higher increase in sensitive cells, proteins upregulated post-IR shown in orange, downregulation in blue, and no change in black.

#### 3.3.1. Vascular Endothelial Growth Factor (VEGF)

VEGF induces endothelial cell proliferation, promotes cell migration, inhibits apoptosis, and induces permeabilization of blood vessels [63,64]. Furthermore VEGF is associated with autophagy, a conserved and essential mechanism for both protecting and killing cells during stress response [65]. Autophagy is carried out by lysosomal degradation of macroproteins or even whole organelles [66,67] and is thought to contribute to normal tissue and tumour radio-resistance [68–70].

Nguyen et al. reported an increase in VEGF secretion 48 h after exposure to 2 Gy IR (137Cs, dose rate 2.7 Gy/min) in CCR6+Th17 T cells, which are highly sensitive to IR-induced senescence. This may contribute to IR-induced normal tissue damage and might facilitate tumour recurrence and metastasis after radiotherapy [39]. Braicu et al. investigated VEGF levels in the serum of patients with locally advanced FIGO stage Ib–IIb cervical cancer before and after chemoradiotherapy (6 MV photon linear acceleration). They demonstrated that a decrease in VEGFA concentration leads to an increase in overall survival; an increase of more than 500 pg/mL VEGF in serum negatively influenced the overall survival due to the resistance to chemoradiotherapy [40]. Fekete et al. described an increase in VEGF levels in non-irradiated MSCs (Bone-Marrow-Derived Mesenchymal Stromal Cells), whereas no significant change was observed in irradiated MSCs (30 Gy, 7, 14, 21, and 28 d post IR with <sup>137</sup>Cs) [47].

VEGF is a key mediator of neovascularisation and is highly expressed in cancer cells and tumour-associated stromal cells [71]. In a meta-analysis conducted to evaluate the relationship between serum VEGF expression and radiosensitivity in Asian non-small cell lung cancer (NSCLC) patients, it was established that lower expression of VEGF led to a longer overall survival and could be a useful biomarker to predict radiosensitivity and prognosis of NSCLC patients [72]. Hu et al. reported IR-induced increased VEGF expression in HeLa cells in vivo and in vitro and a knockdown of VEGF expression in HeLa cells indicated increased cellular sensitivity to radiation [73].

The effect of radiation exposure on VEGF seems to be cell type dependent. However, first in vitro and in vivo studies suggest its importance for normal tissue radiosensitivity. Therefore, it is a promising candidate marker to study radiosensitivity in future projects.

#### 3.3.2. Caspase 3

Caspase 3 is involved in the activation cascade of several caspases responsible for apoptosis by proteolytically cleaving poly(ADP-ribose) polymerase (PARP). Furthermore it cleaves and activates Caspase-6, -7, and -9 [74].

Both, Cao et al. [45] and Nguyen et al. [39] conducted their studies on <sup>137</sup>Cs irradiated T cells (dose rate 2.7 and 4.8 Gy/min, respectively) and observed a radiation induced increase in Caspase 3 concentration, where Cao et al. reported a higher increase in radiosensitive CD4+CD25+ Treg cells compared to normo-sensitive CD4+CD25- T cells after overnight incubation post 0.94, 1.875, and 7.5 Gy. Nguyen et al. described a greater Caspase 3 activation (48 h post 2 Gy) in CCR6negTh cells compared to CCR6+Th17 that are rather prone to IR-induced senescence than to apoptosis. When lymphocytes from healthy donors were irradiated with 1, 2, or 4 Gy (60Co), a dose-dependent increase in active Caspase 3 was observed that included high intra-individual variability [75]. This suggests that Caspase 3 could effectively be used as a tool to detect individual differences in radiosensitivity, which could be used on patients before they undergo radiotherapy. In a study conducted in MCF-7 breast cancer cells, it was discovered that Caspase 3 plays a critical role in radiotherapyinduced apoptosis, and this suggests that Caspase 3 deficiency may contribute to the radio-resistance of breast cancers [76]. Although an activation of Caspase 3 seems to be a potential candidate to define radiosensitive cells, due to limited numbers of donors (5 and 32), the results needs to be validated in further studies.

#### 3.3.3. p16INK4A (Cyclin-Dependent Kinase Inhibitor 2A, CDKN2A)

p16 acts as a negative regulator of normal cell proliferation by inhibiting CDK 4 and CDK 6 interaction with cyclin D and the phosphorylation of retinoblastoma protein, prohibiting progression from G1 phase to S phase [77,78]. p16 is a known marker for senescence through its contribution to the repression of proliferation-associated genes. High-Mobility Group A proteins act together with p16 to promote senescence-associated heterochromatic foci (SAHF) formation () and proliferative arrest [79].

Miyake et al. observed that an increase in p16 expression in keratinocytes (passage 1, 2, and 3), was characterised as radio-resistant but not in fibroblasts or induced pluripotent stem cells (iPSCs) 72 h after 2 Gy <sup>60</sup>Co γ irradiation (dose rate 2.7 Gy/min) [38]. Nguyen et al. showed that p16 expression was higher in CCR6+Th17 cells (radio-resistant compared to Treg cells) 48 h after 2 Gy <sup>137</sup>Cs with a dose rate of 2.7 Gy/min IR and led to IR-induced senescence [39]. In contrast, studies have shown that p16 expression leads to radio-sensitisation in cancer cell lines [80–82]. Since p16 is known to be a marker for senescence and the study results between tumour cell and normal cells are controversial, p16 is not a promising marker to determine individual differences in radiosensitivity.

#### 3.3.4. Interleukin-6 (IL-6)

The pleiotropic cytokine IL-6 comprises a wide variety of biological functions including immunity, tissue regeneration, and metabolism [83]. It is a potent inducer of the acute phase response and a rapid production of IL-6 contributes to host defence during infection or injury. IL-6 expression is tightly regulated, both transcriptionally and post-transcriptionally and its immoderate production causes severe inflammatory diseases.

Cao et al. reported that IL-6 is significantly downregulated in response to 0.94 and 1.87 Gy ( <sup>137</sup> Cs, dose rate 4.8 Gy/min) in radiosensitive Treg cells, but not in T cells showing a normal sensitivity [45]. The study of Fekete et al. found increased IL-6 levels during culture of both exposed and non-exposed MSCs (bone-marrow-derived mesenchymal stromal cells) 7, 14, 21, and 28 d post IR with <sup>137</sup> Cs [47].

Chen et al. showed that irradiation-induced IL-6 and the subsequent recruitment of myeloid-derived suppressor cells could be responsible for tumour regrowth [84]. Several clinical observations have documented increased IL-6 levels in plasma from patients with therapy-resistant metastatic disease compared to patients with earlier stages of the disease and healthy individuals. Higher levels of IL-6 in body fluids were associated with poor prognosis and survival [85–90]. These findings fit to the results of Cao et al. showing that downregulation of IL-6 enhances radiosensitivity. Concerning normal tissue, more evidence is needed to confirm these findings.

#### 3.3.5. Interleukin-1 Beta (IL-1β)

IL-1β is a proinflammatory cytokine and works in coaction with interleukin-12 and induces interferon gamma synthesis from T-helper 1 cells [91]. By inducing VEGF production synergistically with TNF and IL-6, IL-1β is involved in angiogenesis [92].

Like for IL-6, Cao et al found a significantly downregulated IL-1β in response to 0.94 and 1.87 Gy <sup>137</sup>Cs irradiation, delivered with a dose rate of 4.8 Gy/min in radiosensitive Treg cells, but not in normal sensitive T cells [45]. Secretion of IL-1β was increased only in CCR6negTh and not in CCR6+Th17 cells 48 h after 2 Gy (137Cs, dose rate 2.7 Gy/min) irradiation according to Nguyen et al. [39]. Chen et al. reported a significant overexpression of IL-1 beta in cancer specimens compared to non-malignant tissues. By blocking IL-1 β, tumour growth, invasion ability, and treatment resistance were attenuated [93]. Regarding the diverse observations of Cao et al. and Nguyen et al., IL-1β does not seem to be a favourable biomarker.

The studies that contained the previous markers were further evaluated based on a Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach (Table 4). Each study received an initial confidence rating based on the presence or absence of four features, which were (1) controlled exposure, (2) exposure prior to outcome, (3) individual outcome data, and (4) use of comparison group. The studies that received the same initial confidence were pooled together and either up-graded depending on magnitude effect, dose response, residual confounding, consistency, or downgraded based on risk of bias, unexplained inconsistency indirectness, or imprecision. The factors that decreased confidence were risk of bias, unexplained consistency, and indirectness. The detailed information is provided in the protocol [20].


**Table 4.** Accessing confidence in body of evidence in selected studies.

Significant interactions for aforementioned proteins, TP53BP1, and γH2AX (Figure 2), were identified when an in silico protein enrichment was performed on the STRING 11 database [94,95]. The generated network consisted of 7 nodes that are connected via

15 edges, whereas only 7 edges would be expected when using only 7 proteins for analysis. The interactions suggest that the proteins are likely to be biologically connected.

1β, CASP3, TP53BP1, and γH2AX: ( – **Figure 2.** Protein-protein interaction enrichment network generated in STRING 11.0 using proteins identified in at least two studies: p16 (CDKN2A), VEGFA, IL6, IL-1β, CASP3, TP53BP1, and γH2AX: (**a**) The lines represent protein–protein association where pink lines are known experimentally determined interactions, blue from curated databases, green are from text-mining, and black represents co-expression; (**b**) The thickness of the edges display the confidence in interaction: medium (0.400), high (0.700), and highest (0.900) in this network.

#### **4. Outlook**

First of all, it is important to understand the proteomic landscape of normal tissues. Different tissues and cell types harbour divergent baseline protein expression [96]. Most of the studies are focused on blood or blood cell-derived changes, but normal tissue reaction post IR is multifaceted and dependent on tissue types. Therefore more mechanistic studies are required to identify the tissue-specific impact of proteins on radiosensitivity. In this regard the validation of proteins for different dose rates will be an important point in future studies, because new developments in radiotherapy, such as ultra-high dose radiotherapy (FLASH) use much higher dose rates which may affect radiosensitivity differentially.

reaction, thus determining each predictor's overall impact is difficult to characterise. Some Second, radiosensitivity is a complex issue as many risk factors modify the radiation reaction, thus determining each predictor's overall impact is difficult to characterise. Some of the factors that influence radiosensitivity and complicate the discovery of a ubiquitous applicable biomarker are specified in this section.

– There are several known hereditary hyper-radiosensitive disorders arising from rare mutations in DNA repair genes of large effect. All belong to XCIND syndromes, named after distinct hypersensitivity to ionizing radiation (X-ray), cancer susceptibility, immunodeficiency, neurological abnormality, and double-strand DNA breakage. Examples of such syndromes are Ataxia telangiectasia, Fanconi anemia, Ligase IV syndrome, Radiosensitive severe combined immunodeficiency disease (RS-SCID), Radiosensitivity, immunodeficiency, dysmorphic features, and learning difficulties (RIDDLE) syndrome, or ataxia telangiectasia and Rad3-related protein (ATR)-Seckel syndrome [15,97–99]. Polymorphic variants, as well as mutations in multiple genes that lead to similar or different DNA damage response pathways, will contribute to genetically defined radiosensitivity in a complex manner.

– – Age and gender are crucial factors influencing individual differences in radiosensitivity. Children aged 0–5 years are expected to be the most sensitive group concerning radiation-induced leukaemia, as well as skin, breast, thyroid, and brain cancer for both high and low dose radiation exposures [100–105]. Sex influences the radiation response and the radiation-induced cancer risk [106]. Epidemiological studies from the Chernobyl disaster in 1986 and the Hiroshima and Nagasaki atomic bomb survivors provide evidence that females possess a greater risk for solid cancers [107–109] mainly due to cancer of reproductive tissue [110] and thyroid and brain cancer [106,111].

The anatomical structure (organ size, body mass index), as well as breathing rates, and individual metabolism of exposed individuals alter radiation doses received by organs and tissues, which leads to inter-individual variations [112–116]. Lifestyle is another aspect that affects individual cancer susceptibility when radiation exposure is considered. Although smoking and ionizing radiation exposure are the most studied influences, other co-exposures such as heavy metals, medication, alcohol consumption, dietary habits, and combined exposure to other radiation qualities such as radon needs to be taken into account [117–119]. Additionally, already diseased individuals cope poorly to radiation exposure compared to healthy ones. [120,121].

#### **5. Conclusions**

The fact that there is a clear evidence that not all individuals share the same radiationinduced risk of adverse health outcomes is also backed by the reports from the advisory group on ionizing radiation (UK) [122] and International Commission on Radiological Protection (ICRP) [123]. Radiosensitivity represents a complex phenotype and this is perhaps why we identified few IR-induced proteins (γH2AX, TP53BP1, VEGF, CASP3, CDKN2A, IL-6, and IL-1B), that correlated to radiosensitivity, when common markers in at least two studies were considered. These candidate proteins and their possible interaction partners should be investigated further, to discover biomarkers that can properly define radiation sensitivity.

The need to discover biomarkers for disease risk or susceptibility of radiation related risks for individuals or population subgroups is vital and also stressed by MELODI platform [124]. Not only would patients benefit by an individualised cancer treatment but also individualised risk assessment and prevention measurements can protect at-risk occupationally exposed individuals more efficiently. This systematic review highlights the fact that there is a lack of basic studies with a focus on normal tissue in contrast to tumour tissues. More studies based on functional assays are needed to survey the role of specific proteins in different normal tissues. In addition, the frequently statistically underpowered studies do strengthen the need to use large cohorts, as well as very sensitive methods for the biomarker search, as well as focusing on functional tests of potential markers in different accessible normal tissue (lymphocytes, fibroblasts, keratinocytes, and body fluids).

#### **6. Differences between Protocol and the Review**

The GRADE tool to up- or downgrade studies was not performed on all studies but only on studies that included proteins, other than repair foci, reported in at least two studies.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/2075-4 426/11/2/140/s1: Supplementary Information 1 (Search algorithm for ISI Web of Science), Supplementary Information 2 (List of rejected articles), Supplementary Information 3 (Data extraction sheet), Supplementary Information 4 (IR-induced changes in repair foci proteins), Supplementary Information 5 (IR-induced changes in non-repair foci proteins), Supplementary Information 6 (Risk of bias questions), Supplementary Information 7 (Risk of bias categorisation into T1, T2, and T3, PRISMA and SWiM checklist.

**Author Contributions:** Conceptualisation, A.D., M.G., S.M., and P.S.; methodology, A.D., M.G., S.M., P.S.; formal analysis, A.D., M.G., S.M., P.S.; investigation, A.D., M.G., S.M., P.S.; resources, M.G., S.M.; writing—original draft preparation, A.D., M.G., S.M., P.S.; writing—review and editing, A.D., M.G., S.M., P.S.; supervision, M.G., S.M.; project administration, M.G., S.M.; funding acquisition, M.G., S.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** A.D. is funded by the Bundesministeriums für Bildung und Forschung (BMBF, Germany) within the "ReparaturFoci (RF) project (02NUK035D)" and P.S. is funded by the BMBF within the project "Zielstrukturen der individuellen Strahlenempfindlichkeit (ZISStrans) (02NUK047B)".

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data is provided in the manuscript.

**Acknowledgments:** The authors would like to thank Bernd Henschenmacher and Elisa Pasqual for the guidance in writing this review and Lukas Duchrow and David Endesfelder for their help with statistics. Felix Kästle helped organise the table for the list of rejected articles.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**

