第一部分：放疗是头颈部肿瘤主要治疗手段，放疗常常造成包括口干、放射性皮肤炎、放射性口腔黏膜炎等严重急性放疗副反应。严重的放疗副反应影响患者治疗依从性、生活质量甚至预后，并且给患者带来较大的经济负担。本部分研究分为两个模块,利用双向两样本孟德尔随机化分析方法，依据既往已发表的大型GWAS 研究数据，分别探究头颈部肿瘤急性严重放疗副反应与粪便生物标志物（肠道菌群）和血液生物标志物（循环免疫细胞，循环细胞因子）之间的因果关系。

第二部分：目的：探讨鼻咽癌患者放疗前血浆中炎性细胞因子水平与急性放疗副反应的关系，初步建立放疗期间重度急性副反应发生风险的预测模型。方法：横断面研究。回顾性选取2016 年5 月至2019 年3 月就诊于中国医学科学院肿瘤医院接受根治性放疗的85 例鼻咽癌患者。按照美国肿瘤放疗协作组（RTOG）急性放射性损伤评价标准评估放疗期间放射性口腔黏膜炎、放射性皮炎和放射性口干发生的最高等级副反应，以其≥3 级为重度。采用Olink 蛋白质组学技术，检测患者首次放疗前血浆中92 种炎性细胞因子水平（标准化的蛋白表达值）。采用单因素方差分析和独立样本t 检验分析炎性细胞因子与临床因素及与放疗期间3 种急性副反应的关系。基于炎性细胞因子和（或）临床因素，采用二元logistic 回归构建重度急性放疗副反应发生风险的预测模型。以美国RTOG 急性放射性损伤评价标准评定的放疗期间最严重等级的副反应是否重度为金标准，采用受试者工作特征（ROC）曲线分析依据构建的各模型判断重度急性放疗副反应发生的效能。结果85 例患者中，男性68 例，女性17 例；中位年龄［M（Q1，Q3）］49 岁（43 岁，60 岁）；所有患者均接受根治性放疗，其中64 例联合化疗或靶向治疗。19 例（22.1%）出现重度急性放疗副反应。1、2、3 级急性放射性口腔黏膜炎患者放疗前血浆白细胞介素22 受体A（IL⁃22RA1）、白细胞介素18 受体1（IL⁃18R1）、嗜酸性粒细胞趋化因子（CCL11）、肿瘤坏死因子超家族成员14（TNFSF14）、酪氨酸激酶受体3 配体（Flt3L）和单核细胞趋化蛋白2（MCP⁃2）水平差异均有统计学意义（均P＜0.05）；1、2、3 级急性放射性皮炎患者放疗前血浆CD244、CC 趋化因子配体20（CCL20）、白血病抑制因子受体（LIF⁃R）和白细胞介素（IL）⁃4 水平差异均有统计学意义（均P＜0.05）；轻度与重度急性放射性口干患者放疗前血浆IL⁃12B、CXC 型趋化因子配体11（CXCL11）、LIF⁃R 和IL⁃33 水平差异均有统计学意义（均P＜0.05）。单因素方差分析中，各临床因素与严重急性放疗副反应均不相关（均P＞0.05），根据文献选取年龄、T 分期、N 分期、临床分期、是否接受化疗、是否患有糖尿病6 个临床因素建立二元logistic 回归模型M1。根据细胞因子功能和既往文献，在差异细胞因子中选取IL⁃22RA1、IL⁃18R1、MCP⁃2、CCL11、CD244、CCL20 和IL⁃33 建立二元logistic 回归模型M2。结合上述临床因素和细胞因子建立二元logistic 回归模型M3。ROC 曲线分析显示，预测模型M1、M2 和M3 判断重度急性放疗副反应发生的曲线下面积分别为0.787、0.841、0.868。结论不同等级急性放疗副反应患者间放疗前血浆中多种炎性细胞因子表达水平有差异，基于首次放疗前血浆炎性细胞因子水平结合临床因素构建模型能较好地预测鼻咽癌患者重度急性放疗副反应发生风险。

第一部分：Radiotherapy is very important in the treatment of head and neck tumors. The side effects of radiotherapy in patients with head and neck tumor mainly include xerostomia, radiation dermatitis and radiation oral mucositis. Serious side effects of radiotherapy affect prognosis. It also bring greater economic burden to patients. This part of the study is divided into two modules. Two-way two-sample Mendelian randomization analysis method was used to investigate the causal relationship between acute severe radiotherapy side effects of head and neck tumors and fecal biomarkers (intestinal flora) and blood biomarkers (circulating immune cells and circulating cytokines), respectively, based on previously published large GWAS analysis.

第二部分：Objective To investigate the relationship between the inflammatory cytokines level in the plasma of nasopharyngeal carcinoma patients before radiotherapy and acute radiotherapy adverse reactions, and to establish a preliminary model for predicting the risk of severe acute adverse reactions during radiotherapy. Methods A cross-sectional study was conducted. A total of 85 nasopharyngeal carcinoma patients who received radical radiotherapy in Cancer Hospital of Chinese Academy of Medical Sciences from May 2016 to March 2019 were retrospectively collected. The highest grade adverse reactions of oral mucositis, radiation dermatitis and radiation xerostomia during radiotherapy were evaluated according to the American Cancer Radiotherapy Collaboration (RTOG) acute radiation injury evaluation criteria, and the above adverse reactions ≥ grade 3 were treated as the severity. Olink proteomics technology was used to detect the level of 92 inflammatory cytokines (the standardized protein expression values) in the plasma of patients before radiotherapy for the first time. Single factor analysis of variance and independent sample t-test were used to analyze the relationship between inflammatory cytokines and clinical factors, as well as acute adverse reactions during radiotherapy. Based on inflammatory cytokines and/or the clinical factors, binary logistic regression was used to construct a predictive model for the risk of severe acute radiotherapy adverse reactions. Whether the most severe adverse reactions assessed by the American RTOG acute radiation injury evaluation criteria during radiotherapy were severe or not were taken as the gold standard. Receiver operating characteristic (ROC) curve was used to analyze the effectiveness of the established models for judging the severe acute adverse reactions. Results Among the 85 patients, 68 were males and 17 were females, with the median age [M(Q1, Q3)] of 49 years (43 years, 60 years). All patients received radical radiotherapy, of which 64 cases were treated with combination chemotherapy or targeted therapy. A total of 19 cases (22.1%) experienced severe acute radiotherapy adverse reactions. There were statistically significant differences in the levels of interleukin(IL) -22 receptor A1 (IL-22RA1), IL-18 receptor 1(IL-18R1), eotaxin-1(CCL11), tumor necrosis factor ligand superfamily member 14(TNFSF14), FMS-like tyrosine kinase 3 ligand (Flt3L), and monocyte chemotactic protein 2 (MCP-2) in the plasma of patients with grade 1,2, 3 acute radiation oral mucositis before radiotherapy; there were statistically significant differences in the levels of CD244 (all P<0.05); there were statistically significant differences in the levels of CD244, CC chemokines ligand 20 (CCL20), leukemia inhibitory factor ligand (LIF-R) and IL-4 in the plasma of patients with grade 1, 2, 3acute radiation dermatitis before radiotherapy (all P < 0.05); there were statistically significant differences in the levels of IL-12B, CXC chemokines ligand 11 (CCL11) , LIF‐R and IL‐33 in the plasma between patients with mild and those with acute radiation xerostomia before radiotherapy (all P＜0.05）. The result of single factor analysis of variance showed that the clinical factors were not associated with severe acute radiation adverse reactions (all P >0.05). Binary logistic regression model M1 was established by selecting 6 clinical factors including age, T staging, N staging, clinical staging, whether to receive chemotherapy or not and whether to suffer from diabetes or not in the literatures. Based on cytokine function and previous literatures, the binary logistic regression model M2 was established by selecting IL‐22RA1, IL‐18R1, MCP‐2,CCL11, CD244, CCL20 and IL-33 from the differential cytokines. A binary logistic regression model M3 was established by combining the above clinical factors with cytokines. The ROC curve analysis showed that the area under the curve of the M1, M2, M3 predictive models for judging the severe acute radiation adverse reactions was 0.781,0.841, 0.868, respectively. Conclusions There were differences in the expression levels of various inflammatory cytokines in plasma before radiotherapy among patients with different grades of acute radiotherapy adverse reactions. Building the models based on plasma inflammatory cytokine levels combined with clinical factors before the first radiotherapy could effectively predict the risk of severe acute radiotherapy adverse reactions in patients with nasopharyngeal carcinoma.