Pompeu Fabra University

About: Pompeu Fabra University is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Population & Gene. The organization has 8093 authors who have published 23570 publications receiving 858431 citations. The organization is also known as: Universitat Pompeu Fabra & UPF.

PIK3CA mutations are an early genetic alteration associated with FGFR3 mutations in superficial papillary bladder tumors.

Abstract: Bladder tumors constitute a very heterogeneous disease. Superficial tumors are characterized by a high prevalence of FGFR3 mutations and chromosome 9 alterations. High-grade and muscle-invasive tumors are characterized by Tp53 mutations and aneuploidy. We have analyzed the sequence of exons 9 and 20 of PIK3CA in a panel of bladder tumors covering the whole spectrum of the disease. DNA from formalin-fixed, paraffin-embedded tumor sections was amplified by PCR and products were sequenced. In an unselected panel of tumors representative of the disease, the PIK3CA mutation prevalence was 13% (11 of 87). Mutations occurred mainly at the previously identified hotspots (codons 542, 545, 1007, and 1047). The distribution according to stage was as follows: papillary urothelial neoplasms of uncertain malignant potential (PUNLMP; 11 of 43, 25.6%), T(a) (9 of 57, 16%), T(1) (2 of 10, 20%), and muscle-invasive tumors (0 of 20, 0%; P = 0.019). Mutations were associated with low-grade tumors: grade 1 (6 of 27, 22.2%), grade 2 (3 of 23, 13%), and grade 3 (2 of 37, 5.4%; P = 0.047). Overall, PIK3CA mutations were strongly associated with FGFR3 mutations: 18 of 69 (26%) FGFR3(mut) tumors were PIK3CA(mut), versus 4 of 58 (6.9%) FGFR3(wt) tumors (P = 0.005). Our findings indicate that PIK3CA mutations are a common event that can occur early in bladder carcinogenesis and support the notion that papillary and muscle-invasive tumors arise through different molecular pathways. PIK3CA may constitute a novel diagnostic and prognostic tool, as well as a therapeutic target, in bladder cancer.

Transcription factor evolution in eukaryotes and the assembly of the regulatory toolkit in multicellular lineages

Abstract: Transcription factors (TFs) are the main players in transcriptional regulation in eukaryotes. However, it remains unclear what role TFs played in the origin of all of the different eukaryotic multicellular lineages. In this paper, we explore how the origin of TF repertoires shaped eukaryotic evolution and, in particular, their role into the emergence of multicellular lineages. We traced the origin and expansion of all known TFs through the eukaryotic tree of life, using the broadest possible taxon sampling and an updated phylogenetic background. Our results show that the most complex multicellular lineages (i.e., those with embryonic development, Metazoa and Embryophyta) have the most complex TF repertoires, and that these repertoires were assembled in a stepwise manner. We also show that a significant part of the metazoan and embryophyte TF toolkits evolved earlier, in their respective unicellular ancestors. To gain insights into the role of TFs in the development of both embryophytes and metazoans, we analyzed TF expression patterns throughout their ontogeny. The expression patterns observed in both groups recapitulate those of the whole transcriptome, but reveal some important differences. Our comparative genomics and expression data reshape our view on how TFs contributed to eukaryotic evolution and reveal the importance of TFs to the origins of multicellularity and embryonic development.

A new approach to evaluating novel recommendations

Abstract: This paper presents two methods, named Item- and User-centric, to evaluate the quality of novel recommendations. The former method focuses on analyzing the item-based recommendation network. The aim is to detect whether the network topology has any pathology that hinders novel recommendations. The latter, user-centric evaluation, aims at measuring users' perceived quality of novel, previously unknown, recommendations.The results of the experiments, done in the music recommendation context, show that last.fm social recommender, based on collaborative filtering, is prone to popularity bias. This has direct consequences on the topology of the item-based recommendation network. Pure audio content-based methods (CB) are not affected by popularity. However, a user-centric experiment done with 288 subjects shows that even though a social-based approach recommends less novel items than our CB, users' perceived quality is better than those recommended by a pure CB method.