BMP-gated cell-cycle progression drives anoikis during mesenchymal collective migration

Macabenta, Frank; Sun, Hsuan-Te; Stathopoulos, Angelike

doi:10.1016/j.devcel.2022.05.017

Cited by 7 publications

(11 citation statements)

References 72 publications

(92 reference statements)

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“…For instance, Zhou et al [ 42 ] revealed that AEG-1-dependent anoikis resistance is triggered through the PI3K/Akt pathway, which can be reversed by the PI3K inhibitor LY294002. Furthermore, Macabenta et al [ 43 ] demonstrated that during collective mesenchymal migration, BMP-gated cell cycle processes drive anoikis. These studies have shed light on the pivotal roles of signaling pathways such as focal adhesion, cell cycle, and PI3K/Akt pathways in the process of anoikis, suggesting that ARGs may regulate the development of LUAD through these pathways.…”

Section: Discussionmentioning

confidence: 99%

An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma

Jiang,

Gao,

et al. 2023

Heliyon

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Section: Discussionmentioning

confidence: 99%

An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma

Jiang,

Gao,

et al. 2023

Heliyon

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“…Ten hub Args that played important roles in the mechanism of anoikis in NB were obtained. Anoikis is actually a kind of responses of cells to their loss of contact by different signal pathways, and cell cycle regulation is also an important way for cells to generate anoikis or AR ( 47 , 48 ). Previous studies have mentioned that BIRC5 , BUB1 , CDKN3 , CENPF , PLK1 , CHEK2 , Ntrk1 , E2F1 and UBE2C are closely related to cell cycle.…”

Section: Discussionmentioning

confidence: 99%

Construction of a novel anoikis-related prognostic model and analysis of its correlation with infiltration of immune cells in neuroblastoma

et al. 2023

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BackgroundAnoikis resistance (AR) plays an important role in the process of metastasis, which is an important factor affecting the risk stage of neuroblastoma (NB). This study aims to construct an anoikis-related prognostic model and analyze the characteristics of hub genes, important pathways and tumor microenvironment of anoikis-related subtypes of NB, so as to provide help for the clinical diagnosis, treatment and research of NB.MethodsWe combined transcriptome data of GSE49710 and E-MTAB-8248, screened anoikis-related genes (Args) closely related to the prognosis of NB by univariate cox regression analysis, and divided the samples into anoikis-related subtypes by consistent cluster analysis. WGCNA was used to screen hub genes, GSVA and GSEA were used to analyze the differentially enriched pathways between anoikis-related subtypes. We analyzed the infiltration levels of immune cells between different groups by SsGSEA and CIBERSORT. Lasso and multivariate regression analyses were used to construct a prognostic model. Finally, we analyzed drug sensitivity through the GDSC database.Results721 cases and 283 Args were included in this study. All samples were grouped into two subtypes with different prognoses. The analyses of WGCNA, GSVA and GSEA suggested the existence of differentially expressed hub genes and important pathways in the two subtypes. We further constructed an anoikis-related prognostic model, in which 15 Args participated. This model had more advantages in evaluating the prognoses of NB than other commonly used clinical indicators. The infiltration levels of 9 immune cells were significantly different between different risk groups, and 13 Args involved in the model construction were correlated with the infiltration levels of immune cells. There was a relationship between the infiltration levels of 6 immune cells and riskscores. Finally, we screened 15 drugs with more obvious effects on NB in high-risk group.ConclusionThere are two anoikis-related subtypes with different prognoses in the population of NB. The anoikis-related prognostic model constructed in this study can accurately predict the prognoses of children with NB, and has a good guiding significance for clinical diagnosis, treatment and research of NB.

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“…In this study, a predictive signature consisting of eight ARGs [EGF ( 36 ), MYC ( 37 ), PLK1 ( 38 ), EZH2 ( 39 ), AFP ( 40 ), NOX4 ( 41 ), BMP6 ( 42 ), MMP11 ( 43 )] was established and its correlation with anoikis was verified by a literature search. EGF is not only involved in regulating the physiological function of the prostate, but also induces PCa cell proliferation and invasion ( 44 ).The polymorphism of EGF may lead to early recurrence in PCa patients treated with androgen blockade, which is expected to become a potential therapeutic target for castration-resistant PCa ( 45 ).…”

Section: Discussionmentioning

confidence: 99%

An anoikis-related gene signature for prediction of the prognosis in prostate cancer

Zhao,

Wang,

Tang

et al. 2023

Front. Oncol.

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PurposeThis study presents a novel approach to predict postoperative biochemical recurrence (BCR) in prostate cancer (PCa) patients which involves constructing a signature based on anoikis-related genes (ARGs).MethodsIn this study, we utilised data from TCGA-PARD and GEO databases to identify specific ARGs in prostate cancer. We established a signature of these ARGs using Cox regression analysis and evaluated their clinical predictive efficacy and immune-related status through various methods such as Kaplan-Meier survival analysis, subject work characteristics analysis, and CIBERSORT method. Our findings suggest that these ARGs may have potential as biomarkers for prostate cancer prognosis and treatment. To investigate the biological pathways of genes associated with anoikis, we utilised GSVA, GO, and KEGG. The expression of ARGs was confirmed by the HPA database. Furthermore, we conducted PPI analysis to identify the core network of ARGs in PCa.ResultsBased on analysis of the TCGA database, a set of eight ARGs were identified as prognostic signature genes for prostate cancer. The reliability and validity of this signature were well verified in both the TCGA and GEO codifications. Using this signature, patients were classified into two groups based on their risk for developing BCR. There was a significant difference in BCR-free time between the high and low risk groups (P < 0.05).This signature serves as a dependable and unbiased prognostic factor for predicting biochemical recurrence (BCR) in prostate cancer (PCa) patients. It outperforms clinicopathological characteristics in terms of accuracy and reliability. PLK1 may play a potential regulatory role as a core gene in the development of prostate cancer.ConclusionThis signature suggests the potential role of ARGs in the development and progression of PCa and can effectively predict the risk of BCR in PCa patients after surgery. It also provides a basis for further research into the mechanism of ARGs in PCa and for the clinical management of patients with PCa.

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BMP-gated cell-cycle progression drives anoikis during mesenchymal collective migration

Cited by 7 publications

References 72 publications

An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma

An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma

Construction of a novel anoikis-related prognostic model and analysis of its correlation with infiltration of immune cells in neuroblastoma

An anoikis-related gene signature for prediction of the prognosis in prostate cancer

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