Abstract:The epithelial-mesenchymal transition (EMT) represents a biological program during which epithelial cells lose their cell identity and acquire a mesenchymal phenotype. EMT is normally observed during organismal development, wound healing and tissue fibrosis. However, this process can be hijacked by cancer cells and is often associated with resistance to apoptosis, acquisition of tissue invasiveness, cancer stem cell characteristics, and cancer treatment resistance. It is becoming evident that EMT is a complex,… Show more
“…Epithelial-mesenchymal transition is a process in which epithelial cells are transformed into mesenchymal cells and acquire motile and invasive characteristics. 27,28 Recent studies have proven that USP3 promotes GBM progress by regulating the EMT process. 18,29 Therefore, in order to study the molecular mechanism of lncRNA HOXA-AS3 promoting GBM transfer, we detected the level of EMT-related biomarkers in GBM cells F I G U R E 6 MiR-455-5p rescued effect on the proliferation and invasion of lncRNA HOXA-AS3 overexpression glioblastoma multiforme (GBM) cells.…”
Glioblastoma multiforme (GBM) is a fast-growing type of aggressive and lethal primary brain tumour. 1,2 Because the pathologic mechanisms of GBM are not fully understood, more research is needed to identify effective predictive biomarkers and therapeutic targets for GBM. 2,3 Emerging studies, supported by whole-genome sequencing technology and microarray assays, have shown long non-coding RNAs (lncRNAs) to be key regulatory transcripts. 4 LncRNAs are classified
“…Epithelial-mesenchymal transition is a process in which epithelial cells are transformed into mesenchymal cells and acquire motile and invasive characteristics. 27,28 Recent studies have proven that USP3 promotes GBM progress by regulating the EMT process. 18,29 Therefore, in order to study the molecular mechanism of lncRNA HOXA-AS3 promoting GBM transfer, we detected the level of EMT-related biomarkers in GBM cells F I G U R E 6 MiR-455-5p rescued effect on the proliferation and invasion of lncRNA HOXA-AS3 overexpression glioblastoma multiforme (GBM) cells.…”
Glioblastoma multiforme (GBM) is a fast-growing type of aggressive and lethal primary brain tumour. 1,2 Because the pathologic mechanisms of GBM are not fully understood, more research is needed to identify effective predictive biomarkers and therapeutic targets for GBM. 2,3 Emerging studies, supported by whole-genome sequencing technology and microarray assays, have shown long non-coding RNAs (lncRNAs) to be key regulatory transcripts. 4 LncRNAs are classified
“…The EMT represented a biological process during which polarized epithelial cells lost cell identity and experienced various biochemical alterations that allowed it to assume mesenchymal phenotypes [26]. Normally observed during embryonic development, EMT could also be involved in various pathological conditions.…”
Section: In Uence Of Selected Genes On Epithelial-mesenchymal Transitmentioning
confidence: 99%
“…Normally observed during embryonic development, EMT could also be involved in various pathological conditions. Once hijacked by cancer cells, EMT often led to enhanced migration capability, acquisition of resistance to apoptosis, and increased cell proliferation [26][27][28][29]. Thus, we examined the role of selected genes in EMT signaling pathway in breast cancer cells.…”
Section: In Uence Of Selected Genes On Epithelial-mesenchymal Transitmentioning
Background
Recent years, attributed to early detection and new therapies, the mortality rates of breast cancer (BC) decreased. Nevertheless, the global prevalence was still high and the underlying molecular mechanisms were remained largely unknown. The investigation of prognosis-related genes as the novel biomarkers for diagnosis and individual treatment had become an urgent demand for clinical practice.
Methods
Gene expression profiles and clinical information of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database and randomly divided into training (n = 514) and internal validation (n = 562) cohort by using a random number table. The differentially expressed genes (DEGs) were estimated by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In the training set, the gene signature was constructed by the least absolute shrinkage and selection operator (LASSO) method based on DEGs screened by R packages. The results were further tested in the internal validation cohort and the entire cohort. Moreover, functions of five genes were explored by MTT, Colony-Formation, scratch and transwell assays. Western blot analysis was used to explore the mechanisms.
Results
In the training cohort, a total of 2805 protein coding DEGs were acquired through comparing breast cancer tissues (n = 514) with normal tissues (n = 113). A risk score formula involving five novel prognostic associated biomarkers (EDN2, CLEC3B, SV2C, WT1 and MUC2) were then constructed by LASSO. The prognostic value of the risk model was further confirmed in the internal validation set and the entire set. To explore the biological functions of the selected genes, in vitro assays were performed, indicating that these novel biomarkers could markedly influence breast cancer progression.
Conclusion
We established a predictive five-gene signature, which could be helpful for prognosis assessment and personalized management in breast cancer patients.
“…Epithelial-to-mesenchymal transition (EMT) represents a biological program during which epithelial cells lose their identity and acquire a mesenchymal phenotype [ 15 ]. Thus, EMT has dual biological roles, playing a physiological role in sustaining organismal development, but under pathological conditions such as cancer, EMT is associated with increased invasion and migration rates that further promote high metastatic rates [ 15 , 16 ]. This process can be snatched by cancer cells, being frequently linked with resistance to apoptosis, acquisition of cancer stem cell characteristics, and drug resistance [ 16 ].…”
Section: Introductionmentioning
confidence: 99%
“…Thus, EMT has dual biological roles, playing a physiological role in sustaining organismal development, but under pathological conditions such as cancer, EMT is associated with increased invasion and migration rates that further promote high metastatic rates [ 15 , 16 ]. This process can be snatched by cancer cells, being frequently linked with resistance to apoptosis, acquisition of cancer stem cell characteristics, and drug resistance [ 16 ]. EMT programs/processes/mechanisms promote CSC stemness in many epithelial tissues; therefore, understanding these relationships may highlight different therapeutic vulnerabilities that can be further exploited in clinical practice [ 17 ].…”
Breast cancer is one of the most common oncological diseases in women, as its incidence is rapidly growing, rendering it unpredictable and causing more harm than ever before on an annual basis. Alterations of coding and noncoding genes are related to tumorigenesis and breast cancer progression. In this study, several key genes associated with epithelial-to-mesenchymal transition (EMT) and cancer stem cell (CSC) features were identified. EMT and CSCs are two key mechanisms responsible for self-renewal, differentiation, and self-protection, thus contributing to drug resistance. Therefore, understanding of the relationship between these processes may identify a therapeutic vulnerability that can be further exploited in clinical practice, and evaluate its correlation with overall survival rate. To determine expression levels of altered coding and noncoding genes, The Cancer Omics Atlas (TCOA) are used, and these data are overlapped with a list of CSCs and EMT-specific genes downloaded from NCBI. As a result, it is observed that CSCs are reciprocally related to EMT, thus identifying common signatures that allow for predicting the overall survival for breast cancer genes (BRCA). In fact, common CSCs and EMT signatures, represented by ALDH1A1, SFRP1, miR-139, miR-21, and miR-200c, are deemed useful as prognostic biomarkers for BRCA. Therefore, by mapping changes in gene expression across CSCs and EMT, suggesting a cross-talk between these two processes, we have been able to identify either the most common or specific genes or miRNA markers associated with overall survival rate. Thus, a better understanding of these mechanisms will lead to more effective treatment options.
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