Establishment and Analysis of an Individualized EMT-Related Gene Signature for the Prognosis of Breast Cancer in Female Patients

Xue, Wei; Sun, Chenyu; Yuan, Hui; Yang, Xin; Zhang, Qiuping; Liao, Yunnuo; Guo, Hongwei

doi:10.1155/2022/1289445

Cited by 7 publications

(3 citation statements)

References 42 publications

(53 reference statements)

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“…It is known that EMT is a cellular process which has been associated with a variety of tumor functions, including tumor initiation, tumor stemness, tumor cell migration, and drug resistance [ 17 ]. TNBC is one of the most studied malignant tumors, and a growing body of research has revealed that it is closely associated with EMT.…”

Section: Discussionmentioning

confidence: 99%

An EMT-Related Gene Signature to Predict the Prognosis of Triple-Negative Breast Cancer

et al. 2023

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Introduction Epithelial–mesenchymal transition (EMT) is an important biological process in tumor invasion and metastasis, and thus a potential indicator of the progression and drug resistance of breast cancer. This study comprehensively analyzed EMT-related genes in triple-negative breast cancer (TNBC) to develop an EMT-related prognostic gene signature. Methods With the application of The Cancer Genome Atlas (TCGA) database, Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), and the Genotype-Tissue Expression (GTEx) database, we identified EMT-related signature genes (EMGs) by Cox univariate regression and LASSO regression analysis. Risk scores were calculated and used to divide patients with TNBC into high-risk group and low-risk groups by the median value. Kaplan–Meier (K–M) and receiver operating characteristic (ROC) curve analyses were applied for model validation. Independent prognostic predictors were used to develop nomograms. Then, we assessed the risk model in terms of the immune microenvironment, genetic alteration and DNA methylation effects on prognosis, the probability of response to immunotherapy and chemotherapy, and small molecule drugs predicted by The Connectivity Map (Cmap) database. Results Thirteen EMT-related genes with independent prognostic value were identified and used to stratify the patients with TNBC into high- and low-risk groups. The survival analysis revealed that patients in the high-risk group had significantly poorer overall survival than patients in the low-risk group. Populations of immune cells, including CD4 memory resting T cells, CD4 memory activated T cells, and activated dendritic cells, significantly differed between the high- and low-risk groups. Moreover, some therapeutic drugs to which the high-risk group might show sensitivity were identified. Conclusions Our research identified the significant impact of EMGs on prognosis in TNBC, providing new strategies for personalizing TNBC treatment and improving clinical outcomes. Supplementary Information The online version contains supplementary material available at 10.1007/s12325-023-02577-z.

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Section: Discussionmentioning

confidence: 99%

An EMT-Related Gene Signature to Predict the Prognosis of Triple-Negative Breast Cancer

et al. 2023

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“…Based on univariate Cox analysis, we identified survival-associated genes from the most important module and established a risk signature consisting of six genes (LRP8, RNASE2, CLIP4, HAS2, SLC22A11, and KCTD12) using LASSO-Cox regression with the glmnet R package (version 4.1–8) and survival R package (version 3.5–7). After constructing the risk score, we employed Cox regression models, including univariate and multivariate Cox proportional hazards regression models, to investigate the effect of various factors, including the risk score, on survival time ( Xue et al, 2022 ). The TCGA samples were divided into a training set and a test set to validate our model, and with reference to the median score, we classified the KIRC patients into a low-risk group and a high-risk group.…”

Section: Methodsmentioning

confidence: 99%

Development of a prognostic model based on different disulfidptosis related genes typing for kidney renal clear cell carcinoma

Feng,

Wang,

Jiang

et al. 2024

Front. Pharmacol.

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Background: Kidney renal clear cell carcinoma (KIRC) is a common and clinically significant subtype of kidney cancer. A potential therapeutic target in KIRC is disulfidptosis, a novel mode of cell death induced by disulfide stress. The aim of this study was to develop a prognostic model to explore the clinical significance of different disulfidptosis gene typings from KIRC.Methods: A comprehensive analysis of the chromosomal localization, expression patterns, mutational landscape, copy number variations, and prognostic significance of 10 disulfide death genes was conducted. Patients were categorized into distinct subtypes using the Non-negative Matrix Factorization (NMF) typing method based on disulfidptosis gene expression patterns. Weighted Gene Co-expression Network Analysis (WGCNA) was used on the KIRC dataset to identify differentially expressed genes between subtype clusters. A risk signature was created using LASSO-Cox regression and validated by survival analysis. An interaction between risk score and immune cell infiltration, tumor microenvironment characteristics and pathway enrichment analysis were investigated.Results: Initial findings highlight the differential expression of specific DRGs in KIRC, with genomic instability and somatic mutation analysis revealing key insights into their role in cancer progression. NMF clustering differentiates KIRC patients into subgroups with distinct survival outcomes and immune profiles, and hierarchical clustering identifies gene modules associated with key biological and clinical parameters, leading to the development of a risk stratification model (LRP8, RNASE2, CLIP4, HAS2, SLC22A11, and KCTD12) validated by survival analysis and predictive of immune infiltration and drug sensitivity. Pathway enrichment analysis further delineates the differential molecular pathways between high-risk and low-risk patients, offering potential targets for personalized treatment. Lastly, differential expression analysis of model genes between normal and KIRC cells provides insights into the molecular mechanisms underlying KIRC, highlighting potential biomarkers and therapeutic targets.Conclusion: This study contributes to the understanding of KIRC and provides a potential prognostic model using disulfidptosis gene for personalized management in KIRC patients. The risk signature shows clinical applicability and sheds light on the biological mechanisms associated with disulfide-induced cell death.

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“…Nowadays, the mechanisms involved in EMT are increasingly being studied. Several studies highlight new insights into EMT/MET processes, especially relate genetic signature [ 18 ], epigenetic alterations implication [ 19 , 20 ], structural alterations of the extracellular matrix (ECM) [ 20 ] as well as the interplay between immune system [ 21 , 22 ] and metabolic reprogramming (MR) [ 22 , 23 ], and how these factors affect the tumor growth and progression to metastasis of TNBC.…”

Section: Introductionmentioning

confidence: 99%

MCL1 Inhibition Overcomes the Aggressiveness Features of Triple-Negative Breast Cancer MDA-MB-231 Cells

Pratelli

Carlisi

Liberto

et al. 2023

IJMS

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Triple-Negative Breast Cancer (TNBC) is a particularly aggressive subtype among breast cancers (BCs), characterized by anoikis resistance, high invasiveness, and metastatic potential as well as Epithelial–Mesenchymal Transition (EMT) and stemness features. In the last few years, our research focused on the function of MCL1, an antiapoptotic protein frequently deregulated in TNBC. Here, we demonstrate that MCL1 inhibition by A-1210477, a specific BH3-mimetic, promotes anoikis/apoptosis in the MDA-MB-231 cell line, as shown via an increase in proapoptotic markers and caspase activation. Our evidence also shows A-1210477 effects on Focal Adhesions (FAs) impairing the integrin trim and survival signaling pathways, such as FAK, AKT, ERK, NF-κB, and GSK3β-inducing anoikis, thus suggesting a putative role of MCL1 in regulation of FA dynamics. Interestingly, in accordance with these results, we observed a reduction in migratory and invasiveness capabilities as confirmed by a decrease in metalloproteinases (MMPs) levels following A-1210477 treatment. Moreover, MCL1 inhibition promotes a reduction in EMT characteristics as demonstrated by the downregulation of Vimentin, MUC1, DNMT1, and a surprising re-expression of E-Cadherin, suggesting a possible mesenchymal-like phenotype reversion. In addition, we also observed the downregulation of stemness makers such as OCT3/4, SOX2, NANOG, as well as CD133, EpCAM, and CD49f. Our findings support the idea that MCL1 inhibition in MDA-MB-231 could be crucial to reduce anoikis resistance, aggressiveness, and metastatic potential and to minimize EMT and stemness features that distinguish TNBC.

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Establishment and Analysis of an Individualized EMT-Related Gene Signature for the Prognosis of Breast Cancer in Female Patients

Cited by 7 publications

References 42 publications

An EMT-Related Gene Signature to Predict the Prognosis of Triple-Negative Breast Cancer

An EMT-Related Gene Signature to Predict the Prognosis of Triple-Negative Breast Cancer

Development of a prognostic model based on different disulfidptosis related genes typing for kidney renal clear cell carcinoma

MCL1 Inhibition Overcomes the Aggressiveness Features of Triple-Negative Breast Cancer MDA-MB-231 Cells

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