Genome-wide association studies and prediction of normal tissue toxicity

Machine Learning for Head and Neck Cancer: A Safe Bet?-A Clinically Oriented Systematic Review for the Radiation Oncologist

BACKGROUND AND PURPOSE

Machine learning (ML) is emerging as a feasible approach to optimize patients' care path in Radiation Oncology. Applications include autosegmentation, treatment planning optimization, and prediction of oncological and toxicity outcomes. The purpose of this clinically oriented systematic review is to illustrate the potential and limitations of the most commonly used ML models in solving everyday clinical issues in head and neck cancer (HNC) radiotherapy (RT).

MATERIALS AND METHODS

Electronic databases were screened up to May 2021. Studies dealing with ML and radiomics were considered eligible. The quality of the included studies was rated by an adapted version of the qualitative checklist originally developed by Luo et al. All statistical analyses were performed using R version 3.6.1.

RESULTS

Forty-eight studies (21 on autosegmentation, four on treatment planning, 12 on oncological outcome prediction, 10 on toxicity prediction, and one on determinants of postoperative RT) were included in the analysis. The most common imaging modality was computed tomography (CT) (40%) followed by magnetic resonance (MR) (10%). Quantitative image features were considered in nine studies (19%). No significant differences were identified in global and methodological scores when works were stratified per their task (i.e., autosegmentation).

DISCUSSION AND CONCLUSION

The range of possible applications of ML in the field of HN Radiation Oncology is wide, albeit this area of research is relatively young. Overall, if not safe yet, ML is most probably a bet worth making.

Musashi expression in intestinal stem cells attenuates radiation-induced decline in intestinal permeability and survival in Drosophila

Exposure to genotoxic stress by environmental agents or treatments, such as radiation therapy, can diminish healthspan and accelerate aging. We have developed a Drosophila melanogaster model to study the molecular effects of radiation-induced damage and repair. Utilizing a quantitative intestinal permeability assay, we performed an unbiased GWAS screen (using 156 strains from the Drosophila Genetic Reference Panel) to search for natural genetic variants that regulate radiation-induced gut permeability in adult D. melanogaster. From this screen, we identified an RNA binding protein, Musashi (msi), as one of the possible genes associated with changes in intestinal permeability upon radiation. The overexpression of msi promoted intestinal stem cell proliferation, which increased survival after irradiation and rescued radiation-induced intestinal permeability. In summary, we have established D. melanogaster as an expedient model system to study the effects of radiation-induced damage to the intestine in adults and have identified msi as a potential therapeutic target.

Multivalent Binding and Biomimetic Cell Rolling Improves the Sensitivity and Specificity of Circulating Tumor Cell Capture

Purpose: We aimed to examine the effects of multivalent binding and biomimetic cell rolling on the sensitivity and specificity of circulating tumor cell (CTC) capture. We also investigated the clinical significance of CTCs and their kinetic profiles in patients with cancer undergoing radiotherapy treatment.Experimental Design: Patients with histologically confirmed primary carcinoma undergoing radiotherapy, with or without chemotherapy, were eligible for enrollment. Peripheral blood was collected prospectively at up to five time points, including before radiotherapy, at the first week, mid-point and final week of treatment, as well as 4 to 12 weeks after completion of radiotherapy. CTC capture was accomplished using a nanotechnology-based assay (CapioCyte) functionalized with aEpCAM, aHER-2, and aEGFR.Results: CapioCyte was able to detect CTCs in all 24 cancer patients enrolled. Multivalent binding via poly(amidoamine) dendrimers further improved capture sensitivity. We also showed that cell rolling effect can improve CTC capture specificity (% of captured cells that are CK+/CD45-/DAPI+) up to 38%. Among the 18 patients with sequential CTC measurements, the median CTC decreased from 113 CTCs/mL before radiotherapy to 32 CTCs/mL at completion of radiotherapy (P = 0.001). CTCs declined throughout radiotherapy in patients with complete clinical and/or radiographic response, in contrast with an elevation in CTCs at mid or post-radiotherapy in the two patients with known pathologic residual disease.Conclusions: Our study demonstrated that multivalent binding and cell rolling can improve the sensitivity and specificity of CTC capture compared with multivalent binding alone, allowing reliable monitoring of CTC changes during and after treatment. Clin Cancer Res; 24(11); 2539-47. ©2018 AACR.

Radiogenomics: A systems biology approach to understanding genetic risk factors for radiotherapy toxicity?

Adverse reactions in normal tissue after radiotherapy (RT) limit the dose that can be given to tumour cells. Since 80% of individual variation in clinical response is estimated to be caused by patient-related factors, identifying these factors might allow prediction of patients with increased risk of developing severe reactions. While inactivation of cell renewal is considered a major cause of toxicity in early-reacting normal tissues, complex interactions involving multiple cell types, cytokines, and hypoxia seem important for late reactions. Here, we review 'omics' approaches such as screening of genetic polymorphisms or gene expression analysis, and assess the potential of epigenetic factors, posttranslational modification, signal transduction, and metabolism. Furthermore, functional assays have suggested possible associations with clinical risk of adverse reaction. Pathway analysis incorporating different 'omics' approaches may be more efficient in identifying critical pathways than pathway analysis based on single 'omics' data sets. Integrating these pathways with functional assays may be powerful in identifying multiple subgroups of RT patients characterised by different mechanisms. Thus 'omics' and functional approaches may synergise if they are integrated into radiogenomics 'systems biology' to facilitate the goal of individualised radiotherapy.

Radiation oncology in the era of precision medicine

Technological advances and clinical research over the past few decades have given radiation oncologists the capability to personalize treatments for accurate delivery of radiation dose based on clinical parameters and anatomical information. Eradication of gross and microscopic tumours with preservation of health-related quality of life can be achieved in many patients. Two major strategies, acting synergistically, will enable further widening of the therapeutic window of radiation oncology in the era of precision medicine: technology-driven improvement of treatment conformity, including advanced image guidance and particle therapy, and novel biological concepts for personalized treatment, including biomarker-guided prescription, combined treatment modalities and adaptation of treatment during its course.

Incorporating Genetic Biomarkers into Predictive Models of Normal Tissue Toxicity

There is considerable variation in the level of toxicity patients experience for a given dose of radiotherapy, which is associated with differences in underlying individual normal tissue radiosensitivity. A number of syndromes have a large effect on clinical radiosensitivity, but these are rare. Among non-syndromic patients, variation is less extreme, but equivalent to a ±20% variation in dose. Thus, if individual normal tissue radiosensitivity could be measured, it should be possible to optimise schedules for individual patients. Early investigations of in vitro cellular radiosensitivity supported a link with tissue response, but individual studies were equivocal. A lymphocyte apoptosis assay has potential, and is currently under prospective validation. The investigation of underlying genetic variation also has potential. Although early candidate gene studies were inconclusive, more recent genome-wide association studies are revealing definite associations between genotype and toxicity and highlighting the potential for future genetic testing. Genetic testing and individualised dose prescriptions could reduce toxicity in radiosensitive patients, and permit isotoxic dose escalation to increase local control in radioresistant individuals. The approach could improve outcomes for half the patients requiring radical radiotherapy. As a number of patient- and treatment-related factors also affect the risk of toxicity for a given dose, genetic testing data will need to be incorporated into models that combine patient, treatment and genetic data.

Exploiting biological and physical determinants of radiotherapy toxicity to individualize treatment

The recent advances in radiation delivery can improve tumour control probability (TCP) and reduce treatment-related toxicity. The use of intensity-modulated radiotherapy (IMRT) in particular can reduce normal tissue toxicity, an objective in its own right, and can allow safe dose escalation in selected cases. Ideally, IMRT should be combined with image guidance to verify the position of the target, since patients, target and organs at risk can move day to day. Daily image guidance scans can be used to identify the position of normal tissue structures and potentially to compute the daily delivered dose. Fundamentally, it is still the tolerance of the normal tissues that limits radiotherapy (RT) dose and therefore tumour control. However, the dose-response relationships for both tumour and normal tissues are relatively steep, meaning that small dose differences can translate into clinically relevant improvements. Differences exist between individuals in the severity of toxicity experienced for a given dose of RT. Some of this difference may be the result of differences between the planned dose and the accumulated dose (DA). However, some may be owing to intrinsic differences in radiosensitivity of the normal tissues between individuals. This field has been developing rapidly, with the demonstration of definite associations between genetic polymorphisms and variation in toxicity recently described. It might be possible to identify more resistant patients who would be suitable for dose escalation, as well as more sensitive patients for whom toxicity could be reduced or avoided. Daily differences in delivered dose have been investigated within the VoxTox research programme, using the rectum as an example organ at risk. In patients with prostate cancer receiving curative RT, considerable daily variation in rectal position and dose can be demonstrated, although the median position matches the planning scan well. Overall, in 10 patients, the mean difference between planned and accumulated rectal equivalent uniform doses was -2.7 Gy (5%), and a dose reduction was seen in 7 of the 10 cases. If dose escalation was performed to take rectal dose back to the planned level, this should increase the mean TCP (as biochemical progression-free survival) by 5%. Combining radiogenomics with individual estimates of DA might identify almost half of patients undergoing radical RT who might benefit from either dose escalation, suggesting improved tumour cure or reduced toxicity or both.

A Preliminary Study on Racial Differences in HMOX1, NFE2L2, and TGFβ1 Gene Polymorphisms and Radiation-Induced Late Normal Tissue Toxicity

PURPOSE

This study tested whether racial differences in genetic polymorphisms of 4 genes involved in wound repair and response to radiation can be used to predict the occurrence of normal tissue late effects of radiation therapy and indicate potential therapeutic targets.

METHODS AND MATERIALS

This prospective study examined genetic polymorphisms that modulate the expression of 4 genes involved in inflammation and fibrosis and response to radiation (HMOX1, NFE2L2, NOS3, and TGFβ1). DNA from blood samples of 179 patients (∼ 80% breast and head and neck) collected at the time of diagnosis by their radiation oncologist as exhibiting late normal tissue toxicity was used for the analysis. Patient demographics were as follows: 56% white, 43% African American, 1% other. Allelic frequencies of the different polymorphisms of the participants were compared with those of the general American population stratified by race. Twenty-six additional patients treated with radiation, but without toxicity at 3 months or later after therapy, were also analyzed.

RESULTS

Increased frequency of a long GT repeat in the HMOX1 promoter was associated with late effects in both African American and white populations. The single nucleotide polymorphisms (SNP) rs1800469 in the TGFβ1 promoter and the rs6721961 SNP in the NFE2L2 promoter were also found to significantly associate with late effects in African Americans but not whites. A combined analysis of these polymorphisms revealed that >90% of African American patients with late effects had at least 1 of these minor alleles, and 58% had 2 or more. No statistical significance was found relating the studied NOS3 polymorphisms and normal tissue toxicity.

CONCLUSIONS

These results support a strong association between wound repair and late toxicities of radiation. The presence of these genetic risk factors can vary significantly among different ethnic groups, as demonstrated for some of the SNPs. Future studies should account for the possibility of such ethnic heterogeneity in the late toxicities of radiation.

Genome-wide association analysis of radiation resistance in Drosophila melanogaster

Background

Ionizing radiation is genotoxic to cells. Healthy tissue toxicity in patients and radiation resistance in tumors present common clinical challenges in delivering effective radiation therapies. Radiation response is a complex, polygenic trait with unknown genetic determinants. The Drosophila Genetic Reference Panel (DGRP) provides a model to investigate the genetics of natural variation for sensitivity to radiation.

Methods and Findings

Radiation response was quantified in 154 inbred DGRP lines, among which 92 radiosensitive lines and 62 radioresistant lines were classified as controls and cases, respectively. A case-control genome-wide association screen for radioresistance was performed. There are 32 single nucleotide polymorphisms (SNPs) associated with radio resistance at a nominal p<10⁻⁵; all had modest effect sizes and were common variants with the minor allele frequency >5%. All the genes implicated by those SNP hits were novel, many without a known role in radiation resistance and some with unknown function. Variants in known DNA damage and repair genes associated with radiation response were below the significance threshold of p<10⁻⁵ and were not present among the significant hits. No SNP met the genome-wide significance threshold (p = 1.49×10⁻⁷), indicating a necessity for a larger sample size.

Conclusions

Several genes not previously associated with variation in radiation resistance were identified. These genes, especially the ones with human homologs, form the basis for exploring new pathways involved in radiation resistance in novel functional studies. An improved DGRP model with a sample size of at least 265 lines and ideally up to 793 lines is recommended for future studies of complex traits.

Inflammation-related genetic variants predict toxicity following definitive radiotherapy for lung cancer

Definitive radiotherapy improves locoregional control and survival in inoperable non-small cell lung cancer (NSCLC) patients. However, radiation-induced toxicities (pneumonitis/esophagitis) are common dose-limiting inflammatory conditions. We therefore conducted a pathway-based analysis to identify inflammation-related SNPs associated with radiation-induced pneumonitis or esophagitis. 11,930 SNPs were genotyped in 201 stage I-III NSCLC patients treated with definitive radiotherapy. Validation was performed in an additional 220 NSCLC cases. After validation, 19 SNPs remained significant. A polygenic risk score (PRS) was generated to summarize the effect from validated SNPs. Significant improvements in discriminative ability were observed by adding the PRS into the clinical/epidemiological variable-based model. We then used 277 lymphoblastoid cell-lines to assess radiation sensitivity and eQTL relationships of the identified SNPs. Three genes (PRKCE,DDX58 and TNFSF7) were associated with radiation sensitivity. We concluded that inflammation-related genetic variants could contribute to the development of radiation-induced toxicities. These loci could assist in predicting those unfavorable events.

Association of XRCC1 and XRCC3 gene haplotypes with the development of radiation-induced fibrosis in patients with nasopharyngeal carcinoma

Radiation-induced fibrosis is one of the late complications of radiotherapy (RT) for nasopharyngeal carcinoma (NPC). The aim of this study was to investigate the association between X-ray repair cross-complementing protein 1 and 3 (XRCC1 and XRCC3, respectively) gene haplotypes and radiation-induced fibrosis in NPC patients. Genomic DNA was extracted from blood samples of 120 NPC patients previously treated with RT. In total, 12 tag single-nucleotide polymorphisms (SNPs) were selected from the XRCC1 and XRCC3 genes and were genotyped using restriction fragment length polymorphism analysis or unlabeled probe melting analysis. Single-marker and haplotype analyses were performed using multivariate logistic regression analysis. The functional variant rs861539 of XRCC3 may be associated with radiation-induced fibrosis [asymptotic P-value (P_asym)<0.05]. No significant association was observed between radiation-induced fibrosis and any of the tag SNPs of XRCC1 and XRCC3 in either single-marker or haplotype analysis after 10,000 permutations [empirical P-value (P_emp)>0.05]. Our preliminary results indicated that the rs861539 variant of XRCC3 may be associated with an increased risk of radiation-induced fibrosis; however, a large-scale study is required to confirm this result.

Single-nucleotide polymorphisms studied for associations with urinary toxicity from (125)I prostate brachytherapy implants

PURPOSE

To identify clinical, dosimetric, and genetic factors that are associated with late urinary toxicity after a (125)I prostate brachytherapy implant.

METHODS AND MATERIALS

Genomic DNA from 296 men treated with (125)I prostate brachytherapy monotherapy was extracted from saliva samples for this study. A retrospective database was compiled including clinical, dosimetric, and toxicity data for this cohort of patients. Fourteen candidate single-nucleotide polymorphism (SNPs) from 13 genes (TP53, ERCC2, GSTP1, NOS, TGFβ1, MSH6, RAD51, ATM, LIG4, XRCC1, XRCC3, GSTA1, and SOD2) were tested in this cohort for correlations with toxicity.

RESULTS

This study identified 217 men with at least 2 years of followup. Of these, 39 patients developed Grade ≥2 late urinary complications with a transurethral resection of prostate, urethral stricture, gross hematuria, or a sustained increase in their International Prostate Symptom Score. The only clinical or dosimetric factor that was associated with late urinary toxicity was age (p = 0.02). None of the 14 SNPs tested in this study were associated with late urinary toxicity in the univariate analysis.

CONCLUSIONS

This study identified age as the only variable being associated with late urinary toxicity. However, the small sample size and the candidate gene approach used in this study mean that further investigations are essential. Genome-wide association studies are emerging as the preferred approach for future radiogenomic studies to overcome the limitations from a candidate gene approach.

Investigation of genetic polymorphisms related to the outcome of radiotherapy for prostate cancer patients

The purpose of this study was to evaluate the association between ATM, TP53 and MDM2 polymorphisms in prostate cancer patients and morbidity after radiotherapy. The presence of ATM (rs1801516), TP53 (rs1042522, rs1800371, rs17878362, rs17883323, and rs35117667), and MDM2 (rs2279744) polymorphisms was assessed by direct sequencing of PCR fragments from 48 patients with histologically proven prostate adenocarcinoma and treated with external beam radiation. The side effects were classified according to the Radiation Therapy Oncology Group (RTOG) score. The results showed no association between clinical characteristics and the development of radiation toxicities (P > 0.05). The C>T transition in the position 16273 (intron 3) of TP53 (rs35117667) was significantly associated with the risk of acute skin toxicity (OR: 0.0072, 95% CI 0.0002–0.227, P = 0.003). The intronic TP53 polymorphism at position 16250 (rs17883323) was associated with chronic urinary toxicity (OR: 0.071, 95%CI 0.006–0.784, P = 0.032). No significant associations were found for the remaining polymorphisms (P > 0.05). The results show that clinical characteristics were not determinant on the developing of radiation sensitivity in prostate cancer patients, and intronic TP53 polymorphisms would be associated with increased acute and chronic radiation toxicities. These observations corroborate the importance of investigating the genetic profile to predict adverse side effects in patients undergoing radiotherapy.

Polymorphisms in DNA-repair genes in a cohort of prostate cancer patients from different areas in Spain: heterogeneity between populations as a confounding factor in association studies

Background

Differences in the distribution of genotypes between individuals of the same ethnicity are an important confounder factor commonly undervalued in typical association studies conducted in radiogenomics.

Objective

To evaluate the genotypic distribution of SNPs in a wide set of Spanish prostate cancer patients for determine the homogeneity of the population and to disclose potential bias.

Design, Setting, and Participants

A total of 601 prostate cancer patients from Andalusia, Basque Country, Canary and Catalonia were genotyped for 10 SNPs located in 6 different genes associated to DNA repair: XRCC1 (rs25487, rs25489, rs1799782), ERCC2 (rs13181), ERCC1 (rs11615), LIG4 (rs1805388, rs1805386), ATM (rs17503908, rs1800057) and P53 (rs1042522). The SNP genotyping was made in a Biotrove OpenArray® NT Cycler.

Outcome Measurements and Statistical Analysis

Comparisons of genotypic and allelic frequencies among populations, as well as haplotype analyses were determined using the web-based environment SNPator. Principal component analysis was made using the SnpMatrix and XSnpMatrix classes and methods implemented as an R package. Non-supervised hierarchical cluster of SNP was made using MultiExperiment Viewer.

Results and Limitations

We observed that genotype distribution of 4 out 10 SNPs was statistically different among the studied populations, showing the greatest differences between Andalusia and Catalonia. These observations were confirmed in cluster analysis, principal component analysis and in the differential distribution of haplotypes among the populations. Because tumor characteristics have not been taken into account, it is possible that some polymorphisms may influence tumor characteristics in the same way that it may pose a risk factor for other disease characteristics.

Conclusion

Differences in distribution of genotypes within different populations of the same ethnicity could be an important confounding factor responsible for the lack of validation of SNPs associated with radiation-induced toxicity, especially when extensive meta-analysis with subjects from different countries are carried out.

Emerging evidence on the pathobiology of mucositis

BACKGROUND

Considerable progress has been made in our understanding of the biological basis for cancer therapy-induced mucosal barrier injury (mucositis). The last formal review of the subject by MASCC/ISOO was published in 2007; consequently, an update is timely.

METHODS

Panel members reviewed the biomedical literature on mucositis pathobiology published between January 2005 and December 2011.

RESULTS

Recent research has provided data on the contribution of tissue structure changes, inflammation and microbiome changes to the development of mucositis. Additional research has focused on targeted therapy-induced toxicity, toxicity clustering and the investigation of genetic polymorphisms in toxicity prediction. This review paper summarizes the recent evidence on these aspects of mucositis pathobiology.

CONCLUSION

The ultimate goal of mucositis researchers is to identify the most appropriate targets for therapeutic interventions and to be able to predict toxicity risk and personalize interventions to genetically suitable patients. Continuing research efforts are needed to further our understanding of mucositis pathobiology and the pharmacogenomics of toxicity.

Will SNPs be useful predictors of normal tissue radiosensitivity in the future?

The ability to predict individual risk of radiation-induced normal tissue complications is a long sought goal in radiobiology. The last decade saw increasing interest in identifying associations between single nucleotide polymorphisms (SNPs) and normal tissue complication risk. Nevertheless, it remains controversial whether SNPs will be useful predictors of normal tissue radiosensitivity. This paper provides a summary of a scientific debate held at the 31st ESTRO conference in which four scientists argued in favor or against the motion that SNPs will be useful predictors of normal tissue radiosensitivity in the future.

Emerging evidence on the pathobiology of mucositis

BACKGROUND

Considerable progress has been made in our understanding of the biological basis for cancer therapy-induced mucosal barrier injury (mucositis). The last formal review of the subject by MASCC/ISOO was published in 2007; consequently, an update is timely.

METHODS

Panel members reviewed the biomedical literature on mucositis pathobiology published between January 2005 and December 2011.

RESULTS

Recent research has provided data on the contribution of tissue structure changes, inflammation and microbiome changes to the development of mucositis. Additional research has focused on targeted therapy-induced toxicity, toxicity clustering and the investigation of genetic polymorphisms in toxicity prediction. This review paper summarizes the recent evidence on these aspects of mucositis pathobiology.

CONCLUSION

The ultimate goal of mucositis researchers is to identify the most appropriate targets for therapeutic interventions and to be able to predict toxicity risk and personalize interventions to genetically suitable patients. Continuing research efforts are needed to further our understanding of mucositis pathobiology and the pharmacogenomics of toxicity.