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Yu, Jihang
Khan, Md Gulam Musawwir
Mayassi, Nada
Kaushal, Bhuvnesh
Wang, Yi
Next-generation sequencing (NGS) has been well applied to assess genetic abnormalities in various biological samples to investigate disease mechanisms. With the advent of high-throughput and automatic testing platforms, NGS can identify radiation-sensitive and dose-responsive biomarkers, contributing to triage patients and determining risk groups for treatment in a nuclear emergency. While bulk NGS provides a snapshot of the average gene expression or genomic changes within a group of cells after the radiation, it cannot provide information on individual cells within the population. On the other hand, single-cell sequencing involves isolating individual cells and sequencing the genetic material from each cell separately. This approach allows for the identification of gene expression and genomic changes in individual cells, providing a high-resolution view of cellular diversity and heterogeneity within a sample. Single-cell sequencing is particularly useful to identify cell-specific features of dose-response and organ-response genes. While single-cell RNA sequencing (scRNA-seq) technology is still emerging in radiation research, it holds significant promise for identifying biomarkers related to radiation exposure and tailoring post-radiation medical care. This review aims to focus on current methods of radiation dosimetry and recently identified biomarkers associated with radiation exposure. Additionally, it addresses the development of NGS techniques in the context of radiation situations, such as cancer treatment and emergency events, with a particular emphasis on single-cell sequencing technology.
Academic Editor: AlexandrosGeorgakilasReceived: 14 March 2025Revised: 24 May 2025Accepted: 25 May 2025Published: 28 May 2025Citation: Yu, J.; Khan, M.G.M.;Mayassi, N.; Kaushal, B.; Wang, Y.Single-Cell Sequencing: An EmergingTool for Biomarker Development inNuclear Emergencies and RadiationOncology. Cancers 2025, 17, 1801.https://doi.org/10.3390/cancers17111801Copyright: © 2025 by the authors.Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms andconditions of the Creative CommonsAttribution (CC BY) license(https://creativecommons.org/licenses/by/4.0/).ReviewSingle-Cell Sequencing: An Emerging Tool for BiomarkerDevelopment in Nuclear Emergencies and Radiation OncologyJihang Yu 1,* , Md Gulam Musawwir Khan 1, Nada Mayassi 1,2, Bhuvnesh Kaushal 1,3 and Yi Wang 1,4,*1 Radiobiology and Health, Isotopes, Radiobiology & Environment Directorate (IRED), Canadian NuclearLaboratories, Chalk River, ON K0J 1J0, Canada2 Department of Chemistry and Biology, Faculty of Science, Toronto Metropolitan University, 350 VictoriaStreet, Toronto, ON M5B 2K3, Canada3 Faculty of Medicine, The University of British Columbia, Vancouver, BC V6T 1Z3, Canada4 Department of Biochemistry Microbiology and Immunology, Faculty of Medicine, University of Ottawa,Ottawa, ON K1H 8M5, Canada* Correspondence: jihang.yu@cnl.ca (J.Y.); yi.wang@cnl.ca (Y.W.); Tel.: +1-613-584-3311 (ext. 42362) (J.Y.);+1-613-584-3311 (ext. 42653) (Y.W.)Simple Summary: Single-cell sequencing is a state-of-the-art technology that allows scien-tists to investigate gene activity and DNA damage in various groups of cells. It has foundbroad applications in cancer research, microbiology, neurology, and immunology. Further-more, single-cell sequencing is invaluable for identifying unknown cell types and specificgenetic changes. This capability makes it a powerful tool for developing biomarkers associ-ated with radiation exposure. These biomarkers can facilitate rapid emergency responses,improve our understanding of long-term health effects, and allow for cell-specific analysisin relation to cancer radiotherapy. As technology continues to advance, integrating variousvalidation and analysis methods may lead to more efficient ways to measure and manageradiation exposure. In summary, single-cell sequencing holds great promise for advancingresearch on radiation biomarkers, particularly in the context of nuclear emergencies andradiation oncology.Abstract: Next-generation sequencing (NGS) has been well applied to assess geneticabnormalities in various biological samples to investigate disease mechanisms. With theadvent of high-throughput and automatic testing platforms, NGS can identify radiation-sensitive and dose-responsive biomarkers, contributing to triage patients and determiningrisk groups for treatment in a nuclear emergency. While bulk NGS provides a snapshot ofthe average gene expression or genomic changes within a group of cells after the radiation,it cannot provide information on individual cells within the population. On the otherhand, single-cell sequencing involves isolating individual cells and sequencing the geneticmaterial from each cell separately. This approach allows for the identification of geneexpression and genomic changes in individual cells, providing a high-resolution view ofcellular diversity and heterogeneity within a sample. Single-cell sequencing is particularlyuseful to identify cell-specific features of dose-response and organ-response genes. Whilesingle-cell RNA sequencing (scRNA-seq) technology is still emerging in radiation research,it holds significant promise for identifying biomarkers related to radiation exposure andtailoring post-radiation medical care. This review aims to focus on current methods ofradiation dosimetry and recently identified biomarkers associated with radiation exposure.Additionally, it addresses the development of NGS techniques in the context of radiationsituations, such as cancer treatment and emergency events, with a particular emphasis onsingle-cell sequencing technology.Cancers 2025, 17, 1801 https://doi.org/10.3390/cancers17111801Cancers 2025, 17, 1801 2 of 18Keywords: next-generation sequencing; single-cell sequencing; radiation dosimetry;radiation biomarkers; cellular heterogeneity1. IntroductionIn the wake of a significant catastrophic event, such as a pandemic or a natural disaster,many individuals flood hospitals seeking medical assistance. This sudden surge can placeconsiderable strain on medical personnel tasked with triage. In such scenarios, it is vital forCanada to be adequately prepared for potential radiological or nuclear emergencies. Effec-tive preparedness not only ensures that triage protocols are followed but also prioritizesvulnerable populations, particularly children and young people, who are more sensitive toradiation and face greater health risks in these situations.Exposure to ionizing radiation or other harmful chemical substances can cause chro-mosomal aberrations, serving as indicators of cellular damage in both normal cells andtumour tissues [1]. Since the mid-1960s, the field of biological dosimetry has evolvedsignificantly. Among the various assays, the dicentric chromosome assay (DCA) is widelyrecognized as the gold standard for detecting chromosomal rearrangements in peripheralblood lymphocytes [2]. However, despite its sensitivity and specificity, DCA is relativelytime-consuming, low-throughput, and labour-intensive, which limits its practicality inlarge-scale emergency settings [3]. To address these limitations, NGS technologies haveemerged as promising alternatives for radiation biodosimetry. NGS can efficiently assessgenetic abnormalities in the blood, body fluids, and other non-invasive sample types ina high-throughput manner. For example, using targeted NGS, a German research teamsuccessfully analyzed 1000 samples in less than 30 h and identified four genes associatedwith hematological acute radiation syndrome (HARS) [4]. Importantly, HARS-predictivegenes can be detected within a critical time window of 2 h to 3 days after irradiation [5],enabling timely medical interventions. In contrast, DCA typically requires sample collec-tion between 24 h and 4–6 weeks post-exposure for optimal results [6]. Delays in samplecollection for DCA may compromise the accuracy of dose estimation and the timeliness ofclinical response.While rapid, high-throughput triage strategies are being explored for nuclear emergen-cies, it is anticipated that NGS technologies will play a more significant role in biomarkerdevelopment rather than frontline field use for biodosimetry. Understanding radiation-induced molecular changes is essential for developing in vitro diagnostics tests, such asquantitative real-time PCR (RT-qPCR), based on validated biomarkers.This review specifically focuses on the application of NGS technologies—particularlysingle-cell RNA sequencing (scRNA-seq)—in the context of radiation accidents and nuclearemergencies. Although still in its early stages, scRNA-seq is rapidly advancing and offersunprecedented resolution into cellular function and gene expression profiles at the individ-ual cell level. This granular insight supports the identification of biomarker candidates andthe development of rapid diagnostic tools, such as RT-qPCR assays. Moreover, by elucidat-ing the molecular responses of distinct cell populations to radiation exposure, scRNA-seqcan help identify cell types with increased sensitivity or resistance to radiation. Thesefindings not only enhance emergency preparedness but also have important implicationsfor patient management in radiation oncology.Therefore, the objective of this review is to address a critical gap in biodosimetrywhereby traditional methods are limited in speed and sensitivity and cannot capturecell-specific genomic responses or low-dose effects. It is important to note that whilenuclear accidents can increase long-term cancer risk, radiation (in controlled doses) isCancers 2025, 17, 1801 3 of 18also used therapeutically in cancer treatment. This review addresses biomarkers in bothacute accidental exposure and therapeutic contexts, with an emphasis on emergency bio-dosimetry. To this end, we (1) summarize existing biodosimetry approaches, (2) highlightradiation-responsive biomarkers identified over the past decade, and (3) explore howscRNA-seq can complement and enhance conventional methods by providing greatersensitivity and mechanistic insight. Ultimately, our goal is to inform the development ofrapid, field-deployable diagnostic assays, such as RT-qPCR, for use in radiological andnuclear emergency response.2. Current Biodosimetry MethodsBiodosimetry is the assessment of biological responses to ionizing radiation expo-sure, aiding in the evaluation of health risks and guiding appropriate medical interven-tions. Methods for biodosimetry are broadly categorized into physical techniques, suchas detecting radioactivity in a sample, and biological techniques, which assess radiation-induced changes in living cells or tissues [7–10]. Among biological methods, cytogeneticassays—notably the DCA—have long been considered the gold standard [11]. Moreover,emerging molecular and computational tools are revolutionizing biodosimetry capabilitiesby enhancing sensitivity, throughput, and applicability to low-dose or chronic exposures.Therefore, we summarize the currently available biodosimetry methods in this section.2.1. Biologic Techniques2.1.1. DCAThe DCA method is widely regarded as the gold standard in biodosimetry, and was,for many years, the only validated technique available for radiation dose assessment [11].It quantifies dicentric chromosomes—aberrant chromosomes with two centromeres—thatare formed when ionizing radiation induces DNA double-strand breaks. Misrepair of thesebreaks can result in the fusion of chromosome fragments, producing dicentric chromosomes,which serve as a hallmark of radiation exposure [12].In the DCA, peripheral blood lymphocytes are typically irradiated, cultured, andallowed to progress through cell division. Metaphase spreads are then prepared andanalyzed using cytogenetic techniques, such as Giemsa staining or fluorescence in situhybridization (FISH). The number of dicentric chromosomes present in the sample isthen quantified and correlated with the dose estimate, for which a higher frequency ofdicentric chromosomes is directly proportional to the level of damage caused by ionizingradiation [13,14].Despite its high accuracy and reliability, the DCA has several limitations. It is primarilysensitive to doses of radiation above 100–200 mGy (milligray, a unit of absorbed dose ofionizing radiation) [15], limiting its effectiveness for detecting modest to low levels ofenvironmental exposure. Furthermore, because dicentric chromosomes are unstable andlost over successive cell divisions, DCA is most suitable for assessing acute radiationexposure and is not applicable to chronic or long-term dose estimation.The assay is also labour-intensive, requiring skilled personnel to manually scoremetaphase cells under a microscope. This low-throughput nature makes it impractical forrapid, large-scale screening, particularly during a radiological or nuclear emergency, wheretime and resources are known to be the bottleneck for the DCA [16,17].2.1.2. Automation in DCATo reduce the time-consuming manual scoring process, several artificial intelligence(AI)-powered methods for DCA analysis are currently under development.Cancers 2025, 17, 1801 4 of 18These tools aim to enhance automation and throughput. For example, Ryan’s groupdeveloped Chromosome ABerration cAlculation Software (CABAS), while Rogan’s teamcreated an automated Desktop version (ADCI Desktop) that serves as a platform for scoringdicentric chromosomes. Shen’s group introduced the DCScore, a machine learning method-based software that employs clustering and watershed algorithms for automated detection.Wadhwa’s group proposed a deep learning model called InceptionResnetv2 for identifyingdicentric chromosomes with high accuracy [18–21].More recently, a deep learning-based automatic dose-estimation system (DLADES)was developed that integrates dicentric scoring with a well-constructed dose–responsecurve for dose prediction [14]. Although this system was not validated for doses above 4 Gyor below 0.5 Gy, it demonstrated potential for high-throughput assessment and improvedsensitivity, including estimates for doses below 0.1 Gy, to meet the requirement for highercell counts in conventional methods [14].Additionally, Kim et al. applied the YOLOv5 deep neural network architecture toautomate dicentric chromosomes directly from metaphase images [22]. Unlike DLADES,which focuses on dose estimation, the YOLOv5 model prioritizes the rapid identificationand quantification of dicentric chromosomes without the need for dose reconstruction.2.1.3. Other Cytogenetic Biodosimetry TechniquesIn addition to dicentric analysis, several other cytogenetic analysis techniques havebeen developed to assess radiation exposure by targeting alternative biological endpoints.These include FISH-based translocation analysis, premature chromosome condensation(PCC) analysis, and the cytokinesis-block micronucleus (CBMN) assay [11].FISH-based translocation analysis is a robust method for retrospective biodosimetry.It detects radiation-induced chromosomal rearrangement, specifically translocations, andenables the construction of a dose–response curve based on translocation frequencies inlymphocytes [23–25]. While early studies raised concerns about the potential misclassifica-tion of dicentric chromosomes as translocations, this issue was resolved through the use ofcentromeric probes, which improved scoring accuracy [26].PCC analysis, first introduced in 1974 using Chinese hamster ovary (CHO) cells tovisualize radiation-induced chromosome damage in interphase cells, has a key advantagefor evaluating non-dividing cell populations. The degree of chromosome condensationinversely correlates with the extent of radiation damage [27]. Subsequent applicationsin mammalian and human cells confirmed the value of PCC and demonstrated a dose–effect relationship for radiation-induced chromosome aberrations, including micronucleiformation [28,29].Complementary to DCA, the CBMN assay is another one of the most well-validatedcytogenetic methods for assessing radiation-induced chromosome damage in human lym-phocytes. It offers high sensitivity, with a detection limit as low as 5 cGy [30]. Furthermore,CBMN can detect ionizing radiation-induced bystander effects and inter-individual vari-ability in DNA damage responses, indicating it as a valuable tool in population-basedradiation risk assessment [31,32].2.2. Physical TechniquesScientists now recommend changing the criteria for assessing radiation exposure.Instead of focusing solely on the estimated dose received by the individual, they suggestplacing greater emphasis on the biological response of the patient as indicated by radiosensi-tive markers. This shift is based on advancements in biodosimetry methods developed overrecent years and considers the initial decision-making necessary for triage in emergencysituations [33]. The rationale behind this is that even if individuals experience the sameCancers 2025, 17, 1801 5 of 18radiation dose in a radiation disaster, their physiological responses can differ significantly.Factors such as age, sex, individual immunity, and population genetics play a significantrole in these differences. Additionally, even with an accurate measurement of whole-bodydose, different organs may absorb and respond to radiation in distinct ways [33]. Theseobservations have led to a growing interest in developing tools that can provide a morepersonalized and biologically relevant assessment of radiation injury [34].One notable advancement in physical biodosimetry is the use of electron paramagneticresonance (EPR) for in vivo fingernail dosimetry, as described by Swartz et al. [33]. Thistechnique detects radiation-induced free radicals generated in the keratin of fingernailsand toenails, with the EPR signal intensity being directly proportional to the absorbeddose. The approach offers several practical advantages: it is non-invasive, requires minimaltraining, and allows for cross-validation across multiple limbs. Additionally, the stabilityof EPR signals for several weeks post-exposure enhances its utility in delayed-responsescenarios. Recent improvements have also increased the detection resolution from 10Gy to as low as 1 Gy, marking a significant milestone in in vivo dosimetry. Moreover,when combined with organ-specific biomarkers, nail EPR has the potential to providea more comprehensive assessment of dose distribution and biological response, therebyimproving clinical decision-making and resource allocation in radiation emergencies [33].Similar applications are being explored with tooth-based EPR, although further validationis needed to confirm its triage potential [35].This advancement in biodosimetry, from dose estimation to individualized biologicalassessment, sets the stage for a deeper exploration of radiation-induced biomarkers, whichoffer critical insights into both exposure and biological effect. Hence, Table 1 summa-rizes the major biodosimetry methods discussed above, including their dose sensitivity,applicability, and current limitations.Cancers 2025, 17, 1801 6 of 18Table 1. Overview of current biodosimetry methods.Method Principle Dose Sensitivity Throughput Application Limitations ReferencesDCA Dicentric chromosomes(cytogenetics) >100–200 mGy LowAcute exposure, goldstandardLaborious, not forchronic/low doses [11–13,15]DCA + AI (e.g., DLADES) Automated dicentric scoring(deep learning) <0.1 Gy possible HighHigh-throughput,emergency triage Still under validation [14,18–22]FISH TranslocationAnalysisStable chromosomaltranslocations ~100 mGy Medium Retrospective analysis Specialized probes needed [23–26]PCC Analysis Chromosome condensation >1 Gy Medium High-dose, non-dividingcellsLimited use in low-doseexposure [27–29]CBMN Assay Micronuclei in lymphocytes ~50 mGy Medium Bystander effect,inter-individual dif. Requires cytokinesis block [30–32]Nail EPR Free radicals in keratin(physical method) ~1 Gy HighField deployable,non-invasiveLow-dose sensitivity is stillimproving [33]Tooth EPR Free radicals in enamel ~1 Gy High Potential triage tool Requires more validation [35]Biomarker-Based Assays Gene/protein/metaboliteexpression changes Variable HighPersonalized riskassessment Standardization lacking [36,37]Cancers 2025, 17, 1801 7 of 183. Radiation-Induced BiomarkersRadiation-induced biomarkers and biodosimetry methods are both essential tools forassessing exposure to ionizing radiation, yet they differ in their purposes and approaches.Biodosimetry methods aim to directly estimate the absorbed radiation dose, often throughbiological markers like chromosomal aberrations or lymphocyte counts. In contrast, aradiation biomarker refers to a measurable biological indicator that reflects physiological,pathological, or therapeutic responses to radiation exposure [38]. Biomarkers may includegenetic alterations, protein expression profiles, imaging data, blood-based markers, organfunction metrics, or even electrocardiographic patterns [39].Radiation biomarkers can provide information about the molecular and cellular conse-quences of radiation exposure, whereas biodosimetry methods shed light on dose quantifi-cation. Both approaches are complementary and useful for managing radiation exposure,especially in nuclear emergencies or radiological incidents, depending on the context andnature of the information required.In addition to classical cytogenetic endpoints, such as chromosome aberrations, lym-phocyte depletion, and γ-H2AX foci formation [40], advances in molecular biology haveled to the identification of numerous radiation-sensitive molecules. Modern “omics” tech-nologies, including genomics, transcriptomics, proteomics, lipidomics, and metabolomics,are being actively explored to discover novel radiation biomarkers [41].3.1. Systematic Literature Review MethodologyTo comprehensively review current advances, we conducted a systematic literaturesearch in PubMed, using the keywords “biomarker”, “radiation”, and “accident”. Thissearch yielded 360 published studies, of which 254 were screened to focus on studiesfrom approximately the last decade. Out of these, 134 studies were further screened andreviewed according to PRISMA (Preferred Reporting Items for Systematic Reviews andMeta-Analyses) guidelines to ensure a structured and reproducible selection process. ThePRISMA flowchart (Figure 1) illustrates the study selection workflow.Figure 1. PRISMA flow diagram of the literature study. Adapted from the PRISMA template 2020 inaccordance with the terms of the Creative Commons Attribution (CC BY 4.0) license.Cancers 2025, 17, 1801 8 of 183.2. Recent Biomarker DiscoveriesOriginally pioneered by Olivier Guipaud in 2013, serum and plasma proteomics havebecome widely applied to radiation biomarker discovery [42]. For example, C-X-C motifchemokine ligand 10 (CXCL10) has emerged as a promising candidate, as its expression inmouse peripheral blood mononuclear cells (PBMCs) exposed to 1, 3, and 5 Gy of ionizingradiation showed strong correlation with ferredoxin reductase (FDXR), a well-establishedradiation biomarker [43]. In another study, the serum protein BPI Fold-Containing FamilyA Member 2 (BPIFA2) was significantly upregulated in C57BL/6J mice after radiationexposure, highlighting its potential as a novel early biomarker for nuclear incidents [44].Additionally, a secondary increase in serum BPIFA2 showed a second peak in expressionafter exposure to a lethal dose (10 Gy), indicating its prognostic value for predicting fatalradiation outcomes [44]. Similarly, serum amyloid A1 (SAA1) has shown marked elevationat both protein and transcript levels in irradiated models, making it a strong early-stagebiomarker for radiation-induced damage and lethality risk assessment [45]. Moreover, wecompiled Table 2, which includes 49 studies highlighting biomarkers identified in recentresearch over the past decade. A comprehensive version can be found in SupplementaryTable S1.Table 2. Radio-sensitive biomarker candidates identified in the last decade (2012–2024).Category Biomarker(s)Genome BRAF mutation [46]; HLA-genetic predisposition [47]; CNV [48]; MD of autosomal SNPs [49]; C-3SFBP,C-7IUVU [50]mRNAsPTC transcriptomic signature [51]; CCNG1, PHPT1 [52]; RET/PTC1 rearrangement [46]; KDR,CEACAM8, OSM [53]; CLIP2 [54,55]; Agpat9, Plau, Prf1, S100a8 genes [56]; gene expression signatures[57–59]; NF-κB1, NF-κB2, Rel genes [60]; radiation-responsive “signature” genes [61]; CLIP2-PPIL3co-expression [62]; ERCC1, ESCO2 [63]; 15 mRNAs [64]; 131I exposure novel biomarkers [65]; GRB7,B2M, PMAIP1 [66]; CXCL10, FDXR [43]microRNAs miRNA-150 [67]; miR-21 [68]; miRNA signatures [69,70]; 5-miRNA composite signature [71]ProteinsLow proliferation index [46]; CRP [72]; CD11b+CD13+, CD29+CD13+, cell adhesion and migration [73];chronic viral infection [74]; intracellular protein parameters [58]; SAA1 [45]; glutathione transferase,glutathione peroxidase [75]; Keratins K1 and K10 [76]; AMY1A, FLT3L, MCP1 [77]; A2m, CHGA, GPX3[78]; γ-H2AX mean fluorescence intensity [79]; 30+ proteomic biomarkers [80]; BPIFA2 [44]; 131Iexposure novel biomarkers [65]; BRAF/NRAS mutation, PD-L1, PD-1, P16INK4A, Ki-67 [81]; serumsSelectin-L [82]; BAX, DDB2 [83]Metabolites 26 metabolite signals [84]; lipid metabolism (postnatal), steroid hormone metabolism (adult) [85];urinary metabolic signatures [86]CellsCD4+ cells, CD4+/CD8+ ratio [53]; absolute neutrophil count, monocyte count [72]; PHA [87,88];lectin–erythrocyte interactions [89]; telomere length [58,59,74]; TCR-CD4+, γ-H2AX+, and CyclinD1+cell counts [90]; cellular immunity [58]; PPHA [91]3.3. Emerging High-Throughput Platforms for Biomarker DiscoveryTranscriptomics and proteomics approaches have been widely applied to identifyradiation-induced biomarkers, contributing to the development of large-scale databasesthat offer a comprehensive understanding of radio-sensitive and responsive biomolecules.In parallel, high-throughput platforms are being developed to enable rapid and efficientbiomarker discovery, with several panels of candidate biomarkers selected for validation.For instance, the high-throughput biodosimetry test system (REDI-Dx) has beendeveloped for investigational use in the United States [92]. Utilizing a minimally invasiveblood collection technique, REDI-Dx incorporates a panel of 18 dose–response genes alongwith three normalizer genes and two internal controls, assessed via RNA Sanger sequencing.Cancers 2025, 17, 1801 9 of 18This system has demonstrated high sensitivity and specificity for radiation dose estimation,particularly at exposures of 2 Gy and 6 Gy [92].In addition to transcriptomic platforms, metabolomics has emerged as a promisingtool for biomarker discovery, particularly given its capacity to capture systemic metabolicdysregulation following radiation exposure [38]. Several metabolites, including carnitine(C7H15NO3) and citric acid (C6H8O7), have been consistently identified as altered inresponse to varying radiation doses, positioning them as potential candidates for radio-sensitive biomarkers for unexpected nuclear events [38].Furthermore, Maan et al. reported significant dysregulation of multiple metabolicand immunological pathways following exposure to 1 Gy and ultra-high doses (7.5 Gy) ofradiation [93]. These included alterations in lipid metabolism, carbohydrate metabolism,and amino acid metabolism, particularly pathways involving histidine, arginine-prolinemetabolism, and arginine biosynthesis. Therefore, these insights not only deepen ourunderstanding of molecular interactions underlying radiation response but also supportthe integration of multi-omics approaches, combining metabolomics and transcriptomics,for the identification of robust biomarkers. Such integrative analyses have the potential toenhance triage and medical management strategies in radiation emergency scenarios [93].4. Single-Cell Sequencing Technology: A New Era for RadiationBiomarker Discovery4.1. Advantages of Single-Cell Sequencing over Bulk RNA SequencingIn contrast to conventional RNA sequencing (RNA-seq), which provides an averagegene expression across mixed cell populations, single-cell sequencing technologies (in-cluding genome, transcriptome, and epigenome sequencing) allow for the detection ofgene signatures and differential gene expression at the resolution of individual cells. Thisis particularly important for addressing cellular heterogeneity within tissues or popula-tions, which is often masked in bulk RNA-seq data. Consequently, scRNA-seq technologyhas rapidly emerged as a transformative tool for studying gene expression variability atthe single-cell level, offering deeper insights into intra-tumour or intra-organ heterogene-ity [94].Since its initial report in 2009, high-throughput scRNA-seq technology has become anindispensable technique for studying genomic, transcriptomic, and epigenomic landscapesat the single-cell level, gaining wide adoption across fields such as developmental biology,cancer research, and immunology [95].4.2. Technical Approaches for Single-Cell SequencingSingle-cell sequencing can be applied across various molecular domains:• scRNA-seq for transcriptome profiling;• Single-cell DNA sequencing for genome analysis;• Single-cell proteomics for global protein expression profiling in thousands of individ-ual cells.While scRNA-seq shares core steps with bulk RNA sequencing, the critical differ-ence lies in the cell isolation, which includes conventional manual sorting, dilution,laser microdissection (LCM), fluorescence-activated cell sorting (FACS), and microflu-idics/microplate technology [96–98]. Among these, microfluidics platforms greatly en-hance throughput, efficiency, and accuracy, enabling the analysis of large cell populationswith high fidelity [98,99].Cancers 2025, 17, 1801 10 of 184.3. scRNA-Seq in Cancer ResearchTumours exhibit extensive heterogeneity not only among cancer cell populationsharbouring diverse mutations and transcriptional programs but also within the tumourmicroenvironment, which evolves throughout oncogenesis. This complexity poses signifi-cant challenges in biomarker discovery for diagnosis, prognosis, recurrence prediction, andtherapy resistance.scRNA-seq offers a powerful means to dissect this complexity by enabling the de-tection of cell type-specific gene expression patterns within tumours and surroundingstromal or immune compartments [94,100]. For instance, Gao et al. applied single-celltranscriptomics to breast cancer cells exposed to ionizing radiation, uncovering heteroge-neous cellular responses and identifying potential radio-sensitive biomarkers in tumourtreatment [101]. Similarly, scRNA-seq has been used to develop a risk assessment modelbased on epithelial cell markers in colorectal cancer [102] and reveal sex-specific geneexpression in glioma-activated microglia, highlighting its value for personalized cancerresearch [103]. Moreover, scRNA-seq has been employed to identify biomarkers within cir-culating tumour cells (CTCs) from melanoma, hepatocellular carcinoma, and non-small-celllung cancer [104–106].4.4. Potential Applications of scRNA-Seq in Radiation Exposure ScenariosscRNA-seq holds great promise for identifying biomarkers associated with accidentalradiation exposure, nuclear incidents, and space radiation exposure. Acute high-doseradiation can trigger diverse effects on different cell populations within organs, which canbe systematically profiled using scRNA-seq.Recent studies have leveraged scRNA-seq to investigate the impact of space-like ra-diation conditions on human tissue. For example, researchers used engineered humanbone marrow and cardiac tissue combined with single-cell transcriptomics to examine theeffects of high-energy neutron and photon radiation, simulating space mission conditions.They observed a decreased proliferation of CD45+ cells, heightened inflammatory signa-tures, and myeloid cell infiltration and identified potential biomarkers such as MIR22HG,HMOX1, COL24A1, MIR34AHG, and PHLDA3, associated with oxidative stress, fibrosis,and senescence [107]. Additionally, scRNA-seq has been applied to analyze T lympho-cyte subpopulations exposed to ex vivo radiation, revealing differential gene expressionprofiles among subpopulations and providing novel insights into immune responses toradiation [108].Though still in its early stages within radiation research, scRNA-seq is poised torevolutionize biodosimetry by offering a more precise and cell-specific understandingof gene expression changes after radiation exposure, ultimately advancing personalizedcountermeasure development.4.5. scRNA-Seq in Personalized Radiation Therapy and Immune ModulationRadiation therapy, as the most cost-effective treatment of cancer, has been applied tomore than half of cancer patients alone or in combination with surgery or chemotherapy.By profiling radiation-induced biomarkers before and after radiation, scRNA-seq canhelp determine individual radiation sensitivity, allowing for the design of customizedtreatment plans tailored to each patient’s genetic landscape. This technology also enablesthe characterization of the radiation-induced changes not only in tumour cells but also inthe surrounding environment, such as immune cells, blood cells, and mesenchymal cells,thereby offering a holistic view of the treatment response.Recent studies support this application. Ponthan et al. used 10× Genomics scRNA-seqto show that radiotherapy enhances the infiltration of CD8+ T cells expressing naturalCancers 2025, 17, 1801 11 of 18killer granule protein 7 (NKG7) in colorectal carcinoma, suggesting potential targets forimmune modulation strategies [109]. Moreover, NFKB1 was identified via single-cell wholegenome sequencing as a gene that increases the radiation sensitivity of cervical cancer cells,representing a target for precision therapy [110].5. DiscussionIonizing radiation has both harmful and beneficial effects. In uncontrolled exposures,such as nuclear or radiological incidents, it can lead to long-term health risks (e.g., cancer,cataracts, cardiovascular and neurological disorders), making rapid triage and sensitivebiomarkers essential tools for effective and early intervention. In contrast, cancer radiother-apy uses carefully calibrated doses to damage tumour cell DNA while minimizing injuryto healthy tissue. Single-cell sequencing unites these contexts by providing high-resolution,cell type-specific profiles of radiation-induced gene expression and DNA damage responses.This precision enables the identification of early biomarkers for emergency risk assessmentand the refinement of personalized dose planning in the clinic.Despite these clear advantages, bulk-based biomarker studies in both emergency andtherapeutic settings have well-documented limitations that hinder clinical translation. Priorreviews of radiotherapy biomarkers have highlighted significant obstacles to establishinguniversal predictors of radiosensitivity and response, including inter-tumoral heterogene-ity, variable microenvironmental influences, and limited reproducibility of bulk-basedsignatures [111,112]. Many candidate markers fail prospective validation because theyaverage signals across mixed cell populations, masking rare but critical subpopulationsthat determine treatment outcome. Single-cell RNA and its profiling can overcome thesechallenges by: (1) resolving cellular heterogeneity, identifying resistant or sensitive clonesthat constitute a small fraction of the tumour; (2) revealing microenvironmental interactions,such as immune-tumour cell cross-talk, that modulate radiosensitivity; and (3) enablingmulti-layered signatures, where transcriptomic, epigenetic, and proteomic features fromthe same cell can be integrated to yield more robust predictors.Recent studies have begun to apply single-cell techniques in clinical cohorts, includingpilot studies. Applying single-cell profiling in clinical cohorts has outperformed bulk as-says in stratifying radiotherapy responders versus non-responders [111,113]. For instance,Li et al. developed a radio-resistance gene signature in head and neck squamous cell carci-noma by integrating transcriptomic data and patient outcomes, demonstrating improvedprediction of radiotherapy response compared to traditional clinical parameters [114].These examples underscore the potential of single-cell-derived biomarkers to resolve cel-lular heterogeneity and refine predictive models for both emergency biodosimetry andprecision radiotherapy.Beyond ionizing radiation alone, cells are frequently exposed to additional stressors inradiotherapy, such as engineered nanomaterials, that can further influence DNA damage re-sponses. Chow describes nanoparticle properties such as size, shape, and surface chemistrythat govern their cellular uptake and DNA interactions, leading to direct strand breaks orindirect damage via reactive oxygen species generation [115]. Nanomaterials may also inter-fere with DNA repair proteins, altering cellular responses to ionizing radiation. Integratingthese biophysical insights with scRNA-seq would allow for the simultaneous quantifi-cation of physical lesions (e.g., via γ-H2AX imaging) and corresponding transcriptomicchanges in individual cells. Such a multimodal approach can identify cell type-specificbiomarkers of combined radiation–nanomaterial exposure, improving both our mecha-nistic understanding and the development of rapid assays for complex environmental orclinical scenarios.Cancers 2025, 17, 1801 12 of 186. Limitations and Future ProspectsAlthough automation has improved the efficiency of single-cell sequencing workflows,library preparation still requires at least 10 h, excluding sequencing and data analysistime [116]. Furthermore, the need for specialized equipment and stable laboratory environ-ments poses challenges for rapid field deployment. Additionally, the analysis of single-cellsequencing data is computationally intensive and requires specialized expertise, which canbe a limiting factor for rapid turnaround. Nevertheless, the unique capability of single-cellsequencing to uncover novel cellular subsets and specific gene expression signatures acrossdiverse tissues positions it as a valuable platform for advancing biomarker discovery. Itholds particular promise for the development of both rapid ex vivo diagnostic tools anddeeper insights into the long-term biological effects of radiation.Future applications of single-cell multi-omics, integrating transcriptomic, genomic,epigenomic, and proteomic data, may allow for the identification of specialized cellu-lar responses and therapeutic targets. We propose that radiation-sensitive biomarkersidentified via single-cell sequencing be compiled into a comprehensive biomarker matrixpanel (see Figure 2), which could support more accurate triage and personalized medicalcountermeasures following radiation exposure.Figure 2. Development of the radiation-sensitive biomarker panel. Single-cell sequencing wouldprovide biomarker candidates to be selected and validated with faster methods such as qPCR. Oncethe validation is completed, candidates would be measured against gold standard methods, such asDCA, for verification. The biomarker panel would benefit patients for triage and laboratory analysisin the event of a radiation emergency, which would serve not only for dosimetry and radiationprotection but also for guiding treatment in hospital settings, managing prescriptions, and facilitatingfollow-up healthcare.7. ConclusionsSingle-cell sequencing has revolutionized biomarker discovery by providing high-resolution insights into how individual cells respond to radiation. In nuclear emergencies,Cancers 2025, 17, 1801 13 of 18it enables the identification of early markers for rapid triage, while, in radiation oncology,these same insights can guide patient stratification and optimize therapeutic dosing. Giventhe urgency of such situations, single-cell sequencing is best positioned as an upstreamdiscovery tool. The key biomarkers identified through this approach can then be translatedinto faster, more accessible assays, such as quantitative PCR or immunoassays, for use inroutine laboratory settings and rapid triage. As the technology continues to progress, its in-tegration with multi-omics, machine learning, and emerging fields like nanotoxicology willfurther deepen our understanding of complex exposures. Ultimately, this combined strat-egy supports both immediate response efforts after a radiation incident and personalizedtreatment planning in the clinic.Supplementary Materials: The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/cancers17111801/s1, Table S1: Comprehensive Summary of RadiationBiomarker Candidates Identified in the Past Decade.Author Contributions: Conceptualization, Y.W. and J.Y.; writing—original draft preparation, J.Y.,M.G.M.K. and Y.W.; writing—review and editing, J.Y., M.G.M.K., N.M., B.K. and Y.W.; visualization,J.Y.; supervision, Y.W.; funding acquisition, Y.W. and J.Y. All authors have read and agreed to thepublished version of the manuscript.Funding: This research was funded by Atomic Energy of Canada Limited’s Federal Nuclear Scienceand Technology Program.Acknowledgments: The authors acknowledge C. Didychuk, M.-C. Gregoire, B. Ulicny, P. Ram, S.Parsons, J. Zwanenbeek, and B. 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next-generation sequencing
single-cell sequencing
radiation dosimetry
radiation biomarkers
cellular heterogeneity
Single-Cell Sequencing: An Emerging Tool for Biomarker Development in Nuclear Emergencies and Radiation Oncology
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