Biology subjects

del Peso, L.

Publications and source records attributed to del Peso, L..

11 recordsLinked to original sources

bioRxiv2025

Age-dependent chemotherapy response and vitamin D impact in paired patient-derived normal and tumor colorectal organoids

Early-onset colorectal cancer (EO-CRC, <50 years) incidence is rising worldwide. Using paired patient-derived colorectal normal and tumor organoids, we demonstrate the therapeutic window of three standard chemotherapies. Normal organoids were more resistant than tumor organoids to 5-fluorouracil (5-FU) and oxaliplatin in both EO-CRC and late-onset CRC (LO-CRC) patients. However, for SN38, this therapeutic window was observed in LO-CRC but not in EO-CRC patients, revealing age-dependent differences in drug resistance. We also evaluated the effect of calcitriol, the active vitamin D metabolite with anti-CRC activity, on drug sensitivity. Calcitriol reduced the cytotoxicity of 5-FU and SN38 in normal organoids regardless of patient age, while it selectively decreased their cytotoxicity in EO-CRC but not in LO-CRC tumor organoids. This protective effect correlated with calcitriol antiproliferative action and transcriptional effects on drug-metabolism pathways. These findings identify clinically relevant age-dependent differences in chemotherapy response and support vitamin D-based strategies to design age-tailored precision treatments.

cancer biology↗

bioRxiv2025

Transcriptomic profile of embryoid bodies under hypoxia at single cell level

Oxygen availability is a key regulator of cellular physiology and hypoxia plays a central role driving vasculogenesis and angiogenesis during development. While bulk transcriptomics has revealed important oxygen-regulated gene networks, such approaches cannot resolve the cellular heterogeneity and lineage dynamics characteristic of early differentiation. To address this, we generated a single-cell transcriptomic dataset from murine embryoid bodies, a widely used in vitro model of early embryonic development, cultured 8 or 10 days under hypoxic (1% O2) or normoxic (21% O2) conditions for the final 16 or 48 hours of differentiation. This resource enables detailed exploration of how oxygen availability influences lineage specification, vascular and hematopoietic development, and cellular heterogeneity during early differentiation. Beyond developmental biology, the dataset provides a valuable reference for comparative studies of hypoxia responses, benchmarking of single-cell analysis methods, and integrative investigations into oxygen signaling across diverse biological systems.

cell biology↗

bioRxiv2025

Intermittent Hypoxia Drives Early Metabolic Dysfunction in Brown Adipose Tissue

BackgroundObstructive sleep apnea (OSA) is associated with metabolic dysfunction, yet the early impact of intermittent hypoxia (IH)--a defining feature of OSA--on brown adipose tissue (BAT) remains unclear. MethodsWe investigated the direct and early effects of IH on BAT using both in vitro and in vivo approaches. Differentiated mouse brown adipocytes were exposed to IH for 48 hours and analyzed for {beta}3-adrenergic signaling, lipolysis, and thermogenic activation. Complementary in vivo studies assessed transcriptomic, morphological, and functional changes in BAT, white adipose tissue (WAT), and liver after 1 or 4 weeks of IH exposure in mice. ResultsIH blunted {beta}3-adrenergic signaling in cultured brown adipocytes, leading to reduced phosphorylation of key signaling proteins, impaired lipolytic response, and decreased expression of UCP1. In vivo, BAT exhibited early and sustained transcriptomic rewiring characterized by downregulation of pathways related to fatty acid metabolism, oxidative phosphorylation, and peroxisomal function. These molecular changes were accompanied by abnormal lipid droplet enlargement and a reduced lipolytic response to adrenergic stimulation. In contrast, WAT showed transient gene expression changes, and the liver displayed a delayed and robust transcriptomic response evident only after four weeks of IH exposure. Despite these metabolic alterations, thermogenic responses to cold challenge remained intact in IH-treated mice. ConclusionsBAT is uniquely and rapidly affected by intermittent hypoxia, undergoing functional, molecular, and morphological changes within one week of exposure. These alterations precede systemic inflammation and metabolic dysfunction, positioning BAT dysfunction as an early event in the pathogenesis of OSA-associated metabolic disease.

pathology↗

bioRxiv2025

Enhancing TFEA.ChIP with ENCODE Regulatory Maps for Generalizable Transcription Factor Enrichment

Identifying transcription factors (TFs) responsible for gene expression changes remains a central challenge in functional genomics. TFEA.ChIP is a ChIP-seq-based TF enrichment analysis tool that addresses this by linking TF binding profiles to differentially expressed genes through experimentally supported cis-regulatory element (CRE)-gene associations. Unlike motif- or heuristic-based approaches, TFEA.ChIP adopts a biologically grounded strategy by intersecting TF binding data from ReMap2022 with regulatory maps from ENCODEs rE2G and CREdb. To overcome the high context-specificity of rE2G associations, we developed filtering strategies based on confidence scores and recurrence across biosamples. Benchmarking on 369 curated gene sets from the MSigDB C2 CGP collection showed that recurrence-based filtering significantly improved accuracy, outperforming the original GeneHancer-based implementation and leading tools including BARTv2.0, Lisa, ChEA3, and HOMER. A case study on hypoxia further validated the method, demonstrating accurate and pathway-specific enrichment of HIF-related TFs using both overrepresentation analysis and gene set enrichment analysis (GSEA). Additionally, the updated implementation of TFEA.ChIP in R/Bioconductor introduces several user-friendly features, including automated analysis workflows and expression-based filtering of candidate TFs. These additions streamline the integration of TFEA.ChIP into standard RNA-seq analysis pipelines, enabling more efficient and reproducible workflows. Together with its strong benchmarking performance and biologically grounded framework, the updated tool provides a robust and accessible solution for inferring transcriptional regulators from gene expression data.

bioinformatics↗

bioRxiv2024

Bhlhe40 limits proliferation and prevents excessive angiogenesis in mouse embryoid bodies under hypoxia

Knowledge of the molecular mechanisms that underlie the regulation of the major adaptive responses to an unbalanced oxygen tension is central to understanding tissue homeostasis and disease. Hypoxia-inducible transcription factors (HIFs) coordinate changes in the transcriptome that control these adaptive responses. Here, we focused on the functional role of the transcriptional repressor basic-helix-loop-helix family member e40 (Bhlhe40), which we previously identified in a meta-analysis as one of the most consistently up-regulated genes in response to hypoxia across various cell types. We investigated the role of Bhlhe40 in controlling proliferation and angiogenesis using a gene editing strategy in mouse embryonic stem cells (mESCs) that we differentiated in embryoid bodies (EBs). We observed that hypoxia-induced Bhlhe40 expression was compatible with the rapid proliferation of pluripotent mESCs under low oxygen tension. However, in EBs, hypoxia triggered a Bhlhe40-dependent cell cycle arrest in most progenitor cells and endothelial cells within vascular structures. Furthermore, Bhlhe40 knockout increased the basal vascularization of the EBs in normoxia and exacerbated the hypoxia-induced vascularization, supporting a novel role for Bhlhe40 as a negative regulator of blood vessel formation. Our findings implicate Bhlhe40 in mediating key functional adaptive responses to hypoxia, such as proliferation arrest and angiogenesis.

molecular biology↗

bioRxiv2022

p73 controls cell junction dynamics during sprouting angiogenesis and acts via Angiomotin

Preservation of blood vessels integrity, which is critical for normal physiology and organ function, is controlled at multiple levels, including endothelial junctions. However, the mechanism that controls the adequate assembly of endothelial cell junctions is not fully defined. Here we uncover TAp73 transcription factor as a vascular architect that orchestrates transcriptional programs involved in cell junction establishment and developmental blood vessel morphogenesis and identify Angiomotin (AMOT) as a TAp73 direct transcriptional target. Knockdown of p73 in endothelial cells not only results in decreased Angiomotin expression and localization at intercellular junctions, but also affects its downstream function regarding Yes-Associated Protein (YAP) cytoplasmic sequestration upon cell-cell contact. Analysis of adherens junctional morphology after p73-knockdown in human endothelial cells revealed striking alterations, particularly a sharp increase in serrated junctions and actin bundles appearing as stress fibers, both features associated with enhanced barrier permeability. In turn, stabilization of Angiomotin levels rescued those junctional defects, confirming that TAp73 controls endothelial junction dynamics, at least in part, through the regulation of Angiomotin. The observed defects in monolayer integrity were linked to hyperpermeability and reduced transendothelial electric resistance. Moreover, p73-knockout retinas showed a defective sprout morphology coupled to hemorrhages, highlighting the physiological relevance of p73 regulation in the maintenance of vessel integrity in vivo. We propose a new model in which TAp73 acts as a vascular architect integrating transcriptional programs that will impinge with Angiomotin/YAP signaling to maintain junctional dynamics and integrity, whilst balancing endothelial cell rearrangements in angiogenic vessels.

cell biology↗

bioRxiv2021

Hypoxia classifier for transcriptome datasets

Molecular gene signatures are useful tools to characterize the physiological state of cell populations, but most have developed under a narrow range of conditions and cell types and are often restricted to a set of gene identities. Focusing on the transcriptional response to hypoxia, we aimed to generate widely applicable classifiers sourced from the results of a meta-analysis of 69 differential expression datasets which included 425 individual RNA-seq experiments from 33 different human cell types exposed to different degrees of hypoxia (0.1-5%O2) for 2-48h. The resulting decision trees include both gene identities and quantitative boundaries, allowing for easy classification of individual samples without control or normoxic reference. Each tree is composed by 3-5 genes mostly drawn from a small set of just 8 genes (EGLN1, MIR210HG, NDRG1, ANKRD37, TCAF2, PFKFB3, BHLHE40, and MAFF). In spite of their simplicity, these classifiers achieve over 95% accuracy in cross validation and over 80% accuracy when applied to additional challenging datasets. Our results indicate that the classifiers are able to identify hypoxic tumor samples from bulk RNAseq and hypoxic regions within tumor from spatially resolved transcriptomics datasets. Moreover, application of the classifiers to histological sections from normal tissues suggest the presence of a hypoxic gene expression pattern in the kidney cortex not observed in other normoxic organs. Finally, tree classifiers described herein outperform traditional hypoxic gene signatures when compared against a wide range of datasets. This work describes a set of hypoxic gene signatures, structured as simple decision tress, that identify hypoxic samples and regions with high accuracy and can be applied to a broad variety of gene expression datasets and formats.

bioinformatics↗

bioRxiv2021

Formal meta-analysis of hypoxic gene expression profiles reveals a universal gene signature and cell type-specific effects

BackgroundIntegrating transcriptional profiles results in the identification of gene expression signatures that are more robust than those obtained for individual datasets. However, direct comparison of datasets derived from heterogeneous experimental conditions is not possible and their integration requires the application of specific meta-analysis techniques. The transcriptional response to hypoxia has been the focus of intense research due to its central role in tissue homeostasis and in prevalent diseases. Accordingly, a large number of studies have determined the gene expression profile of hypoxic cells. Yet, in spite of this wealth of information, little effort have been done to integrate these dataset to produce a robust hypoxic signature. ResultsWe applied a formal meta-analysis procedure to a dataset comprising 425 RNAseq samples derived from 42 individual studies including 33 different cell types, to derive a pooled estimate of the effect of hypoxia on gene expression. This approach revealed that a large proportion of the transcriptome (8556 genes out of 20888) is significantly regulated by hypoxia. However, only a small fraction of the differentially expressed genes (1265 genes, 15%) show an effect size that, according to comparisons to gene pathways known to be regulated by hypoxia, is likely to be biologically relevant. By focusing on genes ubiquitously expressed we identified a signature of 291 genes robustly and consistently regulated by hypoxia. Finally, by a applying a moderator analysis we found that endothelial cells show a characteristic gene expression pattern that is significantly different from other cell types. ConclusionBy the application of a formal meta-analysis to hypoxic gene profiles, we have developed a robust gene signature that characterizes the transcriptomic response to low oxygen. In addition to identifying a universal set of hypoxia-responsive genes, we found a set of genes whose regulation is cell-type specific and suggest a unique metabolic response of endothelial cells to reduced oxygen tension.

genomics↗

bioRxiv2019

Metabolic labelling of RNA uncovers the contribution of transcription and decay rates on hypoxia-induced changes in RNA levels

Cells adapt to environmental changes, including fluctuations in oxygen levels, through the induction of specific gene expression programs. However, most transcriptomic studies do not distinguish the relative contribution of transcription, RNA processing and RNA degradation processes to cellular homeostasis. Here we used metabolic labeling followed by massive parallel sequencing of newly transcribed and preexisting RNA fractions to simultaneously analyze RNA synthesis and decay in primary endothelial cells exposed to low oxygen tension. We found that the changes in transcription rates induced by hypoxia are the major determinant of RNA levels. However, degradation rates also had a significant contribution, accounting for 24% of the observed variability in total mRNA. In addition, our results indicated that hypoxia led to a reduction of the overall mRNA stability from a median half-life in normoxia of 8.7 hours, to 5.7 hours in hypoxia. Analysis of RNA content per cell confirmed a decrease of both mRNA and total RNA in hypoxic samples and that this effect was mimicked by forced activation of the Hypoxia Inducible Factor pathway and prevented by its interference. In summary, our study provides a quantitative analysis of the contribution of RNA synthesis and stability to the transcriptional response to hypoxia and uncovers an unexpected effect on the latter.

molecular biology↗

bioRxiv2018

TFEA.ChIP: A tool kit for transcription factor binding site enrichment analysis capitalizing on ChIP-seq datasets

The identification of transcription factors (TFs) responsible for the co-regulation of specific sets of genes is a common problem in transcriptomics. Herein we describe TFEA.ChIP, a tool to estimate and visualize TF enrichment in gene lists representing transcriptional profiles. To generate the gene sets representing TF targets, we gathered ChIP-Seq experiments from the ENCODE Consortium and GEO datasets and used the correlation between Dnase Hypersensitive Sites across cell lines to generate a database linking TFs with the genes they interact with in each ChIP-Seq experiment. In its current state, TFEA.ChIP covers 327 different transcription factors from 1075 ChIP-Seq experiments, with over 150 cell types being represented. TFEA.ChIP accepts gene sets as well as sorted lists differentially expressed genes to compute enrichment scores for each of the datasets in its internal database using an Fishers exact association test or a Gene Set Enrichment Analysis. We validated TFEA.ChIP using a wide variety of gene sets representing signatures of genetic and chemical perturbations as input and found that the relevant TF was correctly identified in 103 of a total of 144 analyzed datasets with a median area under the curve (AUC) of 0.86. In depth analysis of an RNAseq dataset, illustrates that the use of ChIP-Seq data instead of PWM-based provides key biological context to interpret the results of the analysis. To facilitate its integration into transcriptome analysis pipelines and allow easy expansion and customization of the TF-gene database, we implemented TFEA.ChIP as an R package that can be downloaded from Bioconductor: https://www.bioconductor.org/packages/devel/bioc/html/TFEA.ChIP.html and github: https://github.com/LauraPS1/TFEA-drafts In addition, make it available to a wide range of researches, we have also developed a web application that runs the package from the server side and enables easy exploratory analysis through interactive graphs: https://www.iib.uam.es/TFEA.ChIP/

bioinformatics↗

bioRxiv2017

The SIN3A histone deacetylase complex is required for a complete transcriptional response to hypoxia

Cells adapt to environmental changes, including fluctuations in oxygen levels, through the induction of specific gene expression programs. To identify genes regulated by hypoxia at the transcriptional level, we pulse-labeled HUVEC cells with 4-thiouridine and sequenced nascent transcripts. Then, we searched genome-wide binding profiles from the ENCODE project for factors that correlated with changes in transcription and identified binding of several components of the Sin3A co-repressor complex, including SIN3A, SAP30 and HDAC1/2, proximal to genes repressed by hypoxia. SIN3A interference revealed that it participates in the downregulation of 75% of the hypoxia-repressed genes in endothelial cells. Unexpectedly, it also blunted the induction of 47% of the upregulated genes, suggesting a role for this corepressor in gene induction. In agreement, ChIP-seq experiments showed that SIN3A preferentially localizes to the promoter region of actively transcribed genes and that SIN3A signal was enriched in hypoxia-repressed genes, prior exposure to the stimulus. Importantly, SINA3 occupancy was not altered by hypoxia in spite of changes in H3K27ac signal. In summary, our results reveal a prominent role for SIN3A in the transcriptional response to hypoxia and suggest a model where modulation of the associated histone deacetylase activity, rather than its recruitment, determines the transcriptional output.

genomics↗