Identification of tumor mutation burden-associated molecular and clinical features in cancer by analyzing multi-omics data

被引:21
|
作者
Li, Mengyuan [1 ,2 ]
Gao, Xuejiao [1 ,2 ]
Wang, Xiaosheng [3 ]
机构
[1] Nanjing Univ Chinese Med, Sch Pharm, Nanjing, Peoples R China
[2] Nanjing Univ Chinese Med, Affiliated Hosp Integrated Tradit Chinese & Wester, Nanjing, Jiangsu, Peoples R China
[3] China Pharmaceut Univ, Sch Basic Med & Clin Pharm, Nanjing, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2023年 / 14卷
关键词
tumor mutation burden; multi-omics; antitumor immunity; cancer immunotherapy; TMB prognostic score; ceRNA; CTLA-4; BLOCKADE; PD-L1; BREAST-CANCER; NIVOLUMAB; PATHWAYS; IMMUNOTHERAPY; EXPRESSION; DOCETAXEL; GENOMES; PROTEIN;
D O I
10.3389/fimmu.2023.1090838
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
BackgroundTumor mutation burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in cancer. Systematic identification of molecular features correlated with TMB is significant, although such investigation remains insufficient. MethodsWe analyzed associations of somatic mutations, pathways, protein expression, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), competing endogenous RNA (ceRNA) antitumor immune signatures, and clinical features with TMB in various cancers using multi-omics datasets from The Cancer Genome Atlas (TCGA) program and datasets for cancer cohorts receiving the immune checkpoint blockade therapy. ResultsAmong the 32 TCGA cancer types, melanoma harbored the highest percentage of high-TMB (>= 10/Mb) cancers (49.4%), followed by lung adenocarcinoma (36.9%) and lung squamous cell carcinoma (28.1%). Three hundred seventy-six genes had significant correlations of their mutations with increased TMB in various cancers, including 11 genes (ARID1A, ARID1B, BRIP1, NOTCH2, NOTCH4, EPHA5, ROS1, FAT1, SPEN, NSD1,and PTPRT) with the characteristic of their mutations associated with a favorable response to immunotherapy. Based on the mutation profiles in three genes (ROS1, SPEN, and PTPRT), we defined the TMB prognostic score that could predict cancer survival prognosis in the immunotherapy setting but not in the non-immunotherapy setting. It suggests that the TMB prognostic score's ability to predict cancer prognosis is associated with the positive correlation between immunotherapy response and TMB. Nine cancer-associated pathways correlated positively with TMB in various cancers, including nucleotide excision repair, DNA replication, homologous recombination, base excision repair, mismatch repair, cell cycle, spliceosome, proteasome, and RNA degradation. In contrast, seven pathways correlated inversely with TMB in multiple cancers, including Wnt, Hedgehog, PI3K-AKT, MAPK, neurotrophin, axon guidance, and pathways in cancer. High-TMB cancers displayed higher levels of antitumor immune signatures and PD-L1 expression than low-TMB cancers in diverse cancers. The association between TMB and survival prognosis was positive in bladder, gastric, and endometrial cancers and negative in liver and head and neck cancers. TMB also showed significant associations with age, gender, height, weight, smoking, and race in certain cohorts. ConclusionsThe molecular and clinical features significantly associated with TMB could be valuable predictors for TMB and immunotherapy response and therefore have potential clinical values for cancer management.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Identification of molecular features correlating with tumor immunity in gastric cancer by multi-omics data analysis
    He, Yin
    Wang, Xiaosheng
    ANNALS OF TRANSLATIONAL MEDICINE, 2020, 8 (17)
  • [2] Multi-omics analysis reveals prognostic value of tumor mutation burden in hepatocellular carcinoma
    Xu, Qianhui
    Xu, Hao
    Deng, Rongshan
    Wang, Zijie
    Li, Nanjun
    Qi, Zhixuan
    Zhao, Jiaxin
    Huang, Wen
    CANCER CELL INTERNATIONAL, 2021, 21 (01)
  • [3] Identifying tumor immunity-associated molecular features in liver hepatocellular carcinoma by multi-omics analysis
    Shen, Qianyun
    He, Yin
    Qian, Jiajie
    Wang, Xiaosheng
    FRONTIERS IN MOLECULAR BIOSCIENCES, 2022, 9
  • [4] Multi-omics analysis of tumor mutation burden combined with immune infiltrates in bladder urothelial carcinoma
    Zhang, Chuanjie
    Shen, Luping
    Qi, Feng
    Wang, JinCheng
    Luo, Jun
    JOURNAL OF CELLULAR PHYSIOLOGY, 2020, 235 (04) : 3849 - 3863
  • [5] Multi-OMICs data analysis identifies molecular features correlating with tumor immunity in colon cancer
    Elsayed, Inas
    Elsayed, Nazik
    Feng, Qiushi
    Sheahan, Kieran
    Moran, Bruce
    Wang, Xiaosheng
    CANCER BIOMARKERS, 2022, 33 (02) : 261 - 271
  • [6] Multi-omics analysis of tumor mutation burden combined with immune infiltrates in melanoma
    Jiang, Feng
    Wu, Chuyan
    Wang, Ming
    Wei, Ke
    Zhou, Guoping
    Wang, Jimei
    CLINICA CHIMICA ACTA, 2020, 511 : 306 - 318
  • [7] Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis
    Yin, Lu
    Zhou, Liuzhi
    Xu, Rujun
    FRONTIERS IN MOLECULAR BIOSCIENCES, 2021, 7
  • [8] Multi-omics analysis reveals prognostic value of tumor mutation burden in hepatocellular carcinoma
    Qianhui Xu
    Hao Xu
    Rongshan Deng
    Zijie Wang
    Nanjun Li
    Zhixuan Qi
    Jiaxin Zhao
    Wen Huang
    Cancer Cell International, 21
  • [9] Molecular Subtyping of Serous Ovarian Cancer Based on Multi-omics Data
    Zhang, Zhe
    Huang, Ke
    Gu, Chenglei
    Zhao, Luyang
    Wang, Nan
    Wang, Xiaolei
    Zhao, Dongsheng
    Zhang, Chenggang
    Lu, Yiming
    Meng, Yuanguang
    SCIENTIFIC REPORTS, 2016, 6
  • [10] A pan-cancer multi-omics analysis of lactylation genes associated with tumor microenvironment and cancer development
    Wu, Zhixuan
    Wu, Haodong
    Dai, Yinwei
    Wang, Ziqiong
    Han, Hui
    Shen, Yanyan
    Zhang, Rongrong
    Wang, Xiaowu
    HELIYON, 2024, 10 (05)