ABSTRACT: Given that aging is the major determinant of cancer incidence, and that cancer incidence is dictated in large part by processes modulating progression of existing subclinical cancers, we demonstrate that aging may be an organizing axis for identifying cancer progression-modulating processes. This would permit the broad understanding of the aging process to directly inform the question of what changes in aggregate host signaling favor cancer progression. Exploring this idea, a syngeneic murine Lewis lung cancer model in adolescent (68 days), young adult (143 days), middle-aged (551 days), and old (736 days) C57BL/6 mice was used to identify the signaling and functional processes varying significantly with host age. As anticipated, many of these specific endpoints proved to be major determinants of cancer progression. Older hosts demonstrated decreased angiogenesis, decreased metabolism and dysregulated apoptosis, all identified as hallmarks of cancer progression. Transforming growth factor 1, downregulated in older hosts, was also identified as a central player in these systemic processes. It is concluded that the strong host-age dependence here observed for tumor advancement facilitates the identification of an overarching tumor control dynamic exerted by the host. Revealed is insight into a mechanistic basis for the role of aging on modulation of tumor progression that may be therapeutically exploitable. For genome-wide expression profiling of tumor tissue, Mouse WG-6 BeadArray chips (Illumina, San Diego, CA) were used. Total RNA was amplified with the Ambion Illumina TotalPrep Amplification Kit (Ambion, Austin, TX) and labeled from all replicate biological samples for each condition. For tumor replicates, 20 tumor samples from adolescent, 10 from young adult, 10 from middle-aged, and 20 from old mice, were used. All replicate samples were run individually. Total RNA was isolated and purified using TRIzol (Invitrogen) and quantified using an Agilent Bioanalyzer. Samples were deemed suitable for amplification and hybridization if they had 28s/18s = 2:1, RIN >7. Total RNA of 500ng per sample was amplified using AmbionTotalPrep, and 1.5ug of the product was loaded onto the chips. Following hybridization at 55C, the chips were washed and then scanned using the Illumina iScan System. The data was checked with GenomeStudio (Illumina) for quality control. Data were corrected through normalization of the housekeeping genes, quantile normalized, then imported into MultiExperiment Viewer, MeV for analysis. Statistically significant genes were determined by applying a one-way ANOVA with an adjusted Bonferroni correction and false discovery rate (FDR) < 0.05 that resulted in a list of significant genes.
