Radiogenomics – current status, challenges and future directions

Andreassen, Christian Nicolaj; Schack, L.M.H.; Laursen, Louise; Alsner, Jan

doi:10.1016/j.canlet.2016.01.035

Cited by 74 publications

(53 citation statements)

References 50 publications

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“…With an odds ratio around 1.3, the phenotypic impact of this SNP is fairly small. This observation is in agreement with the results of many genome wide association studies (GWAS) addressing various biomedical phenotypes in which most of the identified SNPs only had a modest impact on phenotype [1,37,38]. The effect size of the rs1801516 SNP demonstrated by our meta-analysis is below the detectable effect size in the radio-genomics GWASs published so far (2–8).…”

Section: Discussionsupporting

confidence: 92%

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Individual patient data meta-analysis shows a significant association between the ATM rs1801516 SNP and toxicity after radiotherapy in 5456 breast and prostate cancer patients

Andreassen

Rosenstein

Kerns

et al. 2016

Radiotherapy and Oncology

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105

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Purpose Several small studies have indicated that the ATM rs1801516 SNP is associated with risk of normal tissue toxicity after radiotherapy. However, the findings have not been consistent. In order to test this SNP in a well-powered study, an individual patient data meta-analysis was carried out by the International Radiogenomics Consortium. Materials and methods The analysis included 5456 patients from 17 different cohorts. 2759 patients were given radiotherapy for breast cancer and 2697 for prostate cancer. Eight toxicity scores (overall toxicity, acute toxicity, late toxicity, acute skin toxicity, acute rectal toxicity, telangiectasia, fibrosis and late rectal toxicity) were analyzed. Adjustments were made for treatment and patient related factors with potential impact on the risk of toxicity. Results For all endpoints except late rectal toxicity, a significantly increased risk of toxicity was found for carriers of the minor (Asn) allele with odds ratios of approximately 1.5 for acute toxicity and 1.2 for late toxicity. The results were consistent with a co-dominant pattern of inheritance. Conclusion This study convincingly showed a significant association between the ATM rs1801516 Asn allele and increased risk of radiation-induced normal tissue toxicity.

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Section: Discussionsupporting

confidence: 92%

“…Since 2003, more than 100 published studies have tried to link single nucleotide polymorphisms (SNPs) to the risk of normal tissue toxicity after radiotherapy [1]. Except for 7 studies [2–8], all took a candidate gene approach.…”

mentioning

confidence: 99%

Individual patient data meta-analysis shows a significant association between the ATM rs1801516 SNP and toxicity after radiotherapy in 5456 breast and prostate cancer patients

Andreassen

Rosenstein

Kerns

et al. 2016

Radiotherapy and Oncology

Self Cite

105

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“…Another key factor to consider for development of models is that normal tissue radiosensitivity for any particular tissue or organ is a complex trait dependent upon the expression of multiple genes whose variation is a reflection of the collective impact of numerous sequence variants 70, 71 . Hence, susceptibility for the appearance of adverse effects in a specific organ is likely the manifestation of several molecular pathways, which can be impacted by the presence of SNPs in multiple genes.…”

Section: Model Developmentmentioning

confidence: 99%

Radiogenomics: Identification of Genomic Predictors for Radiation Toxicity

Rosenstein

2017

Seminars in Radiation Oncology

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The overall goal of radiogenomics is the identification of genomic markers that are predictive for the development of adverse effects resulting from cancer treatment with radiation. The principal rationale for a focus on toxicity in radiogenomics is that for many patients treated with radiation, especially individuals diagnosed with early stage cancers, the survival rates are high and therefore a substantial number of people will live for a significant period of time beyond treatment. However, many of these patients could suffer from debilitating complications resulting from radiotherapy. Work in radiogenomics has greatly benefited from creation of the Radiogenomics Consortium (RGC), which includes investigators at multiple institutions located in a variety of countries. The common goal of the RGC membership is to share biospecimens and data so as to achieve large scale studies with increased statistical power to enable identification of relevant genomic markers. A principal aim of research in radiogenomics is the development of a predictive instrument to enable identification of people who are at greatest risk for adverse effects resulting from cancer treatment using radiation. It is anticipated that creation of a predictive assay characterized by a high level of sensitivity and specificity will improve precision radiotherapy and assist patients and their physicians to select the optimal treatment for each individual.

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“…Moreover, neither amifostine nor newer radio-protectors have been tested in selected patients at high risk for radiation injury, e.g. identified by their radio-genomics profile (14). As will be discussed later, the selection of the appropriate patients is essential to study radio-protectors or -mitigators.…”

Section: Interventionsmentioning

confidence: 99%

Optimal design and patient selection for interventional trials using radiogenomic biomarkers: A REQUITE and Radiogenomics consortium statement

Ruysscher

Defraene

Ramaekers

et al. 2016

Radiotherapy and Oncology

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The optimal design and patient selection for interventional trials in radiogenomics seem trivial at first sight. However, radiogenomics do not give binary information like in e.g. targetable mutation biomarkers. Here, the risk to develop severe side effects is continuous, with increasing incidences of side effects with higher doses and/or volumes. In addition, a multi-SNP assay will produce a predicted probability of developing side effects and will require one or more cut-off thresholds for classifying risk into discrete categories. A classical biomarker trial design is therefore not optimal, whereas a risk factor stratification approach is more appropriate. Patient selection is crucial and this should be based on the dose-response relations for a specific endpoint. Alternatives to standard treatment should be available and this should take into account the preferences of patients. This will be discussed in detail.

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Radiogenomics – current status, challenges and future directions

Cited by 74 publications

References 50 publications

Individual patient data meta-analysis shows a significant association between the ATM rs1801516 SNP and toxicity after radiotherapy in 5456 breast and prostate cancer patients

Individual patient data meta-analysis shows a significant association between the ATM rs1801516 SNP and toxicity after radiotherapy in 5456 breast and prostate cancer patients

Radiogenomics: Identification of Genomic Predictors for Radiation Toxicity

Optimal design and patient selection for interventional trials using radiogenomic biomarkers: A REQUITE and Radiogenomics consortium statement

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