Analysis of Saliva Gene Expression during Head and Neck Cancer Radiotherapy: A Pilot Study

Radiation Research Society Journal-based Historical Review of the Use of Biomarkers for Radiation Dose and Injury Assessment: Acute Health Effects Predictions

A multiple-parameter based approach using radiation-induced clinical signs and symptoms, hematology changes, cytogenetic chromosomal aberrations, and molecular biomarkers changes after radiation exposure is used for biodosimetry-based dose assessment. In the current article, relevant milestones from Radiation Research are documented that forms the basis of the current consensus approach for diagnostics after radiation exposure. For example, in 1962 the use of cytogenetic chromosomal aberration using the lymphocyte metaphase spread dicentric assay for biodosimetry applications was first published in Radiation Research. This assay is now complimented using other cytogenetic chromosomal aberration assays (i.e., chromosomal translocations, cytokinesis-blocked micronuclei, premature chromosome condensation, γ-H2AX foci, etc.). Changes in blood cell counts represent an early-phase biomarker for radiation exposures. Molecular biomarker changes have evolved to include panels of organ-specific plasma proteomic and blood-based gene expression biomarkers for radiation dose assessment. Maturation of these assays are shown by efforts for automated processing and scoring, development of point-of-care diagnostics devices, service laboratories inter-comparison exercises, and applications for dose and injury assessments in radiation accidents. An alternative and complementary approach has been advocated with the focus to de-emphasize "dose" and instead focus on predicting acute or delayed health effects. The same biomarkers used for dose estimation (e.g., lymphocyte counts) can be used to directly predict the later developing severity degree of acute health effects without performing dose estimation as an additional or intermediate step. This review illustrates contributing steps toward these developments published in Radiation Research.

Applicability of Gene Expression in Saliva as an Alternative to Blood for Biodosimetry and Prediction of Radiation-induced Health Effects

As the great majority of gene expression (GE) biodosimetry studies have been performed using blood as the preferred source of tissue, searching for simple and less-invasive sampling methods is important when considering biodosimetry approaches. Knowing that whole saliva contains an ultrafiltrate of blood and white blood cells, it is expected that the findings in blood can also be found in saliva. This human in vivo study aims to examine radiation-induced GE changes in saliva for biodosimetry purposes and to predict radiation-induced disease, which is yet poorly characterized. Furthermore, we examined whether transcriptional biomarkers in blood can also be found equivalently in saliva. Saliva and blood samples were collected in parallel from radiotherapy (RT) treated patients who suffered from head and neck cancer (n = 8) undergoing fractioned partial-body irradiations (1.8 Gy/fraction and 50-70 Gy total dose). Samples were taken 12-24 h before first irradiation and ideally 24 and 48 h, as well as 5 weeks after radiotherapy onset. Due to the low quality and quantity of isolated RNA samples from one patient, they had to be excluded from further analysis, leaving a total of 24 saliva and 24 blood samples from 7 patients eligible for analysis. Using qRT-PCR, 18S rRNA and 16S rRNA (the ratio being a surrogate for the relative human RNA/bacterial burden), four housekeeping genes and nine mRNAs previously identified as radiation responsive in blood-based studies were detected. Significant GE associations with absorbed dose were found for five genes and after the 2nd radiotherapy fraction, shown by, e.g., the increase of CDKN1A (2.0 fold, P = 0.017) and FDXR (1.9 fold increased, P = 0.002). After the 25th radiotherapy fraction, however, all four genes (FDXR, DDB2, POU2AF1, WNT3) predicting ARS (acute radiation syndrome) severity, as well as further genes (including CCNG1 [median-fold change (FC) = 0.3, P = 0.013], and GADD45A (median-FC = 0.3, P = 0.031)) appeared significantly downregulated (FC = 0.3, P = 0.01-0.03). A significant association of CCNG1, POU2AF1, HPRT1, and WNT3 (P = 0.006-0.04) with acute or late radiotoxicity could be shown before the onset of these clinical outcomes. In an established set of four genes predicting acute health effects in blood, the response in saliva samples was similar to the expected up- (FDXR, DDB2) or downregulation (POU2AF1, WNT3) in blood for up to 71% of the measurements. Comparing GE responses (PHPT1, CCNG1, CDKN1A, GADD45A, SESN1) in saliva and blood samples, there was a significant linear association between saliva and blood response of CDKN1A (R2 = 0.60, P = 0.0004). However, the GE pattern of other genes differed between saliva and blood. In summary, the current human in vivo study, (I) reveals significant radiation-induced GE associations of five transcriptional biomarkers in salivary samples, (II) suggests genes predicting diverse clinical outcomes such as acute and late radiotoxicity as well as ARS severity, and (III) supports the view that blood-based GE response can be reflected in saliva samples, indicating that saliva is a "mirror of the body" for certain but not all genes and, thus, studies for each gene of interest in blood are required for saliva.

Paper-Based Vertical Flow Immunoassay for the Point-of-Care Multiplex Detection of Radiation Dosimetry Genes

In a nuclear or radiological incident, first responders must quickly and accurately measure radiation exposure among civilians as medical countermeasures are radiation dose-dependent and time-sensitive. Although several approaches have been explored to measure absorbed radiation dose, there is an important need to develop point-of-care (POC) bioassay devices that can be used immediately to triage thousands of individuals potentially exposed to radiation. Here we present a proof-of-concept study showing the use of a paper-based vertical flow immunoassay (VFI) to detect radiation dosimetry genes. Using labeled primers during amplification and a multiplex membrane, our results showed that the nucleic acid VFI can simultaneously detect two biodosimetry genes, CDKN1A and DDB2, as well as one housekeeping gene MRPS5. The assay demonstrated good linearity and precision with an inter- and intra-assay coefficient of variance <20% and <10%, respectively. Moreover, the assay showed its ability to discriminate non-irradiated controls (0 Gy) from irradiated samples (1 + 2 Gy) with an overall sensitivity of 62.5% and specificity of 100% (AUC = 0.8672, 95% CI: 0.723-1.000; p = 0.004). Interestingly, the gene combination also showed a dose-dependent response for 0, 1, and 2 Gy, similar to data obtained by real-time PCR benchmark. These preliminary results suggest that a VFI platform can be used to detect simultaneously multiple genes that can be then quantified, thus offering a new approach for a POC biodosimetry assay that could be rapidly deployed on-site to test a large population and help triage and medical management after radiological event.

Saliva Based Liquid Biopsies in Head and Neck Cancer: How Far Are We From the Clinic?

Head and neck cancer (HNC) remains to be a major cause of mortality worldwide because of confounding factors such as late-stage tumor diagnosis, loco-regional aggressiveness and distant metastasis. The current standardized diagnostic regime for HNC is tissue biopsy which fails to determine the thorough tumor dynamics. Therefore, due to the ease of collection, recent studies have focused on the utility of saliva based liquid biopsy approach for serial sampling, early diagnosis, prognosis, longitudinal monitoring of disease progression and treatment response in HNC patients. Saliva collection is convenient, non-invasive, and pain-free and offers repetitive sampling along with real time monitoring of the disease. Moreover, the detection, isolation and analysis of tumor-derived components such as Circulating Tumor Nucleic Acids (CTNAs), Extracellular Vesicles (EVs), Circulating Tumor Cells (CTCs) and metabolites from saliva can be used for genomic and proteomic examination of HNC patients. Although, these circulatory biomarkers have a wide range of applications in clinical settings, no validated data has yet been established for their usage in clinical practice for HNC. Improvements in isolation and detection technologies and next-generation sequencing analysis have resolved many technological hurdles, allowing a wide range of saliva based liquid biopsy application in clinical backgrounds. Thus, in this review, we discussed the rationality of saliva as plausible biofluid and clinical sample for diagnosis, prognosis and therapeutics of HNC. We have described the molecular components of saliva that could mirror the disease status, recent outcomes of salivaomics associated with HNC and current technologies which have the potential to improve the clinical value of saliva in HNC.

Examining potential confounding factors in gene expression analysis of human saliva and identifying potential housekeeping genes

Isolation of RNA from whole saliva, a non-invasive and easily accessible biofluid that is an attractive alternative to blood for high-throughput biodosimetry of radiological/nuclear victims might be of clinical significance for prediction and diagnosis of disease. In a previous analysis of 12 human samples we identified two challenges to measuring gene expression from total RNA: (1) the fraction of human RNA in whole saliva was low and (2) the bacterial contamination was overwhelming. To overcome these challenges, we performed selective cDNA synthesis for human RNA species only by employing poly(A)+-tail primers followed by qRT-PCR. In the current study, this approach was independently validated on 91 samples from 61 healthy donors. Additionally, we used the ratio of human to bacterial RNA to adjust the input RNA to include equal amounts of human RNA across all samples before cDNA synthesis, which then ensured comparable analysis using the same base human input material. Furthermore, we examined relative levels of ten known housekeeping genes, and assessed inter- and intra-individual differences in 61 salivary RNA isolates, while considering effects of demographical factors (e.g. sex, age), epidemiological factors comprising social habits (e.g. alcohol, cigarette consumption), oral hygiene (e.g. flossing, mouthwash), previous radiological diagnostic procedures (e.g. number of CT-scans) and saliva collection time (circadian periodic). Total human RNA amounts appeared significantly associated with age only (P ≤ 0.02). None of the chosen housekeeping genes showed significant circadian periodicity and either did not associate or were weakly associated with the 24 confounders examined, with one exception, 60% of genes were altered by mouthwash. ATP6, ACTB and B2M represented genes with the highest mean baseline expression (Ct-values ≤ 30) and were detected in all samples. Combining these housekeeping genes for normalization purposes did not decrease inter-individual variance, but increased the robustness. In summary, our work addresses critical confounders and provides important information for the successful examination of gene expression in human whole saliva.

Application of liquid biopsy as multi-functional biomarkers in head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) is a molecularly heterogeneous disease, with a 5-year survival rate that still hovers at ~60% despite recent advancements. The advanced stage upon diagnosis, limited success with effective targeted therapy and lack of reliable biomarkers are among the key factors underlying the marginally improved survival rates over the decades. Prevention, early detection and biomarker-driven treatment adaptation are crucial for timely interventions and improved clinical outcomes. Liquid biopsy, analysis of tumour-specific biomarkers circulating in bodily fluids, is a rapidly evolving field that may play a striking role in optimising patient care. In recent years, significant progress has been made towards advancing liquid biopsies for non-invasive early cancer detection, prognosis, treatment adaptation, monitoring of residual disease and surveillance of recurrence. While these emerging technologies have immense potential to improve patient survival, numerous methodological and biological limitations must be overcome before their implementation into clinical practice. This review outlines the current state of knowledge on various types of liquid biopsies in HNSCC, and their potential applications for diagnosis, prognosis, grading treatment response and post-treatment surveillance. It also discusses challenges associated with the clinical applicability of liquid biopsies and prospects of the optimised approaches in the management of HNSCC.

Gene expression for biodosimetry and effect prediction purposes: promises, pitfalls and future directions - key session ConRad 2021

PURPOSE

In a nuclear or radiological event, an early diagnostic or prognostic tool is needed to distinguish unexposed from low- and highly exposed individuals with the latter requiring early and intensive medical care. Radiation-induced gene expression (GE) changes observed within hours and days after irradiation have shown potential to serve as biomarkers for either dose reconstruction (retrospective dosimetry) or the prediction of consecutively occurring acute or chronic health effects. The advantage of GE markers lies in their capability for early (1-3 days after irradiation), high-throughput, and point-of-care (POC) diagnosis required for the prediction of the acute radiation syndrome (ARS).

CONCLUSIONS

As a key session of the ConRad conference in 2021, experts from different institutions were invited to provide state-of-the-art information on a range of topics including: (1) Biodosimetry: What are the current efforts to enhance the applicability of this method to perform retrospective biodosimetry? (2) Effect prediction: Can we apply radiation-induced GE changes for prediction of acute health effects as an approach, complementary to and integrating retrospective dose estimation? (3) High-throughput and point-of-care diagnostics: What are the current developments to make the GE approach applicable as a high-throughput as well as a POC diagnostic platform? (4) Low level radiation: What is the lowest dose range where GE can be used for biodosimetry purposes? (5) Methodological considerations: Different aspects of radiation-induced GE related to more detailed analysis of exons, transcripts and next-generation sequencing (NGS) were reported.

Transcriptomics for radiation biodosimetry: progress and challenges

PURPOSE

Transcriptomic-based approaches are being developed to meet the needs for large-scale radiation dose and injury assessment and provide population triage following a radiological or nuclear event. This review provides background and definition of the need for new biodosimetry approaches, and summarizes the major advances in this field. It discusses some of the major model systems used in gene signature development, and highlights some of the remaining challenges, including individual variation in gene expression, potential confounding factors, and accounting for the complexity of realistic exposure scenarios.

CONCLUSIONS

Transcriptomic approaches show great promise for both dose reconstruction and for prediction of individual radiological injury. However, further work will be needed to ensure that gene expression signatures will be robust and appropriate for their intended use in radiological or nuclear emergencies.

Overcoming challenges in human saliva gene expression measurements

Saliva, as a non-invasive and easily accessible biofluid, has been shown to contain RNA biomarkers for prediction and diagnosis of several diseases. However, systematic analysis done by our group identified two problematic issues not coherently described before: (1) most of the isolated RNA originates from the oral microbiome and (2) the amount of isolated human RNA is comparatively low. The degree of bacterial contamination showed ratios up to 1:900,000, so that only about one out of 900,000 RNA copies was of human origin, but the RNA quality (average RIN 6.7 + /− 0.8) allowed for qRT-PCR. Using 12 saliva samples from healthy donors, we modified the methodology to (1) select only human RNA during cDNA synthesis by aiming at the poly(A)+-tail and (2) introduced a pre-amplification of human RNA before qRT-PCR. Further, the manufacturer’s criteria for successful pre-amplification (Ct values ≤ 35 for unamplified cDNA) had to be replaced by (3) proofing linear pre-amplification for each gene, thus, increasing the number of evaluable samples up to 70.6%. When considering theses three modifications unbiased gene expression analysis on human salivary RNA can be performed.

Salivary Biomarkers for Oral Squamous Cell Carcinoma Diagnosis and Follow-Up: Current Status and Perspectives

Oral cancer is the sixth most common cancer type in the world, and 90% of it is represented by oral squamous cell carcinoma (OSCC). Despite progress in preventive and therapeutic strategies, delay in OSCC diagnosis remains one of the major causes of high morbidity and mortality; indeed the majority of OSCC has been lately identified in the advanced clinical stage (i.e., III or IV). Moreover, after primary treatment, recurrences and/or metastases are found in more than half of the patients (80% of cases within the first 2 years) and the 5-year survival rate is still lower than 50%, resulting in a serious issue for public health. Currently, histological investigation represents the “gold standard” of OSCC diagnosis; however, recent studies have evaluated the potential use of non-invasive methods, such as “liquid biopsy,” for the detection of diagnostic and prognostic biomarkers in body fluids of oral cancer patients. Saliva is a biofluid containing factors such as cytokines, DNA and RNA molecules, circulating and tissue-derived cells, and extracellular vesicles (EVs) that may be used as biomarkers; their analysis may give us useful information to do early diagnosis of OSCC and improve the prognosis. Therefore, the aim of this review is reporting the most recent data on saliva biomarker detection in saliva liquid biopsy from oral cancer patients, with particular attention to circulating tumor DNA (ctDNA), EVs, and microRNAs (miRNAs). Our results highlight that saliva liquid biopsy has several promising clinical uses in OSCC management; it is painless, accessible, and low cost and represents a very helpful source of diagnostic and prognostic biomarker detection. Even if standardized protocols for isolation, characterization, and evaluation are needed, recent data suggest that saliva may be successfully included in future clinical diagnostic processes, with a considerable impact on early treatment strategies and a favorable outcome.

Salivary Metabolomics of Total Body Irradiated Nonhuman Primates Reveals Long-Term Normal Tissue Responses to Radiation

PURPOSE

To identify metabolomic biomarkers of acute radiation exposure in saliva that show time-dependent changes.

METHODS AND MATERIALS

Nonhuman primates were exposed to 4 Gy of total body irradiation with γ-rays. Saliva was collected from 7 animals twice before and at days 1, 3, 5, 7, 15, 21, 28, and 60 after irradiation. Profiling was conducted with liquid chromatography time-of-flight mass spectrometry. Multivariate data analysis and potential biomarker identification was conducted through random Forests and the software MetaboAnalyst. Candidate biomarkers were validated through tandem mass spectrometry, and receiver operating characteristic curves were constructed to show the diagnostic ability of the signature over time.

RESULTS

Untargeted metabolomic analysis revealed significant and persistent effects up to the 60 days evaluated in this study. Biomarkers spanning primarily amino acids and nucleotides were identified, with a significant number showing long-term responses. Fifteen biomarkers showed high statistical significance in the first week after irradiation and 16 at >7 days after irradiation (false discovery rate-adjusted P < .05). The combination of the biomarkers in a single biosignature was able to accurately show the diagnostic ability of the signature in a binary classifier system with receiver operating characteristic curves.

CONCLUSIONS

Radiation can alter the metabolome in saliva, and metabolomics could effectively be used to monitor radiation responses, as a biodosimetry method, in the event of a radiological incident. Saliva metabolomics also has potential relevance in a clinical setting.

Measurement of γ-H2AX foci, miRNA-101, and gene expression as a means to quantify radiation-absorbed dose in cancer patients who had undergone radiotherapy

Radiological accidents and nuclear terrorism pose an increased threat to members of the public who, following such an event, would need to be assessed for medical care by fast triage. Assay methods such as chromosome aberrations (CA), cytokinesis-block micronucleus (CBMN) and fluorescence in situ hybridization (FISH) techniques have been well established for dose estimation and their potential for handling more samples has also been proved with automation. However, culturing of lymphocytes is an inevitable step, which limits the potential of these markers for triage. In vitro analysis of gamma-H2AX (γ-H2AX), gene and microRNA (miRNA) markers do not require culturing of lymphocytes, and as such have been suggested as attractive tools for triage. Despite studies reporting in vitro dose-response curves, limited evidence is available evaluating the suitability of these assays in real situations. In this study, we have measured the absorbed dose using γ-H2AX, gene (GADD45A, FDXR, and CDKN1A) and miRNA-101 expression in blood samples of cancer patients (n = 20) who had undergone partial-body radiotherapy and compared with the derived equivalent whole-body doses (EWBD). The obtained results from all patients showed a significant (p < 0.05) increase of γ-H2AX foci in post-irradiated as compared to pre-irradiated samples. Moreover, estimated doses using γ-H2AX foci showed a correlation with the derived EWBD (r² = 0.60, p = 0.0003) and was also shown to be dependent on the irradiated body volume. Consistent with γ-H2AX foci frequency, an increase in fold change expression of genes and miRNA-101 was observed. However, the estimated dose significantly varied among the subjects and showed poor correlation (r² = 0.09, 0.04, 0.01 and 0.03 for GADD45A, FDXR, CDKN1A and miRNA-101, respectively) with EWBD. The overall results suggest that the established in vitro γ-H2AX assay is suitable for the detection of radiation exposure and can also provide an estimate of the dose in in vivo irradiated samples. The genes and miRNA-101 markers showed increased expression; nevertheless, there is a need for further improvements to measure doses accurately using these markers.

Candidate gene biodosimetry markers of exposure to external ionizing radiation in human blood: A systematic review

Purpose

To compile a list of genes that have been reported to be affected by external ionizing radiation (IR) and to assess their performance as candidate biomarkers for individual human radiation dosimetry.

Methods

Eligible studies were identified through extensive searches of the online databases from 1978 to 2017. Original English-language publications of microarray studies assessing radiation-induced changes in gene expression levels in human blood after external IR were included. Genes identified in at least half of the selected studies were retained for bio-statistical analysis in order to evaluate their diagnostic ability.

Results

24 studies met the criteria and were included in this study. Radiation-induced expression of 10,170 unique genes was identified and the 31 genes that have been identified in at least 50% of studies (12/24 studies) were selected for diagnostic power analysis. Twenty-seven genes showed a significant Spearman’s correlation with radiation dose. Individually, TNFSF4, FDXR, MYC, ZMAT3 and GADD45A provided the best discrimination of radiation dose < 2 Gy and dose ≥ 2 Gy according to according to their maximized Youden’s index (0.67, 0.55, 0.55, 0.55 and 0.53 respectively). Moreover, 12 combinations of three genes display an area under the Receiver Operating Curve (ROC) curve (AUC) = 1 reinforcing the concept of biomarker combinations instead of looking for an ideal and unique biomarker.

Conclusion

Gene expression is a promising approach for radiation dosimetry assessment. A list of robust candidate biomarkers has been identified from analysis of the studies published to date, confirming for example the potential of well-known genes such as FDXR and TNFSF4 or highlighting other promising gene such as ZMAT3. However, heterogeneity in protocols and analysis methods will require additional studies to confirm these results.

Clinical multi-omics strategies for the effective cancer management

Cancer is a global health issue as a multi-factorial complex disease, and early detection and novel therapeutic strategies are required for more effective cancer management. With the development of systemic analytical -omics strategies, the therapeutic approach and study of the molecular mechanisms of carcinogenesis and cancer progression have moved from hypothesis-driven targeted investigations to data-driven untargeted investigations focusing on the integrated diagnosis, treatment, and prevention of cancer in individual patients. Predictive, preventive, and personalized medicine (PPPM) is a promising new approach to reduce the burden of cancer and facilitate more accurate prognosis, diagnosis, as well as effective treatment. Here we review the fundamentals of, and new developments in, -omics technologies, together with the key role of a variety of practical -omics strategies in PPPM for cancer treatment and diagnosis.

BIOLOGICAL SIGNIFICANCE

In this review, a comprehensive and critical overview of the systematic strategy for predictive, preventive, and personalized medicine (PPPM) for cancer disease was described in a view of cancer prognostic prediction, diagnostics, and prevention as well as cancer therapy and drug responses. We have discussed multi-dimensional data obtained from various resources and integration of multisciplinary -omics strategies with computational method which could contribute the more effective PPPM for cancer. This review has provided the novel insights of the current applications of each and combined -omics technologies, which showed their powerful potential for the establishment of PPPM for cancer.