Biology subjects

Fuentes, M.

Publications and source records attributed to Fuentes, M..

6 recordsLinked to original sources

bioRxiv2026

Targeting DNA Methylation Reactivates Type I Interferon Signalling in Bone-Metastatic Breast Cancer

Bone metastasis remains a major clinical challenge in advanced breast cancer. Downregulation of type I interferon signalling, a critical immunomodulatory pathway in anti-cancer immunity and disease progression, is a defining feature of this process. Here, we utilised an IFN-reporter system to perform unbiased epigenetic compound screens to identify agents that could restore type I IFN signalling. This screen identified Decitabine, a DNA hypomethylating agent, that enhanced tumor immunogenicity across a broad range of mouse and human breast cancer cell lines, including bone-derived lines. Mechanistically, suppression of interferon-stimulated genes is highly correlated with elevated DNMT1 expression in bone metastasis compared with primary tumor, in both mouse models and matched human samples. Decitabine treatment was sufficient to reactivate interferon stimulated genes in bone-derived 4T1.2 cell lines via hypomethylation of type I interferon pathway gene promoter regions. Correspondingly, in the syngeneic 4T1.2 metastasis mouse model, Decitabine treatment conferred a survival benefit and reduced metastatic potential, particularly in bone. Our findings reveal DNA methylation as a key regulator of the transcriptional programs underlying bone metastasis, providing mechanistic insight into how Decitabine reactivates type I interferon signalling and reduces metastatic potential, highlighting epigenetic reprogramming as a promising approach for targeting metastatic breast cancer. STATEMENT OF SIGNIFICANCEBone metastasis remains a major clinical challenge and a key mechanism of progression to bone is the suppression of tumor-inherent type I interferon signalling. We identified Decitabine, a DNA hypomethylating agent, as a promising therapeutic agent to enhance tumor immunogenicity across a broad range of breast cancer cell lines, including bone metastasis-derived lines. Our findings support DNA methylation as a key regulator of transcriptional programs associated with bone metastatic progression, and provide mechanistic insight into how Decitabine reactivates type I interferon signalling and reduces metastatic potential in vivo. These results highlight epigenetic reprogramming as a promising approach for targeting metastatic breast cancer.

Cancer Biology↗

bioRxiv2025

Population-level migration modeling of North American birds through data integration with BirdFlow

BackgroundAccurate information on population-level movements of migratory animals is essential for understanding migration and for designing effective conservation strategies in a changing world. Yet such information remains scarce for most migratory species due to the effort and expense needed to collect data across their full distribution ranges. BirdFlow is a probabilistic modeling framework that infers population-level movements from weekly species distribution maps produced by the participatory science project eBird. However, BirdFlow models have only been tuned for a handful of species using high-resolution individual tracking data, which is not available for most migratory species. MethodsHere, we introduce a general tuning and evaluation framework for BirdFlow that enables the first large-scale integration of distributional and individual-level data to infer animal movement across continents and hundreds of migratory species, eliminating reliance on any single individual-tracking data source. By generalizing the BirdFlow model parametrization, we enable tuning and validation using multiple complementary data sources, including GPS tracks, banding recoveries, and radio telemetry data from the Motus Wildlife Tracking System. We investigate the efficacy of this approach by (1) investigating predictive performance compared to null models; (2) validating the biological plausibility of BirdFlow models by comparing movement properties such as route straightness, number of stopovers, and migration speed between model-generated routes and real movement tracks; and (3) comparing the performance of models tuned on species-specific movement data to models tuned using hyperparameters transferred from other species. ResultsOur results show that BirdFlow models produced by the new tuning framework achieve biologically realistic performance, even for prediction horizons of thousands of kilometers and several months. When species-specific data are unavailable, models can still be tuned using data from other phylogenetically adjacent species to achieve improved performance. ConclusionsBy integrating eBird Status & Trends abundance surfaces with data from banding recaptures, radio telemetry, and GPS tracking, we scale BirdFlow model to 153 North American migratory species, representing the first collection of continental-scale population-level movement and forecasting models. Species-specific tuning improves population-level movement forecasts, while taxonomically informed hyperparameter transfer supports the modeling of data-limited species. Overall, our work offers a foundation for more accurate predictions across hundreds of species for research in ecology and conservation, disease surveillance, aviation, and public outreach.

ecology↗

bioRxiv2024

Ancient genomics reveals a genetic continuum with dual structure in the Classic Copan

Copan was a major capital at the southeasternmost of the Maya civilization, serving as a crossroads connecting Central and South America. In 426/427 CE, the city witnessed the establishment of a royal dynasty, which endured for approximately 400 years. Despite extensive historical and archaeological records, there remains limited information regarding the genetic origins of people who resided in Copan. Here, we present seven Classic Copan genomes including an enigmatic dynastic ruler and his sacrificed companion. Our analysis identifies a high genetic affinity of the Classic Copan with present-day Maya. Both groups exhibit an admixture of Mesoamerican and South American Farmer (SAF) ancestry, with a shift in a dominant component from SAF to Mesoamerican. At the individual level, commoners show a more prominent SAF ancestry, while the royal individual demonstrates nearly equal contributions from two ancestors. These results highlight a dual ancestral structure in this geographic extreme of the Classic Maya state, uncovering a cline of Mesoamerican ancestry across individuals.

evolutionary biology↗

bioRxiv2023

Intermediate molecular phenotypes to identify genetic markers of anthracycline-induced cardiotoxicity risk

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex disease whose polygenic component is mainly unidentified. We propose that levels of intermediate molecular phenotypes in the myocardium associated with histopathological damage could explain CDA susceptibility; so that variants of genes encoding these intermediate molecular phenotypes could identify patients susceptible to this complication. A genetically heterogeneous cohort of mice generated by backcrossing (N = 165) was treated with doxorubicin and docetaxel. Cardiac histopathological damage was measured by fibrosis and cardiomyocyte size by an Ariol slide scanner. We determine intramyocardial levels of intermediate molecular phenotypes of CDA associated with histopathological damage and quantitative trait loci (ipQTLs) linked to them. These ipQTLs seem to contribute to the missing heritability of CDA because they improve the heritability explained by QTL directly linked to CDA (cda-QTLs) through genetic models. Genes encoding these molecular subphenotypes were evaluated as genetic markers of CDA in three cancer patient cohorts (N = 517) whose cardiac damage was quantified by echocardiography or Cardiac Magnetic Resonance. Many SNPs associated with CDA were found using genetic models. LASSO multivariate regression identified two risk score models, one for pediatric cancer patients and the other for women with breast cancer. Molecular intermediate phenotypes associated with heart damage can identify genetic markers of CDA risk, thereby allowing a more personalized patient management. A similar strategy could be applied to identify genetic markers of other complex trait diseases.

genetics↗

bioRxiv2022

E4F1 COORDINATES PYRUVATE METABOLISM AND THE ACTIVITY OF THE ELONGATOR COMPLEX TO ENSURE PROTEIN TRANSLATION FIDELITY DURING NEURONAL DEVELOPMENT

Pyruvate metabolism defects lead to severe neuropathies such as the Leigh syndrome (LS) but the molecular mechanisms underlying neuronal cell death remain poorly understood. Here, we unravel a connection between pyruvate metabolism and the regulation of the epitranscriptome that is relevant to LS pathogenesis. We identified the transcription factor E4F1 as a key coordinator of AcetylCoenzyme A (AcCoA) production by the pyruvate dehydrogenase complex (PDC) and its utilization as an essential co-factor by the Elongator complex to acetylate tRNAs at the wobble position uridine 34 (U34). E4F1-mediated direct transcriptional regulation of Dlat and Elp3, two genes encoding key subunits of the PDC and of the Elongator complex, respectively, ensured proper translation fidelity and cell survival in the central nervous system (CNS) during mouse embryonic development. Furthermore, analysis of PDH-deficient cells highlighted a crosstalk linking the PDC to ELP3 expression that is perturbed in LS patients.

developmental biology↗

bioRxiv2022

BirdFlow: Learning Seasonal Bird Movements from Citizen Science Data

Large-scale monitoring of seasonal animal movement is integral to science, conservation, and outreach. However, gathering representative movement data across entire species ranges is frequently intractable. Citizen science databases collect millions of animal observations throughout the year, but it is challenging to infer individual movement behavior solely from observational data. We present BO_SCPLOWIRDC_SCPLOWFO_SCPLOWLOWC_SCPLOW, a probabilistic modeling framework that draws on citizen science data from the eBird database to model the population flows of migratory birds. We apply the model to 11 species of North American birds, using GPS and satellite tracking data to tune and evaluate model performance. We show that BO_SCPLOWIRDC_SCPLOWFO_SCPLOWLOWC_SCPLOW models can accurately infer individual seasonal movement behavior directly from eBird relative abundance estimates. Supplementing the model with a sample of tracking data from wild birds improves performance. Researchers can extract a number of behavioral inferences from model results, including migration routes, timing, connectivity, and forecasts. The BO_SCPLOWIRDC_SCPLOWFO_SCPLOWLOWC_SCPLOW framework has the potential to advance migration ecology research, boost insights gained from direct tracking studies, and serve a number of applied functions in conservation, disease surveillance, aviation, and public outreach.

ecology↗