Identification of diagnostic signatures associated with tumor mutation burden in gastric cancer based on TCGA and machine-learning methods / 西安交通大学学报(医学版)

【Objective】 To select and identify miRNA signatures to predict TMB level in gastric cancer based on The Cancer Genome Atlas (TCGA) database and machine learning methods. 【Methods】 MiRNA expression and somatic mutation profiles of gastric cancer (GC) were downloaded from TCGA database. R "limma" package was performed to select differentially expressed miRNAs between high-TMB and low-TMB groups. Two machine learning algorisms, random forest (RF), and Support Vector Machine-Recursive Feature Elimination were utilized to identify miRNAs with the highest discriminative ability. ROC was used to test the predictive ability of these signatures in multiple datasets. Besides, immune cells of different TMB levels were compared by the CIBERSORT method. 【Results】 A total of 56 differentially expressed miRNAs (DE-miRNAs) were filtered. Functional enrichment analysis showed that these DE miRNAs are mainly enriched in signaling pathways related to tumor occurrence and development as well as immunity-related biological processes. The RF and SVM-RFE algorithms jointly identified 10 diagnostic features of miRNAs, among which only hsa-miR-210-3p is considered the most relevant predictive biomarker for TMB classification. The AUC value of hsa-miR-210-3p in the training, testing, and total sets is 0.822, 0.721, and 0.793, respectively, and has been validated in other cancer types. Besides, CIBERSORT analysis suggests differences in immune cell infiltration between high- and low-TMB groups. Meanwhile, there is a significant positive correlation between the expression of immune checkpoint related genes and mismatch repair related genes and hsa-miR-210-3p. 【Conclusion】 This study successfully identified hsa-miR-210-3p as a predictive biomarker for TMB classification, which can effectively predict TMB values in gastric cancer and other cancer patients and may provide some guidance for immunotherapy.

Correlation analysis between SLC52A2 gene expression and prognosis of patients with uveal melanoma / 国际眼科杂志(Guoji Yanke Zazhi)

AIM: To analyze the correlation between SLC52A2 and uveal melanoma(UM)based on the cancer genome atlas(TCGA)database, and preliminarily explore the influence of SLC52A2 on the prognosis of UM patients and potential mechanism.METHODS: The clinical information on 80 patients with UM and mRNA expression data of SLC52A2 were collected from TCGA database. According to the expression level of SLC52A2, 80 patients were divided into high and low expression groups by median method. The relationship between the expression of SLC52A2 and clinical pathological features, as well as the prognosis was analyzed. The age, sex, clinical stage, pathological stage, and mRNA expression of SLC52A2 were analyzed by univariate and multivariate Cox analysis to search the prognostic factors of UM. Enrichment analyses were used to predict the possible regulatory pathway of SLC52A2 in UM.RESULTS: The survival prognosis of patients with low expression of SLC52A2 was better than that of patients with high expression of SLC52A2(P<0.05). The level of SLC52A2 has no significant correlation with the age, sex, clinical stage, and pathological stage of patients in both groups(P>0.05). Multivariate Cox analysis showed that the high expression of SLC52A2 was a risk factor for poor prognosis. The nomogram prediction model developed by combining the expression of SLC52A2 with clinical pathological features could accurately predict the survival probability of UM patients. The infiltration abundance of Th2 and Treg cells in both groups has difference(all P<0.001). GSEA analysis showed that the gene of JAK-STAT(FDR=0.028, P=0.004)and PI3K/AKT(FDR=0.017, P=0.002)were rich in samples with high expression of SLC52A2.CONCLUSION: The high expression of SLC52A2 is a risk factor for the prognosis of UM patients. SLC52A2 can be used as a biomarker to predict the prognosis and to become a new target for the treatment of patients with UM.

Mitochondrial Fission Protein 1 (FIS1) Overexpression in Human Cervical Cancer Cells Promotes Mitochondrial Fission and Reduces Cell Proliferation and Migration Capacity / 中国生物化学与分子生物学报

Mitochondria are dynamic organelles that continuously divide and fuse. In recent years, in addition to the studies related to mitochondrial metabolism, the unique dynamics of mitochondria have gradually attracted researchers' attention. A growing body of research has revealed that mitochondrial dynamics are related to the biological behavior of tumor cells. Mitochondrial fission proteins (mitochondrial fission protein 1, FIS1) mediate the assembly of mitochondrial fission complexes and participate in the execution of mitochondrial fission. They are important proteins in the process of mitochondrial fusion and fission. However, few studies have revealed the expression and role of FIS1 in human cervical cancer. In this study, the expression level of FIS1 in human cervical cancer tissues and paracancer tissues were compared. The results showed that the level of FIS1 mRNA in human cervical cancer tissues was significantly lower than that in paracancer tissues (P<0. 01). Further KEGG pathway and GO Term-BP pathway analysis showed that the differential genes are mainly related to mitochondrial biological functions. Subsequently, HeLa cells with overexpressed FIS1 were investigated for their proliferation, migration, mitochondrial fission and ROS levels. The experimental results showed that FIS1 overexpression decreased HeLa cell proliferation and migration ability, enhanced mitochondrial fission and higher ROS levels. In conclusion, the expression of FIS1 in human cervical cancer cells was attenuated, while overexpression of FIS1 resulted in a series of abnormal biological functions in human cervical cancer cells. Further studies can be carried out to investigate the role of FIS1 in the treatment of human cervical cancer.

Acetyl-CoA Carboxylase 1 (ACC1) Affects the Proliferation of Clear Cell Renal Cell Carcinoma (ccRCC) by Regulating Cyclin D1/CDK4 / 中国生物化学与分子生物学报

Acetyl-CoA carboxylase (ACC) is the rate limiting enzyme of fatty acid synthesis pathway. Studies have shown that ACC1 is implicated in a variety of metabolic diseases and cancer. However, the role and mechanism of action of ACC1 in clear cell renal cell carcinoma (ccRCC) have not been reported. In this study, 786-O and Caki-1 clear cell renal carcinoma cells were used as research objects to investigate the effect of abnormal expression of ACC1 on their proliferation and unravel the underlying mechanism. Red oil-O-staining results showed that the lipid content of 786-O and Caki-1 cells was significantly higher than that of human kidney 2 (HK2) cells. By searching TCGA database, we found that the expression of ACC1 proteins in ccRCC was significantly higher than that in normal renal tissues (P < 0.001). Plus, ACC1 protein expression in all clinical TNM stages was significantly higher than that in normal tissues, and the higher the expression of ACC1, the higher the pathological grade. Furthermore, high expression of ACC1 mRNA is positively correlated with poor prognosis in ccRCC patients. Western blotting analysis showed that the expression of ACC1 in 786-O and Caki-1 cells was significantly higher than that in HK2 cells. The results of red oil-O-staining showed that knocking down ACC1 could significantly reduce the lipid content of 786-O and Caki-1 cells. The results of CCK-8 assays and clonogenicity analysis showed that knocking down ACC1 could significantly reduce the proliferation and colony forming ability of 786-O and Caki-1 cells. Flow cytometry analysis showed that after knocking down ACC1, the cell cycle was blocked at the G

Integrated analysis of hypoxia-induced miR-210 signature as a potential prognostic biomarker of hepatocellular carcinoma: a study based on The Cancer Genome Atlas / 浙江大学学报（英文版）（B辑：生物医学和生物技术）

Hepatocellular carcinoma (HCC) is one of the most common types of liver cancer and is the second leading cause of cancer mortality with an estimated 745 500 deaths annually (Jemal et al., 2011). Although new therapeutic modalities including novel chemotherapeutic interventions and targeted therapy have been applied, the prognosis of HCC patients remains unsatisfactory due to the high incidence of intrahepatic and distal metastases (Siegel et al., 2018).

Expression and clinical significance of UBE2T in primary liver cancer / 实用肿瘤学杂志

Objective The objective of this study was to analyze the expression of ubiquitin -conjugating enzyme E2T (UBE2T)in primary liver cancer and its relationship with clinicopathological parameters and prognosis of patients with liver cancer. Methods The second generation sequencing data and clinical pathological data of UBE2T gene mRNA in normal liver tissues and liver cancer tissues were downloaded from the Cancer Genome Atlas(TCGA)database. The expression of UBE2T in cancer tissues and normal tissues was analyzed to elucidate the relationship between UBE2T at mRNA level and clinicopathological parameters of patients with liver cancer. Kaplan-Meier was used for prognostic analysis. The Cox proportional hazard regression model was performed for the multivariate analysis of the prognostic factors associated with HCC. Based on the results of gene set enrichment analysis(GSEA), UBE2T was involved in the possible regulating pathways of HCC development. Results The expression of UBE2T at mRNA level in hepatocarcinoma tissues was significantly higher than that in adjacent tissues(P<0. 01). The high expression of UBE2T was closely related to pathological grade,TNM staging,and vascular invasion(P<0. 01),suggesting a poor prognosis of patients with liver cancer. Multivariate Cox regression analysis showed that TNM staging,vascular invasion and UBE2T expression were independent risk factors affecting the prognosis of patients with liver cancer. Conclusion The high expression of UBE2T is significantly associated with the clinicopathological factors and prognosis of patients with liver cancer. It can be used as a potential marker for predicting the prognosis of liver cancer patients and a target for tumor therapy.

A new bioinformatics approach for prediction of potential tumor neoantigens based on the cancer genome atlas dataset / 生物工程学报

Tumor-specific gene mutations might generate suitable neoepitopes for cancer immunotherapy that are highly immunogenic and absent in normal tissues. The high heterogeneity of the tumor genome poses a big challenge for precision cancer immunotherapy. Mutations characteristic of each tumor can help to distinguish it from other tumors. Based on these mutations' characteristic, it is possible to develop immunotherapeutic strategies for specific tumors. In this study, a tumor neoantigen prediction scheme was proposed, in which both the intracellular antigen presentation process and the ability to bind with extracellular MHC molecule were taken into consideration. The overall design is meritorious and may help reduce the cost for validation experiments compared with conventional methods. This strategy was tested with several cancer genome datasets in the TCGA database, and a number of potential tumor neoantigens were predicted for each dataset. These predicted neoantigens showed tumor type specificity and were found in 20% to 70% of cancer patients. This scheme might prove useful clinically in future.