A genome-wide association study of radiotherapy induced toxicity in head and neck cancer patients identifies a susceptibility locus associated with mucositis

Attempts to Understand Oral Mucositis in Head and Neck Cancer Patients through Omics Studies: A Narrative Review

Oral mucositis (OM) is a common and clinically impactful side effect of cytotoxic cancer treatment, particularly in patients with head and neck squamous cell carcinoma (HNSCC) who undergo radiotherapy with or without concomitant chemotherapy. The etiology and pathogenic mechanisms of OM are complex, multifaceted and elicit both direct and indirect damage to the mucosa. In this narrative review, we describe studies that use various omics methodologies (genomics, transcriptomics, microbiomics and metabolomics) in attempts to elucidate the biological pathways associated with the development or severity of OM. Integrating different omics into multi-omics approaches carries the potential to discover links among host factors (genomics), host responses (transcriptomics, metabolomics), and the local environment (microbiomics).

Systematic Review of Genetic Polymorphisms Associated with Acute Pain Induced by Radiotherapy for Head and Neck Cancers

Background/objective

Pain is the most common acute symptom following radiation therapy (RT) for head and neck cancer (HNC). The multifactorial origin of RT-induced pain makes it highly challenging to manage. Multiple studies were conducted to identify genetic variants associated with cancer pain, however few of them focused on RT-induced acute pain. In this review, we summarize the potential mechanisms of acute pain after RT in HNC and identify genetic variants associated with RT-induced acute pain and relevant acute toxicities.

Methods

A comprehensive search of Ovid Medline, EMBASE and Web of Science databases using terms including "Variants", "Polymorphisms", "Radiotherapy", "Acute pain", "Acute toxicity" published up to February 28, 2022, was performed by two reviewers. Review articles and citations were reviewed manually. The identified SNPs associated with RT-induced acute pain and toxicities were reported, and the molecular functions of the associated genes were described based on genetic annotation using The Human Gene Database; GeneCards.

Results

A total of 386 articles were identified electronically and 8 more articles were included after manual search. 21 articles were finally included. 32 variants in 27 genes, of which 25% in inflammatory/immune response, 20% had function in DNA damage response and repair, 20% in cell death or cell cycle, were associated with RT-inflammatory pain and acute oral mucositis or dermatitis. 4 variants in 4 genes were associated with neuropathy and neuropathic pain. 5 variants in 4 genes were associated with RT-induced mixed types of post-RT-throat/neck pain.

Conclusion

Different types of pain develop after RT in HNC, including inflammatory pain; neuropathic pain; nociceptive pain; and mixed oral pain. Genetic variants involved in DNA damage response and repair, cell death, inflammation and neuropathic pathways may affect pain presentation post-RT. These variants could be used for personalized pain management in HNC patients receiving RT.

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types

BACKGROUND

This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung).

METHODS

A genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV-formerly SNP)-based heritability of rSTATacute in all patients and for each cancer type.

RESULTS

Shared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 × 10‒8 < P < 1.0 × 10‒5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size ‒0.17; P = 1.7 × 10‒7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 × 10‒6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected).

CONCLUSIONS

There is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta-genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.

Redefining precision radiotherapy through liquid biopsy

Precision radiotherapy refers to the ability to deliver radiation doses with sub-millimetre accuracy. It does not however consider individual variation in tumour or normal tissue response, failing to maximise tumour control and minimise toxicity. Combining precise delivery with personalised dosing, through analysis of cell-free DNA, would redefine precision in radiotherapy.

Normal Tissue Toxicity Prediction: Clinical Translation on the Horizon

Improvements in radiotherapy delivery have enabled higher therapeutic doses and improved efficacy, contributing to the growing number of long-term cancer survivors. These survivors are at risk of developing late toxicity from radiotherapy, and the inability to predict who is most susceptible results in substantial impact on quality of life and limits further curative dose escalation. A predictive assay or algorithm for normal tissue radiosensitivity would allow more personalized treatment planning, reducing the burden of late toxicity, and improving the therapeutic index. Progress over the last 10 years has shown that the etiology of late clinical radiotoxicity is multifactorial and informs development of predictive models that combine information on treatment (eg, dose, adjuvant treatment), demographic and health behaviors (eg, smoking, age), co-morbidities (eg, diabetes, collagen vascular disease), and biology (eg, genetics, ex vivo functional assays). AI has emerged as a useful tool and is facilitating extraction of signal from large datasets and development of high-level multivariable models. Some models are progressing to evaluation in clinical trials, and we anticipate adoption of these into the clinical workflow in the coming years. Information on predicted risk of toxicity could prompt modification of radiotherapy delivery (eg, use of protons, altered dose and/or fractionation, reduced volume) or, in rare instances of very high predicted risk, avoidance of radiotherapy. Risk information can also be used to assist treatment decision-making for cancers where efficacy of radiotherapy is equivalent to other treatments (eg, low-risk prostate cancer) and can be used to guide follow-up screening in instances where radiotherapy is still the best choice to maximize tumor control probability. Here, we review promising predictive assays for clinical radiotoxicity and highlight studies that are progressing to develop an evidence base for clinical utility.

A two-stage genome-wide association study identifies novel germline genetic variations in CACNA2D3 associated with radiotherapy response in nasopharyngeal carcinoma

BACKGROUND

Radiotherapy (RT) is the standard treatment for nasopharyngeal carcinoma (NPC). However, due to individual differences in radiosensitivity, biomarkers are needed to tailored radiotherapy to cancer patients. However, comprehensive genome-wide radiogenomic studies on them are still lacking. The aim of this study was to identify genetic variants associated with radiotherapy response in patients with NPC.

METHODS

This was a large‑scale genome-wide association analysis (GWAS) including a total of 981 patients. 319 individuals in the discovery stage were genotyped for 688,783 SNPs using whole genome-wide screening microarray. Significant loci were further genotyped using MassARRAY system and TaqMan SNP assays in the validation stages of 847 patients. This study used logistic regression analysis and multiple bioinformatics tools such as PLINK, LocusZoom, LDBlockShow, GTEx, Pancan-meQTL and FUMA to examine genetic variants associated with radiotherapy efficacy in NPC.

RESULTS

After genome-wide level analysis, 19 SNPs entered the validation stage (P < 1 × 10^- 6), and rs11130424 ultimately showed statistical significance among these SNPs. The efficacy was better in minor allele carriers of rs11130424 than in major allele carriers. Further stratified analysis showed that the association existed in patients in the EBV-positive, smoking, and late-stage (III and IV) subgroups and in patients who underwent both concurrent chemoradiotherapy and induction/adjuvant chemotherapy.

CONCLUSION

Our study showed that rs11130424 in the CACNA2D3 gene was associated with sensitivity to radiotherapy in NPC patients.

TRIAL REGISTRATION NUMBER

Effect of genetic polymorphism on nasopharyngeal carcinoma chemoradiotherapy reaction, ChiCTR-OPC-14005257, Registered 18 September 2014, http://www.chictr.org.cn/showproj.aspx?proj=9546 .

The sex-dependent impact of PER2 polymorphism on sleep and activity in a novel mouse model of cranial-irradiation-induced hypersomnolence

Background

Hypersomnolence is a common and disruptive side effect of cranial radiotherapy and is associated with fatigue and disturbances in mood and cognition in primary brain tumor (PBT) patients. The biological underpinnings of this effect are not understood. Our laboratory has previously found that the presence of a single nucleotide polymorphism (rs934945, G-E mutation) in the PERIOD2 (PER2) clock gene was associated with a decreased likelihood of fatigue in PBT patients. Here, we aim to understand the effects of PER2 polymorphism on radiation susceptibility within a murine model of cranial-irradiation-induced hypersomnolence (C-RIH).

Methods

Male and female transgenic mice were generated using CRISPR-Cas9, replacing the endogenous mouse PER2:CRY1 binding domain with its human isoform with (hE1244 KI) or without the SNP rs934945 (hG1244 KI). Activity and sleep were monitored continuously 10 days before and after cranial irradiation (whole brain, 15Gy, single fraction). Behavioral assessments measuring anxiety, depression, and working memory were used to assess mood and cognitive changes 2 months postradiation.

Results

During their active phase, hE1244 knock-ins (KIs) had less radiation-induced suppression of activity relative to hG1244 KIs and female hE1244 KIs saw a reduction of hypersomnolence over 10 days. hE1244 KIs displayed less anxiety behavior and were more ambulatory within all behavioral tests.

Conclusions

The PER2 rs934945 polymorphism had long-lasting behavioral effects associated with radiation toxicity, particularly in sleep in females and the activity of all animals. Our findings shed light on biological mechanisms underlying C-RIH.

Germline genetic biomarkers to stratify patients for personalized radiation treatment

Background

Precision medicine incorporating genetic profiling is becoming a standard of care in medical oncology. However, in the field of radiation oncology there is limited use of genetic profiling and the impact of germline genetic biomarkers on radiosensitivity, radioresistance, or patient outcomes after radiation therapy is poorly understood. In HNSCC, the toxicity associated with treatment can cause delays or early cessation which has been associated with worse outcomes. Identifying potential biomarkers which can help predict toxicity, as well as response to treatment, is of significant interest.

Methods

Patients with HNSCC who received RT and underwent next generation sequencing of somatic tumor samples, transcriptome RNA-seq with matched normal tissue samples were included. Patients were then grouped by propensity towards increased late vs. early toxicity (Group A) and those without (Group B), assessed by CTCAE v5.0. The groups were then analyzed for association of specific germline variants with toxicity and clinical outcomes.

Results

In this study we analyzed 37 patients for correlation between germline variants and toxicity. We observed that TSC2, HLA-A, TET2, GEN1, NCOR2 and other germline variants were significantly associated with long term toxicities. 34 HNSCC patients treated with curative intent were evaluated for clinical outcomes. Group A had significantly improved overall survival as well as improved rates of locoregional recurrence and metastatic disease. Specific variants associated with improved clinical outcomes included TSC2, FANCD2, and PPP1R15A, while the HLA-A and GEN1 variants were not correlated with survival or recurrence. A group of five HLA-DMA/HLA-DMB variants was only found in Group B and was associated with a higher risk of locoregional recurrence.

Conclusions

This study indicates that germline genetic biomarkers may have utility in predicting toxicity and outcomes after radiation therapy and deserve further investigation in precision radiation medicine approaches.