Functions of EMT in pituitary progenitor regulation from mouse to human

M INÉS PÉREZ MILLÁN

Congreso; ENDO meeting; 2018

Mutations in PROP1 are the most common known cause of hypopituitarism in humans; therefore, unraveling its mechanism of action is highly relevant from a therapeutic perspective. We determined that PROP1 is essential for stimulating stem cells to undergo an epithelial to mesenchymal transition-like process necessary for cell migration and differentiation. During pituitary development, there is a reduction in E-cadherin expression at the ventral aspect of Rathke´s cleft, and progenitor cells switch from tightly packed, polarized, planar shape to a rounded cell morphology, and these cells migrate into the parenchyma of the organ where they commence differentiation. This process fails in Prop1 mutant mice, resulting in a highly dysmorphic and hypoplastic anterior pituitary. Gene expression profiling of adherent stem cell colonies revealed that many genes in the Notch, TGFb, WNT, SHH and Eph/ephrin signaling pathways were affected in Prop1 mutants. Prop1 mutant colonies have up-regulated epithelial cell markers like E-cadherin, keratins and claudins, and down-regulation of mesenchymal cell markers like metalloproteinases and the EMT inducer Zeb2. A better understanding of the factors regulating embryonic pituitary progenitor cells may lead new candidate genes for human patients with hypopituitarism. Approximately 84% of cases have no molecular diagnosis. To rapidly screen new patients, we recently implemented a novel and cost-effective approach based on Molecular inversion probe (MIP) capture. We captured 693 coding exons of 30 known genes and 37 candidate genes. We captured genomic DNA from 51 pediatric patients from Argentina with CPHD or IGHD and their relatives and conducted next generation sequencing. We obtained deep coverage over targeted regions and found a dominant mutation GH1, p.R183H, in a three-generation pedigree with IGHD. Identifying these potential variants will make it feasible to predict clinical outcomes from genetic data, which is necessary for patient diagnosis and prognosis, and for assessing the risk of future affected individuals.