An miRNA signature associated with tumor mutation burden in endometrial cancer.

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.

Zhou H ，Chen L ，Qin M ，Lei Y ，Li T ，Li H ，Cheng X ... -  《-》

Development and Clinical Validation of Novel 8-Gene Prognostic Signature Associated With the Proportion of Regulatory T Cells by Weighted Gene Co-Expression Network Analysis in Uterine Corpus Endometrial Carcinoma.

Uterine corpus endometrial carcinoma (UCEC) is a gynecological malignant tumor with low survival rate and poor prognosis. The traditional clinicopathological staging is insufficient to estimate the prognosis of UCEC. It is necessary to select a more effective prognostic signature of UCEC to predict the prognosis and immunotherapy effect of UCEC. CIBERSORT and weighted correlation network analysis (WGCNA) algorithms were combined to screen modules related to regulatory T (Treg) cells. Subsequently, univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were used to identify the genes in key modules. The difference in overall survival (OS) between high- and low-risk patients was analyzed by Kaplan-Meier analysis. The Tregs-related risk signature (TRRS) was screened by uni- and multivariate Cox analyses. Afterward, we analyzed the expression difference of TRRS and verified its ability to predict the prognosis of UCEC and the effect of immunotherapy. Red module has the highest correlation with Tregs among all clustered modules. Pathways enrichment indicated that the related processes of UCEC were primarily associated to the immune system. Eight genes (ZSWIM1, NPRL3, GOLGA7, ST6GALNAC4, CDC16, ITPK1, PCSK4, and CORO1B) were selected to construct TRRS. We found that this TRRS is a significantly independent prognostic factor of UCEC. Low-risk patients have higher overall survival than high-risk patients. The immune status of different groups was different, and tumor-related pathways were enriched in patients with higher risk score. Low-risk patients are more likely take higher tumor mutation burden (TMB). Meanwhile, they are more sensitive to chemotherapy than patients with high-risk score, which indicated a superior prognosis. Immune checkpoints such as PD-1, CTLA4, PD-L1, and PD-L2 all had a higher expression level in low-risk group. TRRS expression really has a relevance with the sensitivity of UCEC patients to chemotherapeutic drugs. We developed and validated a TRRS to estimate the prognosis and reflect the immune status of UCEC, which could accurately assess the prognosis of patients with UCEC and supply personalized treatments for them.

Liu J ，Geng R ，Yang S ，Shao F ，Zhong Z ，Yang M ，Ni S ，Cai L ，Bai J ... -  《Frontiers in Immunology》

Integrated analysis of tumor mutation burden and immune infiltrates in endometrial cancer.

To explore the prognostic value of tumor mutation burden (TMB) and its correlation with immune infiltrates in endometrial cancer. Transcriptome and somatic mutation profiles of Uterine Corpus Endometrial Carcinoma (UCEC) were downloaded from TCGA database. Somatic mutations were analyzed by "maftools" and visualized in waterfall plot. We calculated TMB of each patients and divided all patients into the high-TMB group and the low-TMB group by the median threshold. Survival analysis and Wilcoxon test were used to investigate the prognostic value of TMB and its association with clinical variables. Differentially expressed genes (DEGs) were identified in 2 TMN groups and functional analysis was performed to find out significant biological pathways. A TMB-related signature was conducted by multivariate analysis, receiver operating characteristic (ROC) curve was performed to predict accuracy of the model, meanwhile, a validation cohort from Fudan University Shanghai Cancer Center (FUSCC) was obtained to verify the signature. Then we estimated association between TMB and immune infiltrates by CIBERSORT algorithm and figured out prognostic immune cells of UCEC in TIMER database. Total 575 samples including 25 normal tissues and 552 tumor samples were enrolled from TCGA database. PTEN mutations accounted for the most and single nucleotide polymorphism and C>T transitions were most frequent forms of somatic mutations in UCEC. The low-TMB group possessed worse survival than the high-TMB group (P = 0.004). DEGs in 2 TMB groups were mostly enriched in adaptive immune response and immunoglobulin/immune receptor component. A TMB-related signature consisting of GFAP, EDN3, CXCR3, PLXNA4, SST presented good predictability with area under the curve (AUC) = 0.686. In FUSCC validation cohort, the high-risk group possessed worse survival outcome than the low-risk group (P = 0.015). Immune infiltrates was correlated to survival in UCEC and low TMB were associated with less immune infiltrates, which suggested poor immune response. TMB was not only related to overall survival but also immune infiltrates in UCEC. The TMB-related signature (GFAP, EDN3, CXCR3, PLXNA4, SST) had good predictability for overall survival in endometrial cancer. Our study might have some merits in elucidating potential mechanism of TMB and immune infiltrates in UCEC and providing guidance of immunotherapy for endometrial cancer.

Zhou H ，Chen L ，Lei Y ，Li T ，Li H ，Cheng X ... -  《-》

MiRNA based tumor mutation burden diagnostic and prognostic prediction models for endometrial cancer.

Lu N ，Liu J ，Ji C ，Wang Y ，Wu Z ，Yuan S ，Xing Y ，Diao F ... -  《-》

Identification and validation of a miRNA-related expression signature for tumor mutational burden in colorectal cancer.

Xu L ，Zheng Q 《World Journal of Surgical Oncology》