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Tumor-Host Signaling Interaction Reveals a Systemic, Age-Dependent Splenic Immune Influence on Tumor Development [control mice]

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NIAID Data Ecosystem2026-03-10 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73450
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The concept of age-dependent host control of cancer development raises the natural question of how these effects manifest across the host tissue/organ types with which a tumor interacts, one important component of which is the aging immune system. To investigate this, changes in the spleen, an immune nexus in the mouse, was examined for its age-dependent interactive influence on the carcinogenesis process. The model is the C57BL/6 male mice (adolescent, young adult, middle-aged, and old or 68, 143, 551 and 736 days old respectively) with and without a syngeneic murine tumor implant. Through global transcriptome analysis, immune-related functions were found to be key regulators in the spleen associated with tumor progression as a function of age with CD2, CD3, CCL19, and CCL5 being the key molecules involved. Surprisingly, other than CCL5, all key factors and immune-related functions were not active in spleens from non-tumor bearing old mice. Our findings of age-dependent tumor-spleen signaling interaction suggest the existence of a global role of the aging host in carcinogenesis. Suggested is a new avenue for therapeutic improvement that capitalizes on the pervasive role of host aging in dictating the course of this disease. For genome-wide expression profiling of spleen tissue from wild-type non-tumor bearing C57BL/6 mice, 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 spleen replicates, 10 spleen samples from adolescent mice, 10 from young adult mice , 10 from middle-aged mice, and 10 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 COMBAT correction, quantile normalized, collapsed to genes from probes, 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.
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2019-01-16
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