33342, which can be extruded by ATP-binding cassette
subfamily-G member 2 (ABCG2, also known as CDw338/ breast cancer resistance protein
(BCRP)) and ATP-binding cassette subfamily-B member 1 (ABCB1), respectively [169,170].
YAP/TAZ activation leads to the induction and maintenance of CSC properties in a wide
range of human tumors, including GBM [171,172] and NSCLC [173]. YAP/TAZ activation
in response to IR has been shown to drive tumor growth, transformation, and metas-
tasis [174]. Nestin overexpressing after IR has been demonstrated to correlate with the
transformation of various human malignancies [175].

3.2. *Cancer Stem Cells Signaling Pathways*

CSCs exhibit deregulated activation of self-renewal pathways [103], a process that can
lead to extensive cell proliferation and malignant transformation [176].

Furthermore, IR is an antitumor treatment modality that triggers multiple signal
transduction networks [177]. Exploring CSC-specific signaling mechanisms and charac-
teristics is clinically important for better-targeted radiotherapy strategies. Regulatory
networks consisting of the Notch, Hedgehog (Hh), Janus kinase/signal transducer and
activator of transcription (JAK-STAT), canonical and non-canonical Wingless and Int-1
(WNT/β- catenin), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB),
phosphatase and tensin homolog (PTEN) [129], transforming growth factor and moth-
ers against decapentaplegic (TGF/SMAD), phosphatidylinositol-3-kinase (PI3K)/Akt and
the mammalian target of rapamycin (mTOR), peroxisome proliferator-activated receptors
(PPAR) [178,179], Hippo-YAP/TAZ [148], mitogen-activated protein kinase and extracel-
lular signal-regulated kinase (MAPK/ERK) [180,181], and miRNAs [179] pathways have
all been shown experimentally to play an essential role in regulating CSCs functions [129],
controlling their properties [67], and causing radioresistance by expediting tumor recur-
rence [182,183]. Many of these pathways are inextricably interwoven networks of signaling
mediators that feed one another, facilitating inter-pathway crosstalk [184]. For example,
Notch signaling inhibition in GBM has been shown to downregulate its target Hes1, a tran-
scriptional repressor, which in turn upregulates GLI transcription in the Hh pathway [185].
NF-κB and TGF proinflammatory signaling pathways have been shown to be activated in
tumor cells in response to IR [186]. Recent studies have reported that the canonical WNT/β-
catenin signaling cascade participates in the formation of tumor radioresistance by affecting
the cell cycle, proliferation, apoptosis, invasion, and DNA damage repair (DDR) [187]. Hh
signaling has been reported to play a fundamental role in growth, recurrence, metastasis,
radioresistance, and acquisition of a CSC-like phenotype via the EMT process in various
tumors [62,188]. It has been confirmed that Notch signaling is an important mediator of
IR-induced EMT and responsible for IR-enhanced tumor malignancy [182,189–191]. Many
studies have supported the role of the Hippo-YAP/TAZ signaling pathway in the induction
of EMT, tumorigenesis, and chromatin remodeling. Moreover, this pathway has been
shown to promote tumor radioresistance via escalating DDR [192–194].