Dorsomorphin reverses the mesenchymal phenotype of breast cancer initiating cells by inhibition of bone morphogenetic protein signaling

Garulli, Chiara; Kalogris, Cristina; Pietrella, Lucia; Bartolacci, Caterina; Andreani, Cristina; Falconi, Maurizio; Marchini, Cristina; Amici, Augusto

doi:10.1016/j.cellsig.2013.11.022

Cited by 32 publications

(18 citation statements)

References 35 publications

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“…We interrogated CMap utilizing the gene expression signatures from SHH MB samples with high and low mRNAsi levels. The CMap analysis precisely identified some compounds that have been shown to specifically impact CSCs in other tumor types (Angeletti et al, 2016;Batsaikhan et al, 2014;Battula et al, 2017;Bonuccelli et al, 2017;Bozok Cetintas et al, 2016;Chen et al, 2015Chen et al, , 2016Cheng et al, 2017;Dominguez-Gomez et al, 2018;Garulli et al, 2014;Hong et al, 2011;Hou et al, 2018;Malkomes et al, 2016;Xiang et al, 2017;Xu et al, 2016;Yeh et al, 2013;Yin et al, 2018;You et al, 2009;Zhang et al, 2013;Zheng et al, 2013a,b). These compounds include the CDK inhibitors palbociclib and alvocidib, the AMPK inhibitor dorsomorphin, the IKK inhibitor BMS-345541, the smoothened receptor antagonist cyclopamine, the topoisomerase inhibitors topotecan and doxorubicin, the GABA receptor agonist ivermectin, the NF-jB pathway inhibitor auranofin, the MTOR inhibitor dactolisib, the AKT inhibitors MK-2206 and pyrvinium-pamoate, the HMGCR inhibitor simvastatin, the HDAC inhibitors apicidin, vorinostat, and givinostat, and the DNA synthesis inhibitor anisomycin.…”

Section: Correlation Of the Immune Cells With Mdnasimentioning

confidence: 99%

Integrative analysis of gene expression and DNA methylation through one‐class logistic regression machine learning identifies stemness features in medulloblastoma

et al. 2019

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Most human cancers develop from stem and progenitor cell populations through the sequential accumulation of various genetic and epigenetic alterations. Cancer stem cells have been identified from medulloblastoma (MB), but a comprehensive understanding of MB stemness, including the interactions between the tumor immune microenvironment and MB stemness, is lacking. Here, we employed a trained stemness index model based on an existent one‐class logistic regression (OCLR) machine‐learning method to score MB samples; we then obtained two stemness indices, a gene expression‐based stemness index (mRNAsi) and a DNA methylation‐based stemness index (mDNAsi), to perform an integrated analysis of MB stemness in a cohort of primary cancer samples (n = 763). We observed an inverse trend between mRNAsi and mDNAsi for MB subgroup and metastatic status. By applying the univariable Cox regression analysis, we found that mRNAsi significantly correlated with overall survival (OS) for all MB patients, whereas mDNAsi had no significant association with OS for all MB patients. In addition, by combining the Lasso‐penalized Cox regression machine‐learning approach with univariate and multivariate Cox regression analyses, we identified a stemness‐related gene expression signature that accurately predicted survival in patients with Sonic hedgehog (SHH) MB. Furthermore, positive correlations between mRNAsi and prognostic copy number aberrations in SHH MB, including MYCN amplifications and GLI2 amplifications, were detected. Analyses of the immune microenvironment revealed unanticipated correlations of MB stemness with infiltrating immune cells. Lastly, using the Connectivity Map, we identified potential drugs targeting the MB stemness signature. Our findings based on stemness indices might advance the development of objective diagnostic tools for quantitating MB stemness and lead to novel biomarkers that predict the survival of patients with MB or the efficacy of strategies targeting MB stem cells.

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Section: Correlation Of the Immune Cells With Mdnasimentioning

confidence: 99%

Integrative analysis of gene expression and DNA methylation through one‐class logistic regression machine learning identifies stemness features in medulloblastoma

et al. 2019

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“…Inhibiting the BMP pathway with Dorsomorphin causes mesenchymal stem cells to acquire epithelial-like traits, including the expression of cytokeratin-18 and E-cadherin. The progress occurs through the downregulation of Snail, Slug and COX2 to affect cell motility, invasiveness and tumor growth in vitro (69). Moreover, in CRC initiation, BMP signaling maintains the balanced control of stem cell self-renewal by inhibiting the Wnt pathway.…”

Section: Pathways Involved In the Self-renewal Of Ccscsmentioning

confidence: 99%

Self-renewal molecular mechanisms of colorectal cancer stem cells

Zhu

2016

International Journal of Molecular Medicine

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Colorectal cancer stem cells (CCSCs) represent a small fraction of the colorectal cancer cell population that possess self-renewal and multi-lineage differentiation potential and drive tumorigenicity. Self-renewal is essential for the malignant biological behaviors of colorectal cancer stem cells. While the self-renewal molecular mechanisms of colorectal cancer stem cells are not yet fully understood, the aberrant activation of signaling pathways, such as Wnt, Notch, transforming growth factor-β (TGF-β)/bone morphogenetic protein (BMP) and Hedgehog-Gli (HH-GLI), specific roles mediated by cell surface markers and micro-environmental factors are involved in the regulation of self-renewal. The elucidation of the molecular mechanisms behind self-renewal may lead to the development of novel targeted interventions for the treatment of colorectal cancer.

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“…In A17 breast cancer cells, DM reduced cell proliferation and reduced expression of EMT markers Vimentin, Snail and Slug [152]. In mammary epithelial cell lines and primary murine tumour cells, LDN-193189 inhibited clonogenicity and cell migration [153].…”

Section: The Use Of Small Molecule Bmp Inhibitors In Preclinical Modementioning

confidence: 99%

Emerging roles of the bone morphogenetic protein pathway in cancer: potential therapeutic target for kinase inhibition

Jiramongkolchai

Owens

Hong

2016

Biochemical Society Transactions

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Bone morphogenetic proteins (BMPs) belong to the transforming growth factor-β (TGF-β) family signalling pathway. Similar to TGF-β, the complex roles of BMPs in development and disease are demonstrated by their dichotomous roles in various cancers and cancer stages. Although early studies implicated BMP signalling in tumour suppressive phenotypes, the results of more recent experiments recognize BMPs as potent tumour promoters. Many of these complexities are becoming illuminated by understanding the role of BMPs in their contextual role in unique cell types of cancer and the impact of their surrounding tumour microenvironment. Here we review the emerging roles of BMP signalling in cancer, with a focus on the molecular underpinnings of BMP signalling in individual cancers as a valid therapeutic target for cancer prevention and treatment.

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Dorsomorphin reverses the mesenchymal phenotype of breast cancer initiating cells by inhibition of bone morphogenetic protein signaling

Cited by 32 publications

References 35 publications

Integrative analysis of gene expression and DNA methylation through one‐class logistic regression machine learning identifies stemness features in medulloblastoma

Integrative analysis of gene expression and DNA methylation through one‐class logistic regression machine learning identifies stemness features in medulloblastoma

Self-renewal molecular mechanisms of colorectal cancer stem cells

Emerging roles of the bone morphogenetic protein pathway in cancer: potential therapeutic target for kinase inhibition

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