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IOVANNA, J. L.

Publications and source records attributed to IOVANNA, J. L..

2 recordsLinked to original sources

p97/VCP induces GLI1 to control XBP1-dependent endoplasmic reticulum stress transcriptional response

Upon accumulation of improperly folded proteins in the ER, an adaptive pathway named the UPR is triggered to restore ER homeostasis. The induction of stress genes controlling ER dynamics is a condition sine qua non for an effective UPR. Although this requirement has been extensively characterized, the transcriptional mechanism underlying this process remains in part elucidated. Here, we show that p97/VCP, an AAA+ ATPase known to modulate ER stress-induced gene expression, dynamically interacts with RUVBL2 and the mSin3A-HDAC1/2 complex. Further analysis of the mechanism defined a novel interplay between the aforementioned molecules and the transcription factor USF2 to control expression of GLI1, a primary effector of Hedgehog (Hh) signaling. Under basal conditions, GLI1 is repressed by RUVBL2-mSin3A-HDAC1/2 while upon ER stress GLI1 is induced through a mechanism requiring p97/VCP-mediated extraction of the repressor complex. Further analysis showed that GLI1 cooperate with ATF6f to activate the expression of XBP1, a transcription factor regulating the expression of genes controlling cellular stress response, under ER conditions. Overall, our work demonstrates that p97/VCP orchestrates the activation of GLI1 upon ER stress in a Hh ligand-independent fashion and defines the interplay between the newly identified p97/VCP-mSin3A-HDAC1/2 complex and the transcription factor USF2 as an essential player in this process.

cancer biology

Metabolomic profiling of pancreatic adenocarcinoma reveals fundamental clinical features

In this study, we perform the metabolomics profiling of 77 PDAC patient-derived tumor xenografts (PDTX) to investigate the relationship of metabolic profiles with overall survival (OS) in PDAC patients, tumor phenotypes and resistance to five anticancer drugs (gemcitabine, oxaliplatin, docetaxel, SN-38 and 5-Fluorouracil). We identified a metabolic signature that was able to predict the clinical outcome of PDAC patients (p < 0.001, HR=2.68 [95% CI: 1.5-4.9]). The correlation analysis showed that this metabolomic signature was significantly correlated with the PDAC molecular gradient (PAMG) (R = 0.44 and p < 0.001) indicating significant association to the transcriptomic phenotypes of tumors. Resistance score established, based on growth rate inhibition metrics using 35 PDTX-derived primary cells, allowed to identify several metabolites related to drug resistance which was globally accompanied by accumulation of several diacy-phospholipids and decrease in lysophospholipids. Interestingly, targeting glycerophospholipid synthesis improved sensitivity to the three tested cytotoxic drugs indicating that interfering with metabolism could be a promising therapeutic strategy to overcome the challenging resistance of PDAC. Short abstractTargeting metabolism of cancer cells gives a precious opportunity to overcome challenges related to the high mortality and chemoresistance in PDAC. Metabolic profiling of PDAC patient-derived tumor xenografts used in this study allowed highlighting the strong link between metabolism and both clinical outcome of the patients and chemoresistance. Metabolic signature was able to discriminate between good and bad prognosis groups of patients based on their level of key metabolites. Identification of key metabolic markers associated to chemoresistance allowed to improve sensitivity to anticancer drugs. These results provide new insights to help to predict patient survival and elaborate new combinatory therapies against chemoresistance in PDAC patients attesting of the important clinical value of this work.

cancer biology