RNA seq of tumors derived from irradiated versus sham hosts transplanted with Trp53 null mammary tissue and fed either Control diet versus Caffeic Acid Phenethyl Ester (CAPE) diet.

Irradiated hosts gave rise to significantly more Trp53 null mammary cancers that grew more rapidly than those in sham-irradiated mice and exhibited an immunosuppressive tumor microenvironment . CAPE prevented the effect of host irradiation on tumor growth rate, immune signature and immunosuppression. 10 week-old BALB/c mice were transplanted with Trp53 null mammary tissue 3 days after exposure to low doses of ionizing g-radiation radiation. Over the next 600 days, tumors were collected. In order to test the hypothesis that host irradiation promotes chronic inflammation, radiation-genetic chimera mice were fed chow containing a honeybee-derived compound with anti-inflammatory and immunomodulatory properties, caffeic acid phenethyl ester (CAPE). RNA sequencing was done on ER negative tumors usingTruSeq RNA Sample Preparation Guide Protocol by Illumina® (#15008136 A). Raw sequencing data were received in FASTQ format. Read mapping was performed using Tophat 2.0.9 against the mm10 human reference genome. The resulting BAM alignment files were processed using the HTSeq 0.6.1 python framework and respective mm10 GTF gene annotation, obtained from the University of California, Santa Cruz (UCSC) database. Subsequently, the Bioconductor package DESeq2(3.2) was used to identify differentially expressed genes (DEG).

辐照宿主所产生的Trp53基因缺失型乳腺癌（Trp53 null mammary cancers）数量显著多于假辐照小鼠（sham-irradiated mice），且肿瘤生长速度更快，同时呈现免疫抑制性肿瘤微环境（immunosuppressive tumor microenvironment）。咖啡酸苯乙酯（CAPE）可阻断宿主辐照对肿瘤生长速率、免疫特征及免疫抑制状态的影响。本研究将10周龄的BALB/c小鼠在接受低剂量电离γ辐射（ionizing γ-radiation）3天后，移植Trp53基因缺失型乳腺组织；在后续600天内，定期收集肿瘤样本。为验证“宿主辐照可促进慢性炎症”这一假说，研究人员对辐照-遗传嵌合小鼠饲喂含有蜜蜂来源的抗炎及免疫调节特性化合物——咖啡酸苯乙酯（CAPE）的饲料。对雌激素受体阴性（ER negative）肿瘤开展RNA测序（RNA sequencing），实验采用伊卢米纳（Illumina®）公司的《TruSeq RNA样本制备指南方案》（货号#15008136 A）。原始测序数据以FASTQ格式获取。使用Tophat 2.0.9软件，将测序读段比对至mm10参考基因组。生成的BAM比对文件通过HTSeq 0.6.1 Python框架，以及从加州大学圣克鲁兹分校（UCSC）数据库获取的对应mm10 GTF基因注释文件进行处理。随后，使用Bioconductor软件包DESeq2(3.2)筛选差异表达基因（DEG）。