目的: 基于蛋白组、代谢组的多平台组学关联分析绝经后乳腺癌（BC）妇女行内分泌治疗发生动脉粥样硬化性心血管疾病（ASCVD）的相关危险因素及其临床预测意义。方法: 选取2020年1月―2021年9月本院收治的浸润性乳腺癌患者147例,根据颈动脉IMT检查及临床综合诊断将患者分为ASCVD组68例和非ASCVD组79例。收集两组患者的临床资料,用蛋白组和代谢组的多平台组学关联分析与ASCVD发生有关的脂质分子,将单因素分析中P<0.05因素纳入并多因素Logistic分析绝经后内分泌治疗乳腺癌患者发生ASCVD的危险因素,绘制ROC曲线分析危险因素指标对乳腺癌患者发生ASCVD的诊断价值。结果: 三酰甘油（TG）、低密度脂蛋白胆固醇（LDL-C）、血脂总胆固醇（TC）、高密度脂蛋白胆固醇（HDL-C）是多平台组学分析筛选出与乳腺癌妇女发生ASCVD明显相关的脂蛋白分子。单因素分析ASCVD组、非ASCVD组的HDL-C、TC、LDL-C、TG、高血压、非甾体AI药物存在明显差异。多因素Logistic分析非甾体AI药物使用、HDL-C、TC、LDL-C、TG是绝经后乳腺癌患者发生ASCVD的危险因素。HDL-C、TC、LDL-C、TG、高血压、非甾体AI药物诊断绝经后乳腺癌行内分泌治疗发生ASCVD的AUC均>0.73且敏感度、特异度均>60.00%。结论: 绝经后乳腺癌妇女经内分泌治疗发生ASCVD主要危险因素为非甾体AI药物使用、HDL-C、TC、LDL-C、TG,其对预测该类患者发生ASCVD具有重要的指导意义。
Abstract
Objective To analyze the risk factors of atherosclerotic cardiovascular disease (ASCVD) in postmenopausal breast cancer (BC) women receiving endocrine therapy and its clinical predictive significance based on proteomics and metabolomics multi-platform omics association. Methods A total of 147 patients with invasive breast cancer admitted to our hospital from January 2020 to September 2021 were selected as the research objects. According to carotid IMT examination and clinical comprehensive diagnosis, the patients were divided into ASCVD group (68 cases) and non-ASCVD group (79 cases). The clinical data of the two groups were collected, and the lipid molecules related to ASCVD were analyzed by multi-platform proteomics and metabolomics association analysis. The factors with P<0.05 in univariate analysis were included and multivariate Logistic analysis was used to analyze the risk factors of ASCVD in postmenopausal breast cancer patients with endocrine therapy. Receiver operating characteristic (ROC) curve was drawn to analyze the diagnostic value of risk factors for ASCVD in breast cancer patients. Results Triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C) were identified as lipoprotein molecules significantly associated with ASCVD in breast cancer women by multi-platform omics analysis. Univariate analysis showed that there were significant differences in HDL-C, TC, LDL-C, TG, hypertension, and non-steroidal AI drugs between the ASCVD group and the non-ASCVD group. Multivariate Logistic analysis showed that the use of non-steroidal AI drugs, HDL-C, TC, LDL-C and TG were risk factors for ASCVD in postmenopausal breast cancer patients. The AUC of HDL-C, TC, LDL-C, TG, hypertension, and non-steroidal AI drugs in the diagnosis of ASCVD in postmenopausal breast cancer treated with endocrine therapy were all >0.73, and the sensitivity and specificity were all >60.00%. Conclusions The use of non-steroidal AI drugs, HDL-C, TC, LDL-C and TG are the main risk factors for ASCVD in postmenopausal breast cancer women with endocrine therapy, which have important guiding significance in predicting ASCVD in such patients.
关键词
多平台组学 /
内分泌治疗 /
绝经 /
乳腺癌 /
动脉粥样硬化心血管疾病
Key words
multi-platform omics /
endocrine therapy /
menopause /
breast cancer /
atherosclerosis cardiovascular disease
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基金
2021年深圳市宝安区基础研究项目（医疗卫生类,2021JD130）
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