Literature DB >> 31765737

Somatic gene mutation signatures predict cancer type and prognosis in multiple cancers with pan-cancer 1000 gene panel.

Hai-Long Wang1, Peng-Fei Liu1, Jie Yue2, Wen-Hua Jiang3, Yun-Long Cui4, He Ren5, Han Wang6, Yan Zhuang7, Yong Liu8, Da Jiang9, Qian Dong9, Hui Zhang10, Jia-Hui Mi11, Zan-Mei Xu12, Cai-Juan Tian12, Zhen-Zhen Zhang12, Xiao-Wei Wang12, Mei-Na Su12, Wei Lu13.   

Abstract

Most cancers are caused by somatic mutations. Some common mutations in the same cancer type can form a "signature" to specifically predict the prognosis or to distinguish it from other cancers. In this study, 710 somatic cell mutations were identified in 142 cases, including digestive, lung and urogenital cancers, and the digestive cancers were further divided into liver, stomach, intestinal, esophageal and cardia cancer. The above mutations were located in 166 genes. In addition, a group of high-frequency mutation genes with specific characteristics were screened to form predictive signatures for each cancer. Verification using TCGA suggested that the signatures could predict the stages, progression-free survival, and overall survival of digestive, intestinal, and liver cancers (P < 0.05). The validation cases further confirmed the predictive role of digestive and liver cancers signatures in diagnosis and prognosis. Overall, this study established predictive signatures for different cancer systems and their subtypes. These findings enable a better understanding in cancer genome, and contribute to the personalized diagnosis and treatment.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Intestinal cancer; Liver cancer; Stage; Survival time; System classification

Mesh:

Substances:

Year:  2019        PMID: 31765737     DOI: 10.1016/j.canlet.2019.11.022

Source DB:  PubMed          Journal:  Cancer Lett        ISSN: 0304-3835            Impact factor:   8.679


  10 in total

1.  Establishment and Validation of an Interferon-Stimulated Genes (ISGs) Prognostic Signature in Pan-cancer Patients: A Multicenter, Real-world Study.

Authors:  Zheng Zhou; Yujia Zheng; Shaobo Mo; Shuofeng Li; Xinlei Zheng; Ran Wei; Tao Fan; Tianli Chen; Chu Xiao; Chunxiang Li; Jie He
Journal:  Int J Biol Sci       Date:  2022-05-21       Impact factor: 10.750

2.  Characteristics of Pan-Cancer Patients With Ultrahigh Tumor Mutation Burden.

Authors:  Hong Yuan; Jun Ji; Min Shi; Yan Shi; Jing Liu; Junwei Wu; Chen Yang; Wenqi Xi; Qingyuan Li; Wei Zhu; Jingjie Li; Xiaoli Gong; Jun Zhang
Journal:  Front Oncol       Date:  2021-04-22       Impact factor: 6.244

Review 3.  The Application of Bayesian Methods in Cancer Prognosis and Prediction.

Authors:  Jiadong Chu; N A Sun; Wei Hu; Xuanli Chen; Nengjun Yi; Yueping Shen
Journal:  Cancer Genomics Proteomics       Date:  2022 Jan-Feb       Impact factor: 4.069

4.  MicroRNA-497-5p Is Downregulated in Hepatocellular Carcinoma and Associated with Tumorigenesis and Poor Prognosis in Patients.

Authors:  Lin-Lin Tian; Bin Qian; Xiao-Hui Jiang; Yu-Shan Liu; Tong Chen; Cheng-You Jia; Ya-Li Zhou; Ji-Bin Liu; Yu-Shui Ma; Da Fu; Sen-Tai Ding
Journal:  Int J Genomics       Date:  2021-03-16       Impact factor: 2.326

5.  Long Noncoding RNA OIP5-AS1 Promotes the Progression of Liver Hepatocellular Carcinoma via Regulating the hsa-miR-26a-3p/EPHA2 Axis.

Authors:  Yu-Shui Ma; Kai-Jian Chu; Chang-Chun Ling; Ting-Miao Wu; Xu-Chao Zhu; Ji-Bin Liu; Fei Yu; Zhi-Zhen Li; Jing-Han Wang; Qing-Xiang Gao; Bin Yi; Hui-Min Wang; Li-Peng Gu; Liu Li; Lin-Lin Tian; Yi Shi; Xiao-Qing Jiang; Da Fu; Xiong-Wen Zhang
Journal:  Mol Ther Nucleic Acids       Date:  2020-06-01       Impact factor: 8.886

6.  Identification of Iron Metabolism-Related Gene Signatures for Predicting the Prognosis of Patients With Sarcomas.

Authors:  Jianyi Li; Chuan Hu; Yukun Du; Xiaojie Tang; Cheng Shao; Tongshuai Xu; Zheng Zhao; Huiqiang Hu; Yingyi Sheng; Jianwei Guo; Yongming Xi
Journal:  Front Oncol       Date:  2021-01-07       Impact factor: 6.244

7.  Integration of Tumor Heterogeneity for Recurrence Prediction in Patients with Esophageal Squamous Cell Cancer.

Authors:  Zihang Mai; Qianwen Liu; Xinye Wang; Jiaxin Xie; Jianye Yuan; Jian Zhong; Shuogui Fang; Xiuying Xie; Hong Yang; Jing Wen; Jianhua Fu
Journal:  Cancers (Basel)       Date:  2021-12-02       Impact factor: 6.639

Review 8.  Targeting Strategies for Aberrant Lipid Metabolism Reprogramming and the Immune Microenvironment in Esophageal Cancer: A Review.

Authors:  Meng-Ying Cui; Xing Yi; Zhen-Zhen Cao; Dan-Xia Zhu; Jun Wu
Journal:  J Oncol       Date:  2022-09-05       Impact factor: 4.501

9.  Construction of a Myc-associated ceRNA network reveals a prognostic signature in hepatocellular carcinoma.

Authors:  Dan-Dan Zhang; Yi Shi; Ji-Bin Liu; Xiao-Li Yang; Rui Xin; Hui-Min Wang; Pei-Yao Wang; Cheng-You Jia; Wen-Jie Zhang; Yu-Shui Ma; Da Fu
Journal:  Mol Ther Nucleic Acids       Date:  2021-05-01       Impact factor: 8.886

10.  Diagnostic model of combined ceRNA and DNA methylation related genes in esophageal carcinoma.

Authors:  Xiaojiao Guan; Yao Yao; Guangyao Bao; Yue Wang; Aimeng Zhang; Xinwen Zhong
Journal:  PeerJ       Date:  2020-03-31       Impact factor: 2.984

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.