Biology subjects

Malats, N.

Publications and source records attributed to Malats, N..

8 recordsLinked to original sources

bioRxiv2026

Nerve growth factor receptor identifies a basal subpopulation linked to poor prognosis and reduced immunotherapy responses in bladder cancer

PurposeBladder cancer (BLCA) is a heterogeneous tumor type. Only one third of muscle-invasive (MIBC) patients respond to immune checkpoint inhibitors (ICIs). Reliable resistance markers are needed to guide clinical decisions. We investigated the nerve growth factor receptor (NGFR) in BLCA and analyzed its correlation with disease progression and response to immunotherapy. Experimental DesignWe analyzed NGFR expression in BLCA cell lines, organoids, mouse models and patient samples. The cohorts used were The Cancer Genome Atlas (TCGA), enriched in muscle-invasive bladder cancer (MIBC) (n=407); IMvigor210, representing MIBC patients treated with ICIs (n=348); and UROMOL2, as a non-muscle-invasive bladder cancer (NMIBC)-specific cohort (n=535). IMvigor010 was also included (n=728). Patients were stratified by NGFR expression quartiles. We analyzed survival and tumor subtypes and performed stromal deconvolution and functional profiling. We assessed stemness- and invasion-related features in SCaBER cells. ResultsNGFR marks a basal tumor cell subcluster and is independently associated with poor prognosis in TCGA and IMvigor210. NGFR-high tumors show stromal content enriched in cancer-associated fibroblasts, lower neoantigen burden, higher CD8+ T effector signature together with an immune-excluded phenotype, and a CAF-specific TGF{beta} signature. In the immunotherapy-treated cohort, high NGFR expression was also associated with poorer outcome. Functionally, NGFR appears to promote a stem-like/pro-invasive program in BLCA cells. ConclusionsNGFR identifies a basal-like BLCA subpopulation linked to poor survival, while its association with immunotherapy response requires further validation. In addition, our in vitro analyses support a role of NGFR in stem-like and invasive traits, highlighting its relevance as a biomarker in BLCA.

cancer biology↗

bioRxiv2026

Learning from Drops: AI-Guided Integration of Liquid Biopsy Features in Cancer Studies

Cancer is a major global health issue with rising incidence and mortality. Early detection, tumor characterization, and disease surveillance are crucial for timely and effective treatment, ultimately reducing mortality rates. Liquid biopsy (LB) has emerged as a valuable detection tool offering a non-invasive method to determine tumor-derived biomarkers in body fluids with demonstrated translational potential. To increase biomarker sensitivity, high-throughput sequencing platforms deliver massive volumes of data. Artificial Intelligence (AI) is pivotal in enabling huge and complex data integration. This contribution aims to assess the current state of integrative AI-based research in the LB field and provide methodological guidance. First, we conducted a PubMed search and found that the literature is sparse in studies integrating LB features, particularly by applying AI. When adopting the latter approach, defining the study objectives is crucial to guide the subsequent methodological aspects, including study design, patient selection criteria, sample size, nature of the LB features, and metadata to collect. Specifically, we propose strategies and tools for data preprocessing, including normalization and batch correction, as well as handling outliers and missing data. Furthermore, we recommend various Machine/Deep Learning approaches for feature selection techniques to ensure model robustness, and we highlight the importance of undergoing rigorous internal and external validations of the selected models. Assessing clinical utility and interpretability is often overlooked but fundamental for real-world implementation. In conclusion, we provide the LB scientific community with an AI-based methodological guidance to bridge the two fields and enhance the integrative analysis of LB features. Graphical abstractWorkchart for multiomics integrative studies in the liquid biopsy field. Note: CTCs, circulating tumor cells; ctDNA, circulating tumor-DNA; TEPs, tumor-educated platelets; miRNA, microRNA; cfRNAs, cell-free RNAs. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/724535v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1f250b2org.highwire.dtl.DTLVardef@18fe36corg.highwire.dtl.DTLVardef@19c02b9org.highwire.dtl.DTLVardef@176f6e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

DEVELOPMENT OF A CONSENSUS MOLECULAR CLASSIFIER FOR PANCREATIC DUCTAL ADENOCARCINOMA

Pancreatic ductal adenocarcinoma (PDAC) presents a significant challenge, with a five-year survival rate of approximately 10%. Tumor heterogeneity contributes to the limited effectiveness of treatments. Several tumor and stroma molecular classifiers have attempted to clarify this heterogeneity with moderate agreement. Recognizing the complexity introduced by this extensive array of taxonomies, this study aims to develop a consensus molecular classifier by including both tumor and stroma features. We integrated gene expression data through Virtual Microdissection and classified the training samples to apply Machine Learning algorithms for each previous classifier. The consensus classifier was then derived using a Markov Clustering Algorithm, and its association with overall survival was assessed. The results indicated that Elastic-Net emerged as the superior model. We identified two classes for tumor components (Consensus Classical and Consensus Non-classical) and stroma components (Consensus Normal-Immune and Consensus Activated-ECM). The consensus Random Forest achieved a balanced accuracy of 96.33% and 98.92%, respectively. While not consistent across retrospective series, the algorithm (PDAConsensus) independently predicted overall survival. We developed a robust consensus classifier for PDAC that integrates tumor and stroma features and made it accessible through the R package PDACMOC (PDACMolecularOmniClassifier, https://github.com/pavillos/PDACMOC) and a Shiny app (https://pdacmoc.cnio.es/).

bioinformatics↗

bioRxiv2024

A common CTRB misfolding variant associated with pancreatic cancer risk causes ER stress and inflammation in mice

ObjectiveGenome wide association studies have identified an exon 6 CTRB2 deletion variant that associates with increased risk of pancreatic cancer. To acquire evidence on its causal role, we developed a new mouse strain carrying an equivalent variant in Ctrb1, the mouse orthologue of CTRB2. DesignWe used CRISPR/Cas9 to introduce a 707bp deletion in Ctrb1 encompassing exon 6 (Ctrb1{Delta}exon6). This mutation closely mimics the human deletion variant. Mice carrying the mutant allele were extensively profiled at 3 months to assess their phenotype. ResultsCtrb1{Delta}exon6 mutant mice express a truncated CTRB1 that accumulates in the ER. The pancreas of homozygous mutant mice displays reduced chymotrypsin activity and total protein synthesis. The histological aspect of the pancreas is inconspicuous but ultrastructural analysis shows evidence of dramatic ER stress and cytoplasmic and nuclear inclusions. Transcriptomic analyses of the pancreas of mutant mice reveals acinar program down-regulation and increased activity of ER stress-related and inflammatory pathways. Heterozygous mice have an intermediate phenotype. Agr2 is one of the most up-regulated genes in mutant pancreata. Ctrb1{Delta}exon6 mice exhibit impaired recovery from acute caerulein-induced pancreatitis. Administration of TUDCA or sulindac partially alleviates the phenotype. A transcriptomic signature derived from the mutant pancreata is significantly enriched in normal human pancreas of CTRB2 exon 6 deletion variant carriers from the GTEx cohort. ConclusionsThis mouse strain provides formal evidence that the Ctrb1{Delta}exon6 variant causes ER stress and inflammation in vivo, providing an excellent model to understand its contribution to pancreatic ductal adenocarcinoma development and to identify preventive strategies. SUMMARY BOX What is already known about this subject?- CTRB2 is one of the most abundant proteins produced by human pancreatic acinar cells. - A common exon 6 deletion variant in CTRB2 has been associated with an increased risk of pancreatic ductal adenocarcinoma. - Misfolding of digestive enzymes is associated with pancreatic pathology. What are the new findings?- We developed a novel genetic model that recapitulates the human CTRB2 deletion variant in the mouse orthologue, Ctrb1. - Truncated CTRB1 misfolds and accumulates in the ER; yet, mutant mice display a histologically normal pancreas at 3 months age. - CTRB1 and associated chaperones colocalize in the ER, the cytoplasm, and the nucleus of acinar cells. - Transcriptomics analysis reveals reduced activity of the acinar program and increased activity of pathways involved in ER stress, unfolded protein response, and inflammation. - Mutant mice are sensitized to pancreatic damage and do not recover properly from a mild caerulein-induced pancreatitis. - TUDCA administration partially relieves the ER stress in mutant mice. How might it impact on clinical practice in the foreseeable future?- The new mouse model provides a tool to identify the mechanisms leading to increased pancreatic cancer risk in CTRB2 exon 6 carriers. - The findings suggest that drugs that cause ER stress relief and/or reduce inflammation might provide preventive opportunities.

cancer biology↗

bioRxiv2021

GATA4 and GATA6 loss-of-expression is associated with extinction of the classical programme and poor outcome in pancreatic ductal adenocarcinoma

ObjectiveGATA6 is a master regulator of pancreatic differentiation and a key regulator of the classical phenotype in pancreatic ductal adenocarcinoma (PDAC). Low GATA6 expression is associated with poor patient outcome. GATA4 is the second most expressed GATA factor in the pancreas. The aim was to assess whether, and how, GATA4 contributes to PDAC phenotype and to analyze the association of expression with clinical outcome. DesignWe analyzed PDAC transcriptomic data, stratifying cases according to GATA4 and GATA6 expression, and identified differentially expressed genes and pathways. A multicenter TMA study to assess GATA4 and GATA6 expression in PDAC samples (n=745) from patients undergoing tumour resection was performed using immunohistochemistry with antibodies of validated specificity. GATA4 and GATA6 levels were dichotomized into high/low categorical variables; association with outcome was assessed using univariable and multivariable Cox regression models. ResultsSubtype classification using transcriptomic data revealed that GATA4 mRNA is enriched in classical, compared to basal-like tumours. We classified samples in 4 groups as high/low for GATA4 and GATA6. Reduced expression of GATA4 did not have a major transcriptional impact. However, concomitant low expression of GATA4 enhanced the transcriptomic effects of GATA6 low expression. Reduced expression of both proteins in tumours was associated with the worst patient survival. GATA4 and GATA6 expression significantly decreased in metastases and negatively correlated with basal markers. ConclusionsOur analyses uncover a cooperative interaction between GATA4 and GATA6 to maintain the classical PDAC phenotype and provide compelling clinical rationale for assessing their expression as biomarkers of poor prognosis. SUMMARY BOXO_ST_ABSWhat is already known about this subject?C_ST_ABS- Patients with classical-type PDAC have a better outcome - Retrospective analyses suggest that classical-type PDAC is more sensitive to 5-FU-based chemotherapy - GATA6 is a surrogate biomarker of classical tumours and its expression is associated with better survival - GATA4 and GATA6 have overlapping and unique functions during pancreatic and gastrointestinal development What are the new findings?- Tumours displaying only low GATA4 expression have a transcriptomic profile similar to those with preserved expression of both transcription factors - Combined low expression of GATA4 and GATA6 has the highest transcriptomic impact - In a large multicenter tissue microarray study, patients with tumours showing low expression of both GATA4 and GATA6 have the worst overall survival - Low expression of GATA4 and GATA6 is an independent predictor of survival in patients with resectable PDAC - GATA4 levels are down-regulated in liver metastases and are negatively correlated with basal markers such as KRT5/6, KRT14, and TP63 How might it impact on clinical practice in the foreseeable future?- The combined assessment of GATA4 and GATA6 expression may improve prognostic stratification of patients with PDAC - Prospective studies should confirm whether GATA4 and GATA6 expression is also predictive of response to chemotherapy in PDAC patients

cancer biology↗

bioRxiv2019

Immunohistochemistry-based taxonomical classification of bladder cancer predicts response to neoadjuvant chemotherapy

Platinum-based neoadjuvant chemotherapy (NAC) increases the survival of patients with organ-confined urothelial bladder cancer (UBC). Because not all patients benefit from treatment, NAC has not been widely applied in the clinical setting. There is strong evidence, based on retrospective studies, that patients with Basal/Squamous (BASQ)-like tumours present with more advanced disease and have worse prognosis; global transcriptomics can identify tumour subtypes associated with response to NAC. We aimed to investigate whether tumour immunohistochemical (IHC) subtyping predicts NAC response. Patients with muscle-invasive UBC having received platinum-based NAC were identified in two hospitals in Spain. Tissue microarrays were constructed; RNA and DNA were extracted from full sections. Nanostring analysis and immunohistochemistry to identify BASQ-like tumours and mutational analysis of UBC oncogenes. We used hierarchical clustering to classify 126 tumours and adjusted logistic regression to assess association with treatment response. Outcomes were progression-free survival and disease-specific survival; univariable and multivariate Cox regression models were applied. We found very high concordance between mRNA and protein for the 4 markers analyzed. We identified three main subgroups: BASQ-like (FOXA1/GATA3 low; KRT5/6/14 high), Luminal-like (FOXA1/GATA3 high; KRT5/6/14 low), and mixed-cluster (FOXA1/GATA3 high; KRT5/6 high; KRT14 low). Patients with BASQ-like tumours were more likely to achieve a pathological response to NAC, displaying a disease-specific survival similar to that of the remaining patients. In conclusion, patients with BASQ-like tumours - identified through simple and robust immunohistochemistry - have a higher likelihood of undergoing a pathological complete response to NAC. Prospective validation in independent series is required.\n\nNovelty and impactNeoadjuvant chemotherapy is an important component of the management of patietns with muscle-invasive bladder cancer but improved stratification is necessary. This retrospective study shows that patients with BASQ-like tumors can be identified using immunohistochemistry on paraffin-embedded tissue and are 4-fold more likely to achieve a pathological complete response to platinum-based NAC. The disease-specific survival of patients with BASQ-like tumours treated with NAC was not different from that of other tumour subtypes.

pathology↗

bioRxiv2018

The consensus molecular classification of muscle-invasive bladder cancer

Muscle-Invasive Bladder Cancer (MIBC) is a molecularly diverse disease with heterogeneous clinical outcomes. Several molecular classifications have been proposed, yielding diverse sets of subtypes, which hampers the clinical implications of such knowledge. Here, we report the results of a large international effort to reach a consensus on MIBC molecular subtypes. Using 1750 MIBC transcriptomes and a network-based analysis of six independent MIBC classification systems, we identified a consensus set of six molecular classes: Luminal Papillary (24%), Luminal Non-Specified (8%), Luminal Unstable (15%), Stroma-rich (15%), Basal/Squamous (35%), and Neuroendocrine-like (3%). These consensus classes differ regarding underlying oncogenic mechanisms, infiltration by immune and stromal cells, and histological and clinical characteristics. This consensus system offers a robust framework that will enable testing and validating predictive biomarkers in future clinical trials.

cancer biology↗

bioRxiv2017

Transcriptional regulation by NR5A2 couples cell differentiation and inflammation in the pancreas

Tissue-specific differentiation and inflammatory programmes are thought to independently contribute to disease. The orphan nuclear receptor NR5A2 is a key regulator of pancreas differentiation and SNPs in or near the human gene are associated with risk of pancreatic cancer. In mice, Nr5a2 heterozygosity sensitizes the pancreas to damage, impairs regeneration, and cooperates with mutant KRas in tumor progression. Through global transcriptomic analysis, we uncover a basal pre-inflammatory state in the pancreas of Nr5a2 heterozygous mice that is reminiscent of pancreatitis-induced inflammation and is conserved in histologically normal human pancreata with reduced NR5A2 mRNA expression. In Nr5a2+/- mice, Nr5a2 undergoes a dramatic transcriptional switch relocating from tissue-specific to inflammatory loci thereby promoting AP-1-dependent gene transcription. Importantly, deletion of c-Jun in the pancreas of these mice rescues the pre-inflammatory phenotype and the defective regenerative response to damage. These findings provide compelling evidence that the same transcriptional networks supporting homeostasis in normal tissue can be subverted to foster inflammation upon genetic or environmental constraints.

cancer biology↗