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Biological data: The use of -omics in outcome models
Published in Issam El Naqa, A Guide to Outcome Modeling in Radiotherapy and Oncology, 2018
Issam El Naqa, Sarah L. Kerns, James Coates, Yi Luo, Corey Speers, Randall K. Ten Haken, Catharine M.L. West, Barry S. Rosenstein
Single nucleotide polymorphisms (SNPs) and small insertions and deletions (indels) are the most widely studied genomic variants to date. Common SNPs are single base pair variable sites that are generally present in at least 1% of the population. SNPs can affect protein coding sequences, non-coding introns, and intergenic regions that may include cis-acting and/or trans-acting regulatory sites. There are approximately 10 million SNPs in the average human genome, occurring approximately every 300 nucleotides. In contrast to common SNPs, rare variants are present in less than 1% of the population. Rare variants can also occur in protein coding sequences, non-coding introns, and intergenic regions. Because of their rarity, very large sample sizes are needed to detect associations with disease, but rare variants may be more causally related to disease than SNPs. SNPs generally tag a genomic locus, or region, that contains one or more causal variants. Advances in technology, and decreases in costs, for large-scale genotyping and sequencing projects have enabled the application of genome-wide approaches to the study of disease. In contrast to candidate-gene studies, genome-wide association studies (GWAS) have demonstrated more robust and reproducible results. For instance, SNPs in TANC1 were found to be significantly associated with overall late urinary and rectal toxicity in prostate cancer patients in a three-stage GWAS [53]. TANC1 plays a role in regeneration of damaged muscle tissue, representing a pathway not previously implicated in radiotherapy toxicity. A meta-analysis of four GWAS, also in prostate cancer patients, identified two additional loci: SNP rs17599026, which lies in KDM3B, was associated with increased urinary frequency; and rs7720298, which lies in DNAH5, was associated with decreased urine stream [54]. Neither of these genes was previously implicated in cellular radiation response, and they appear to be novel radiosensitivity genes. While these initial results are promising, they likely suffer from overfitting and require testing in independent studies. Evidence from polygenic models of other complex diseases suggests that many SNPs will be required to develop predictive models with high sensitivity and specificity. Indeed, results from a simulation study of radiogenomics outcomes suggests that tens to hundreds of SNPs will be required for good performance models, depending on the allele frequency and effect size of each SNP [204].
Potential screening assays for individual radiation sensitivity and susceptibility and their current validation state
Published in International Journal of Radiation Biology, 2020
Maria Gomolka, Benjamin Blyth, Michel Bourguignon, Christophe Badie, Annette Schmitz, Christopher Talbot, Christoph Hoeschen, Sisko Salomaa
Radiation genomics (hereafter, radiogenomics) aims to identify genetic markers of radiation responsiveness, with significant progress coming through collaborations organized by the Radiogenomics Consortium (West et al. 2010). Three genetic polymorphisms found by candidate gene studies have replicated evidence for association with adverse reactions, near or in the ATM, TNF and XRCC1 genes (Talbot et al. 2012; Seibold et al. 2015; Andreassen et al. 2016b). These studies were conducted with breast and prostate cancer patients, with each with group sizes of several thousand patients. Additional associations have been found by genome-wide association studies (GWAS) including in the TANC1, SATB2 and CCRN4L genes (Barnett et al. 2014; Fachal et al. 2014). Even when the whole genome is studied, when particular tissue toxicities are investigated by correlation to variant genotypes, identified variants may be limited in their effects to that single toxicity by a tissue-specific mechanism, or may be informative for radiosensitivity more generally. For example, variants in the KDM3B and DNAH5 loci were found to be associated with increased urinary frequency and decreased urine stream, respectively, after radiotherapy for prostate cancer (Kerns et al. 2016). The mechanistic relationship proposed suggests bladder- and kidney-specific roles for these proteins which might be unlikely to translate to normal tissue toxicity risk in other sites (reviewed in Benafif et al. 2018). The genetic associations found to date explain only a small proportion of the heritability of radiosensitivity phenotypes, with the data suggesting the remaining genetic contribution is comprised of hundreds of variants which are common in the population but with small effect size, although the presence of additional rare variants with large effect sizes cannot be ruled out.