肺癌标志物无创快速可视化传感检测新方法

An olfactory-sensitive non-invasive rapid and visualization sensing detection method which is capable of specifically and molecularly recognizing for VOCs makers of lung cancer was studied in this project. It is structured by micro array sensor, based on multi-dimensional nano-porphyrin and further illustrates the sensing mechanism. Nano-porphyrin is designed and synthesized by such as molecular shear, chiral grafting and nano self-assembly and the design method of target molecule according to the molecularly structural characteristics of VOCs markers of lung cancer. The colorimetric specific spectral characteristics of RGB through a mapping relationship combining chemical response and optical response from the specific molecular recognition mechanism of the porphyrin micro-sensor and the lung cancer VOCs markers were obtained. And a specific molecular recognition "fingerprint" for lung cancer VOCs markers will be established by pattern recognition calculation method of the micro-sensors and the molecular markers, the calculating for quantitative results were obtained according to statistics theory and neural network theory after acquisition, transformation and treatment of the optical signal were studied. the sensing mechanism of olfactory-sensitive, non-invasive, rapid and visual inspection for VOCs makers of lung cancer was also revealed depending on the related theoretical studies of quantum chemistry, spectroscopy theory, molecular orbital theory and information convert. Meanwhile, the detection limits, sensitivity, response time and influential factors were researched as well. It bears far-reaching significance to improving the level of medical technology in China，and promoting the development of medical equipment and safeguard the health of people.

本项目旨在建立一种对肺癌VOCs标志物有特异性分子识别的无创快速可视化传感检测新方法，以多维纳米卟啉构建微阵列传感器并阐明其传感作用机制。针对肺癌VOCs标志物分子结构特征，按目标分子设计方法，通过分子剪切、手性嫁接、纳米自组装等方法设计、合成制备出纳米卟啉材料。结合微传感器对肺癌VOCs标志物具有特异性分子识别作用化学响应与光学响应信息的映射关系，获得可视化的特异RGB光谱特性，通过微传感器标志物分子识别的模式识别计算方法、光学信号采集、转化、处理研究，依据统计理论与神经网络理论计算得到定量表达结果，建立对肺癌VOCs标志物特异性分子识别"指纹图谱"。通过量子化学、光谱理论、分子轨道理论及信息转换相关理论，阐明对肺癌VOCs标志物无创快速可视化检测的传感作用机制。同时研究其检测限、灵敏度、响应时间及影响因素。项目对提高我国医疗技术水平、促进医疗器械产业发展和保障人民身体健康具有重要意义。

项目按目标分子设计方法，合成制备出如5-(4-羧基苯基)-10,15,20-三苯基卟啉等，通过单体卟啉分子间的自缩合反应或者与桥连基团1,4-对苯二甲酸和己二酸反应得到自由碱二聚体卟啉，采用表面活性剂辅助自组装备方法制备出多维纳米卟啉材料，并对材料进行了表征，研究了敏感材料与肺癌患者呼出气体VOCs标志物分子间相互作用的光谱响应机制，阐明了敏感材料与肺癌呼出气体VOCs标志物的作用机制。项目系统研究了肺癌患者呼出气体VOCs标志物模式识别算法，RGB值数据分析、卟啉分子阵列传感芯片与肺癌患者呼出气体VOCs标志物光谱作用机制，可视化传感器的响应机制，获得了肺癌呼出气体VOCs标志物指纹图谱，建立了对肺癌VOCs标志物无创快速可视化传感检测新方法。针对肺腺癌细胞A549、人高转移肺腺癌细胞95D、小细胞肺癌NCI-h446、正常肺上皮细胞MRC5及氨基酸进行了可视化检测研究，并获得四种细胞代谢液的指纹图谱及不同氨基酸指纹图谱。项目对肺癌患者临床呼气进行了研究，获得了肺癌患者特征图谱，并发现肺癌患者特征图谱有14个特征点，通过对RGB值计算得出欧氏距离范围在168-224之间，根据健康人特征图谱的11个特征点和肺癌患者的14个特征点，经统计（p=0.04）筛选出8个点在区分肺癌与健康者时具有统计学差异的特征点，通过测试样本主成分分析、聚类分析、判别分析结果显示，该传感阵列及检测系统对临床样本具有良好的识别能力。项目研究按照项目计划进程安排执行，未作计划调整。项目发表高水平学术论文19篇，其中SCI检索论文17篇，EI检索论文1篇，CSCD核心论文1篇，申请相关国家专利21项，目前已获权国家发明专利9项，培养博士研究生3名、硕士研究生3名，并进行了国际合作与交流，项目研究完成项目目标任务。项目对提高我国医疗技术水平、促进医疗器械产业发展和保障人民身体健康具有重要意义。