Proton irradiation augments the reduction in tumor progression observed with advanced age

Proton irradiation is touted for its improved tumor targeting due to the physical advantages of ion beams for radiotherapy. Recent studies from our laboratory have shown that in addition to targeting advantages proton irradiation can inhibit angiogenic and immune factors and thereby modulate tumor progression. High-energy protons also constitute a principal component of the galactic cosmic rays to which astronauts are exposed. Increased understanding of the biological effects of proton exposure would thus contribute to both improved cancer therapy and carcinogenesis risk assessment for space travel. In addition age plays a major role in tumor incidence and is a critical consideration for estimating cancer risk. We investigated the effects of host age and proton exposure on tumor progression. Tumor lag time and growth dynamics were tracked following injection of murine Lewis lung carcinoma (LLC) cells into young (68 day) versus old (736 day) mice with or without coincident irradiation. Tumor progression was suppressed in old compared to young mice. Differences in progression were further modulated by proton irradiation (1GeV) with increased inhibition evident in old mice. Through global transcriptome analysis TGFB1 and TGFB2 were determined to be key players that contributed to the tumor dynamics observed. These findings point to older hosts providing decreased systemic tumor support which can be further inhibited by proton irradiation. Overall design: 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 thirty tumor samples from adolescent and thirty tumor samples from old mice for a total of 60 tumor samples were used. All replicate samples were run individually. For each age group ten tumor samples had received proton irradiation while twenty tumor samples were from unirradiated mice (as described above). 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. In GenomeStudio data was background subtracted and rank invariant normalization was applied. Data was imported into MultiExperiment Viewer MeV for statistical analysis. The statistically significant genes were determined using MeV by applying a one-way ANOVA analysis with standard Bonferroni correction with a FDR <0.05 that resulted in a list of significant genes. Average gene expression signals <10 were filtered out due to signal being

质子辐照因其离子束在放射治疗中的物理优势而被誉为改进肿瘤靶向的有效手段。近期，我们实验室的研究表明，除了靶向优势外，质子辐照还能抑制血管生成和免疫相关因子，从而调节肿瘤进展。高能质子也是宇航员所暴露的银河宇宙射线的主要组成部分。因此，对质子辐照的生物效应的深入了解将有助于提升癌症治疗效果，并评估太空旅行中的致癌风险。此外，年龄在肿瘤发生率中扮演着重要角色，也是估算癌症风险的关键因素。我们探讨了宿主年龄和质子辐照对肿瘤进展的影响。在将小鼠Lewis肺腺癌（LLC）细胞注入年轻（68天）与老年（736天）小鼠，并伴随或不伴随辐照的情况下，追踪了肿瘤的滞后时间和生长动力学。与年轻小鼠相比，老年小鼠的肿瘤进展受到抑制。进一步研究表明，质子辐照（1GeV）可调节肿瘤进展差异，在老年小鼠中表现出更强的抑制作用。通过全局转录组分析，确定TGFB1和TGFB2是肿瘤动态变化的关键参与者。这些发现表明，老年宿主提供的系统性肿瘤支持减少，而质子辐照可以进一步抑制这种支持。总体设计：为了进行肿瘤组织的全基因组表达分析，使用了Mouse WG-6 BeadArray芯片（Illumina，圣地亚哥，加州）。总RNA使用Ambion Illumina TotalPrep扩增试剂盒（Ambion，奥斯汀，德克萨斯州）进行扩增，并从每个条件下的所有重复生物样本中进行标记。对于肿瘤重复样本，使用了30个来自青春期小鼠和30个来自老年小鼠的肿瘤样本，共计60个肿瘤样本。所有重复样本均单独运行。对于每个年龄组，有10个肿瘤样本接受了质子辐照，而20个肿瘤样本来自未辐照的小鼠（如上所述）。使用TRIzol（Invitrogen）提取和纯化总RNA，并使用Agilent Bioanalyzer进行定量。如果28s/18s的RIN比大于7，则认为样本适合进行扩增和杂交。每个样本使用500ng的总RNA进行扩增，并将1.5ug的产物加载到芯片上。杂交后，在55°C下清洗芯片，然后使用Illumina iScan系统进行扫描。使用GenomeStudio（Illumina）进行质量控制，对数据进行背景校正和秩不变归一化。数据导入MultiExperiment Viewer MeV进行统计分析。使用MeV通过进行单因素方差分析并应用标准的Bonferroni校正，FDR <0.05，来确定统计学上显著的基因。平均基因表达信号小于10的基因被过滤掉，因为信号太弱。