Tumor Mutation Burden-Related Histopathologic Features for Predicting Overall Survival in Gliomas Using Graph Deep Learning

作者全名："Sun, Caixia; Luo, Tao; Liu, Zhenyu; Ge, Jia; Shao, Lizhi; Liu, Xiangyu; Li, Bao; Zhang, Song; Qiu, Qi; Wei, Wei; Wang, Shuo; Bian, Xiu-Wu; Tian, Jie"

作者地址："[Sun, Caixia; Wang, Shuo; Tian, Jie] Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Engn Med, Beijing 100191, Peoples R China; [Sun, Caixia; Wang, Shuo; Tian, Jie] Beihang Univ, Key Lab Big Data Based Precis Med, Minist Ind & Informat Technol, Beijing, Peoples R China; [Sun, Caixia; Liu, Zhenyu; Shao, Lizhi; Liu, Xiangyu; Li, Bao; Zhang, Song; Qiu, Qi; Wei, Wei; Wang, Shuo; Tian, Jie] Chinese Acad Sci, Inst Automat, Chinese Acad Sci Key Lab Mol Imaging, Beijing Key Lab Mol Imaging, Beijing, Peoples R China; [Luo, Tao; Ge, Jia; Bian, Xiu-Wu] Third Mil Med Univ, Southwest Hosp, Army Med Univ, Chongqing, Peoples R China; [Luo, Tao; Bian, Xiu-Wu] Minist Educ China, Key Lab Tumor Immunopathol, Chongqing 400038, Peoples R China; [Liu, Zhenyu] Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China; [Tian, Jie] Xidian Univ, Sch Life Sci & Technol, Engn Res Ctr Mol & Neuro Imaging, Minist Educ, Xian, Peoples R China"

通信作者："Tian, J (通讯作者)，Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Engn Med, Beijing 100191, Peoples R China.; Bian, XW (通讯作者)，Third Mil Med Univ, Southwest Hosp, Army Med Univ, Chongqing, Peoples R China.; Bian, XW (通讯作者)，Minist Educ China, Key Lab Tumor Immunopathol, Chongqing 400038, Peoples R China."

来源：AMERICAN JOURNAL OF PATHOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001124361300001

JCR分区：Q1

影响因子：6

年份：2023

卷号：193

期号：12

开始页：2111

结束页：2121

文献类型：Article; Early Access

关键词：　

摘要："Tumor mutation burden (TMB) is a potential biomarker for evaluating the prognosis and response to immune checkpoint inhibitors, but its costly and time-consuming method of measurement limits its widespread application. This study aimed to identify the TMB-related histopathologic features from hematoxylin and eosin slides and explore their prognostic value in gliomas. TMB-related features were detected using a graph convolutional neural network from whole-slide images of patients from The Cancer Genome Atlas data set (619 patients), and the correlation between features and TMB was evaluated in an external validation set (237 patients). TMB-related features were used for predicting overall survival (OS) of patients to investigate whether these features have potential for prognostic prediction. Moreover, biological pathways underlying the prognostic value of the features were further explored. Histopathologic features derived from whole-slide images were significantly associated with patient TMB (P = 0.007 in the external validation set). TMB-related features showed excellent per-formance for OS prediction, and patients with lower-grade gliomas could be further stratified into different risk groups according to the features (P = 0.00013; hazard ratio, 4.004). Pathways involved in the cell cycle and execution of immune response were enriched in patients with higher OS risk. The TMB-related features could be used to estimate TMB and aid in prognostic risk stratification of patients with glioma with dysregulated biological pathways. (Am J Pathol 2023, 193: 2111-2121; https:// doi.org/10.1016/j.ajpath.2023.08.015)"

基金机构："National Key R&D Program of China [2021YFF1201003, 2021YYF1201002]; National Natural Science Foundation of China [92059103, 62333022, 92259301, 82371936]; Beijing Natural Science Foundation [JQ23034]; Natural Science Basic Research Pro-gram of Shaanxi [2023-JC-YB-682]"

基金资助正文："Supported by the National Key R & D Program of China 2021YFF1201003 (Z.L.) and 2021YYF1201002 (T.L.) ; the National Natural Science Foundation of China 92059103 (Z.L.) , 62333022 (Z.L.) , 92259301 (Z.L.) , and 82371936 (W.W.) ; the Beijing Natural Science Foundation JQ23034 (Z.L.) ; and the Natural Science Basic Research Pro-gram of Shaanxi 2023-JC-YB-682 (W.W.) ."