Abstract LB064: Using a genomic only approach to a radiation-age association for supplementing differentiation amongst lung diseases and cancer using PMBCs

Abstract

Abstract Purpose: Ionizing radiation may serve as a reference variable to estimating biological age since it mirrors cumulative DNA damage similar to aging processes. To do this, we aim to establish a rad-age association using genomics as its foundation and clinical applicability with lung disease as an overlapping health concern. Methods: Two datasets were combined and used to empirically find the age cutoff between young and old patients: GSE42488 (Data-A1) and GSE53351 (Data-A2). With age as both a categorical and continuous variable, two other datasets that include radiation exposure are used to test the interaction between radiation and age: GSE21240 (Data-B1) and GSE23515 (Data-B2). A radiation only data was also used in conjunction to evaluate trend analysis with increasing exposure levels: GSE20173 (Data-R1). The gene lists are oriented in preranked lists for both pathway and diseases functional analysis. Finally, these genes are used to evaluate another dataset via GSE42834 (Data-D1) on the clinical relevance in differentiating lung diseases given ethnicity and sex using both pairwise t-tests and linear models including pneumonic, tuberculosis, active and non-active sarcoidosis, lung cancer, and healthy controls. Results: Using 12 well-known genes associated with aging, a threshold of 29 years old was found to be the difference between young and old patients. The two interaction tests (rad and age as continuous plus rad and age as categorical) yielded 234 unique genes such that pathway analysis flagged IL-1 signaling and PRPP biosynthesis as significant with high cell proliferation diseases and carcinomas being a common trend. From the radiation only t-tests, we see a trend of continued upregulation in gene expression as radiation levels increase in 15 of the 17 common genes. When looking at pairwise comparison of disease, ethnicity, or sex, 10 genes were statistically significant, 3 of which had a combination of pairwise significance and fold-change, while LAPTM4B (probe identifier ILMN1680196) was the only gene with significant interaction (p-value=0.004) between lung disease, ethnicity, and sex and fold change greater than two. Conclusion: The results corroborate an initial association between radiation and age given inflammation and metabolic pathways and multiple genes emphasizing mitochondrial function, oxidation, and histone modification. Being able to tie rad-age genes to lung disease supplements a geroscience approach in future work. Citation Format: Nathan A. Ruprecht, Sonalika Singhal, Kalli Schaefer, Jappreet S. Gill, Benu Bansal, Sandeep K. Singhal. Using a genomic only approach to a radiation-age association for supplementing differentiation amongst lung diseases and cancer using PMBCs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB064.