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The interaction of upar with vegfr2 promotes vegf-induced angiogenesis
Herkenne S, Paques C, Nivelles O, Lion M, Bajou K, Pollenus T, Fontaine M, Carmeliet P, Martial JA, Nguyen NQ, Struman I.
Science Signaling
.
2015;8:ra117
In endothelial cells, binding of vascular endothelial growth factor (VEGF) to the receptor VEGFR2 activates multiple signaling pathways that trigger processes such as proliferation, survival, and migration
that are necessary for angiogenesis. VEGF-bound VEGFR2 becomes internalized, which is a key step in the proangiogenic signal. We showed that the urokinase plasminogen activator receptor (uPAR)
interacted with VEGFR2 and described the mechanism by which this interaction mediated VEGF signaling and promoted angiogenesis. Knockdown of uPAR in human umbilical vein endothelial cells
(HUVECs) impaired VEGFR2 signaling, and uPAR deficiency in mice prevented VEGF-induced angiogenesis. Upon exposure of HUVECs to VEGF, uPAR recruited the low-density lipoprotein receptor-related
protein 1 (LRP-1) to VEGFR2, which induced VEGFR2 internalization. Thus, the uPAR-VEGFR2 interaction is crucial for VEGF signaling in endothelial cells.
Lipin-1 regulates cancer cell phenotype and is a potential target to potentiate rapamycin treatment
Brohee L, Demine S, Willems J, Arnould T, Colige AC, Deroanne CF.
Oncotarget.
2015;6:11264-11280
Lipogenesis inhibition was reported to induce apoptosis and repress proliferation of cancer cells while barely affecting normal cells. Lipins exhibit dual function as enzymes catalyzing the dephosphoryla-
tion of phosphatidic acid to diacylglycerol and as co-transcriptional regulators. Thus, they are able to regulate lipid homeostasis at several nodal points. Here, we show that lipin-1 is up-regulated in several
cancer cell lines and overexpressed in 50 % of high grade prostate cancers. The proliferation of prostate and breast cancer cells, but not of non-tumorigenic cells, was repressed upon lipin-1 knock-down.
Lipin-1 depletion also decreased cancer cell migration through RhoA activation. Lipin-1 silencing did not significantly affect global lipid synthesis but enhanced the cellular concentration of phosphatidic
acid. In parallel, autophagy was induced while AKT and ribosomal protein S6 phosphorylation were repressed. We also observed a compensatory regulation between lipin-1 and lipin-2 and demonstrated
that their co-silencing aggravates the phenotype induced by lipin-1 silencing alone. Most interestingly, lipin-1 depletion or lipins inhibition with propranolol sensitized cancer cells to rapamycin. These data
indicate that lipin-1 controls main cellular processes involved in cancer progression and that its targeting, alone or in combination with other treatments, could open new avenues in anticancer therapy.
Circulating microrna-based screening tool for breast cancer
Freres P, Wenric S, Boukerroucha M, Fasquelle C, Thiry J, Bovy N, Struman I, Geurts P, Collignon J, Schroeder H, Kridelka F, Lifrange E, Jossa V, Bours V, Josse C, Jerusalem G.
Oncotarget.
2015
Circulating microRNAs (miRNAs) are increasingly recognized as powerful biomarkers in several pathologies, including breast cancer. Here, their plasmatic levels were measured to be used as an alterna-
tive screening procedure to mammography for breast cancer diagnosis. A plasma miRNA profile was determined by RT-qPCR in a cohort of 378 women. A diagnostic model was designed based on the
expression of 8 miRNAs measured first in a profiling cohort composed of 41 primary breast cancers and 45 controls, and further validated in diverse cohorts composed of 108 primary breast cancers, 88
controls, 35 breast cancers in remission, 31 metastatic breast cancers and 30 gynecologic tumors. A receiver operating characteristic curve derived from the 8-miRNA random forest based diagnostic
tool exhibited an area under the curve of 0.81. The accuracy of the diagnostic tool remained unchanged considering age and tumor stage. The miRNA signature correctly identified patients with metastatic
breast cancer. The use of the classification model on cohorts of patients with breast cancers in remission and with gynecologic cancers yielded prediction distributions similar to that of the control group.
Using a multivariate supervised learning method and a set of 8 circulating miRNAs, we designed an accurate, minimally invasive screening tool for breast cancer.