Biology subjects

Madrid, L.

Publications and source records attributed to Madrid, L..

6 recordsLinked to original sources

bioRxiv2026

WNT-driven chromosomal instability as a biomarker for PORCN inhibition

Targeting Porcupine (PORCN), a key regulator of the WNT-signalling pathway, has shown therapeutic potential in multiple cancers. Despite strong target engagement and acceptable safety profiles through human phase I clinical trials, low phase II efficacy has stalled further clinical development. Given that aberrant WNT signalling can drive tumorigenesis by inducing chromosomal instability (CIN), we hypothesised that genomic CIN signatures might serve as a predictive biomarker to help improve response rates. Using a controlled in vitro model and single-cell whole-genome sequencing, we demonstrate that acute WNT-activation directly induces three distinct types of CIN: whole genome duplication, replication stress, and impaired homologous recombination. We translated these observations into a composite CIN signature biomarker that significantly correlated with both genetic dependency and pharmacological inhibition of PORCN across 195 and 24 cell lines, respectively. Through a large-scale meta-analysis of patient-derived and cell line xenografts, we established that this composite CIN signature biomarker quantitatively predicts in vivo PORCN inhibitor sensitivity (R=-0.71, p<0.002). By applying an optimised biomarker threshold, refined through modelling of human patient data, to the The Cancer Genome Atlas dataset, we successfully retrospectively modelled previous trial results and identified gastroesophageal cancers as a high-prevalence (36.6%) indication for future development. We validated this strategy in a mouse clinical trial of gastric and esophageal xenografts, where biomarker-guided stratification achieved an objective response rate of 60% and significantly decreased risk of progression (HR=0.21, p=0.0345). These data establish an actionable, trail-ready framework for further PORCN inhibitor clinical development.

cancer biology↗

bioRxiv2025

Synaptic changes contribute to persistent extra-motor behaviour deficits in the rNLS8 TDP-43 mouse model of amyotrophic lateral sclerosis

Extra-motor symptoms are increasingly recognised in amyotrophic lateral sclerosis (ALS), encompassing cognitive, social, and behavioural deficits that can substantially impact quality of life. TAR DNA binding protein 43 (TDP-43) pathology is the central disease marker of almost all cases of ALS and approximately half of all frontotemporal dementia (FTD). However, the mechanisms linking TDP-43 pathology with extra-motor symptoms in TDP-43-associated neurodegenerative diseases remain unresolved. In this study, we used the rNLS8 mouse model, which expresses human TDP-43 with an ablated nuclear localisation sequence (hTDP-43∆NLS) in a doxycycline-regulatable manner causing progressive motor decline reminiscent of ALS, to delineate the molecular changes associated with disease-relevant phenotypes. We found that in addition to previously reported dramatic motor decline, rNLS8 mice also develop extra-motor phenotypes consistent with FTD, including disinhibition-like and anxiety-like behaviours, and social interaction impairments. These changes began in the earliest disease stages and remained readily detectable even when rNLS8 mice became severely motor impaired. Notably, extra-motor deficits persisted in rNLS8 mice that had recovered motor function upon hTDP-43∆NLS transgene suppression, regardless of whether recovery was initiated at timepoints prior to or after overt neurodegeneration begins. Transcriptomic analysis of rNLS8 mouse cortex tissues revealed early alterations in expression of 321 genes, most notably involving neuroinflammatory-related pathway activation, and all but 2 of these genes returned to control levels upon suppression of hTDP-43∆NLS expression. Further, 814 genes showed differential exon usage, indicating changes in alternative splicing, in rNLS8 mouse cortex. Of these, differential exon usage of 10 neuronal genes persisted after hTDP-43∆NLS transgene suppression, including synapse component genes Nrxn1, Unc13a, and Gls. Similarly, proteomics analysis of the cortex of rNLS8 mice revealed depletion of synaptic proteins, particularly those involved in glutamatergic signalling pathways, which also persisted following hTDP-43∆NLS transgene suppression. Similar glutamatergic pathway changes were detected in human ALS and FTD post-mortem cortex tissues. Our findings indicate that extra-motor phenotypes emerge early in disease in rNLS8 mice and remain evident despite progressive motor impairments. Further, extra-motor phenotypes persist even upon motor recovery, correlating with specific synaptic gene expression and splicing changes. Overall, this study suggests the potential utility of an expanded suite of behavioural paradigms in preclinical testing using rNLS8 mice, with enhanced relevance to the diversity of TDP-43 proteinopathies including FTD. Our findings further suggest that targeting glutamatergic synaptic components may be an avenue to correct extra-motor deficits associated with TDP-43 pathology.

neuroscience↗

bioRxiv2023

Predicting response to cytotoxic chemotherapy

Cytotoxic chemotherapies have been a crucial part of cancer treatment for over 40 years. While their primary target is cancer cells, they can also harm normal cells, resulting in dose-limiting toxicity. Most chemotherapies were approved before the advent of precision biomarkers, as such, many patients experience severe toxic side effects without any benefit. To address this challenge, we have developed three precision biomarkers to predict response to platins, taxanes, and anthracyclines. Based on chromosomal instability (CIN) signatures, these biomarkers can be computed from a single genomic test. For platins and taxanes, we used CIN signatures related to impaired homologous recombination, while for anthracyclines, we discovered a CIN signature representing micronuclei induction which predicts resistance. In a clinical study involving 41 high-grade serous ovarian cancers, patients predicted to be sensitive by these biomarkers showed significantly prolonged progression-free survival. To further validate the effectiveness of the taxane and anthracycline predictors, we conducted a retrospective randomised control study involving 182 ovarian and 219 breast cancer patients. Patients predicted as resistant showed increased risk of time to treatment failure compared to standard of care, hazard ratios of 1.73 (95%CI=0.98-3.07) for taxane in ovarian, 3.67 (95%CI=2.12-6.34) for taxane in breast, and 1.93 (95%CI=1.22-3.04) for doxorubicin in ovarian. We also found that liquid biopsies can be used to make these predictions in up to 30% of ovarian cancer patients. Our findings highlight the clinical value of CIN signatures in predicting treatment response to various chemotherapies across multiple different types of cancer. The ability to quantify multiple CIN signature biomarkers using a single genomic test offers a unified approach to guide treatment decisions for cytotoxic chemotherapies. Ultimately, this has the potential to transform the current one-size-fits-all chemotherapy approach into a more precise and tailored form of medicine.

cancer biology↗

bioRxiv2020

Biomarkers to distinguish bacterial from viral pediatric clinical pneumonia in a malaria endemic setting

BACKGROUNDDifferentiating the etiology of acute febrile respiratory illness in children is a challenge in low-income, malaria-endemic settings because the main pathogens responsible (viruses, bacteria, and malaria parasites) overlap in clinical presentation and frequently occur together as mixed infections. The critical task is to rapidly identify bacterial pneumonia to enable appropriate antibiotic treatment, ideally at point of care. Current diagnostic tests are insufficient and there is a need for the discovery and development of new tools. Here we report the identification of a unique biomarker signature that can be identified in blood samples. METHODSBlood samples from 195 pediatric Mozambican patients with clinical pneumonia were analyzed with an aptamer-based high dynamic range assay to quantify [~]1200 proteins. For discovery of new biomarkers, we identified a training set of patient samples in which the underlying etiology of the pneumonia was established as bacterial, viral or malaria. Proteins whose abundances varied significantly between patients with verified etiologies (FDR<0.01) formed the basis for predictive diagnostic models that were created using machine learning techniques (Random Forest, Elastic Net). These models were validated on a dedicated test set of samples. RESULTS219 proteins had significantly different abundances between bacterial and viral infections, and 151 differed between bacterial infections and a mixed pool of viral and malaria infections. Predictive diagnostic models achieved >90% sensitivity and >80% specificity, regardless of whether one or two pathogen classes were present. Bacterial pneumonia was strongly associated with markers of neutrophil activity, in particular neutrophil degranulation. Degranulation markers included HP, LCN2, LTF, MPO, MMP8, PGLYRP1, RETN, SERPINA1, S100A9, and SLPI. CONCLUSIONBlood protein signatures highly associated with neutrophil biology reliably differentiated bacterial pneumonia from other causes. With appropriate technology, these markers could provide the basis for a rapid diagnostic for field-based triage for antibiotic treatment of pediatric pneumonia.

genomics↗

bioRxiv2020

Autosomal Recessive Alzheimer disease (arAD): homozygosity mapping of genomic regions containing arAD loci

Long runs of homozygosity (ROH) are contiguous stretches of homozygous genotypes, which are a footprint of recent inbreeding and recessive inheritance. The presence of recessive loci is suggested for Alzheimers disease (AD). However, the search for recessive variants has been poorly assessed to date. To investigate homozygosity in AD, we performed a fine-scale ROH analysis including 21,100 individuals from 10 cohorts of European ancestry (11,919 AD cases and 9,181 controls). We detected an increase of homozygosity in AD cases compared to controls [{beta}FROH (CI95%) = 0.051 (0.023 - 0.078); P = 3.25 x 10-4]. ROHs increasing the risk of AD (OR > 1) were significantly overrepresented compared to ROHs increasing protection (p < 2.20 x 10-16). The top associated ROH with AD risk ({beta} (CI95%) = 1.09 (0.48 - 1.48), p value = 9.03 x 10-4) was detected upstream the HS3ST1 locus (chr4:11,189,482-11,305,456), previously related to AD. Next, to construct a homozygosity map of AD cases, we selected ROHs shared by inbred AD cases extracted from an outbred population. We used whole-exome sequencing data from 1,449 individuals from the Knight-ADRC-NIA-LOAD (KANL) cohort to identify potential recessive variants in candidate ROHs. We detected a candidate marker, rs117458494, mapped in the SPON1 locus, which has been previously associated with amyloid metabolism. Here, we provide a research framework to look for recessive variants in AD using outbred populations. Our results showed that AD cases have enriched homozygosity, suggesting that recessive effects may explain a proportion of AD heritability.

genetics↗

bioRxiv2019

Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer disease and three causality networks of AD: the GR@ACE project.

BackgroundGenetics plays a major role in Alzheimers Disease (AD). To date, 40 genes associated with AD have been identified, although most remain undiscovered. Clinical, neuropathological and genetic variability might impact genetic discoveries and complicate dissection of the biological pathways underlying AD. MethodsGR@ACE is a genome-wide study of dementia and its clinical endophenotypes that encompasses 4,120 cases and 3,289 controls from Spain. GR@ACE phenotypes were defined according to ADs clinical certainty and the presence of vascular co-morbidity. To explore whether clinical endophenotypes reflect variation in underlying biological pathways, we first assessed the impact of known AD loci across endophenotypes to generate three loci categories. Next, we incorporated gene co-expression data and conducted pathway analysis on each category. To assess the impact of heterogeneity in the GWAS findings, the GR@ACE series were meta-analyzed with: 1) genotype-level data from dbGaP (N=21,235); and 2) summary statistics from IGAP Stages I and II (n=61,571 and n=81,455 respectively). FindingsWe classified known AD loci in three categories, which might reflect the disease clinical heterogeneity, from vascular and mixed forms to pure AD pathology. Immune system pathways were detected in all categories. Intriguingly, vascular processes were only detected as a causal mechanism in probable AD. A meta-analysis of GR@ACE with additional GWAS datasets revealed the ANKRD31-rs4704171 signal in the HMGCR genomic region. We confirmed NDUFAF6-rs10098778 and SCIMP-rs7225151, which were previously detected by IGAP, to be suggestive signals. We also confirmed CD33-rs3865444 to be genome-wide significant. InterpretationThe regulation of vasculature is a prominent causal component of probable AD. In that context, cerebral amyloid angiopathy, the unique identified link between the vascular and amyloid hypotheses, deserves further investigation. The GR@ACE meta-analysis revealed novel AD genetic signals. GWAS results are strongly driven by the presence of clinical heterogeneity in the AD series. FundingGrifols SA, Fundacion bancaria "La Caixa", Fundacio ACE and ISCIII (Instituto de Salud Carlos III).

neuroscience↗