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A clinical-information-free method for early diagnosis of lung cancer from the patients with pulmonary nodules based on backpropagation neural network model

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机构： [1]School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China. [2]Department of Obstetrics and Gynecology, West China Second University Hospital of Sichuan University, Chengdu 610041, China. [3]Department of medical oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu 610041, China. [4]Department of Thoracic Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu 610041, China. [5]Department of Health Management Center & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China. [6]Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu 610072, China. [7]Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu 610041, China. [8]School of Healthcare Technology, Chengdu Neusoft University, Chengdu, Sichuan 611844, China.

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关键词： Lung cancer Early diagnosis Backpropagation neural network TCRβ repertoire Characteristic TCR clone

摘要：

Lung cancer is the main cause of cancer-related deaths worldwide. Due to lack of obvious clinical symptoms in the early stage of the lung cancer, it is hard to distinguish between malignancy and pulmonary nodules. Understanding the immune responses in the early stage of malignant lung cancer patients may provide new insights for diagnosis. Here, using high-through-put sequencing, we obtained the TCRβ repertoires in the peripheral blood of 100 patients with Stage I lung cancer and 99 patients with benign pulmonary nodules. Our analysis revealed that the usage frequencies of TRBV, TRBJ genes, and V-J pairs and TCR diversities indicated by D50s, Shannon indexes, Simpson indexes, and the frequencies of the largest TCR clone in the malignant samples were significantly different from those in the benign samples. Furthermore, reduced TCR diversities were correlated with the size of pulmonary nodules. Moreover, we built a backpropagation neural network model with no clinical information to identify lung cancer cases from patients with pulmonary nodules using 15 characteristic TCR clones. Based on the model, we have created a web server named "Lung Cancer Prediction" (LCP), which can be accessed at http://i.uestc.edu.cn/LCP/index.html.© 2024 The Authors.

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大类 | 2 区生物学

小类 | 3 区生化与分子生物学

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无

最新[2023]版：

Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

影响因子： 4.5 最新[2023版] 5.1 最新五年平均 4.5 出版当年[2023版] 0 出版当年五年平均 4.5 出版前一年[2023版]

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第一作者机构： [1]School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.

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通讯机构： [1]School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China. [8]School of Healthcare Technology, Chengdu Neusoft University, Chengdu, Sichuan 611844, China. [*1]School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.

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A clinical-information-free method for early diagnosis of lung cancer from the patients with pulmonary nodules based on backpropagation neural network model

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