The conventional chemotherapeutic treatment strategies have certain drawbacks linked to the systemic administration and nonspecific distribution of the drugs through the body. This can, for instance, result in limited accessibility of the drug to the tumor, requiring high therapeutic doses and causing off-target toxicity due to damage to healthy cells. Besides, cancers can develop resistance to chemotherapeutic drugs, which is an important factor in treatment failure. Nanoparticles have the potential to improve these aspects by acting as drug delivery systems (DDS). In fact, nanoparticles can efficiently hold a massive payload of the drug, improving the solubility and stability of the drug in the blood circulation. In addition, they enable targeted delivery of the drug to the tumor sites and promote transport across membranes. Altogether, nanoparticle-based drug delivery has the potential to enhance the efficacy of the chemotherapeutic treatment, while minimizing the side effects. Furthermore, in order to counteract multidrug resistance, nanoparticles can be used to deliver multiple therapeutic agents, including chemo-sensitizers, small interfering RNA, microRNA, enhancing antitumor effects.


Therapeutic agents can typically be loaded on nanoparticles through physical packaging, covalent binding, or electrostatic complexation. Lipid-based nanoparticles, such as liposomes, consisting out of a double lipid layer are the most popular structures in nanoparticle-based drug delivery thanks to their excellent biocompatibility and biodegradability. Furthermore, they can transport both hydrophilic and hydrophobic drugs, encapsulated in the aqueous core and the bilayer membrane, respectively. Other organic nanoplatforms used for drug delivery include polymers, micelles, and dendrimers. On the other hand, inorganic nanoparticles such as carbon-based nanotubes, gold nanoparticles, silica nanoparticles, and iron oxide nanoparticles are also used as drug delivery systems because of their advanced multi-functionality, excellent stability, high drug payload, and unique surface properties.


To improve the precision of drug delivery, it is possible to engineer a cancer-targeted, stimulus-sensitive DDS, which releases the drug at the tumor site in a controlled and sustained manner upon encountering an endogenous or exogenous trigger, without affecting the regions near the tumor site. The tumor microenvironment features conditions that substantially differ from those in normal tissues, such as an acidic pH, high enzyme levels of matrix metalloproteinases (MMPs) and proteases, hypoxia, metabolic shift to anaerobic glycolysis, and a high redox activity. These endogenous stimuli can induce nanoparticle degradation and subsequent drug release. The development of nanocarriers sensitive for exogenous stimuli such as near infrared light, heat or sound waves enables an “on-demand” drug delivery that is tightly controlled from outside the body [212].


As mentioned in a previous section, hyperthermia can help in tumor control thanks to its tumor vasculature effect. Briefly, hyperthermia triggers vasodilation. In healthy vasculature, it helps to efficiently dissipate the heat and avoid tissue damage. However, in the aberrant organization and structure of tumor vasculature, it initially increases the blood flow and oxygen supply to the tumor tissue until the heat accumulated in the tissue reaches 42 °C triggering the collapse of tumor blood vessels that promotes cancer cell death. Therefore, it is important to localize hyperthermia to the tumor tissue while avoiding prolonged exposure of healthy cells to elevated temperatures.


Interestingly, the increase in tumor blood flow induced by hyperthermia can be used to sensitize cancer cells and to enhance the delivery of drugs improving the efficacy of chemotherapy and RT, respectively. Nanoparticles have unique properties, which enables them to efficiently convert incident energy into heat. For instance, alternating magnetic fields activate magnetic nanoparticles, such as iron oxide nanoparticles, stimulating heat production. On the other hand, plasmonic nanoparticles, such as gold nanoparticles, typically hold a unique optical characteristic called the surface plasmon resonance (SPR). This phenomenon implies the interaction of light of a specific wavelength with the free electrons on the surface of the nanoparticle, resulting in the absorbance and scattering of light, and the generation of heat [213]. Finally, carbon nanotubes absorb electromagnetic radiation over an extremely broad frequency spectrum, ranging from near infrared light to radiofrequency waves. The absorbance of electromagnetic energy induces electron excitation and relaxation within the nanoparticle, causing heat production. The ability to target and accumulate nanoparticles in the tumor tissue allows the nanoparticle-mediated heat generation to be localized at the tumor site.


In 2004, it was demonstrated that gold nano-objects injected in tumors can enhance the effect of radiation by improving tumor control in mice treated with kilovoltage X-rays. Since this pioneering work, extensive experimental validations were performed evidencing the potential of a large series of metal-based nanoparticles as radiosensitizer at preclinical level. However, the mechanism(s) of action, a complex mixture between physical, chemical, and biological contributions is still under debate [214]. Physical contribution resides in their ability to increase the dose deposited (radioenhancement effect) via the emission of secondary Auger and photoelectrons following the interaction with IR. The capacity of nanoparticles to increase radiolysis processes leading to a higher oxidative stress in cellular systems constitutes a chemical contribution to the mechanism of action. Finally, the biological effect is based on cell detoxification and DNA repair system impairment, enabling to potentiate the effect of irradiation (radiosensitization effect) [215, 216].


Researchers designed complex and multimodal nanoplatforms enabling the simultaneous use of nano-objects for diagnostic and therapeutic applications. These nano-objects are called “theranostics” agents. They enable a non-invasive and real-time tracking of the in vivo nanomaterial distribution and facilitate the dose and toxicity management, as discussed previously, fine-tuning the patient-specific treatment protocol [217]. Superparamagnetic iron oxide nanoparticles (SPIONs) is one interesting example of theranostic agent. While it has been used for years as contrast agents in MRI, enabling to increase the quality of images used for diagnostics (with higher spatial resolution), these nanoparticles have recently shown radiosensitizing properties. The presence of these nano-objects within the tumor allows to better define the area to treat and to increase the efficiency of the treatment. These SPIONs can also be coupled to chemotherapeutic drugs, such as doxorubicin, further increasing their therapeutic impact.


Currently, only a relatively small amount of nano-objects are FDA approved for cancer treatment, since the translation toward clinics is an expensive and time-consuming process that is associated with two main challenges [218]:
Large-Scale Manufacture
To enable large clinical trials, drugs have to be produced on a large scale. The Good Manufacturing Practices (GMP) of nanoparticle technology is characterized by a high complexity compared to conventional formulation technologies that usually contain free drug dispersed in a given medium. Indeed, the efficacy of nano-objects is determined by optimal parameters that should be preserved during the scaling-up process. Therefore, nanoparticles have to be manufactured with proper quality standards and with a strict batch-to-batch reproducibility to ensure product specification. Finally, they have to be stable during long-duration storage ensuring the product quality at the time of clinical administration.

Extensive Toxicity Studies
Before a drug candidate can be tested in humans, its safety profile must be proven in animal models. These preliminary tests allow a thorough understanding of its pharmacokinetics and toxicity as well as the establishment of safe limits for further clinical trials.
Preclinical in vivo studies have demonstrated nano-object accumulation in liver and spleen for several months post intravenous injection, raising the question of long-term toxicity for which time-consuming approaches are needed. These toxicological studies are governed by specific rules and regulations of Good Laboratory Practice (GLP), a quality system ensuring the uniformity, consistency, reproducibility, and reliability of non-clinical safety tests. Nevertheless, the current regulatory approaches used for the toxicological assessment of conventional drugs may not be appropriate to fully assess the toxicity of nanomaterials requiring the development of new specific approaches.


To enable large clinical trials, drugs have to be produced on a large scale. The Good Manufacturing Practices (GMP) of nanoparticle technology is characterized by a high complexity compared to conventional formulation technologies that usually contain free drug dispersed in a given medium. Indeed, the efficacy of nano-objects is determined by optimal parameters that should be preserved during the scaling-up process. Therefore, nanoparticles have to be manufactured with proper quality standards and with a strict batch-to-batch reproducibility to ensure product specification. Finally, they have to be stable during long-duration storage ensuring the product quality at the time of clinical administration.


Before a drug candidate can be tested in humans, its safety profile must be proven in animal models. These preliminary tests allow a thorough understanding of its pharmacokinetics and toxicity as well as the establishment of safe limits for further clinical trials.


Preclinical in vivo studies have demonstrated nano-object accumulation in liver and spleen for several months post intravenous injection, raising the question of long-term toxicity for which time-consuming approaches are needed. These toxicological studies are governed by specific rules and regulations of Good Laboratory Practice (GLP), a quality system ensuring the uniformity, consistency, reproducibility, and reliability of non-clinical safety tests. Nevertheless, the current regulatory approaches used for the toxicological assessment of conventional drugs may not be appropriate to fully assess the toxicity of nanomaterials requiring the development of new specific approaches.


Although often used interchangeably, there is a fundamental difference between second and secondary cancers. Second cancer is a more general name for any tumor occurring in patients who have been treated earlier for a first cancer, while the development of a secondary cancer can be ascribed to the treatment for the first cancer. This is not uncommon and should be discussed as part of the process of taking informed consent when explaining the treatment with chemotherapy or RT.


The risk of developing a secondary malignancy following RT depends on:
The organs irradiated

The age at treatment, with younger patients having an increased risk compared to a teenager or adult

The total dose of radiation received

The time from treatment

The prior use of alkylating agent chemotherapy

Underlying genetic predisposition


The age at treatment, with younger patients having an increased risk compared to a teenager or adult


The risk of developing a secondary tumor is cumulative and increasing over time. However, as age increases, the risk relative to the normal population decreases as cancer becomes more common in the general population as well.


Well-known examples are breast cancer, meningiomas, thyroid cancer, and sarcomas. There is an increased risk of development of breast cancer in girls treated for Hodgkin lymphoma under 16 years of age, with a 20% cumulative incidence of breast cancer by the age of 45 [219]. Girls treated with whole lung RT for Wilms tumor are also at risk of breast cancer. There is a well-documented increased incidence of meningiomas associated with cranial RT, with young age at time of RT and time from treatment associated with higher risk. An excess of thyroid cancer and bone and soft tissue sarcoma are also seen in relation to previous RT [220].


There have been concerns about the “low-dose bath” effect of modern RT techniques such as intensity modulated radiotherapy or arc therapy (IMRT/IMAT) increasing the risk of secondary cancers, compared with simple conformal RT. However, IMRT results in greater conformality and reduces the non-target high dose volume. This may offset the increased volume of normal tissue receiving low-dose irradiation. As of today, the feared increase in secondary cancers has not been proven. A major advantage of proton beam RT is the expected reduced risk of secondary malignancy.


Molecular RT may lead to an increased risk of secondary leukemias and cancers, both from the general effects of irradiation of the whole body, and from organ-specific dose, e.g., thyroid uptake of free radioiodine in meta-iodobenzylguanidine (mIBG) therapy, despite the use of thyroid blockade.


RT is not alone in causing cancer. Chemotherapy, particularly alkylating agents, may predispose to the development of myelodysplasia, secondary leukemias, and other malignancies. Chemotherapy and RT may be synergistic in this regard.


Predisposing genetic factors such as retinoblastoma, Li–Fraumeni syndrome, or neurofibromatosis type 1 (NF1) also increase the risk of induction of secondary, but also second, malignancies.


The risk is also related to the underlying cancer, with an increase seen after treatment for Hodgkin lymphoma and sarcoma.


Finally, lifestyle factors contribute to the risk, hence the importance of emphasizing healthy living choices, for example, smoking cessation, normal body weight, and good intake of fruit and vegetables, in survivors to try to mitigate this where possible.


Q1.
Which statement is true? The Continuous Hyperfractionated Accelerated RadioTherapy (CHART) irradiation protocol is characterized by:(a)
A fraction size <2 Gy.
 (b)
Reduced overall treatment time compared with conventional fractionation.
 (c)
Irradiation is continued during the weekend.
 (d)
a, b, and c are all correct.

 Q2.
Why is hyperfractionation potentially beneficial when it comes to late normal tissue sparing relative to conventional fractionation?(a)
The α/β ratio is high.
 (b)
The repair of sublethal damage is very effective.
 (c)
The fraction size <2 Gy.
 (d)
The number of fractions is larger.

 Q3.
On the basis of radiobiological aspects, what would be the optimal number of fractions in a hypofractionated treatment regimen?
 Q4.
Which of the following is not true about Stereotactic Body Radiation Therapy (SBRT)(a)
In SBRT a high dose per fraction is used.
 (b)
SBRT has high conformality.
 (c)
SBRT has a large margin for the beam penumbra.
 (d)
In SBRT image guidance is required for geometric verification of targets.

 Q5.
Please indicate which of the following statements is wrong when it comes to the SBRT treatment planning.(a)
The dose is prescribed to lower isodose lines.
 (b)
A homogeneous dose distribution is seen.
 (c)
There is a sharp dose falloff outside target volume.
 (d)
An isotropic grid size of 2 mm or finer is recommended for dose calculation.

 Q6.
Below are some statements related to how targeted therapy may sensitize tumors to radiation therapy (RT). Please indicate which statements are correct or wrong:(a)
Inhibition of the DNA repair enzyme PARP1 with small molecules is a possible RT sensitizer for all types of tumors.
 (b)
To increase the function of Bcl-2 is a RT sensitizing strategy.
 (c)
Inhibitors toward EGFR is a promising RT sensibilization option for some tumors.
 (d)
Reverting hypoxia is a way for RT sensitization.

 Q7.
Please name a key reason why RT can be combined with some immune therapies?
 Q8.
Hyperthermia has been shown to increase the effect of radiation therapy. Describe a DNA repair pathway that hyperthermia can inhibit.
 Q9.
Name an advantage and a disadvantage of photon spatially fractionated radiation therapy (SFRT), proton minibeam radiotherapy (pMBRT) and ion MBRT?
 Q10.
Give an example of a vectorized radiopharmaceutical used in the clinic and outline how it works.
 Q11.
Helium ions are good candidates in RT of tumors. What makes them good candidates?(a)
Helium ions produce more secondary neutrons compared to protons.
 (b)
Helium ions produce more nuclear fragments compared to carbon ions.
 (c)
Helium ions have higher radiobiological effect (RBE) compared to protons.
 (d)
Helium ions have lower oxygen enhancement ratio (OER) compared to protons.


Which statement is true? The Continuous Hyperfractionated Accelerated RadioTherapy (CHART) irradiation protocol is characterized by:(a)
A fraction size <2 Gy.
 (b)
Reduced overall treatment time compared with conventional fractionation.
 (c)
Irradiation is continued during the weekend.
 (d)
a, b, and c are all correct.


Why is hyperfractionation potentially beneficial when it comes to late normal tissue sparing relative to conventional fractionation?(a)
The α/β ratio is high.
 (b)
The repair of sublethal damage is very effective.
 (c)
The fraction size <2 Gy.
 (d)
The number of fractions is larger.


On the basis of radiobiological aspects, what would be the optimal number of fractions in a hypofractionated treatment regimen?


Which of the following is not true about Stereotactic Body Radiation Therapy (SBRT)(a)
In SBRT a high dose per fraction is used.
 (b)
SBRT has high conformality.
 (c)
SBRT has a large margin for the beam penumbra.
 (d)
In SBRT image guidance is required for geometric verification of targets.


In SBRT image guidance is required for geometric verification of targets.


Please indicate which of the following statements is wrong when it comes to the SBRT treatment planning.(a)
The dose is prescribed to lower isodose lines.
 (b)
A homogeneous dose distribution is seen.
 (c)
There is a sharp dose falloff outside target volume.
 (d)
An isotropic grid size of 2 mm or finer is recommended for dose calculation.


An isotropic grid size of 2 mm or finer is recommended for dose calculation.


Below are some statements related to how targeted therapy may sensitize tumors to radiation therapy (RT). Please indicate which statements are correct or wrong:(a)
Inhibition of the DNA repair enzyme PARP1 with small molecules is a possible RT sensitizer for all types of tumors.
 (b)
To increase the function of Bcl-2 is a RT sensitizing strategy.
 (c)
Inhibitors toward EGFR is a promising RT sensibilization option for some tumors.
 (d)
Reverting hypoxia is a way for RT sensitization.


Inhibition of the DNA repair enzyme PARP1 with small molecules is a possible RT sensitizer for all types of tumors.


To increase the function of Bcl-2 is a RT sensitizing strategy.


Inhibitors toward EGFR is a promising RT sensibilization option for some tumors.


Please name a key reason why RT can be combined with some immune therapies?


Hyperthermia has been shown to increase the effect of radiation therapy. Describe a DNA repair pathway that hyperthermia can inhibit.


Name an advantage and a disadvantage of photon spatially fractionated radiation therapy (SFRT), proton minibeam radiotherapy (pMBRT) and ion MBRT?


Give an example of a vectorized radiopharmaceutical used in the clinic and outline how it works.


Helium ions are good candidates in RT of tumors. What makes them good candidates?(a)
Helium ions produce more secondary neutrons compared to protons.
 (b)
Helium ions produce more nuclear fragments compared to carbon ions.
 (c)
Helium ions have higher radiobiological effect (RBE) compared to protons.
 (d)
Helium ions have lower oxygen enhancement ratio (OER) compared to protons.


Helium ions have lower oxygen enhancement ratio (OER) compared to protons.


SQ1.
Alternative (d). All statements (a, b, c) about the CHART irradiation protocol are correct. It involves a fraction size of <2 Gy and treatments are given during weekends giving a reduced treatment time compared to a conventional fractionation scheme.
 SQ2.
Alternative (c). The fraction size <2 Gy.
 SQ3.
Taking the normal tissue dose-volume constraints into account and considering, e.g., the kinetics of reoxygenation, the activation of the immune system and the abscopal effect, a number of six to eight medium sized fractions spaced 72 h might be optimal regarding tumor control. However, this is still a point of debate.
 SQ4.
Alternative (c). In SBRT, small or no margin is given for beam penumbra to improve sharp dose falloff.
 SQ5.
Alternative (b). SBRT treatment plans have a heterogenous dose distribution.
 SQ6.
(a). The statement is wrong. PARP1 is primarily a target in tumors that have mutations in BRCA1/BRAC2 or have a “BRACAness” phenotype. Such tumors lack functional DNA repair via HR and hence blocking PARP can impair repair of RT-induced DNA DSB. This is called synthetic lethality. PARP inhibition can also be applied for tumors with impairment in ATM or ATR. (b). The statement is wrong. Bcl-2 is an anti-apoptotic protein. Its activity/expression needs to be inhibited in order for RT to more prominently trigger cell death. (c). The statement is correct. EGFR inhibitors work in EGFR-mutant tumors, i.e., NSCLC or in tumors over-expressing EGFR. (d). The statement is correct. Tumor hypoxia can be attacked for RT sensitization purpose in several different ways.
 SQ7.
Since radiotherapy (RT) does exert both, immune stimulatory and immune suppressive effects, immune therapies aim to switch off the immune suppressive effects of RT or to boost the immune activating ones can be applied. This may result in effective local and systemic antitumor immune responses.
 SQ8.
Hyperthermia can temporarily downregulate the BRCA2 protein, thereby blocking the homologous recombination.
 SQ9.

Photon SFRT

Proton MBRT

Ion MBRT

Advantage

Easy implementation in clinic

Homogeneous tumor irradiation already from one direction

(Almost) no widening on the way to the tumor

Disadvantage

Low PVDR compared to MBRT

Widening of the beams on the way to the tumor

Technically challenging as interlacing necessary for homogeneous tumor irradiation

 SQ10.
Examples of vectorized radionuclide therapy are 177Lu-PSMA-617 for the treatment of prostate cancer, 177Lu-NeoB for the treatment of solid metastatic tumors, 177Lu-DOTATATE for the treatment of neuroendocrine tumors, and 90Y-ibritumomab tiuxetan (Zevalin®) for the treatment of CD20-positive Non-Hodgkin lymphoma. Brief description of the principle: A radiopharmaceutical comprises a targeting moiety, which targets a specific molecule expressed on certain cells, and a radionuclide, which emits IR. By linking the targeting moiety to the radionuclide, molecules (e.g., somatostatin receptors, PSMA, CD20, etc.) that are highly expressed on the target tissue can be targeted to treat disease. Thus, the targeting moiety ensures specific delivery of toxic IR to the targeted cells which ensures treatment of the tumor disease, while causing minimal damage to surrounding healthy tissues.
 SQ11.
Alternative (c). Helium ions have higher RBE compared to protons.


Alternative (d). All statements (a, b, c) about the CHART irradiation protocol are correct. It involves a fraction size of <2 Gy and treatments are given during weekends giving a reduced treatment time compared to a conventional fractionation scheme.


Alternative (c). The fraction size <2 Gy.


Taking the normal tissue dose-volume constraints into account and considering, e.g., the kinetics of reoxygenation, the activation of the immune system and the abscopal effect, a number of six to eight medium sized fractions spaced 72 h might be optimal regarding tumor control. However, this is still a point of debate.


Alternative (c). In SBRT, small or no margin is given for beam penumbra to improve sharp dose falloff.


Alternative (b). SBRT treatment plans have a heterogenous dose distribution.


(a). The statement is wrong. PARP1 is primarily a target in tumors that have mutations in BRCA1/BRAC2 or have a “BRACAness” phenotype. Such tumors lack functional DNA repair via HR and hence blocking PARP can impair repair of RT-induced DNA DSB. This is called synthetic lethality. PARP inhibition can also be applied for tumors with impairment in ATM or ATR. (b). The statement is wrong. Bcl-2 is an anti-apoptotic protein. Its activity/expression needs to be inhibited in order for RT to more prominently trigger cell death. (c). The statement is correct. EGFR inhibitors work in EGFR-mutant tumors, i.e., NSCLC or in tumors over-expressing EGFR. (d). The statement is correct. Tumor hypoxia can be attacked for RT sensitization purpose in several different ways.


Since radiotherapy (RT) does exert both, immune stimulatory and immune suppressive effects, immune therapies aim to switch off the immune suppressive effects of RT or to boost the immune activating ones can be applied. This may result in effective local and systemic antitumor immune responses.


Hyperthermia can temporarily downregulate the BRCA2 protein, thereby blocking the homologous recombination.


Photon SFRT

Proton MBRT

Ion MBRT

Advantage

Easy implementation in clinic

Homogeneous tumor irradiation already from one direction

(Almost) no widening on the way to the tumor

Disadvantage

Low PVDR compared to MBRT

Widening of the beams on the way to the tumor

Technically challenging as interlacing necessary for homogeneous tumor irradiation


Examples of vectorized radionuclide therapy are 177Lu-PSMA-617 for the treatment of prostate cancer, 177Lu-NeoB for the treatment of solid metastatic tumors, 177Lu-DOTATATE for the treatment of neuroendocrine tumors, and 90Y-ibritumomab tiuxetan (Zevalin®) for the treatment of CD20-positive Non-Hodgkin lymphoma. Brief description of the principle: A radiopharmaceutical comprises a targeting moiety, which targets a specific molecule expressed on certain cells, and a radionuclide, which emits IR. By linking the targeting moiety to the radionuclide, molecules (e.g., somatostatin receptors, PSMA, CD20, etc.) that are highly expressed on the target tissue can be targeted to treat disease. Thus, the targeting moiety ensures specific delivery of toxic IR to the targeted cells which ensures treatment of the tumor disease, while causing minimal damage to surrounding healthy tissues.


Alternative (c). Helium ions have higher RBE compared to protons.


The term “radiosensitivity” is one of the most extensively used words in radiobiology. It was described as radiation-induced tissue reactions (e.g., skin is radiosensitive) in the first decade of the nineteenth century [1]. Since 1930s, with the first Congresses of Radiology, the term “radiosensitivity” was also used as a synonym of radiation-induced cancers (e.g., thyroid is a radiosensitive organ) and progressively was used for radiation-induced cataracts (e.g., eyes are radiosensitive [2]). All these different uses lead to an actual confusion and notably raise legal issues since radiation-induced cancers, cataracts, or skin burns do not correspond to the same level of clinical injuries [3].


To avoid these confusions, a possible approach is to consider all the major clinical features of the response to radiation by using unequivocal terms that could be indifferently applied to the individual, tissue, cellular, or molecular scales. To consolidate this approach, it is important to document the individual response to radiation through a complete knowledge of its different features. For example, it is noteworthy that ataxia telangiectasia (AT), caused by homozygous mutations of the AT mutated (ATM) gene resulting in aberrant ATM protein, is associated with post-RTfatal reactions and high risk of leukemia [4], while Li Fraumeni’s syndrome is associated with cancer proneness but not with significant post-RT adverse tissue reactions [5]. Conversely, Cockayne’s syndrome is associated with significant tissue radiosensitivity but no cancer proneness [6].


Hence, the following definition has been therefore proposed in literature [7] and summarized in Table 7.1.Table 7.1
Summary of the terms—radiosensitivity, radiosusceptibility, and radioresistance

Radiosensitivity

Radiosensitivity refers to adverse healthy tissue reactions like burns, dermatitis, rectitis, etc., that is, any reaction led by radiation-induced cell death that may be generally accompanied by inflammation.

Radiosensitivity also refers to the inherent response of tumor/cancer cells to radiation which can be measured by the reduction of the volume, the extent of regression, rapidity of response, and response durability that are also linked to radiation-induced cell death.

The degree of radiosensitivity depends on the combination of various genetic traits, interaction with each other, ability to repair damage, hypoxia, cell cycle position, growth fraction, hormonal balance, immune system, and various environmental factors.

The probable cause of radiosensitivity may be an insufficient repair of the radiation-damaged DNA generally due to defective DNA damage signaling and/or repair mechanism.

Radiosusceptibility

The proneness to radiation-induced cancers generally linked to radiation-induced cell transformation and mis-repaired DNA damage.

It is also an important issue for both low- and high-dose radiation exposures to an individual who exhibits higher cancer risk spontaneously.

Differences in radiosusceptibility between individuals, or groups, may relate to genetic constitution, but also to other characteristics such as age at exposure, health status and comorbidity, epigenetic factors, lifestyle, and co-exposures to other stressors.

Radiodegeneration

The term is to describe any aspects of IR responses (non-cancer effects) attributable to mechanisms related to accelerated aging.

Radioresistance

Radioresistance describes a normal response to IR at any level; whether molecular, cellular, tissular, and clinical.

In terms of radiosensitivity, radioresistance is the synonym of absence of any adverse tissue reactions and of a normal DNA damage repair (rate and efficiency).

In terms of radiosusceptibility, radioresistance is synonymous with a low risk of radiation-induced cancer.

In terms of radiodegeneration, radioresistance is synonymous with a low risk of radiation-induced aging.


“Radiosensitivity” is the proneness to radiation-induced adverse tissue events that are considered as non-cancer effects attributable to cell death. Radiosensitivity is generally correlated with unrepaired DNA damage and observed in response to high doses of radiation [8] (Box 7.1).

“Radiosusceptibility” is the proneness to radiation-induced cancers which are non-toxic effects attributable to cell transformation and/or genomic instability (in part correlated with DNA misrepair). Since IR is considered to be a carcinogenic agent, radiosusceptibility is distinctly and strongly linked to susceptibility to spontaneous cancer induction. The term “radiosusceptibility” was proposed due to its similarities with “cancer susceptibility,” extensively used in the ICRP (International Commission on Radiological Protection) reports and since it introduces the notions of stochastic events [9].

“Radiodegeneration” responses are non-cancer effects attributable to mechanisms which are related to accelerated aging and often correlated with unrepaired DNA damage that is tolerated by and accumulated in cells [9]. Radiodegeneration responses cannot be considered like radiosensitivity responses as defined above since their incidence rates, the types of cellular death, and the genes involved are different.


“Radiosensitivity” is the proneness to radiation-induced adverse tissue events that are considered as non-cancer effects attributable to cell death. Radiosensitivity is generally correlated with unrepaired DNA damage and observed in response to high doses of radiation [8] (Box 7.1).


“Radiosusceptibility” is the proneness to radiation-induced cancers which are non-toxic effects attributable to cell transformation and/or genomic instability (in part correlated with DNA misrepair). Since IR is considered to be a carcinogenic agent, radiosusceptibility is distinctly and strongly linked to susceptibility to spontaneous cancer induction. The term “radiosusceptibility” was proposed due to its similarities with “cancer susceptibility,” extensively used in the ICRP (International Commission on Radiological Protection) reports and since it introduces the notions of stochastic events [9].


“Radiodegeneration” responses are non-cancer effects attributable to mechanisms which are related to accelerated aging and often correlated with unrepaired DNA damage that is tolerated by and accumulated in cells [9]. Radiodegeneration responses cannot be considered like radiosensitivity responses as defined above since their incidence rates, the types of cellular death, and the genes involved are different.


Radiosensitivity differs throughout the cell cycle with, in general, G1 phase taking an intermediate position, and late S phase being most radioresistant.

The greater proportion of repair by HR than by NHEJ in late S phase may explain the resistance of late S phase cells.

Chromatin compaction and poor repair competence (reduced enzyme access) could explain the high radiosensitivity in G2/M.


Radiosensitivity differs throughout the cell cycle with, in general, G1 phase taking an intermediate position, and late S phase being most radioresistant.


The greater proportion of repair by HR than by NHEJ in late S phase may explain the resistance of late S phase cells.


Chromatin compaction and poor repair competence (reduced enzyme access) could explain the high radiosensitivity in G2/M.


A biomarker is an objective feature with one or more defined characteristics which indicate specific normal biological and pathological processes, or responses to an exposure or to therapeutic interventions. To date, radiation biomarkers are primarily identified in blood or saliva and are measurable indicators that reflect an interaction between a biological system and one or more environmental agents (chemical, physical, or biological). Biomarkers provide crucial information on the complex molecular cascade of events and their mechanisms underlying the pathological conditions or pharmacological responses to a therapeutic intervention.


Biomarkers can be used to assess various different types of biological characteristics or parameters. These include genetic sequences, receptor expression patterns, radiographic or other imaging-based measurements, blood composition, electrocardiographic parameters, or organ function. Since biomarkers are quantifiable, they can be used to characterize the response to direct or indirect IR exposure, to select radiation dose, and to assess the potential safety issues related to dose administration. A large number of such biomarkers have been developed over the years; the characteristics of the different classes of radiation biomarkers will be reviewed in Sect. 7.2.2.


Although the definitions, nature, and use of biomarkers are multiple and rapidly evolving with the sophisticated—omics technologies, they must be evaluated in terms of their ability to address etiology and genetic susceptibility, predict and quantify dose of exposure. There are certain properties which are desirable when linking a biomarker with an exposure, e.g., IR. These include high specificity and sensitivity, known variability in the general population, should give reproducible results when assessed and multiplexing of analyses to allow for screening purposes. Some additional desirable characteristics of an ideal biomarker can be listed for use in large scale molecular epidemiological studies: (a) Early expressivity; (b) Linear relationship across time; (c) Strong correlation with a health effect; (d) Reproducible between laboratories; (e) Biologically plausible; (f) Inexpensive and feasible for sample collection; (g) Consistency (the same exposure will produce the same concentration of the biomarker every time).


Radiation biology research has identified several approaches, especially the “omics” fields, as promising avenues for the development of suitable biomarkers of high sensitivity and specificity for radiation exposure. Radiation epidemiology biomarkers should preferably be specific to radiation and independent of other environmental exposures such as tobacco or cigarette smoke. Such a biomarker would simplify analysis and help to substantiate radiation causality. Though biological biomarker often lack specificity, they can still be informative in predicting the development of radiation-induced disease if such exposures are additive or interactive. Multi-biomarker approaches should be particularly useful in epidemiological studies, both for (1) assessing exposure–response relationships and how they vary with individual susceptibility and (2) to understand better disease mechanisms and the interplay of different possible pathways.


Contrariwise, carefully planned molecular epidemiological studies are crucial for the validation and verification of biomarkers, to determine their specificity and sensitivity as well as factors that might influence them (e.g., age, sex, smoking status, environmental agents, chronic conditions such as inflammation or individual sensitivity) [10].


The ultimate goal of using biomarkers in molecular epidemiological studies is to be able to predict health risk. The types of biomarkers mentioned in Table 7.2 hold substantial prospective in epidemiological studies; however, there are a number of key questions to be considered which are generic to their application. Among these are: “What to measure?” “Where to measure?” and “When to measure?”Table 7.2
Classification of biomarkers based on temporal parameters

Biomarkers of exposure

• Available at some point after exposure.
• Suitable for estimating the dose received and identifying human internal exposure to environmental and occupational chemicals/radiation by using novel techniques and approaches.
• Biomarkers of this category can have potential for use in radiation oncology to provide information on the probable outcome of RT.
• Cytogenetic biomarkers are the best dosimetry biomarkers of radiation exposure as they show a high degree of specificity and sensitivity.
• Emerging biomarkers related to alterations in transcriptional profiles can have potential as biomarkersBiomarkers of exposure [11].

Biomarkers of susceptibility

• Available before, during, or after exposure.
• Provide key information which reflect intrinsic characteristics toward adverse effects of an exposure and thus predict an increased risk of radiation-induced health effects.
• Appropriate to provide meticulous knowledge of the exposure-risk relationship, and variability of risks between individuals of identical or different population/subgroups.
• Genetic variants (polymorphism) and/or metabolic phenotypes associated with cancer predisposition may prove to be useful biomarkers of susceptibility.
• Cytogenetic endpoints (e.g., the G2 assay) are of interest as biomarkers of susceptibility.

Biomarkers of late effects

• Suitable for assessing a long-time health effects post exposure, even before clinical detection of radiation induced disease or death.
• Cytogenetic assays emphasize some potential as biomarkers of late effects of radiation exposure to predict the risk of RT side effects.
• Transcriptional biomarkers can be employed to identify either pathways or gene expression signatures predictive of susceptibility and late health effects.

Biomarkers of persistent effects

• Applicable to assess radiation effects present a long period of time after exposure.
• Biomarkers of exposure and effects may potentially be used to identify individuals at higher risk of development of cancer.
• Chiefly an aspirational category on the basis of current science.


Determining if a biomarker is a good biomarker (the characteristics to determine an ideal biomarker are outlined in Fig. 7.1) for molecular epidemiological studies is complex because this relies on a number of different concepts associated with the radiation exposure and otherwise, which will very much depend on the biological samples such as cells (buccal cells, fibroblasts, hair follicle cells, etc.), blood, saliva, urine, tooth, hair, nail which can be collected non-invasively at different time points post IR exposure to study biological effects.

An illustration of characteristics of an ideal biomarker. For molecular epidemiological studies: validity of the assay and marker, suitability of the marker and assay, invasiveness, and acceptability. General: Ease, cost, interindividual variation, speed, background, and radiation specificity.

Fig. 7.1
Characteristics to determine an ideal biomarker. An ideal biomarker for molecular epidemiological studies (top) and general considerations of a good biomarker (bottom)


An illustration of characteristics of an ideal biomarker. For molecular epidemiological studies: validity of the assay and marker, suitability of the marker and assay, invasiveness, and acceptability. General: Ease, cost, interindividual variation, speed, background, and radiation specificity.


There is a great interest in developing new biomarkers for radiation exposure, which could be used in large molecular epidemiological studies in order to correlate estimated doses received by individuals and health effects using high-throughput technologies, i.e., “omics.” In these instances, biomarkers can provide a measure of external exposure as well as internal absorption of radioactive material and can thus be markers of internal dose as well. However, factors other than the exposure may influence biomarker expression, and thus there may not always be a simple relationship between external exposure and internal dose. For example, DNA or protein adducts may be applicable as markers of other processes such as absorption, distribution, metabolism, and DNA repair, as well as of exogenous exposure. As a result, the measured internal radiation doses (biomarkers) will be an amalgam of exposure and these variables.


In a nutshell, reliable radiation biomarkers databases can be shaped by integrating the information from radiation genomics, metabolomics, and proteomic analysis in order to expand the scientific frontiers on predicting and/or monitoring radiation exposure-associated effects. Such protocols along with more sophisticated technologies are probably vital for the development of personalized medicine and will undoubtedly prove highly useful to bring a new horizon of therapeutic possibilities [12] (Box 7.2).


Biomarkers and/or biological dosimeters are essential for predicting and/or monitoring radiation exposure-associated effects, quantifying the exposure, estimating absorbed radiation dose in certain accidental situations or a suspected radiation overexposure.

Radiation epidemiology biomarkers should be specific to radiation and independent of other factors that might influence them (such as age, chronic conditions, smoking, tobacco, or individual sensitivity).

Identifying biomarkers of IR exposure employs a multi-parametric approach to achieve an accurate dose and risk estimation.


Biomarkers and/or biological dosimeters are essential for predicting and/or monitoring radiation exposure-associated effects, quantifying the exposure, estimating absorbed radiation dose in certain accidental situations or a suspected radiation overexposure.


Radiation epidemiology biomarkers should be specific to radiation and independent of other factors that might influence them (such as age, chronic conditions, smoking, tobacco, or individual sensitivity).


Identifying biomarkers of IR exposure employs a multi-parametric approach to achieve an accurate dose and risk estimation.


Several biological responses can act as potential biomarkers for IR exposure. They are linked to cellular or physiological mechanisms which have been shown to change soon after radiation exposure. The use of various “omic” technologies together with hypothesis-driven approaches may be highly useful to measure radiation biomarkers in a biological system. Some biomarkers could be used as response markers or as surrogate endpoints to predict radiation side effects. The expression levels of many biomarkers can be expected to be correlated with each other and so could be classified in multiple categories, such as
Phosphorylated histone H2AX (γ-H2AX) acts as protein biomarker for radiation exposure but is useful as a DNA damage marker; suggesting a close one-to-one relationship between initial as well as residual radiation-induced DNA DSBs and γ-H2AX foci.

8-oxo-dG acts as a marker of nucleotide damage but is strongly associated as a maker of oxidative DNA damage suggesting it is produced abundantly in DNA exposed to free radicals and reactive oxygen species (ROS).

Phosphoproteomic profiling insights into processes influenced by epigenetic modifications, but also uncovers signaling pathways.


Phosphorylated histone H2AX (γ-H2AX) acts as protein biomarker for radiation exposure but is useful as a DNA damage marker; suggesting a close one-to-one relationship between initial as well as residual radiation-induced DNA DSBs and γ-H2AX foci.


8-oxo-dG acts as a marker of nucleotide damage but is strongly associated as a maker of oxidative DNA damage suggesting it is produced abundantly in DNA exposed to free radicals and reactive oxygen species (ROS).


Phosphoproteomic profiling insights into processes influenced by epigenetic modifications, but also uncovers signaling pathways.


These biomarkers can be organized in categories such as (a) cytogenetic; (b) nucleotide pool damage and DNA damage; (c) germline inherited mutations or variants; (d) induced mutations; (e) transcriptional and translational changes; (f) epigenetic modifications; (g) lipid peroxidation; (h) others, including biophysical markers (Fig. 7.2).

An illustration of the types of radiation biomarkers. The types are cytogenetics, nucleotide pool damage and D N A damage, germline inherited mutations or variants, induced mutations, transcriptional and translational changes, epigenetic modifications, lipid peroxidation, biophysical, and others.

Fig. 7.2
Biological classification of radiation biomarkers. (Reproduced with permission, with some modification (changed layout and some content), from [10]; licensed under CC BY-NC-ND 3.0)


An illustration of the types of radiation biomarkers. The types are cytogenetics, nucleotide pool damage and D N A damage, germline inherited mutations or variants, induced mutations, transcriptional and translational changes, epigenetic modifications, lipid peroxidation, biophysical, and others.


Biomarkers of radiation exposure are further discussed in Chaps. 2, 3, and 8.


Over the past decades, the definition and classification of the different types of biomarkers have varied slightly, depending on the biomedical field considered. Biomarkers are an important aspect of radiation countermeasure development and can be used as a trigger for intervention as well as in selecting a radiation dose and treatment regimen in humans, e.g., in the context of RT of cancer ([13] and as further discussed here in Chap. 7 and in Chap. 8). Biomarkers can also provide information on potential modifying/confounding factors to allow an assessment of biological interactions. Pernot et al. [10], Hall et al. [14] classified biomarkers into four broad categories, based on their temporal parameters Table 7.2.


One should be cognizant of the fact that overlap does exist between these different types of biomarkers. Taken together, these attributes enable a better understanding of exposure and its effect on biological pathways across different forms of exposure, health changes, disease headway; providing more meaningful comprehensive risk assessment (Fig. 7.3). This classification is acceptable not only with respect to the timing of processes that can be measured with these biomarkers, but also in considering the most adequate designs and sampling procedures in molecular epidemiological studies (Box 7.3).

An illustration of the progression of different biomarkers over time when there is a low dose ionizing radiation exposure. Exposure: Increases and decreases. Susceptibility: Remains constant. Late effects: Increases. Persistent effect: Remains constant through stages.

Fig. 7.3
Timeline of radiation-induced disease progressions and relation with different types of radiation biomarkers. (Reproduced with permission, with some modification (changed color and layout), from [10]; licensed under CC BY-NC-ND 3.0)


An illustration of the progression of different biomarkers over time when there is a low dose ionizing radiation exposure. Exposure: Increases and decreases. Susceptibility: Remains constant. Late effects: Increases. Persistent effect: Remains constant through stages.


Biomarkers of exposure are available at some point after exposure and are suitable for estimating the dose received.

Biomarkers of susceptibility can be available before, during, or after exposure and can predict an increased risk of radiation effects.

Biomarkers of late effects can be used to assess health effects that are present a long time after exposure before clinical detection of the radiation induced disease or death.

Biomarkers of persistent effects allow the assessment of radiation effects present a long period of time after exposure.


Biomarkers of exposure are available at some point after exposure and are suitable for estimating the dose received.


Biomarkers of susceptibility can be available before, during, or after exposure and can predict an increased risk of radiation effects.


Biomarkers of late effects can be used to assess health effects that are present a long time after exposure before clinical detection of the radiation induced disease or death.


Biomarkers of persistent effects allow the assessment of radiation effects present a long period of time after exposure.


Not only since the “age of OMICS,” it is well known that the collection of samples from patients and healthy volunteers is essential for future research [15]. Especially in radiation research, the collection of biological samples represents a significant part of translational research, since, especially in studies on radiation protection, the collected biological samples represent an essential parameter for analysis of (historic) radiation exposure [14]. Also, in therapeutic trials, the sampling of tissues and body fluids has an immense impact on the search, discovery, and validation of novel biomarkers supporting the pathological diagnosis as well as for the determination of therapy toxicity and/or outcome [15, 16]. The collected samples may safely expand the possibilities of the entire analytical process within prospective and retrospective trials in radiation science. However, the collection and storage of biological samples should always be done within a quality-controlled manner [17]. In contrast to tissue sampling, the sampling of body fluids also has the big advantage, that these samples are nearly always available or easy to access like vein puncture. In addition, the sampling of blood can be done mostly together with clinical mandatory blood draws, minimizing the burden of the patient/donor, and enhancing the amount of time points of sampling as well as it also increases the donor’s acceptance of giving blood for research. Since the collection of samples at biobanks accelerate the process of transferring scientific knowledge into therapeutic application, it should be the duty of clinical researchers adding translational programs with sample collection to the prospective clinical trials. In our hands, the sampling and analysis of immunological parameters lead to predictive biomarkers supporting the pathological diagnosis and therapeutic intervention and helping radiation treatment in precision medicine [16, 18].


The sampling, the processing, as well as the storage have to be done in a quality-controlled manner as outlined before by Winter and colleagues [19] or at the respective international biobank consortia like the European, Middle Eastern and African Society for Biopreservation and Biobanking (ESBB), or the European research infrastructure for biobanking (BBMRI-ERIC; [20]). There are another three very important things to keep in mind when collecting samples for later analysis: The best collections are almost worthless if they are not connected with clinical, radiation exposure, and patients/donor data. Along with this, the informed consent of the donor should allow use of the samples for the respective analyses even when the samples will be given for, e.g., “OMICS” analysis to a cooperation partner or to the statistician who performs the analysis of the data. Lastly, a biobank is a living “thing” which should be used for research and not as a secure vault to store samples for eternity. Taken together, it should be the duty of research on humans to collect and store samples for further analyses, but also processing and storage should be carried out in accordance with applicable regulations and standards. This is the only way to ensure that the samples do not suffer any loss of value and are available for later applications.


Tissue reactions induced by IR are the result of different types of cell death (mitotic death, apoptosis, autophagy, senescence, etc.). Loss of clonogenicity (and not physical disappearance or metabolic shutdown) appeared to be common to all types of cell death.


In 1957, Puck and Markus proposed to use clonogenic assays (or colony method) to quantify cellular radiosensitivity [21] (Fig. 7.4). The assay is based on the ability of an individual tumor cell to grow into a colony after exposure to various doses of radiation given the surviving fraction (SF) at each dose. The fraction of cells surviving after 2 Gy (SF2) has been demonstrated to be a robust predictor for radiation sensitivity but colony formation can take 7–14 days. Several predictive tests have been proposed to approach clonogenic survival but with a suboptimal statistical power.

An illustration of eight steps in the clonogenic assay. 1. Collect patient tumor material. 2. Obtain single cell suspension. 3. Seed cells into plate wells. 4. Irradiate cells. 5. Wait 1 to 3 weeks for results. 6. Stain cells. 7. Manually enumerate colonies. 8. Calculate survival fraction.

Fig. 7.4
Brief overview of the original clonogenic assay


An illustration of eight steps in the clonogenic assay. 1. Collect patient tumor material. 2. Obtain single cell suspension. 3. Seed cells into plate wells. 4. Irradiate cells. 5. Wait 1 to 3 weeks for results. 6. Stain cells. 7. Manually enumerate colonies. 8. Calculate survival fraction.


The original clonogenic assay can be performed in two different ways (1) irradiation after plating or (2) plating after irradiation. The first is usually carried out to investigate intrinsic radiosensitivity to varying modalities (types) of treatment, and the second allows for the assessment of reproductive ability. The irradiation after plating method is presented in Fig. 7.4 as it is usually used in radiobiological studies. Further details on the clonogenic assay can be seen in Chap. 3.


Several techniques continue to rely on cell culture:
The level of radiation-induced micronuclei (MN) has been quantitatively correlated with radiosensitivity since the 1960s thanks to a simple and robust protocol consisting of blocking the process of cytokinesis by drugs such as cytochalasin B [22].

The premature chromosome condensation (PCC) assay consists in making chromosome fragments appear more quickly by fusing the tested cell with a cell in mitosis. The heterokaryon thus formed allows the exchange of mitotic factors in the cell into G0/G1 and then produces premature condensation of the chromatin [23].

The enumeration of chromosomal aberrations by fluorescence in situ hybridization technique.


The level of radiation-induced micronuclei (MN) has been quantitatively correlated with radiosensitivity since the 1960s thanks to a simple and robust protocol consisting of blocking the process of cytokinesis by drugs such as cytochalasin B [22].


The premature chromosome condensation (PCC) assay consists in making chromosome fragments appear more quickly by fusing the tested cell with a cell in mitosis. The heterokaryon thus formed allows the exchange of mitotic factors in the cell into G0/G1 and then produces premature condensation of the chromatin [23].


The enumeration of chromosomal aberrations by fluorescence in situ hybridization technique.


It made sense to focus on the molecular mechanisms of the cellular response to radio-induced damage to DNA and in particular to DNA repair, since a quantitative link between unrepaired Double-Strand Breaks (DSB), chromosomal breaks, and radiation-induced clonogenic cell death was demonstrated [24]. Moreover, the vast majority of genetic syndromes associated with individual radiosensitivity are linked to mutations in genes involved in radiation-induced DSB signaling or repair. DSB measurement techniques were investigated with some confusion on their specificity and instead reflected other types of damage [7]. The first techniques for measuring DSB were based on discriminating radiation-induced DNA fragments based on their size. This was particularly the case with sedimentation in sucrose gradients, neutral elution, and pulsed-field electrophoresis. Such a principle has the advantage of measuring the repair of DSBs independently of any molecular repair pathways regardless of the post-irradiation time. On the other hand, these techniques do not make it possible to assess the quality of the repair, that is to say whether it is faithful or at fault.


The halo technique consists, using fluorescent intercalators, in quantifying such an increase in the nucleus. The comet technique combines electrophoresis and the halo technique, both applied individually to each cell. Data from the comet technique are usually given in the form of the product of the increase in the size of the nucleus (comet head) times the distance that DNA fragments migrate (comet tail) [25].


From 2003, with indirect immunofluorescence, it became possible to follow precisely and in real time in the nucleus and for a wide dose spectrum, the kinetics of appearance/disappearance of DNA repair proteins (foci). A correlation between SF2 and the rate of unrepaired DSB 24 h after 2 Gy (γ-H2AX marker) could be demonstrated—constituting a functional repair test [26]. A second marker significantly increased the performance of the test—based on the speed of nuclearization and the functionality of the pATM protein in the nucleus [8].


Genome-wide association (GWAS) studies have been widely used to identify associations between commonly occurring variations in DNA sequence, such as single nucleotide polymorphisms (SNP) and human traits such as individual radiosensitivity [27]. A few SNP as well as mitochondrial haplogroups have been reported.


The interest in the predictive power of the transcriptome began in the early 2000s and in vitro transcriptomic signatures for individual radiosensitivity then emerged. The identified predictive genes were associated with cellular functions such as TGFβ pathway, particularly extracellular matrix remodeling, apoptosis, proliferation, and ROS scavenging [28, 29] (Table 7.3).Table 7.3
Reported gene expression signatures for individual radiosensitivity

Publication

RS patients

RR patients

Radiation scheme

Selected differentially expressed genes

Assay used for gene selection

Quarmby et al. [28]

3

3

Not irradiated

FMLP-R-I, TNFα, NGFR, EPHB2, PDGFB, NTRK1, LFNG, DDR1; IFNGR1

Cytokine array

Alsner et al. [30]

22

4

3 × 3.5 Gy over 3 days, RNA extracted 2 h after last irradiation

CDC6, CDON, CXCL12, FAP, FBLN2, LMNB2, LUM, MT1X, MXRA5, SLC1A3, SOD2, SOD3, WISP2

15K cDNA microarray

Rødningen et al. [31]

10

4

3 × 3.5 Gy over 3 days, RNA extracted 2 h after last irradiation

PLAGL1, CCND2, CDC6, DEGS1, CDON, CXCL12, MXRA5, LUM, MT1X, MT1F, MT1H, C1S, NF1, ARID5B, SCL1A3, TM4SF10, MGC33894, ZDHHC5/MFGE8

15K cDNA microarray

Forrester et al. [32]

6

8

Not irradiated

FBN2, FST, GPRC5B, NOTCH3, PLCB1, DPT, DDIT4L, SGCG

GeneChip Human Exon 1.0 ST Array


Epigenetic modifications include histone modifications such as acetylations and methylations, DNA methylation, particularly on CpG island, non-coding RNAs, and three-dimensional chromatin organization. As this a relatively new field, only few studies have been conducted on the epigenetic regulations of skin fibrosis, mainly on miRNAs [32, 33].


Ozsahin et al. [34] developed a rapid radiosensitivity test (<24 h) based on lymphocyte apoptosis, a biological response developing 6–72 h after irradiation. The authors showed that low Radio-Induced Lymphocytic Apoptosis (RILA) was significantly correlated with late grade ≥2 tissue toxicities.


In recent years, the identification of routinely available blood and clinical markers that may help to predict the response to immune therapies alone and in multimodal settings including RT has been in focus of scientists of several disciplines and clinicians [35, 36]. Here, immune markers of the peripheral blood are key factors, since they circulate in the body and enter several tissues in response to disease, therapy, and stressors such as radiation. Stress and immune parameters should jointly be considered, and a differentiation between primary radiation signatures and consecutive systemic immune biosignatures is challenging, but anyhow interconnected [37, 38]. Notably, single immune parameters are insufficient, but rather immune profiles that reflect the complexity of the immune system and the manifold interactions of its cellular and soluble components [16, 39].


Tumor response to RT is a multi-faceted metric of outcomes after radiotherapeutic treatment, often observed through biopsy of the tumor or liquid biopsy. There is currently no universal definition of tumor response, but it can generally be considered as any favorable response of the tumor to therapy. Tumor biopsies may aid in the development of personalized patient treatment regimens by providing molecular and structural material for use in developing metrics capable of identifying who will or who will not favorably respond to RT. For patients who do not respond favorably to treatment, they can be offered another more effective avenue of treatment, sparing them from treatment toxicity.


Identifying treatment-resistant phenotypes/genotypes and therapeutic targets that may influence tumor response is at the center of current radiation biology research. Robust, patient-specific, and predictive biomarkers are critical to assess tumor response to improve patient treatment and outcomes. There is an unmet clinical need to identify translational biomarkers that allow for tailor-made and optimized patient-specific treatment. Patient tumor samples such as tissue and liquid biopsies along with varying modalities of analysis that can be performed to identify predictive biomarkers of RT treatment response will be discussed in this subsection (Figs. 7.5 and 7.6).

An illustration of different modalities of analysis. When the patient tumor sample is collected, the three modalities of analysis, namely P D Xs, P D Os, and I H C are used. P D Xs and P D Os are patient-derived 3 D models.

Fig. 7.5
Patient tissue biopsy sample types and different modalities of analysis that can be performed to identify predictive biomarkers of RT treatment response

An illustration of four analysis methods of the sample obtained by liquid biopsy. The methods are transmission electron microscopy, size exclusion chromatography, western blot, and polymerase chain reaction.

Fig. 7.6
Schematic of clinically informative elements obtained by liquid biopsy and various analysis methods. (Reproduced with permission from [40])


An illustration of different modalities of analysis. When the patient tumor sample is collected, the three modalities of analysis, namely P D Xs, P D Os, and I H C are used. P D Xs and P D Os are patient-derived 3 D models.


An illustration of four analysis methods of the sample obtained by liquid biopsy. The methods are transmission electron microscopy, size exclusion chromatography, western blot, and polymerase chain reaction.


Tissue biopsies are the current gold standard for profiling tumors and can provide both key pathological and molecular information [41]. Numerous studies have investigated the potential of tumor tissue biopsies to predict the biological behavior of tumors, before and during RT, which could highlight the modes of biological action toward radioresistance. Examples of studies are provided in Table 7.4.Table 7.4
Examples of studies that have used tumor biopsies to predict response to RT.

Research team

Technique

Tissue type

Main outcome

Pollack et al. [42]

Tissue biopsy—IHC

Prostate cancer

Ki67, a marker of cellular proliferation, and apoptotic proteins bcl2 and bax are independently associated with BCDF.

Wilkins et al. [43]

Tissue biopsy—IHC

Prostate cancer

Ki67 is an independent prognostic factor for BCDF.

Driehuis et al. [44]

PDOs—Next generation sequencing and dose response kill curve

HNSCC

A patient with a prolonged response to RT had an organoid line with the highest sensitivity to RT.
Relapsed patients post-RT also had the most resistant organoid lines.

Yao et al. [45]

PDOs—Whole-exome sequencing and organoid size

Locally advanced rectal cancer

The PDOs matched the clinical outcomes of the patient with a 85% match ratio (n = 80).

Abbreviations: IHC immunohistochemistry, PDOs patient tumor tissue-derived organoids, HNSCC head and neck squamous cell carcinoma, BCDF biochemical or clinical disease failure, RT radiotherapy


Immunohistochemistry (IHC) is a low-cost technique used by pathologists that involves staining fresh, frozen, or paraffin-embedded tissue and is widely applied in a clinical diagnostic setting. IHC has been used to identify predictive tissue biomarkers for RT response and include markers related to cell proliferation; ki67 and PKA (protein kinase), cell cycle checkpoint; p53 and p16, apoptosis; bcl2 and bax, growth factor receptors; EGFR (epidermal growth factor receptor) and finally, hypoxia; HIF1α (hypoxia-inducible factor 1-alpha (e.g., [42])). IHC facilitates the direct assessment of antigen expression in tissues through enzyme-conjugated antibodies. Initially, IHC was designed to classify the cellular origin of a tumor but with enzyme-conjugated antibodies and paraffin embedding, IHC is also capable of assessing treatment efficacy and is useful for tumor subtyping as well as in predicting patient response to RT. However, IHC is prone to pre-analytical subjectivity, operator subjectivity, and limited to known proteins [46]. Patient-derived 3D models can also be used to assess tumor response to RT and will be discussed in the following section.


In the last decade, patient-derived organoids (PDOs) have provided novel models for preclinical and translational research for assessing tumor response toward personalization of treatment. Organoids have the potential to be used as predictors for patient treatment response due to their ability to reflect the biological characteristics of primary tumors, i.e., intra-tumor heterogeneity, genotype, and phenotype [47] as well as the tumor microenvironment [48]. Compared to 2D models, PDOs possess improved cell morphology, differentiation, and viability, rendering them more relevant to the in vivo context [49]. Assays that can be performed on organoids include genomic profiling, survival assays, flow cytometric analysis, immunofluorescent, and histological staining. The main limitations associated with organoids include their high cost both in an economic and time-input sense [50].


PDXs are mouse models that are widely used in modern cancer research and are proving to be another useful platform in the development of personalized medicine strategies due to an improved relationship with the context in vivo. PDXs also demonstrate similar susceptibility to anti-cancer therapies, they closely resemble patient tumor features, have similar histological and molecular characteristics, and can be cultured long-term in vitro [51, 52]. The tumor material to be used in PDXs is derived from fresh tumor tissue collected from a patient during surgery. Small tumor pieces are then implanted into severely immunodeficient or humanized mice. Although PDXs are a promising tool for translational research, they are difficult to apply as tumors may not grow or metastasize. Other disadvantages include the long process required to establish a model which requires significant involvement by pathologists, sampling and representational issues due to tumor heterogeneity, the overall economic cost of their development, their inability to evaluate the involvement of the immune system ex vivo, the potential for grafts to be rejected (“engraftment rate”), and the required use of regulated and approved animal facilities [53].


PDX models have been used to investigate biomarkers of RT response with the aim of stratifying patients based on risk and facilitating the individualization of treatment, as exemplified recently in PDX models of glioblastoma. The CHGA and MAPK8 gene signatures have been associated with increased survival in patients with glioblastoma who have received RT [54]. As the use of PDXs to reliably predict clinical activity of treatment options is still in its infancy, it is currently unknown whether these models can be used to guide individual treatment strategies in a time frame that is useful for a patient. Future technological advancements may accelerate their involvement clinically.


The invasive nature of tumor sample acquisition lends to many of the limitations associated with this sample type, including being painful and difficult to collect, time-taxing, having limited repeatability due to localized sampling of tissue. In addition serial assessments are often limited, and this diagnostic approach requires expert pathologists for evaluation, with the potential to introduce new risks to patients. Importantly a tumor may not be fully represented by a single tissue biopsy due to tumor heterogeneity which potentially adversely affects the accuracy of the test. Lastly, if the condition of a patient has worsened, the acquisition of tissue biopsy is not feasible [55, 56].


As the collection of tissue biopsies from patients often introduces unnecessary risks to the patient, there has been a recent increase in the focus on safer and less invasive sample collection methods, including via liquid biopsies. Liquid biopsies are generally a rich source of tumor-specific biomarkers, providing a temporal snapshot of the genomic character of a tumor, and can help overcome the complication of intra-tumor heterogeneity [56]. However, there are several limitations associated with liquid biopsies, including the lack of standardization of methodologies and inadequate technical/clinical validation for routine clinical utility [57].


It is known that intra-tumoral components are released into the bloodstream, urine, cerebrospinal fluids, pleural fluid, and so on, and that each contains information relating to tumor-specific material [58]. Blood is the most widely investigated liquid biopsy and where intra-tumoral components such as circulating tumor cells, circulating cell-free DNA, and extracellular vesicles (EVs) can be found [59]. These are the most investigated of the intra-tumoral components and will be discussed in this subsection (Fig. 7.6). Other intra-tumor components include circulating RNA, circulating proteins, and tumor-educated platelets; however, they will not be discussed in this subsection. Due to recent technological advances, these circulating biomarkers can be detected and researchers have identified them as a novel and promising avenue for stratifying patients based on risk and identifying patients who may be radiosensitive or possess radioresistant disease.


CTCs have recently been discovered to be potential biomarkers for predicting tumor response to RT. A recent study by Qian et al. [60] demonstrated that nasopharyngeal patients with a complete response to concurrent chemoradiotherapy exhibited decreased CTC levels when compared to patients with a partial response. CTCs enter the bloodstream or lymphatic system and are disseminated throughout the body as they are released from primary, metastatic, or recurrent tumors. Metastatic tumors in distant locations can also form through CTCs that evade immune cell recognition [61]. These cells are rare, and the proportion present in peripheral blood is quite low when compared to white and red blood cells [62]. Molecular heterogeneity and the low concentration of CTCs in peripheral blood lead to multiple limitations in terms of their isolation, enumeration, and detection [63]. Current platforms to isolate and analyze CTCs are based on distinguishing features between CTCs and white and red blood cells such as morphology, biophysical and biomechanical properties along with modification, synthesis, regulation, and concentration of protein [64]. CTC isolation/enrichment platforms include microfiltration devices and dielectrophoretic field flow fractionation (DEP). CTC recognition platforms can be split into two groups: (1) label independent and (2) label dependent. The former includes PARSORTIX and CytoTrack. The latter includes iCHIP, CTC-Chip, and CELLSEARCH [64]. CELLSEARCH is an FDA-approved platform and is based on the expression of cell surface markers such as epithelial cell adhesion molecule (EpCAM), cluster of differentiation (CD)45 (CD45), cytokeratins 8, 18, and/or 19 [65]. This platform uses antibodies against these cell surface markers conjugated with magnetic nanoparticles or immobilized on microfluidic chips.


EVs can be isolated from a wide range of body fluids, such as bile, cerebrospinal fluid, saliva, breast milk, urine, blood, and amniotic fluid. Various cell-derived membrane structures are collectively termed EVs and include exosomes, microvesicles, and apoptotic bodies [66]. Exosomes are ideal candidates to study response to RT because radiation not only alters exosome manufacturing, but also affects their molecular cargo [67]. However, investigating the role of exosomes in radiosensitivity is a relatively novel approach, and studies currently are limited to in vitro studies that require translation  in vivo to broaden our understanding of the mechanisms behind the development of radioresistance.


Current exosome isolation methods include immunoaffinity capture, ultracentrifugation, density gradient centrifugation, size exclusion chromatography, and exosome precipitation, while characterization methods include western blotting, ELISA, and transmission electron microscopy [68]. The disadvantages associated with these techniques currently make them unsuitable for clinical utility. These include (1) the large amount of starting sample and costly instrumentation that is required for analysis and (2) the labor- and time-intensive nature of the procedures required for sample isolation.


cfDNA is reported to be found in elevated levels in cancer patients when compared to healthy individuals [69]. Usually, cfDNA is found in fragments ranging from 120 to 220 base pairs (or multiples thereof) [70]. The mechanisms responsible for the release of cfDNA into the bloodstream are not fully understood, but it is thought that it may be facilitated via apoptosis, necrosis, senescence, and actively through cell secretion [71]. In the blood, cfDNA is mostly nucleosome associated, and the tumor derived element in cancer patients is circulating tumor DNA (ctDNA) where concentrations of ctDNA have a linear relationship with tumor size and metastasis [72, 73]. Disease stage will also influence ctDNA concentration with late-stage disease associated with higher levels than early-stage disease [74].


ctDNA is more fragmented than cfDNA ranging from 100 to 200 base pairs and exists at much lower concentrations [75]. Detectable alterations that are tumor relevant include mutations, chromosomal rearrangements, copy number aberrations, methylation, DNA fragment lengths, tumor gene expression, and the presence of viral sequences (in tumors associated with oncogenic viruses) [73]. In patients with advanced stage nasopharyngeal carcinoma, plasma Epstein–Barr virus DNA load at the midpoint of RT is associated with a worse clinical outcome [76]. Detectable circulating HPV-DNA at the end of chemoradiation is associated with lower progression-free survival in HPV+ cervical cancer patients [77]. Somatic mutations in ATM, a DNA repair gene, can determine exceptional responses to RT in patients with head and neck squamous cell carcinoma, endometrial cancer, and lung cancer [78]. Several methods have been developed to extract and sequence ctDNA. These methods include, but are not limited to:1.
Polymerase chain reaction (PCR)-based techniques: BEAMing PCR (beads, emulsion, amplification, and magnetics), droplet digital PCR (ddPCR), and real-time quantitative PCR (qPCR).
 2.
Tumor-informed sequencing approaches: cancer personalized profiling by deep sequencing (CAPP-Seq), Signatera, and targeted digital sequencing (TARDIS).


Polymerase chain reaction (PCR)-based techniques: BEAMing PCR (beads, emulsion, amplification, and magnetics), droplet digital PCR (ddPCR), and real-time quantitative PCR (qPCR).


Tumor-informed sequencing approaches: cancer personalized profiling by deep sequencing (CAPP-Seq), Signatera, and targeted digital sequencing (TARDIS).


Drawbacks associated with some of these techniques include that only one or a small number of mutations can be investigated at a time, a large amount of blood is needed to identify a small number of mutations due to low concentrations of ctDNA in the blood, and prior knowledge related to the tumor must be acquired before analysis, which usually requires invasive sample collection [79]. Next generation sequencing-based techniques include whole-exome sequencing (WES) and whole-genome sequencing (WGS) are also used for ctDNA analysis and limitations related to these techniques include that a large initial concentration of ctDNA is required and low sensitivity has previously been reported for WGS [80]. Examples of studies exploring these circulatory biomarkers can be found in Table 7.5.Table 7.5
Examples of studies that have utilized biomarkers from liquid biopsies to predict tumor response to RT (see the referenced publications for the full study details, including RT regime)

Research team

Biomarker

Methodology

Study population

Main outcome

Sun et al. [81]

CTCs

Fluorescence microscopy

Locally advanced colorectal patients (n = 115)

Baseline CTC counts of biological responders were significantly elevated when compared to non-responders

Jeong et al. [82]

ctDNA

Hybrid capture-based approach (Capp-Seq)

Non-small cell lung cancer (n = 44)

KEAP1 mutations in the NRF2 pathway; present in plasma baseline samples, promoted radiosensitivity and prediction of the rate of local failure post-treatment

Salami et al. [83]

CTCs

Epic Sciences CTC platform

Patients with high-risk localized prostate cancer (n = 19)

Higher number of baseline CTCs associated with BCR after therapy

Liang et al. [84]

EBV ctDNA

RT-qPCR

Patients with nasopharyngeal carcinoma (n = 940)

IMRT of CC patients with elevated baseline levels of EBV ctDNA (>4000 copies/mL) demonstrated greater disease-free survival and distant metastasis-free survival compared to IMRT patients

Dai et al. [85]

Exosomes

CCK-8, invasion, and apoptosis assay

GBM cell lines

Exosomes originating from long non-coding RNA AHIF overexpressing GBM cells enhanced radioresistance, viability, and invasion

Tang et al. [86]

Exosomes

miRNA technology

Non-small cell human lung cancer cells

Radiation-induced miR-208a enhanced proliferation and decreased cell apoptosis through activation of p21 of the AKT/mTOR pathway

Abbreviations: SABR stereotactic ablative radiotherapy, RT radiotherapy, KEAP1 Kelch-like ECH associated protein 1, NRF2 nuclear factor-erythroid factor 2-related factor, ADT androgen deprivation therapy, BCR biochemical recurrence, EBV Epstein-Barr virus, GBM glioblastoma, RT-qPCR real-time quantitative polymerase chain reaction, IMRT intensity modulated radiotherapy, CC concurrent chemotherapy, HGM human glioblastoma multiforme, AHIF antisense hypoxia-inducible factor, CCK-8 cell counting kit-8, miR-208a microRNA-208, AKT protein kinase B, mTOR mechanistic target of rapamycin


Further studies are needed to elucidate the role of biomarkers in predicting tumor response to RT as currently there are limited studies that investigate their potential. Furthermore, biomarker identification is in its infancy, with liquid biopsies and 3D patient-derived models providing an enormous opportunity to further advance precision medicine. The limitations associated with these techniques may be mitigated in the coming years through technological advancements that allow the creation of more specific and sensitive assays. Along with harmonization and standardization of methodologies, the techniques mentioned in this section may move from a translational phase to routine clinical use. It can be expected that research on liquid biopsies and patient-derived 3D models will only grow in the coming years, and with this comes the potential to revolutionize patient care and treatment.


The radiosensitivity of normal cells, tissues, and tumors varies considerably between patients. There is variability in the patient’s response to RT, and most patients experience few or no side effects during or after treatment. However, due to this variability, many patients will receive suboptimal treatment dosing due to current dose thresholds being applied as a protective measure against toxicity events in radiosensitive patients. For patients who will develop side effects, a small number of these may develop more extreme side effects. Extreme side effects related to late radiation toxicity can be irreversible and life-threatening and greatly affect the quality of life of a patient. Identifying patients who possess intrinsic radiosensitivity prior to starting treatment would be clinically beneficial, as RT could do more harm than good in this small subset of patients. Identifying potential predictive biomarkers of normal tissue response to RT has been the focus of intense research within the clinical radiobiology arena over the years. Numerous attempts have been made by various research groups to develop an assay capable of predicting radiosensitivity, yet to date, no biomarkers to predict radiosensitivity are in clinical use. Assays have been developed with the aim of studying and predicting radiosensitivity in normal tissues and tumors. However, current developed methods have produced conflicting results and come with many limitations that make them impractical for clinical use (Table 7.6).Table 7.6
Examples of studies using traditional and emerging techniques to assess radiosensitivity

Assay

Sample type

Research team

Study outcome

Clonogenic assay

EGFR mutant (n = 6) and wild-type (n = 9) NSCLC cell lines

Anakura et al. [87]

Compared to wild-type cell lines, EGFR mutant lines demonstrate to be significantly more radiosensitive to low-dose and low fraction-sized irradiation (2 and 4 Gy).

Clonogenic assay

HNSCC patients (n = 38)

Stausbøl-Grøn and Overgaard [88]

Loco-regional tumor control was not correlated with SF2 after exposure to 62–68 Gy.

MTT assay

Radioresistance EAC cell line

Mekkawy et al. [89]

The EAC cell line can be radiosensitized if incubated with bromelain prior to irradiation. Bromelain may have clinical application in protecting normal tissues from damage.

CBMNcyt

PBLCs of LARC patients (n = 134)

Dröge et al. [90]

Cytogenetic damage of lymphocytes is not a predictor of the outcome of RCT (50.4 Gy) outcome in LARC patients.

G2 MN assay

PBLCs from 18 BRCA2 mutation carriers, BRCA1 (n = 9) and BRCA2 (n = 8) families that do not exhibit the familial mutation (non-carriers) and healthy volunteers (n = 18)

Baert et al. [91]

Increased radiosensitivity in carriers of the BRAC2 mutation compared to healthy volunteers after exposure to 2 Gy irradiation.

γ-H2AX DNA damage assay

Lymphocytes from prostate cancer patients (n = 50)

Pinkawa et al. [92]

No correlation was found between the development of toxicity and the number of γ-H2AX foci was found.

γ-H2AX DNA damage assay

PBMCs of NSCLC patients (n = 38)

Lobachevsky et al. [93]

Patients with compromised DNA repair had an elevated risk of developing toxicity.

FTIR spectroscopy

Plasma from prostate cancer patients (n = 53)

Medipally et al. [94]

Variations in FTIR spectral signatures related to lipids, proteins, nucleic acids, and amide I/II when comparing late toxicity grade 2+ patients with toxicity grade 1.

Raman spectroscopy

Lymphocytes from prostate cancer patients (n = 42)

Cullen et al. [95]

Variations in Raman spectral signatures related to Amide III, lipids, proteins, and DNA when comparing late toxicity grade 2+ patients with toxicity grade 1.

Abbreviations: EGFR epidermal growth factor receptor, HNSCC head and neck squamous carcinoma, EAC Ehrlich ascites carcinoma, CBNMcyt cytokinesis block micronucleus cytome, PBLCs peripheral blood lymphocytes, LARC locally advanced rectal cancer patients, RCT radiochemotherapy, BRAC breast cancer gene, PBMCs peripheral blood mononuclear cells, NSCLC non-small cell lung carcinoma


Cell viability assays are used predominantly to study cell response by measuring cell survival and proliferation after exposure to cytotoxic compounds. However, they are also extensively used in radiobiology studies. Clonogenic and MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assays are well-known assays for assessing in vitro radiosensitivity. The clonogenic assay is currently the gold standard for determining cellular radiosensitivity [96]. Further details on this assay can be found in Chaps. 3 and 7.


Early clonogenic studies provided evidence that in patients with cervical cancer and breast carcinoma, SF2 correlates with radiotherapeutic outcome [97, 98]. On the contrary, other early clonogenic studies have not found a correlation between SF2 and radiotherapeutic outcomes in head and neck cancer and multiforme glioblastoma multiforme [88, 99].


Numerous disadvantages are associated with the clonogenic assay, i.e., invasive sample acquisition, observer subjectivity through manual counting, merging of colonies that grow close together, long wait time for results as post-irradiation colonies can form 1–3 weeks later, labor intensive and technically difficult to perform [100–102]. As results from the clonogenic assay have a slow turn-around time, receiving results quite some time after sample collection/analysis would be of very little benefit to the patient, and it is clear that more efficient, rapid, and high-throughput methods need to be developed.


Plate-based cellular viability assays using tetrazolium salts such as MTT have also been used to assess radiosensitivity and can determine cell growth after irradiation [103].


Mitochondrial enzymes within metabolically active cells reduce the yellow MTT to water-insoluble purple formazan crystals. The amount of formazan crystals formed is directly proportional to the number of viable cells present in the sample, and this allows for the determination of viable cells through absorbance measurements obtained via a spectrometer at 492 nm ([103]; also discussed in Chap. 2). Buch et al. [103] also demonstrated that MTT performs similarly to the clonogenic assay when assessing the survival of irradiated human NSCLC and human glioblastoma cell lines. Compared to the clonogenic assay, the MTT assay is technically easier to perform and provides rapid results [104]. Rai et al. [105] also found that the MTT assay underestimated radiation induced cellular growth inhibition in numerous cell lines by comparing MTT values with cell numbers.


The MTT assay also has multiple disadvantages that make this assay unsuitable for routine clinical use, including:


1.
Lack of specificity since tetrazolium reductions also reflect cell metabolism and not just cell proliferation.
 2.
Interference from reducing compounds.
 3.
Additionally, excessive direct light exposure of reagents and higher pH of culture medium can lead to sporadic reduction of tetrazolium salts resulting in raised background absorbance values.
 4.
MTT is cytotoxic and has been reported to inhibit cellular respiration leading to apoptosis [106–108].


Lack of specificity since tetrazolium reductions also reflect cell metabolism and not just cell proliferation.


Additionally, excessive direct light exposure of reagents and higher pH of culture medium can lead to sporadic reduction of tetrazolium salts resulting in raised background absorbance values.


MTT is cytotoxic and has been reported to inhibit cellular respiration leading to apoptosis [106–108].


These assays are used to identify chemicals and physical agents with genotoxic potential including irradiation.


During mitosis, MN are extranuclear bodies that are separated from the nucleus and contain defective chromosome fragments produced from DNA breakage and/or full chromosomes produced by interference of the mitotic machinery. MN and the micronucleus assay are discussed in detail in Chap. 3.


An early MN study carried out by Rached et al. [109] in the late 90s demonstrated that the MN assay had no predictive power for normal tissue reactions to irradiation. In this study, no variations in MN scores were observed between patients of various cancers who did or did not develop severe acute toxicities. Another study performed by Batar et al. [110] did not reveal any significant differences in MN scores between breast cancer patients who did or did not develop acute toxicities. However, a more recent study found a statistically significant difference in MN frequency per 1000 binucleated lymphocytes from patients who developed late cutaneous toxicity grade ≥3 when compared to grade ≤2 when irradiated with 10 Gy. Limitations of the MN assay include poor reproducibility due to high intra-individual variation and inter-laboratory variability, under certain conditions pseudo- MN can occur, and different types of chromosomal aberrations cannot be distinguished by micronuclei alone [111–113].


The γ-H2AX foci assay has also been explored as a prognostic technique for radiosensitivity. Please refer to Chap. 3, Sect. 3.6 (Cytogenetics and DNA Damage Measurements for Assessments of Radiation Effects) for more information. More recently, this assay was used to predict radiosensitivity in patients with oral squamous cell carcinoma and human colorectal cell lines [114, 115]. Other studies have also shown that γ-H2AX foci enumeration is not an ideal method for the prediction of acute and late toxicity development in prostate cancer, breast cancer, and rectal carcinoma [92, 116, 117]. On the contrary, other studies have used the γ-H2AX foci assay to identify patients at risk of developing radiation-induced toxicity in patients with lung cancer and breast cancer [93, 118]. These conflicting results on the fitness-of-use of γ-H2AX to predict intrinsic radiosensitivity further reinforce the idea that a novel method of analysis that can produce accurate and reproducible results needs to be developed. Disadvantages related to this assay include poor predictive performance and observer objectivity if γ-H2AX foci are enumerated by eye, and this is a fastidious and time-taxing process [119]. Inter-laboratory variations are also produced by this assay where significant variation in manually scored γ-H2AX foci yields obtained from irradiated lymphocytes has been observed [120].


The previously mentioned assays have limited clinical use due to their significant shortcomings, and a more practical approach needs to be developed to further investigate intrinsic radiosensitivity as a predictor of radiotherapeutic outcome.


Novel approaches to identify potential predictive biomarkers for radiosensitivity include Raman and Fourier transform infrared (FTIR) spectroscopic analysis of biofluids and cells. These techniques fall under the vibrational spectroscopy umbrella and are based on the transitions between quantized vibrational energy states of molecules due to the interaction between the sample and electromagnetic radiation [121]. Both techniques have numerous advantages over the previously mentioned predictive assays including minimal sample preparation and minimally invasive sample collection, speed, ease, and cost of analysis; they also allow for non-destructive and label-free analysis of a sample [121].


Each technique provides a biochemical fingerprint of a sample. Researchers in biomedical fields tend to focus on the range from 400 to 4000 cm−1 and, in particular, the fingerprint region from 600 to 1800 cm−1, as vibrations in these spectral regions produce refined bands and rich biochemical information related to disease prognostics and diagnostics. A major disadvantage of IR spectroscopy is the interference of water, which can overshadow crucial biochemical information [122]. However, Raman spectroscopy has a weak water signal and minimal water interference, making it ideal for the analysis of biological materials [123].


FTIR and Raman spectroscopy have recently been shown to be capable of discriminating patients on radiotherapeutic response [94, 95]. Both studies were successful in identifying variations in spectral intensities between patients with late toxicity grade 0–1 and grade 2+ with a high degree of sensitivity and specificity.


Current research from the same group involving Raman spectroscopy includes the analysis of biofluids and lymphocytes for the prediction of late normal tissue toxicity in high-risk localized prostate cancer patients and HPV+ head and neck cancer patients. Vibrational spectroscopy is far from being translated into the clinic, as currently there are no standardized protocols regarding the handling, storage, and preparation of samples to facilitate uniform spectroscopic analysis. However, researchers active in this area are currently investigating this to provide optimal protocols that will generate accurate and reproducible results [124, 125] (Fig. 7.7).

An illustration of the basic schematic of a Raman spectrometer. Incident beam strikes the target. The scattered beams are anti-Stokes scattering, Stokes-scattering, and Rayleigh scattering. A graph is obtained from the scattered beams.

Fig. 7.7
Basic schematic of a Raman spectrometer


An illustration of the basic schematic of a Raman spectrometer. Incident beam strikes the target. The scattered beams are anti-Stokes scattering, Stokes-scattering, and Rayleigh scattering. A graph is obtained from the scattered beams.


Raman spectroscopy is based on the inelastic scattering of light and scattering occurs when a sample is probed by a monochromatic light source. Most of the scattered light will be Rayleigh scattered where the laser photons will neither gain nor lose vibrational energy and will have the same energy as the incident light. Rayleigh scattering is also known as the elastic scattering of light and provides no information about molecular vibrational transitions [124]. A small fraction of light (approximately 1 in 107 photons) is scattered at optical frequencies different from that of the incident light [125]. The Raman effect occurs when light probes a molecule and interacts with the electrons of the molecular bonds and the scattered light vibrational energy is not equal to that of the incident light. This process leaves the molecule in an altered vibrational state. Other light scattering processes take place with Rayleigh scattering, i.e., Raman scattering, and two forms exist: stokes (dashed arrow) and anti-stokes. Anti-Stokes scattering occurs when atoms or molecules lose energy during the transition from higher to lower vibrational energy states. Stokes scattering occurs when the atoms or molecules relax into a high vibrational excited state from the ground virtual state, resulting in a vibrational energy level higher than that of the incident light [124]. The Stokes scattered light will enter the Raman spectrometer and by a series of optics and mirrors will be directed to a monochromator. The collected light will be analyzed by the spectrometer and displayed as a Raman spectrum on a computer.


RT is a mainstay in cancer therapy, and due to recent technological advances, therapeutic efficacy has improved over the years. However identification of patients at risk of toxicity, as well as those who are radiosensitive or radioresistant remains a research challenge, which, if successful, could save patients from unnecessary treatment and avoid normal tissue toxicity and potentially result in improved tumor control. Numerous studies have attempted to identify a robust predictive biomarker of patient response to RT. Although the results of the studies have been promising, to date no biomarkers have been validated or translated successfully into the clinic. The assays mentioned here are not an exhaustive list of those currently being used for research purposes to study radiosensitivity (Box 7.4).


There is patient variability in response to RT with most patients experiencing few or no side effects during or post-treatment.

A small subset of patients may experience life changing and deliberating toxicities.

Currently, no biomarker is in use in the clinic today to predict normal tissue toxicity.

Disadvantages of conventional radiobiological assays deem them unsuitable for translation into the clinic.

Novel methods such as vibrational spectroscopy demonstrate great potential in the hunt for a predictive biomarker.


There is patient variability in response to RT with most patients experiencing few or no side effects during or post-treatment.


A small subset of patients may experience life changing and deliberating toxicities.


Currently, no biomarker is in use in the clinic today to predict normal tissue toxicity.


Disadvantages of conventional radiobiological assays deem them unsuitable for translation into the clinic.


Novel methods such as vibrational spectroscopy demonstrate great potential in the hunt for a predictive biomarker.