The Endosomal Protein CEMIP Links WNT Signaling to MEK1–ERK1/2 Activation in Selumetinib-Resistant Intestinal Organoids

Duong, Hong Quan; Nemazanyy, Ivan; Rambow, Florian; Tang, Seng Chuan; Delaunay, Sylvain; Tharun, Lars; Florin, Alexandra; Büttner, Reinhard; Vandaele, Daniel; Close, Pierre; Marine, Jean–Christophe; Shostak, Kateryna; Chariot, Alain

doi:10.1158/0008-5472.can-17-3149

Cited by 34 publications

(32 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To identify potential therapeutic targets derived from CAFs, we selected genes with frequent decrease (in ≥5 pairs) and also with gene products likely to be localised in plasma membrane or extracellular space. There were 34 such genes, and included a WNT ligand, WNT5A ,16 32 and its regulator, CEMIP ,33 stem cell niche factors, such as NOG ,34 GREM1 35 and EDIL3 ,36 and growth factors, such as IGF2 37 (online supplementary figure S4A). This result supported the promoting effect of CAF-derived CM on cell growth and migration and the idea of isolating targets for cancer-starving therapy based on H3K27me3 changes.…”

Section: Resultsmentioning

confidence: 99%

“…Recent studies defined essential factors for maintenance of gastric epithelial stem cells, WNT signal activators, EGF, FGF10, BMP inhibitors, and TGF-β inhibitors 39–41. Many of them were among the genes with decreased H3K27me3 in CAFs, such as WNT signal activator ( WNT5A and CEMIP 33), and BMP inhibitors (Noggin, NOG 34 and GREM1 42). Potential therapeutic targets included a well-known growth factor IGF2 ,37 and an angiogenesis mediator, EDIL3 36.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Cancer cell niche factors secreted from cancer-associated fibroblast by loss of H3K27me3

Maeda

Takeshima²,

Iida³

et al. 2019

Gut

View full text Add to dashboard Cite

ObjectiveCancer-associated fibroblasts (CAFs), a major component of cancer stroma, can confer aggressive properties to cancer cells by secreting multiple factors. Their phenotypes are stably maintained, but the mechanisms are not fully understood. We aimed to show the critical role of epigenetic changes in CAFs in maintaining their tumour-promoting capacity and to show the validity of the epigenomic approach in identifying therapeutic targets from CAFs to starve cancer cells.DesignTwelve pairs of primary gastric CAFs and their corresponding non-CAFs (NCAFs) were established from surgical specimens. Genome-wide DNA methylation and H3K27me3 analyses were conducted by BeadArray 450K and ChIP-on-Chip, respectively. Functions of potential a therapeutic target were analysed by inhibiting it, and prognostic impact was assessed in a database.ResultsCAFs had diverse and distinct DNA methylation and H3K27me3 patterns compared with NCAFs. Loss of H3K27me3, but not DNA methylation, in CAFs was enriched for genes involved in stem cell niche, cell growth, tissue development and stromal–epithelial interactions, such as WNT5A, GREM1, NOG and IGF2. Among these, we revealed that WNT5A, which had been considered to be derived from cancer cells, was highly expressed in cancer stromal fibroblasts, and was associated with poor prognosis. Inhibition of secreted WNT5A from CAFs suppressed cancer cell growth and migration.ConclusionsH3K27me3 plays a crucial role in defining tumour-promoting capacities of CAFs, and multiple stem cell niche factors were secreted from CAFs due to loss of H3K27me3. The validity of the epigenetic approach to uncover therapeutic targets for cancer-starving therapy was demonstrated.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Cancer cell niche factors secreted from cancer-associated fibroblast by loss of H3K27me3

Maeda

Takeshima²,

Iida³

et al. 2019

Gut

View full text Add to dashboard Cite

show abstract

“…IL27RA might participate in immune regulation in CNS (Iwasaki et al, 2015;Yoshida and Hunter, 2015). CEMIP may be related to brain function and development (Yoshino et al, 2017(Yoshino et al, , 2018, MEK/ERK-induced Schwann-cell dedifferentiation (Boerboom et al, 2017), immune response in glioblastoma (Motaln et al, 2012), and WNT signaling (Li et al, 2017;Duong et al, 2018;Liang et al, 2018). It was frequently reported in colorectal cancers as well (Fink et al, 2015;Zhang et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Construction and Validation of a 13-Gene Signature for Prognosis Prediction in Medulloblastoma

et al. 2020

View full text Add to dashboard Cite

Background: Recent studies have identified several molecular subgroups of medulloblastoma associated with distinct clinical outcomes; however, no robust gene signature has been established for prognosis prediction. Our objective was to construct a robust gene signature-based model to predict the prognosis of patients with medulloblastoma. Methods: Expression data of medulloblastomas were acquired from the Gene Expression Omnibus (GSE85217, n = 763; GSE37418, n = 76). To identify genes associated with overall survival (OS), we performed univariate survival analysis and least absolute shrinkage and selection operator (LASSO) Cox regression. A risk score model was constructed based on selected genes and was validated using multiple datasets. Differentially expressed genes (DEGs) between the risk groups were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and protein-protein interaction (PPI) analyses were performed. Network modules and hub genes were identified using Cytoscape. Furthermore, tumor microenvironment (TME) was evaluated using ESTIMATE algorithm. Tumor-infiltrating immune cells (TIICs) were inferred using CIBERSORTx. Results: A 13-gene model was constructed and validated. Patients classified as high-risk group had significantly worse OS than those as low-risk group (Training set: p < 0.0001; Validation set 1: p < 0.0001; Validation set 2: p = 0.00052). The area under the curve (AUC) of the receiver operating characteristic (ROC) analysis indicated a good performance in predicting 1-, 3-, and 5-year OS in all datasets. Multivariate analysis integrating clinical factors demonstrated that the risk score was an independent predictor for the OS (validation set 1: p = 0.001, validation set 2: p = 0.004). We then identified 265 DEGs between risk groups and PPI analysis predicted modules that were highly related to central nervous system and embryonic development. The risk score was significantly correlated with programmed deathligand 1 (PD-L1) expression (p < 0.001), as well as immune score (p = 0.035), stromal score (p = 0.010), and tumor purity (p = 0.010) in Group 4 medulloblastomas. Correlations between the 13-gene signature and the TIICs in Sonic hedgehog and Group 4 medulloblastomas were revealed.

show abstract

“…Numerous studies have demonstrated that organoid can serve as an excellent model for evaluating specific responses of cancer patients [ 26 , 69 , 81 , 95 , 96 ]. Besides, it also can be an extraordinary alternative to explore the detailed causal epigenetic and genetic alterations underlying drug resistance [ 97 ]. Several organoid biobanks of cancers so far have been established for the purposes of identifying and testing novel drugs [ 37 , 38 , 98 ], and healthy organoids can be utilized to test toxicology.…”

Section: Organoids In Drug Developmentmentioning

confidence: 99%

Organoid technology and applications in cancer research

et al. 2018

View full text Add to dashboard Cite

During the past decade, the three-dimensional organoid technology has sprung up and become more and more popular among researchers. Organoids are the miniatures of in vivo tissues and organs, and faithfully recapitulate the architectures and distinctive functions of a specific organ.These amazing three-dimensional constructs represent a promising, near-physiological model for human cancers, and tremendously support diverse potential applications in cancer research. Up to now, highly efficient establishment of organoids can be achieved from both normal and malignant tissues of patients. Using this bioengineered platform, the links of infection-cancer progression and mutation-carcinogenesis are feasible to be modeled. Another potential application is that organoid technology facilitates drug testing and guides personalized therapy. Although organoids still fail to model immune system accurately, co-cultures of organoids and lymphocytes have been reported in several studies, bringing hope for further application of this technology in immunotherapy. In addition, the potential value in regeneration medicine might be another paramount branch of organoid technology, which might refine current transplantation therapy through the replacement of irreversibly progressively diseased organs with isogenic healthy organoids.In conclusion, organoids represent an excellent preclinical model for human tumors, promoting the translation from basic cancer research to clinical practice. In this review, we outline organoid technology and summarize its applications in cancer research.

show abstract

The Endosomal Protein CEMIP Links WNT Signaling to MEK1–ERK1/2 Activation in Selumetinib-Resistant Intestinal Organoids

Cited by 34 publications

References 48 publications

Cancer cell niche factors secreted from cancer-associated fibroblast by loss of H3K27me3

Cancer cell niche factors secreted from cancer-associated fibroblast by loss of H3K27me3

Construction and Validation of a 13-Gene Signature for Prognosis Prediction in Medulloblastoma

Organoid technology and applications in cancer research

Contact Info

Product

Resources

About