Insights into the cholecystokinin 2 receptor binding site and processes of activation.

International audienceThe cholecystokinin (CCK) 2 receptor (CCK2R) appears as a pharmacological target for the treatment of many major diseases. To complete the mapping of the CCK2R binding site and its activation processes, we have looked for the receptor residues that interact with Trp6, an essential residue for CCK binding and activity. In our molecular model of the CCK-occupied CCK2R, the indole group of Trp6 stacked with the phenyl ring of Phe120 (ECL1) and interacted with the imidazole group of His381(H7.39) and the phenyl ring of Tyr385(H7.43). Mutagenesis and pharmacological studies validated these interactions. It is noteworthy that the mutation of Phe120 to Trp conferred constitutive activity to the CCK2R. Molecular modeling and experimental works identified the residues involved in the activation cascade initiated by Trp6 and revealed that the constitutively active F120W mutation mimics the conformational changes induced by Trp6 resulting in: 1) the exposure of Glu151(E3.49) of the conserved E/DRY motif 2) the formation of an amphiphatic pocket involving protonated Glu151(E3.49) and Leu330 (ICL3), and 3) the opening of the intracellular loops 2 and 3 and the release of Arg158 (ICL2). The R158A mutation was shown to affect inositol phosphate production, whereas the E151A and L330E mutations induced constitutive inositol phosphate production. Given that a constitutively active variant of the CCK2R has been identified in different cancers and the fact that the E151A mutant has been reported to induce tumors, these studies should help in the development of potent inverse agonists to inhibit the constitutive activation of the CCK2R

Microsomal antiestrogen-binding site ligands induce growth control and differentiation of human breast cancer cells through the modulation of cholesterol metabolism.

International audienceThe microsomal antiestrogen-binding site (AEBS) is a high-affinity membranous binding site for the antitumor drug tamoxifen that selectively binds diphenylmethane derivatives of tamoxifen such as PBPE and mediates their antiproliferative properties. The AEBS is a hetero-oligomeric complex consisting of 3beta-hydroxysterol-Delta8-Delta7-isomerase and 3beta-hydroxysterol-Delta7-reductase. High-affinity AEBS ligands inhibit these enzymes leading to the massive intracellular accumulation of zymostenol or 7-dehydrocholesterol (DHC), thus linking AEBS binding to the modulation of cholesterol metabolism and growth control. The aim of the present study was to gain more insight into the control of breast cancer cell growth by AEBS ligands. We report that PBPE and tamoxifen treatment induced differentiation in human breast adenocarcinoma cells MCF-7 as indicated by the arrest of cells in the G0-G1 phase of the cell cycle, the increase in the cell volume, the accumulation and secretion of lipids, and a milk fat globule protein found in milk. These effects were observed with other AEBS ligands and with zymostenol and DHC. Vitamin E abrogates the induction of differentiation and reverses the control of cell growth produced by AEBS ligands, zymostenol, and DHC, showing the importance of the oxidative processes in this effect. AEBS ligands induced differentiation in estrogen receptor-negative mammary tumor cell lines SKBr-3 and MDA-MB-468 but with a lower efficiency than observed with MCF-7. Together, these data show that AEBS ligands exert an antiproliferative effect on mammary cancer cells by inducing cell differentiation and growth arrest and highlight the importance of cholesterol metabolism in these effects

Dendrogenin A arises from cholesterol and histamine metabolism and shows cell differentiation and anti-tumour properties.

10 pages + 11 pages SIInternational audienceWe previously synthesized dendrogenin A and hypothesized that it could be a natural metabolite occurring in mammals. Here we explore this hypothesis and report the discovery of dendrogenin A in mammalian tissues and normal cells as an enzymatic product of the conjugation of 5,6α-epoxy-cholesterol and histamine. Dendrogenin A was not detected in cancer cell lines and was fivefold lower in human breast tumours compared with normal tissues, suggesting a deregulation of dendrogenin A metabolism during carcinogenesis. We established that dendrogenin A is a selective inhibitor of cholesterol epoxide hydrolase and it triggered tumour re-differentiation and growth control in mice and improved animal survival. The properties of dendrogenin A and its decreased level in tumours suggest a physiological function in maintaining cell integrity and differentiation. The discovery of dendrogenin A reveals a new metabolic pathway at the crossroads of cholesterol and histamine metabolism and the existence of steroidal alkaloids in mammals

Identification of a tumor-promoter cholesterol metabolite in human breast cancers acting through the glucocorticoid receptor

International audienceBreast cancer (BC) remains the primary cause of death from cancer among women worldwide. Cholesterol-5,6-epoxide (5,6-EC) metabolism is deregulated in BC but the molecular origin of this is unknown. Here, we have identified an oncometabolism downstream of 5,6-EC that promotes BC progression independently of estrogen receptor α expression. We show that cholesterol epoxide hydrolase (ChEH) metabolizes 5,6-EC into cholestane-3β,5α,6β-triol, which is transformed into the oncometabolite 6-oxo-cholestan-3β,5α-diol (OCDO) by 11β-hydroxysteroid-dehydrogenase-type-2 (11βHSD2). 11βHSD2 is known to regulate glucocorticoid metabolism by converting active cortisol into inactive cortisone. ChEH inhibition and 11βHSD2 silencing inhibited OCDO production and tumor growth. Patient BC samples showed significant increased OCDO levels and greater ChEH and 11βHSD2 protein expression compared with normal tissues. The analysis of several human BC mRNA databases indicated that 11βHSD2 and ChEH overexpression correlated with a higher risk of patient death, highlighting that the biosynthetic pathway producing OCDO is of major importance to BC pathology. OCDO stimulates BC cell growth by binding to the glucocorticoid receptor (GR), the nuclear receptor of endogenous cortisol. Interestingly, high GR expression or activation correlates with poor therapeutic response or prognosis in many solid tumors, including BC. Targeting the enzymes involved in cholesterol epoxide and glucocorticoid metabolism or GR may be novel strategies to prevent and treat BC

Signaling through cholesterol esterification: a new pathway for the cholecystokinin 2 receptor involved in cell growth and invasion

Several studies indicate that cholesterol esterification is deregulated in cancers. The present study aimed to characterize the role of cholesterol esterification in proliferation and invasion of two tumor cells expressing an activated cholecystokinin 2 receptor (CCK2R). A significant increase in cholesterol esterification and activity of Acyl-CoA:cholesterol acyltransferase (ACAT) was measured in tumor cells expressing a constitutively activated oncogenic mutant of the CCK2R (CCK2R-E151A cells) compared with nontumor cells expressing the wild-type CCK2R (CCK2R-WT cells). Inhibition of cholesteryl ester formation and ACAT activity by Sah58-035, an inhibitor of ACAT, decreased by 34% and 73% CCK2R-E151A cell growth and invasion. Sustained activation of CCK2R-WT cells by gastrin increased cholesteryl ester production while addition of cholesteryl oleate to the culture medium of CCK2R-WT cells increased cell proliferation and invasion to a level close to that of CCK2R-E151A cells. In U87 glioma cells, a model of autocrine growth stimulation of the CCK2R, inhibition of cholesterol esterification and ACAT activity by Sah58-035 and two selective antagonists of the CCK2R significantly reduced cell proliferation and invasion. In both models, cholesteryl ester formation was found dependent on protein kinase zeta/ extracellular signal-related kinase 1/2 (PKCζ/ERK1/2) activation. These results show that signaling through ACAT/cholesterol esterification is a novel pathway for the CCK2R that contributes to tumor cell proliferation and invasion

Fuzzy logic selection as a new reliable tool to identify molecular grade signatures in breast cancer – the INNODIAG study

International audienceBackground : Personalized medicine has become a priority in breast cancer patient management. In addition to the routinely used clinicopathological characteristics, clinicians will have to face an increasing amount of data derived from tumor molecular profiling. The aims of this study were to develop a new gene selection method based on a fuzzy logic selection and classification algorithm, and to validate the gene signatures obtained on breast cancer patient cohorts.Methods : We analyzed data from four published gene expression datasets for breast carcinomas. We identified the best discriminating genes by comparing molecular expression profiles between histologic grade 1 and 3 tumors for each of the training datasets. The most pertinent probes were selected and used to define fuzzy molecular grade 1-like (good prognosis) and fuzzy molecular grade 3-like (poor prognosis) profiles. To evaluate the prognostic performance of the fuzzy grade signatures in breast cancer tumors, a Kaplan-Meier analysis was conducted to compare the relapse-free survival deduced from histologic grade and fuzzy molecular grade classification.Results : We applied the fuzzy logic selection on breast cancer databases and obtained four new gene signatures. Analysis in the training public sets showed good performance of these gene signatures for grade (sensitivity from 90% to 95%, specificity 67% to 93%). To validate these gene signatures, we designed probes on custom microarrays and tested them on 150 invasive breast carcinomas. Good performance was obtained with an error rate of less than 10%. For one gene signature, among 74 histologic grade 3 and 18 grade 1 tumors, 88 cases (96%) were correctly assigned. Interestingly histologic grade 2 tumors (n = 58) were split in these two molecular grade categories. Conclusion : We confirmed the use of fuzzy logic selection as a new tool to identify gene signatures with good reliability and increased classification power. This method based on artificial intelligence algorithms was successfully applied to breast cancers molecular grade classification allowing histologic grade 2 classification into grade 1 and grade 2 like to improve patients prognosis. It opens the way to further development for identification of new biomarker combinations in other applications such as prediction of treatment response