Biology subjects

Guerrero, S.

Publications and source records attributed to Guerrero, S..

14 recordsLinked to original sources

bioRxiv2026

GENETIC AND PHARMACOLOGIC ACTIVATION OF BECLIN1 PREVENTS ALDOSTERONE-INDUCED CARDIOVASCULAR DAMAGE

BackgroundAldosterone promotes endothelial dysfunction and cardiovascular injury through mineralocorticoid receptor (MR) activation. Autophagy is essential for endothelial homeostasis, yet its role in aldosterone-mediated vascular dysfunction remains unclear. We tested whether aldosterone impairs autophagic flux and whether restoring autophagy via Beclin1 (BCN1) activation protects vascular and cardiac function. MethodsEndothelial and vascular responses to aldosterone were assessed in wild-type mice, BCN1 gain-of-function mice (Becn1), and mice treated with spermidine or a BCN1- activating TB-peptide. Vascular function, nitric oxide (NO)/reactive oxygen species (ROS) production, autophagy markers, endothelial migration, and cardiac fibrosis were evaluated using wire myography, fluorescence assays, Western blotting, confocal microscopy, migration assays, and histology. ResultsAldosterone impaired endothelium-dependent relaxation, decreased NO, increased ROS, and disrupted autophagic flux in an MR-dependent manner, indicated by LC3 accumulation and reduced p62 and BCN1 expression. Spermidine restored endothelial function and normalized NO and ROS levels. BCN1 gain-of-function mice were protected from aldosterone-induced endothelial dysfunction and exhibited reduced coronary and myocardial fibrosis. TB-peptide activation of BCN1 enhanced autophagic flux, improved vascular function, decreased cardiac fibrosis, and rescued endothelial migration impaired by aldosterone. ConclusionsAldosterone induces endothelial dysfunction by suppressing autophagic flux through MR activation. Genetic or pharmacologic enhancement of BCN1-dependent autophagy restores endothelial homeostasis and prevents vascular and cardiac injury, identifying autophagy activation as a promising therapeutic approach for cardiovascular diseases associated with mineralocorticoid excess.

physiology↗

bioRxiv2025

Diverse activity in prefrontal projections promotes temporal control of action

Prefrontal neurons can have diverse activity during cognitive functions like working memory, attention, and timing; however, the importance of this heterogeneity is unclear. Our goal was to better understand the diversity of prefrontal activity through connectivity. We harnessed circuit-specific tools to capture activity within prefrontal projections during interval timing, an elementary cognitive process that requires working memory for temporal rules and attention to the passage of time to estimate a temporal interval of several seconds. We used human electroencephalography and single neuronal recordings in mice to capture prefrontal activity during interval timing, with major patterns characterized by time-dependent ramping (monotonic changes) over a temporal interval. We then leveraged retrograde viruses to interrogate prefrontal cortex (PFC) projections to the mediodorsal thalamus (PFC-MD) and to the dorsomedial striatum (PFC-DMS). We report three novel results. First, circuit-specific calcium fiber photometry revealed that PFC-MD and PFC-DMS activity encoded distinct temporal signals, with PFC-MD projections ramping down and PFC-DMS ramping up to interval timing response times. Second, circuit-specific inactivation revealed that PFC-DMS inactivation disrupted animals internal estimates of time. Third, circuit-specific single-nucleus RNA sequencing of prefrontal projections revealed distinct transcriptomic profiles between PFC-MD and PFC-DMS projections, with enriched genes for cortical layers and neuromodulators, and specific genes such as Cux2, Camk2n1, Htr4, and Foxp2. These data suggest differences in gene expression and connectivity give rise to the diversity of prefrontal activity during interval timing. These findings advance our fundamental understanding of prefrontal function and dysfunction in human disease.

neuroscience↗

bioRxiv2024

Temperature-dependent and sex-specific phenotypic plasticity in Heliconius charithonia

External environmental cues can influence the development trajectory of organisms and lead to the formation of distinct phenotypes from the same genotype. Phenotypic plasticity is common in Lepidoptera, with temperature frequently playing a key role. The zebra-longwing (Heliconius charithonia) gets its name from its characteristic black wings with yellow stripes. In some populations, yellow scales are sometimes partially replaced by orange ( rusty) scales. The proportion of individuals with rusty scales varies geographically and individuals within the same population can vary drastically for this phenotype. Whether such variation is genetically encoded, or environment-dependent is not known. Here we test the influence of temperature in producing the rusty scales phenotype, as well as on the developmental rates, weight, and mortality in this species. Only female butterflies reared in warm controlled conditions develop rusty scales on the yellow parts of their wings. However, under more extreme (warmer) conditions, both males and females exhibit pronounced rusty scale phenotypes, indicating a sexually dimorphic response to temperature that affects both sexes. This temperature-sensitive trait can be triggered during both larval and pupal stages. Temperature also affects life-history traits, and we observed a trade-off between developmental rate and mortality. Individuals raised in warmer conditions develop more rapidly than those in cooler environments, but this accelerated growth is accompanied by higher mortality across all developmental stages.

developmental biology↗

bioRxiv2021

An mRNA expression-based signature for oncogene-induced replication-stress

BackgroundOncogene-induced replication stress characterizes many aggressive cancers, including triple-negative breast cancer (TNBC). Several drugs are being developed that target replication stress, although it is unclear how tumors with high levels of replication stress can be identified. We aimed to develop a gene expression signature of oncogene-induced replication stress. MethodsTNBC and non-transformed RPE1-TP53wt and RPE1-TP53mut cell lines were engineered to overexpress the oncogenes CDC25A, CCNE1 or MYC. DNA fiber analysis was used to measure replication kinetics. Analysis of RNA sequencing data of cell lines and patient-derived tumor samples (TCGA n=10,592) was used to identify differential gene expression. Immunohistochemical validation was conducted on breast cancer samples (n=330). ResultsRNA sequencing revealed 52 commonly upregulated genes after induction of CDC25A, CCNE1 or MYC in our cell line panel. Integration with gene expression data of TGCA samples with amplification of replication stress-inducing oncogenes (CDC25A, CCNE1, MYC, CCND1, MYB, MOS, KRAS, ERBB2, and E2F1), yielded a six-gene signature of oncogene-induced replication stress (NAT10, DDX27, ZNF48, C8ORF33, MOCS3, and MPP6). Expression of NAT10 in breast cancer samples was correlated with phospho-RPA (R=0.451, p=1.82x10-20) and {gamma}H2AX (R=0.304, p=2.95x10-9). Applying the oncogene-induced replication stress signature to patient samples (TCGA n=8,862 and GEO n=13,912) defined the replication stress landscape across 27 tumor subtypes, and identified diffuse large B cell lymphoma, ovarian cancer, TNBC and colorectal carcinoma as cancer subtypes with high levels of oncogene-induced replication stress. ConclusionWe developed a gene expression signature of oncogene-induced replication stress, which may facilitate patient selection for agents that target replication stress.

cancer biology↗

bioRxiv2021

A conserved uORF impacts APOBEC3G translation and is essential for translational inhibition by the HIV-1 Vif protein

The HIV-1 Vif protein is essential for viral fitness and pathogenicity. Vif decreases expression of cellular restriction factors APOBEC3G (A3G), A3F, A3D and A3H, which inhibit HIV-1 replication by inducing hypermutation during reverse transcription. Vif counteracts A3G at several levels (transcription, translation and protein degradation) that together reduce the levels of A3G in cells and prevent its incorporation into viral particles. How Vif affects A3G translation remains unclear. Here, we uncovered the importance of a short conserved uORF (upstream ORF) located within two critical stem-loop structures of the 5 untranslated region (5UTR) of A3G mRNA for this process. A3G translation occurs through a combination of leaky-scanning and translation re-initiation and the presence of an intact uORF decreases the extent of global A3G translation under normal conditions. Interestingly, the uORF is also absolutely required for Vif-mediated translation inhibition and redirection of A3G mRNA into stress granules. Overall, we discovered that A3G translation is regulated by a small uORF conserved in the human population and that Vif uses this specific feature to repress its translation.

microbiology↗

bioRxiv2020

Characterization Of Ancestral Origin Of Cystic Fibrosis Of Patients With New Reported Mutations In CFTR

The incidence of Cystic fibrosis (CF) and the frequency of the variants for CFTR depend on the population; furthermore, CF symptomatology is characterized by obstructive lung disease, pancreatic insufficiency among others, reliant on the individual genotype. Ecuadorian population is a mixture of Native Americans, Europeans, and Africans. That population admixture could be the reason for the new mutations reported in a previous study by Ruiz et al. (2019). A panel of 46 Ancestry Informative Markers was used to estimate the ancestral proportions of each available sample (12 samples in total). As a result, the Native American ancestry proportion was the most prevalent in almost all individuals, except for three patients from Guayaquil with the mutation [c.757G>A:p.Gly253Arg; c.1352G>T:p.Gly451Val] who had the highest European composition.

genetics↗

bioRxiv2020

TCGA Pan-Cancer genomic analysis of Alternative Lengthening of Telomeres (ALT) related genes

Telomere maintenance mechanisms (TMM) are used by cancer cells to avoid apoptosis, 85-90% reactivate telomerase, while 10-15% use the alternative lengthening of telomeres (ALT). Due to anti-telomerase-based treatments, some tumors have the ability to switch from a telomerase-dependent mechanism to ALT, in fact, the co-existence between telomerase and the ALT pathway have been observed in a variety of cancer types. Despite different elements in the ALT pathway have been uncovered, the molecular mechanism and other factors are still poorly understood, which difficult the detection and treatment of ALT-positive cells, which are known to present poor prognosis. Therefore, with the aim to identify potential molecular markers to be used in the study of ALT, we combined simplistic in silico approaches in 411 telomere maintenance (TM) genes which have been previously validated or predicted to be involved in the ALT pathway. In consequence, we conducted a genomic analysis of these genes in 31 Pan-Cancer Atlas studies (n=9,282) from The Cancer Genome Atlas in the cBioPortal and found 325,936 genomic alterations, being mRNA high and low the top alterations with 65.8% and 10.7% respectively. Moreover, we analyzed the highest frequency means of genomics alterations, identified and proposed 20 genes, which are highly mutated and up and down regulated in the cancer studies and could be used for future analysis in the study of ALT. Finally, we made a protein-protein interaction network and enrichment analysis to obtain an insight into the main pathways these genes are involved. We could observe their role in main processes related to the ALT mechanism like homologous recombination, homology directed repair (HDR), HDR through homologous recombination and telomere maintenance and organization.. Overall, due to the lack of understanding of the molecular mechanisms and detection of ALT-positive cancers, we identified and proposed more molecular targets that can be used for expression analysis and additional ex vivo assays to validate them as new potential therapeutic markers in the study of the ALT mechanism.

cancer biology↗

bioRxiv2020

Metastatic signaling of hypoxia-related genes across TCGA Pan-Cancer types

Many primary-tumor subregions have low levels of molecular oxygen, termed hypoxia. Hypoxic tumors are at elevated risk for local failure and distant metastasis. Metastatic disease is the leading cause of cancer-related deaths and involves critical interactions between tumor cells and the microenvironment. Here we focused on elucidating the molecular hallmarks of tumor hypoxia that remains poorly defined. To fill this gap, we analyzed the genomic alterations and hypoxia score of 233 hypoxia-related genes of 6,343 individuals across 17 TCGA Pan-Cancer types. In addition, we analyzed a protein-protein interactome (PPi) network and the shortest paths from hypoxic proteins to metastasis. As results, mRNA high alteration was prevalent in all cancer types. Genomic alterations and hypoxia score presented a highest frequency in tumor stage 4 and positive metastasis status in all cancer types. The most significant signaling pathways were HIF-1, ErbB, PI3K-Akt, FoxO, mTOR, Ras and VEGF. The PPi network revealed a strong association among hypoxic proteins, cancer driver proteins and metastasis driver proteins. The analysis of shortest paths revealed 99 ways to spread metastasis signaling from hypoxic proteins. Additionally, we proposed 62 hypoxic genes strongly associated with metastasis and 27 of them with high amount of genomic alterations. Overall, tumor hypoxia may drive aggressive molecular features across cancer types. Hence, we identified potential biomarkers and therapeutic targets regulated by hypoxia that could be incorporated into strategies aimed at improving novel drug development and treating metastasis.

cancer biology↗

bioRxiv2020

In silico analyses reveal new putative Breast Cancer RNA-binding proteins

Breast cancer (BC) is the leading cause of cancer-associated death among women worldwide. Despite treatment efforts, advanced BC with distant organ metastases is considered incurable. A better understanding of BC molecular processes is therefore of great interest to identify new therapeutic targets. Although large-scale efforts, such as The Cancer Genome Atlas (TCGA), have completely redefined cancer drug development, diagnosis, and treatment, additional key aspects of tumor biology remain to be discovered. In that respect, post-transcriptional regulation of tumorigenesis represents an understudied aspect of cancer research. As key regulators of this process, RNA-binding proteins (RBPs) are emerging as critical modulators of tumorigenesis but only few have defined roles in BC. To unravel new putative BC RBPs, we have performed in silico analyses of all human RBPs in three major cancer databases (TCGA-Breast Invasive Carcinoma, the Human Protein Atlas, and the Cancer Dependency Map project) along with complementary bioinformatics resources (STRING protein-protein interactions and the Network of Cancer Genes 6.0). Thus, we have identified six putative BC progressors (MRPL13, SCAMP3, CDC5L, DARS2, PUF60, and PLEC), and five BC suppressors RBPs (SUPT6H, MEX3C, UPF1, CNOT1, and TNKS1BP1). These proteins have never been studied in BC but show similar cancer-associated features than well-known BC proteins. Further research should focus on the mechanisms by which these proteins promote or suppress breast tumorigenesis, holding the promise of new therapeutic pathways along with novel drug development strategies.

cancer biology↗

bioRxiv2019

Prediction of breast cancer proteins using molecular descriptors and artificial neural networks: a focus on cancer immunotherapy proteins, metastasis driver proteins, and RNA-binding proteins

BackgroundBreast cancer (BC) is a heterogeneous disease characterized by an intricate interplay between different biological aspects such as ethnicity, genomic alterations, gene expression deregulation, hormone disruption, signaling pathway alterations and environmental determinants. Due to the complexity of BC, the prediction of proteins involved in this disease is a trending topic in drug design. MethodsThis work is proposing accurate prediction classifier for BC proteins using six sets of protein sequence descriptors and 13 machine learning methods. After using a univariate feature selection for the mix of five descriptor families, the best classifier was obtained using multilayer perceptron method (artificial neural network) and 300 features. ResultsThe performance of the model is demonstrated by the area under the receiver operating characteristics (AUROC) of 0.980 {+/-} 0.0037 and accuracy of 0.936 {+/-} 0.0056 (3-fold cross-validation). Regarding the prediction of 4504 cancer-associated proteins using this model, the best ranked cancer immunotherapy proteins related to BC were RPS27, SUPT4H1, CLPSL2, POLR2K, RPL38, AKT3, CDK3, RPS20, RASL11A and UBTD1; the best ranked metastasis driver proteins related to BC were S100A9, DDA1, TXN, PRNP, RPS27, S100A14, S100A7, MAPK1, AGR3 and NDUFA13; and the best ranked RNA-binding proteins related to BC were S100A9, TXN, RPS27L, RPS27, RPS27A, RPL38, MRPL54, PPAN, RPS20 and CSRP1. ConclusionsThis powerful model predicts several BC-related proteins which should be deeply studied to find new biomarkers and better therapeutic targets. The script and the results are available as a free repository at https://github.com/muntisa/neural-networks-for-breast-cancer-proteins.

bioinformatics↗

bioRxiv2019

Massively parallel single-cell B-cell receptor sequencing enables rapid discovery of diverse antigen-reactive antibodies

Using high-throughput single-cell B-cell receptor sequencing (scBCR-seq) we obtained accurately paired full-length heavy- and light-chain variable domains from thousands of individual B cells in a massively parallel fashion. We sequenced more than 250,000 B cells from rat, mouse and human repertoires to characterize their lineages and expansion. In addition, we immunized rats with chicken ovalbumin and profiled antigen-reactive B cells from lymph nodes of immunized animals. The scBCR-seq data recovered 81% (n = 56/69) of B-cell lineages identified from hybridomas generated from the same set of B cells that were subjected to scBCR-seq. Importantly, scBCR-seq identified an additional 710 candidate lineages that were not recovered as hybridomas. We synthesized, expressed and tested 93 clones from the identified lineages and found that 99% (n = 92/93) of the clones were antigen-reactive. Our results establish scBCR-seq as a powerful tool for antibody discovery.

immunology↗

bioRxiv2019

OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine

Breast cancer (BC) is a heterogeneous disease where each OncoOmics approach needs to be fully understood as a part of a complex network. Therefore, the main objective of this study was to analyze genetic alterations, signaling pathways, protein-protein interaction networks, protein expression, dependency maps and enrichment maps in 230 previously prioritized genes by the Consensus Strategy, the Pan-Cancer Atlas, the Pharmacogenomics Knowledgebase and the Cancer Genome Interpreter, in order to reveal essential genes to accelerate the development of precision medicine in BC. The OncoOmics essential genes were rationally filtered to 144, 48 (33%) of which were hallmarks of cancer and 20 (14%) were significant in at least three OncoOmics approaches: RAC1, AKT1 CCND1, PIK3CA, ERBB2, CDH1, MAPK14, TP53, MAPK1, SRC, RAC3, PLCG1, GRB2, MED1, TOP2A, GATA3, BCL2, CTNNB1, EGFR and CDK2. According to the Open Targets Platform, there are 111 drugs that are currently being analyzed in 3151 clinical trials in 39 genes. Lastly, there are more than 800 clinical annotations associated with 94 genes in BC pharmacogenomics.

genomics↗

bioRxiv2019

Pharmacogenomics, biomarker network and allele frequencies in colorectal cancer

Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Over the last decades, several studies have shown that tumor-related genomic alterations predict tumor prognosis, drug response and toxicity. These observations have led to the development of a number of precision therapies based on individual genomic profiles. As part of these approaches, pharmacogenomics analyses genomic alterations that may predict an efficient therapeutic response. Studying these mutations as biomarkers for predicting drug response is of a great interest to improve precision medicine. Here we conduct a comprehensive review of the main pharmacogenomics biomarkers and genomic alterations affecting enzyme activity, transporter capacity, channels and receptors, and therefore the new advances in CRC precision medicine to select the best therapeutic strategy in populations worldwide, with a focus on Latin America.

genomics↗

bioRxiv2019

Genomic, Ancestral and Networking Analyses of a High-Altitude Native American Ecuadorian Patient with Congenital Insensitivity to Pain with Anhidrosis

Congenital insensitivity to pain with anhidrosis (CIPA) is an extremely rare autosomal recessive disorder characterized by insensitivity to pain, inability to sweat and intellectual disability. CIPA is caused by mutations in the neurotrophic tyrosine kinase receptor type 1 gene (NTRK1) that encodes the high-affinity receptor of nerve growth factor (NGF). Patients with CIPA lack the primary afferents and sympathetic postganglionic neurons leading to lack of pain sensation and the presence of anhidrosis, respectively. Herein, we conducted a genomic analysis of 4,811 genes and 18,933 variants, including 54 mutations of NTRK1 in a high-altitude indigenous Ecuadorian patient with CIPA. As results, the patient presented 87.8% of Native American ancestry, 6.6% of African ancestry and 5.6% of European ancestry. The mutational analysis of the kinase domain of NTRK1 showed two pathogenic mutations, rs80356677 (Asp674Tyr) and rs763758904 (Arg602*). The genomic analysis showed 68 pathogenic and/or likely pathogenic variants in 45 genes, and two variants of uncertain significance in CACNA2D1 (rs370103843) and TRPC4 (rs80164537) genes involved in the pain matrix. The GO enrichment analysis showed 28 genes with relevant mutations involved in several biological processes, cellular components and molecular functions. In addition, the protein-protein interaction (PPi) networking analysis showed that NTRK1, SPTBN2 and GRM6 interact with several proteins of the pain matrix. In conclusion, this is the first time that a study associates genomic, ancestral and networking data in a high-altitude Native American Ecuadorian patient with consanguinity background in order to better understand CIPA pathogenesis.

genetics↗