ArticleBioscience reports2020
An miRNA signature associated with tumor mutation burden in endometrial cancer.
Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Unveiling the predictive role of systemic inflammation marker in mortality outcomes: a nationwide analysis of cancer survivorship in the United States.Discover oncology · 2025Article
- Present progress in biomarker discovery of endometrial cancer by multi-omics approaches.Clinical proteomics · 2025Review
- Biomarkers and immunotherapy in endometrial cancer: mechanisms and clinical applications.Frontiers in immunology · 2025Review
- The interplay of sex steroid hormones and microRNAs in endometrial cancer: current understanding and future directions.Frontiers in endocrinology · 2023Review
- Targeting non-coding RNAs to overcome cancer therapy resistance.Signal transduction and targeted therapy · 2022Review
- [MiR-671-5p negatively regulates SMAD3 to inhibit migration and invasion of osteosarcoma cells].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2021Article
- Identification and validation of a miRNA-related expression signature for tumor mutational burden in colorectal cancer.World journal of surgical oncology · 2021Article
- Prognosis Value of microRNA-3677-3p in Lung Adenocarcinoma and Its Regulatory Effect on Tumor Progression.Cancer management and research · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor mutation burden (TMB) is an essential biomarker to predict immunotherapy response. TMB measurement was mainly evaluated by whole-exome sequencing (WES), which was costly and difficult to be widely applied. In the present study, we aimed to establish and validate a miRNA signature to predict TMB level in endometrial cancer using The Cancer Genome Atlas (TCGA) database. MiRNA expression and somatic mutation profiles of uterine corpus endometrial carcinoma (UCEC) were downloaded from TCGA database. Total 518 patients with UCEC were randomly classified into training set (n=311) and validation set (n=207). Thirty-five differentially expressed miRNAs between high-TMB and low-TMB group were identified in training set. Least absolute shrinkage and selection operator (LASSO) method was performed to select out 26 miRNAs to establish the optimal signature. The accuracy of the miRNA signature for predicting TMB level was 0.833 for training set, 0.749 for validation set and 0.799 for total set. Moreover, the miRNA signature had significant correlation with immune checkpoints related genes (PD-1, PD-L1, CTLA-4) and mismatch repair related genes (BRCA1, BRCA2, MLH1, MSH6) expression. In conclusion, this miRNA signature could predict TMB level in endometrial cancer and might have some merits in providing guidance for immunotherapy in endometrial cancer.
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