4.6 Article

Development and Validation of a Tumor Mutation Burden-Related Immune Prognostic Signature for Ovarian Cancers

期刊

FRONTIERS IN GENETICS
卷 12, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2021.688207

关键词

ovarian cancer; tumor mutation burden; immune risk score; prognostic biomarkers; immune checkpoint

资金

  1. Natural Science Foundation of China [81872684]
  2. Fundamental Research Funds for the Central Universities
  3. Southeast University Zhongying Young Scholars Project
  4. Six Talent Peaks Project in Jiangsu Province [wsw-201]
  5. SIX ONE Talent Research Project for the High-level Health Personnel of Jiangsu Province [LGY2020050]
  6. Fifth Scientific Research Project of Nantong (226 Project)
  7. Nantong Commission of Health [MB2020018]
  8. Postgraduate Research&Practice Innovation Program of Jiangsu Province [KYCX21_0162]

向作者/读者索取更多资源

We found that tumor mutation burden (TMB) is closely associated with the prognosis of ovarian cancer (OC). The TMB associated immune risk score (TMB-IRS) signature can effectively predict the prognosis of OC patients. Furthermore, TMB-IRS is also correlated with immune cell infiltration levels and immune checkpoint molecules in OC.
Ovarian cancer (OC), one of the most common malignancies of the female reproductive system, is characterized by high incidence and poor prognosis. Tumor mutation burden (TMB), as an important biomarker that can represent the degree of tumor mutation, is emerging as a key indicator for predicting the efficacy of tumor immunotherapy. In our study, the gene expression profiles of OC were downloaded from TCGA and GEO databases. Subsequently, we analyzed the prognostic value of TMB in OC and found that a higher TMB score was significantly associated with a better prognosis (p = 0.004). According to the median score of TMB, 9 key TMB related immune prognostic genes were selected by LASSO regression for constructing a TMB associated immune risk score (TMB-IRS) signature, which can effectively predict the prognosis of OC patients (HR = 2.32, 95% CI = 1.68-3.32; AUC = 0.754). Interestingly, TMB-IRS is also closely related to the level of immune cell infiltration and immune checkpoint molecules (PD1, PD-L1, CTLA4, PD-L2) in OC. Furthermore, the nomogram combined with TMB-IRS and a variety of clinicopathological features can more comprehensively evaluate the prognosis of patients. In conclusion, we explored the relationship between TMB and prognosis and validated the TMB-IRS signature based on TMB score in an independent database (HR = 1.60, 95% CI = 1.13-2.27; AUC = 0.639), which may serve as a novel biomarker for predicting OC prognosis as well as possible therapeutic targets.

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