Dataset Information

TRIM27 Functions as a Novel Oncogene in Non-Triple-Negative Breast Cancer by Blocking Cellular Senescence through p21 Ubiquitination.

ABSTRACT: In the current study, we aimed to explore the correlation between TRIM27 and breast cancer prognosis, as well as the functions of TRIM27 in breast cancer and their underlying mechanisms. Bioinformatics analyses were used to examine the correlation between TRIM27 and breast cancer prognosis. Moreover, TRIM27 knockdown and overexpression in breast cancer cells were performed to investigate its functions in breast cancer. Tamoxifen (TAM) was applied to evaluate the influence of TRIM27 on chemoresistance of breast cancer cells, while co-immunoprecipitation (coIP) was performed to identify the E3 ubiquitin ligase capability of TRIM27. High expression of TRIM27 was found in non-triple-negative breast cancer (non-TNBC) tumor tissues and was positively correlated with the mortality of non-TNBC patients. Moreover, TRIM27 could suppress non-TNBC cell apoptosis and senescence, promote cell viability and tumor growth, counteract the anti-cancer effects of TAM, and mediate ubiquitination of p21. In addition, EP300 could enhance the expression of TRIM27 and its transcription promoter H3K27ac. TRIM27, through ubiquitination of p21, might serve as a prognostic biomarker for non-TNBC prognosis. TRIM27 functions as a novel oncogene in non-TNBC cellular processes, especially suppressing cell senescence and interfering with non-TNBC chemoresistance.

SUBMITTER: Xing L

PROVIDER: S-EPMC7666371 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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TRIM27 Functions as a Novel Oncogene in Non-Triple-Negative Breast Cancer by Blocking Cellular Senescence through p21 Ubiquitination.

Xing Li L Tang Xiaolong X Wu Kaikai K Huang Xiong X Yi Yi Y Huan Jinliang J

Molecular therapy. Nucleic acids 20201015

In the current study, we aimed to explore the correlation between TRIM27 and breast cancer prognosis, as well as the functions of TRIM27 in breast cancer and their underlying mechanisms. Bioinformatics analyses were used to examine the correlation between TRIM27 and breast cancer prognosis. Moreover, TRIM27 knockdown and overexpression in breast cancer cells were performed to investigate its functions in breast cancer. Tamoxifen (TAM) was applied to evaluate the influence of TRIM27 on chemoresis ...[more]

PMID: 33251042

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Project description:BackgroundTriple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with high heterogeneity, poor prognosis, and a low 10-year survival rate of less than 50%. Although cellular senescence displays extensive effects on cancer, the comprehensions of cellular senescence-related characteristics in TNBC patients remains obscure.MethodSingle-cell RNA sequencing (scRNA-seq) data were analyzed by Seurat package. Scores for cellular senescence-related pathways were computed by single-sample gene set enrichment analysis (ssGSEA). Subsequently, unsupervised consensus clustering was performed for molecular cluster identification. Immune scores of patients in The Cancer Genome Atlas (TCGA) dataset and associated immune cell scores were calculated using Estimation of STromal and Immune cells in MAlignantTumours using Expression data (ESTIMATE) and Microenvironment Cell Populations-counter (MCP-counter), Tumor Immune Estimation Resource (TIMER) and Estimating the Proportion of Immune and Cancer cells (EPIC) methods, respectively. Immunotherapy scores were assessed using TIDE. Furthermore, feature genes were identified by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses; these were used to construct a risk model. Additionally, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and transwell assay were conducted for in vitro validation of hub genes.ResultTNBC was classified into three subtypes based on cellular senescence-related pathways as clusters 1, 2, and 3. Specifically, cluster 1 showed the best prognosis, followed by cluster 2 and cluster 3. The levels of gene expression in cluster 2 were the lowest, whereas these were the highest in cluster 3. Moreover, clusters 1 and 3 showed a high degree of immune infiltration. TIDE scores were higher for cluster 3, suggesting that immune escape was more likely in patients with the cluster 3 subtype who were less likely to benefit from immunotherapy. Next, the TNBC risk model was constructed and validated. RT-qPCR revealed that prognostic risk genes (MMP28, ACP5 and KRT6A) were up-regulated while protective genes (CT83) were down-regulated in TNBC cell lines, validating the results of the bioinformatics analysis. Meanwhile, cellular experiments revealed that ACP5 could promote the migration and invasion abilities in two TNBC cell lines. Finally, we evaluated the validity of prognostic models for assessing TME characteristics and TNBC chemotherapy response.ConclusionIn conclusion, these findings help to assess the efficacy of targeted therapies in patients with different molecular subtypes, have practical applications for subtype-specific treatment of TNBC patients, and provide information on prognostic factors, as well as guidance for the revelation of the molecular mechanisms by which senescence-associated genes influence TNBC progression.

Project description:BackgroundOxidative stress and cellular senescence (OSCS) have great impacts on the occurrence and progression of triple-negative breast cancer (TNBC). This study was intended to construct a prognostic model based on oxidative stress and cellular senescence related difference expression genes (OSCSRDEGs) for TNBC.MethodsThe Cancer Genome Atlas (TCGA) databases and two Gene Expression Omnibus (GEO) databases were used to identify OSCSRDEGs. The relationship between OSCSRDEGs and immune infiltration was examined using single-sample gene-set enrichment analysis (ssGSEA), ESTIMATE, and the CIBERSORT algorithm. Least absolute shrinkage and selection operator (LASSO) regression analyses, Cox regression and Kaplan-Meier analysis were employed to construct a prognostic model. Receiver operating characteristic (ROC) curves, nomograms, and decision curve analysis (DCA) were used to evaluate the prognostic efficacy. Gene Set Enrichment Analysis (GSEA) Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to explore the potential functions and mechanism.ResultsA comprehensive analysis identified a total of 27 OSCSRDEGs, out of which 15 genes selected for development of a prognostic model. A high degree of statistical significance was observed for the riskscores derived from this model to accurately predict TNBC Overall survival. The decision curve analysis (DCA) and ROC curve analysis further confirmed the superior accuracy of the OSCSRDEGs prognostic model in predicting efficacy. Notably, the nomogram analysis highlighted that DMD exhibited the highest utility within the model. In comparison between high and low OSCScore groups, the infiltration abundance of immune cells was statistically different in the TCGA-TNBC dataset.ConclusionThese studies have effectively identified four essential OSCSRDEGs (CFI, DMD, NDRG2, and NRP1) and meticulously developed an OSCS-associated prognostic model for individuals diagnosed with TNBC. These discoveries have the potential to significantly contribute to the comprehension of the involvement of OSCS in TNBC.

Dataset Information

TRIM27 Functions as a Novel Oncogene in Non-Triple-Negative Breast Cancer by Blocking Cellular Senescence through p21 Ubiquitination.

Publications

TRIM27 Functions as a Novel Oncogene in Non-Triple-Negative Breast Cancer by Blocking Cellular Senescence through p21 Ubiquitination.

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