Evaluation of immune infiltrating of thyroid cancer based on the intrinsic correlation between pair-wise immune genes
Evaluation of immune infiltrating of thyroid cancer based on the intrinsic correlation between pair-wise immune genes
复制标题
基于成对免疫基因内在相关性的甲状腺癌免疫浸润评估
DOI：
10.1016/j.lfs.2020.118248
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发表时间：
2020-10-15
期刊：
影响因子：
6.1
通讯作者：
Liu, Yang
中科院分区：
文献类型：
--
作者：
Jia, Meng;Li, Zhuyao;Liu, Yang
简介：与大多数突变驱动的癌症不同，甲状腺癌被认为高度依赖于人类激素水平的变化。利用基因表达水平的变化作为检测和诊断标志已成为研究热点。利用两个基因与疾病发展之间的内在关系，避免单基因波动造成的不稳定。目的利用IGPS（免疫基因对）实现甲状腺癌肿瘤发生和复发过程中的早期诊断。方法：从癌症基因组图谱（TCGA）中提取甲状腺癌数据，使用CIBERSORT算法渗透出22种免疫细胞类型。我们筛选出不同群体之间差异显着的IGPS，然后使用LinearSVC模型学习和筛选特征，结合深度学习神经网络模型来预测良恶性癌症以及不同群体的患者。主要发现：肿瘤分期和复发样本中免疫细胞比例存在显着差异。我们在正常肿瘤组和非复发组中分别筛选出42个和64个IGPS，例如ASCC3-MAP3K7和ATF2-SOCS5，其IGPS表达具有显着相关性。然后我们使用IGPS来训练肿瘤诊断分类器，经过十次交叉验证后得到平均AUC均为0.99。意义：IGPS为我们探索甲状腺癌免疫细胞浸润提供了新的见解，深度学习模型可以进一步用于甲状腺癌的早期诊断和复发风险的估计。
Introduction: Unlike most mutation-driven cancers, thyroid cancer is thought to be highly dependent on changes in human hormone levels. It has become research hotspot using the change of gene expression level as a detection and diagnostic marker. The internal relationship between two genes and disease development is used to avoid the instability caused by single gene fluctuation.AimIt is possible to achieve early diagnosis in thyroid cancer during tumorigenesis and recurrence using IGPS (immune gene pairs).Methods: We extracted thyroid cancer data from The Cancer Genome Atlas (TCGA), using CIBERSORT algorithm to infiltrate out 22 immune cells types. We screened out IGPS that differ significantly between different groups, then used LinearSVC model to learn and screen features, combined with deep learning neural network model to predict benign and malignant cancer as well as patients at different groups.Key findings: There are significant differences of immune cell ratio in tumor stages and relapse samples. We screen out 42 and 64 IGPS for in normal-tumor and non-relapsed groups respectively, for example ASCC3-MAP3K7 and ATF2-SOCS5, have significant correlation in IGPS expression. Then we use the IGPS to train the tumor diagnostic classifier, obtain average AUC are both 0.99 after ten times cross-validation.Significance: The IGPS gives us new insight to explore immune cell infiltration of thyroid cancer, deep learning model can be further used in early diagnosis of thyroid cancer and estimation of the risk of recurrence.