Mechanism of epithelial‐mesenchymal transition in cancer and its regulation by natural compounds

Ang, Hui Li; Mohan, Chakrabhavi Dhananjaya; Shanmugam, Muthu K.; Leong, Hin Chong; Makvandi, Pooyan; Rangappa, Kanchugarakoppal S.; Bishayee, Anupam; Kumar, Alan Prem; Sethi, Gautam

doi:10.1002/med.21948

Cited by 66 publications

(26 citation statements)

References 460 publications

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“…Various factors, including deregulated oncogenic signaling pathways, hypoxia, and cells present in the tumor microenvironment, can initiate and promote EMT. As a result, EMT leads to the loss of epithelial cell polarity and cell-cell adhesion, while promoting enhanced invasive and migratory properties (27). We can speculate that the increased EMT activity in the high-risk group promotes the progression of OC, thus making the prognosis of high-risk patients worse.…”

Section: Discussionmentioning

confidence: 99%

Regulatory T cell-associated signature: predicting prognosis and immunotherapy in ovarian cancer

Liu

Sun

et al. 2023

Preprint

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Background Immunosuppression is a key feature of cancer, promoting tumor growth and progression. Regulatory T cells (Tregs) are a specialized subset of T lymphocytes that mediate immunosuppression in cancer. However, the role of Treg-related genes in ovarian cancer (OC) remains largely unexplored.Methods To identify marker genes related to Tregs in OC, we utilized scRNA-seq analysis. Treg scores were then constructed using single-sample gene set enrichment analysis (ssGSEA) based on these markers. To identify gene modules with the strongest correlation with Treg scores in bulk RNA-seq data, we employed the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm. Multiple machine learning algorithms were then used to construct risk models with superior predictive performance, which were validated using external independent datasets. A risk score was developed for each OC sample based on the optimal model to evaluate differences in prognosis, immune infiltration, pathway activity, and immunotherapy between high and low-risk groups.Results We identified 365 genes regulating Treg activity using the WGCNA algorithm, and found that 70 of these genes were associated with the prognosis of OC based on univariate cox analysis. Using a combination of the Random Survival Forest (RSF) and Lasso algorithms, we constructed a risk model with the highest c-index based on the assigned risk scores. The model's performance was validated using four external datasets. Our analysis revealed that the low-risk group had a better prognosis, more immune cell infiltration, higher immune checkpoint expression, and significant differences in pathway enrichment and immunotherapy efficacy between the different risk groups.Conclusion Our findings provide new insights into the role of Treg cells in the development and progression of OC and highlight the potential for developing novel Treg-targeted therapies for the treatment of this disease.

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Section: Discussionmentioning

confidence: 99%

Regulatory T cell-associated signature: predicting prognosis and immunotherapy in ovarian cancer

Liu

Sun

et al. 2023

Preprint

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“…Various factors, including deregulated oncogenic signaling pathways, hypoxia, and cells present in TME, can initiate and promote EMT. As a result, EMT leads to the loss of epithelial cell polarity and cell-cell adhesion, while promoting enhanced invasive and migratory properties (30). We can speculate that the increased EMT activity in the high-risk group promotes the progression of OC, thus making the prognosis of high-risk patients worse.…”

Section: Discussionmentioning

confidence: 99%

Prognostic and Immunotherapeutic Potential of Regulatory T Cell- Associated Signature in Ovarian Cancer

Liu,

Shan,

Sun

et al. 2023

Preprint

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Background: Immunosuppression is a key feature of cancer, promoting tumor growth and progression. Regulatory T cells (Tregs) are a specialized subset of T lymphocytes that mediate immunosuppression in cancer. However, the role of Treg-related genes in ovarian cancer (OC) remains largely unexplored. Methods: To identify marker genes related to Tregs in OC, we utilized scRNA-seq analysis. Treg scores were then constructed using single-sample gene set enrichment analysis (ssGSEA) based on these markers. To identify gene modules with the strongest correlation with Treg scores in bulk RNA-seq data, we employed the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm. Multiple machine learning algorithms were then used to construct risk models with superior predictive performance, which were validated using external independent datasets. A risk score was developed for each OC sample based on the optimal model to evaluate differences in prognosis, immune infiltration, pathway activity, and immunotherapy between high and low-risk groups. Results: We identified 365 genes governing Treg functionality utilizing the WGCNA algorithm, and determined that 70 of these genes were linked to the prognosis of OC based on univariate Cox analysis. By employing a fusion of the Random Survival Forest (RSF) and Lasso algorithms, we developed a risk model showcasing the most elevated c-index derived from the allocated risk scores. The model's efficacy was substantiated through the utilization of four external datasets. Our analysis unveiled that the low-risk cohort exhibited a more favorable prognosis, augmented infiltration of immune cells, elevated expression of immune checkpoints, as well as noteworthy disparities in pathway enrichment and immunotherapy efficacy among the distinct risk groups. Conclusion: Our findings provide new insights into the role of Treg cells in the development and progression of OC and highlight the potential for developing novel Treg-targeted therapies for the treatment of this disease.

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“… 339 , 340 Over the years, it has been observed that EMT is reactivated during tumor progression, emerging as a pivotal mechanism for cancer cells to acquire malignant properties. 341 , 342 Various signaling pathways participate in the regulation of EMT, including the Notch signaling pathway (Fig. 3 ).…”

Section: The Mechanism Of Notch Signaling Patyway-mediated Tumorigene...mentioning

confidence: 99%

Notch signaling pathway in cancer: from mechanistic insights to targeted therapies

Shi,

Xue,

Zeng

et al. 2024

Sig Transduct Target Ther

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Notch signaling, renowned for its role in regulating cell fate, organ development, and tissue homeostasis across metazoans, is highly conserved throughout evolution. The Notch receptor and its ligands are transmembrane proteins containing epidermal growth factor-like repeat sequences, typically necessitating receptor-ligand interaction to initiate classical Notch signaling transduction. Accumulating evidence indicates that the Notch signaling pathway serves as both an oncogenic factor and a tumor suppressor in various cancer types. Dysregulation of this pathway promotes epithelial-mesenchymal transition and angiogenesis in malignancies, closely linked to cancer proliferation, invasion, and metastasis. Furthermore, the Notch signaling pathway contributes to maintaining stem-like properties in cancer cells, thereby enhancing cancer invasiveness. The regulatory role of the Notch signaling pathway in cancer metabolic reprogramming and the tumor microenvironment suggests its pivotal involvement in balancing oncogenic and tumor suppressive effects. Moreover, the Notch signaling pathway is implicated in conferring chemoresistance to tumor cells. Therefore, a comprehensive understanding of these biological processes is crucial for developing innovative therapeutic strategies targeting Notch signaling. This review focuses on the research progress of the Notch signaling pathway in cancers, providing in-depth insights into the potential mechanisms of Notch signaling regulation in the occurrence and progression of cancer. Additionally, the review summarizes pharmaceutical clinical trials targeting Notch signaling for cancer therapy, aiming to offer new insights into therapeutic strategies for human malignancies.

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Mechanism of epithelial‐mesenchymal transition in cancer and its regulation by natural compounds

Cited by 66 publications

References 460 publications

Regulatory T cell-associated signature: predicting prognosis and immunotherapy in ovarian cancer

Regulatory T cell-associated signature: predicting prognosis and immunotherapy in ovarian cancer

Prognostic and Immunotherapeutic Potential of Regulatory T Cell- Associated Signature in Ovarian Cancer

Notch signaling pathway in cancer: from mechanistic insights to targeted therapies

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