(Sunday, 7/29/2018) 3:00 PM - 6:00 PM
Room: Exhibit Hall
Purpose: Identifying genetic variants associated with normal tissue radiosensitivity would be useful to personalize dose through predictive screening. Our hypothesis is that there are specific genetic profiles that may cause increased breast cancer (BCa) predisposition and have adverse effects to normal tissue radiosensitivity.
Methods: Our preliminary data curated >2,000 exon variants with a predicted negative impact on protein function and ≥5% allele frequencies difference between African and Caucasian ancestries. We used bioinformatics techniques to determine variant association with BCa as a function of ancestry. Files from the Cancer Genome Atlas (cases, N=511) and HapMap (controls, N=700) were processed using a Genomic Analysis ToolKit pipeline. We assigned genotypes to 83 DNA-repair genes. Statistical associations were tested using a linear-regression analysis. A select number of variants with significant associations were also functionally tested in normal tissue cell cultures via CRISPR-Cas9 genomic editing tools.
Results: We have statistical results on 51 of 83 genetic variants in patients versus controls. There were 29 of 51 variants associated with case status. For example, in the MUS81, GEN1, RNF168, and MUS81 genes were associated with BCa risk (p=0.035-0.02). African descent had a higher risk for BCa with MUS81 variant (p<0.0001). Haplotype analysis determined that in combination, these variants were also associated with a significant risk for BCa (p<0.0095), and in women of African descent, this haplotype had a much higher risk (p<0.0001). Notably, 14 of the 51 DNA repair genes where involved in DNA double strand break repair that may dramatically effect response to IR exposure. Five variants are being functionally tested in response to IR exposure.
Conclusion: Our results have shown a significant correlation of genetic variants with BCa and warrants testing in response to IR. We ultimately hope to create a panel of predictive markers useful in the personalization of radiation oncology treatments.
Keywords
Radiosensitivity, Radiobiology, Risk
Taxonomy
TH- Radiobiology(RBio)/Biology(Bio): Bio- tissue and microenvironment
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