Biology subjects

Lozano, J. J.

Publications and source records attributed to Lozano, J. J..

9 recordsLinked to original sources

bioRxiv2025

ZEB1 regulates BCL2 in cancer-associated fibroblasts to promote cholangiocarcinoma chemoresistance to gemcitabine and cisplatin

Intrahepatic cholangiocarcinoma (iCCA) is an agressive tumour from the biliary tree that is characterized by a prominent desmoplastic stroma mainly composed of cancer-associated fibroblasts (CAF) and a poor prognosis due to its late clinical presentation and the lack of effective non-surgical treatments. Current therapies still include chemotherapeutic combinations of gemcitabine and cisplatin for the majority of the patients showing poor results due the apparition of resistance. This situation led us to interrogate the potential role in the development of chemoresistance of ZEB1, an EMT-inducing transcription factor (EMT-TF) that we previously identified as a pro tumorigenic factor in tumour cells and CAF of iCCA. By analysing human CCA samples and sc-RNAseq public databases, we show here that ZEB1 is present in the tumour microenvironment of all iCCA patients tested and is prominently expressed by CAF. Using cellular models of CAF, we show that cells depleted for ZEB1 are more sensitive to gemcitabine and cisplatin, via a mechanism involving the regulation of the anti-apoptotic gene BCL2. Moreover, ZEB1 expressing CAF protect iCCA tumour cells against the toxicity of the chemotherapeutic drugs, an event that could be reversed by a BCL2 inhibitor venetoclax. Therefore, our results point to the use of BCL2 inhibitors to improve the efficacy of current chemotherapeutic regimens of gemcitabine and cisplatin in iCCA patients.

cancer biology↗

bioRxiv2025

Patient-derived liver biopsy organoids enable precision alcohol-associated liver disease modeling

Background & AimsAlcohol-associated liver disease (ALD) is a major cause of liver disease worldwide with scarce therapeutic options. Animal models poorly recapitulate advanced ALD precluding the development of new treatments. Organoids have emerged as a powerful human-based preclinical tool. However, current patient-derived liver organoids fail to recapitulate the epithelial heterogeneity and its generation requires liver surgical resections, thus limiting personalized disease modeling. Here, we report the development of organoids from liver needle biopsies (b-Orgs) from patients with ALD. Methodsb-Orgs were generated from tru-cut biopsies from patients at early (n=28) and advanced (n=34) stages of ALD. b-Orgs were characterized by immunofluorescence, bulk and single cell RNA-sequencing and compared to parental tissues. b-Orgs were used to model ALD progression, identify pathogenic drivers, induce alcohol-associated hepatitis (AH) and evaluate response to prednisolone. ResultsPhenotypic and functional analysis of b-Orgs showed hepatocyte- enriched features. Single-cell RNA-sequencing revealed a heterogeneous cell composition comprising hepatocyte, biliary and progenitor populations, mirroring the epithelial landscape found in patients with advanced ALD. Moreover, b-Orgs preserved disease-stage features and allowed to identify the association of ELF3 with cell plasticity and disease progression. Finally, stimulation of b-Orgs with drivers of ALD induced pathophysiological features of alcohol-associated hepatitis, including ROS production, lipid accumulation, inflammation and decreased cell proliferation, which were mitigated in response to prednisolone. Conclusions Overall, we provide a human-based model that recapitulates epithelial complexity and patient specific features, allowing to identify drivers of cell plasticity and expanding organoid-based liver disease modeling for personalized medicine. Impact and implications Here, we describe the generation of biopsy-derived organoids (b-Orgs) from patients with liver disease. b-Orgs reproduce the liver epithelial cell composition found in patients liver tissue and are efficiently generated from different stages of the disease, providing a platform for patient- tailored disease modeling and drug testing.

cell biology↗

bioRxiv2024

Trajectory analysis of hepatic stellate cell differentiation reveals metabolic regulation of cell commitment and fibrosis

Defining the trajectory of cells during differentiation and disease offers the possibility to understand the mechanisms driving cell fate and identity. However, trajectories of human cells are largely unexplored. By investigating the proteome trajectory of iPSCs differentiation to hepatic stellate cells (dHSCs), we identified RORA as a key transcription factor governing the metabolic reprogramming of HSCs necessary for HSCs commitment, identity, and activation. Using RORA deficient iPSCs and pharmacologic interventions, we showed that RORA is required for mesoderm differentiation and prevents dHSCs activation by reducing the high energetic state of the cells. While RORA knockout mice had enhanced fibrosis, RORA agonists rescued multi- organ fibrosis in in vivo models. RORA expression was consistently found to be negatively correlated with liver fibrosis and HSCs activation markers in patients with liver disease. This study reveals that RORA regulates cell metabolic plasticity, crucial for mesoderm differentiation, pericyte quiescence, and fibrosis, influencing cell commitment and disease mechanisms. SummaryThis study describes the trajectory of induced pluripotent stem cells (iPSCs) differentiation to hepatic stellate cells (dHSCs). We identify RAR-related orphan receptor alpha (RORA) as a transcription factor essential for mesoderm commitment and dHSCs identity and fibrogenic activation by regulating metabolic plasticity.

cell biology↗

bioRxiv2024

Glutaminase as a metabolic target of choice to counter acquired resistance to Palbociclib by colorectal cancer cells

Several mechanisms of resistance of cancer cells to cyclin-dependent kinase inhibitors (CDKi) have been identified, including the upregulation of metabolic regulators such as glutaminase. However, whether such mechanisms and targets are optimal has not been determined. Here, we have systematically analyzed metabolic reprogramming in colorectal cancer cells exposed to Palbociclib, a CDKi selectively targeting CDK4/6, or Telaglenestat, a selective glutaminase inhibitor. Through multiple approaches, we show that Palbociclib and Telaglenestat elicit complementary metabolic responses and are thus uniquely suited to counter the metabolic reprogramming induced by the reciprocal drug. As such, while Palbociclib induced reduced tumor growth in vivo, and Telaglenestat did not show a significant effect, the drug combination displayed a strong synergistic effect on tumor growth. Likewise, initial responses to Palbociclib were followed by signs of adaptation and resistance, which were prevented by combining Palbociclib with Telaglenestat. In conclusion, combination with Telaglenestat optimally forestalls acquired resistance to Palbociclib in cancer cells.

cancer biology↗

bioRxiv2023

Metabolic and mitochondria alterations induced by SARS-CoV-2 accessory proteins ORF3a, ORF9b, ORF9c and ORF10

Antiviral signaling, immune response and cell metabolism in human body are dysregulated by SARS-CoV-2, the causative agent of the COVID-19. Here, we show that SARS-CoV-2 accessory proteins ORF3a, ORF9b, ORF9c and ORF10 induce a significant mitochondrial and metabolic reprogramming in A549 lung epithelial cells. While all four ORFs caused mitochondrial fragmentation and altered mitochondrial function, only ORF3a and ORF9c induced a marked structural alteration in mitochondrial cristae. ORF9b, ORF9c and ORF10 induced largely overlapping transcriptomes. In contrast, ORF3a induced a distinct transcriptome, including the downregulation of numerous genes for proteins with critical mitochondrial functions and morphology. Genome-Scale Metabolic Models predicted common and private metabolic flux reprogramming, notably a depressed amino acid metabolism, and an enhanced metabolism of specific lipids distinctly induced by ORF3a. These findings reveal metabolic dependencies and vulnerabilities prompted by SARS-CoV-2 accessory proteins that may be exploited to identify new targets for intervention. One-Sentence SummaryMitochondria and metabolic alterations induced by SARS- CoV-2 accessory proteins ORF3a, ORF9b, ORF9c, ORF10 in pulmonary cells unravel new targets of intervention.

immunology↗

bioRxiv2023

Hepatocyte Dedifferentiation Profiling In Alcohol-Related Liver Disease Identifies CXCR4 As A Driver Of Cell Reprogramming

Background and AimsLoss of hepatocyte identity is associated with impaired liver function in alcohol-related hepatitis (AH). In this context, hepatocyte dedifferentiation gives rise to cells with a hepatobiliary (HB) phenotype expressing biliary and hepatocytes markers and showing immature features. However, the mechanisms and the impact of hepatocyte dedifferentiation in liver disease are poorly understood. MethodsHB cells and ductular reaction (DR) cells were quantified and microdissected from liver biopsies from patients with alcohol-related liver disease (ALD). Hepatocyte- specific overexpression or deletion of CXCR4, and CXCR4 pharmacological inhibition were assessed in mouse liver injury. Patient-derived and mouse organoids were generated to assess plasticity. ResultsHere we show that HB and DR cells are increased in patients with decompensated cirrhosis and AH, but only HB cells correlate with poor liver function and patients outcome. Transcriptomic profiling of HB cells revealed the expression of biliary-specific genes and a mild reduction of hepatocyte metabolism. Functional analysis identified pathways involved in hepatocyte reprogramming, inflammation, stemness and cancer gene programs. CXCR4 pathway was highly enriched in HB cells, and correlated with disease severity and hepatocyte dedifferentiation. In vitro, CXCR4 was associated with biliary phenotype and loss of hepatocyte features. Liver overexpression of CXCR4 in chronic liver injury decreased hepatocyte specific gene expression profile and promoted liver injury. CXCR4 deletion or its pharmacological inhibition ameliorated hepatocyte dedifferentiation and reduced DR and fibrosis progression. ConclusionsThis study shows the association of hepatocyte dedifferentiation with disease progression and poor outcome in AH. Moreover, the transcriptomic profiling of HB cells revealed CXCR4 as a new driver of hepatocyte-to-biliary reprogramming and as a potential therapeutic target to halt hepatocyte dedifferentiation in AH. Lay summaryHere we describe that hepatocyte dedifferentiation is associated with disease severity and a reduced synthetic capacity of the liver. Moreover, we identify the CXCR4 pathway as a driver of hepatocyte dedifferentiation and as a therapeutic target in alcohol-related hepatitis.

cell biology↗

bioRxiv2022

Age-dependent lipid droplet-rich microglia worsen stroke outcome in old mice

Microglial cells of the aged brain manifest signs of dysfunction that could contribute to the worse neurological outcome of stroke in the elderly. Treatment with colony-stimulating factor-1 receptor antagonists enable transient microglia depletion that can be followed by microglia repopulation after interruption of the treatment, causing no known harm to mice. Using this strategy, we aimed to restore microglia function and ameliorate stroke outcome in aged mice. Cerebral ischemia/reperfusion induces strong innate immune responses in microglia highlighted by prominent type I interferon signaling, together with cellular metabolic perturbances and lipid droplet biogenesis in young mice. In aged mice, a subset of microglia accumulates lipid droplets under steady state and displays exacerbated innate immune responses after stroke. Microglia renewal in old mice reduces the lipid droplet content, prevents the ischemia-induced exaggerated type I interferon response, and improves the neurological outcome of stroke. This study shows that age-dependent lipid droplet-enriched microglia contribute to impair stroke outcome in old mice.

neuroscience↗

bioRxiv2021

Copy-number intratumor heterogeneity contributes to predict relapse in chemotherapy-naive stage II colon cancer

Optimal selection of high-risk patients with stage II colon cancer is crucial to ensure clinical benefit of adjuvant chemotherapy after surgery. Here, we investigate the prognostic and predictive value of genomic intratumor heterogeneity and aneuploidy for disease recurrence. We combined SNP arrays, targeted next-generation sequencing, fluorescence in situ hybridization and inmunohistochemistry on a retrospective cohort of 84 untreated stage II colon cancer patients. We assessed the subclonality of copy-number alterations (CNAs) and mutations, CD8+ lymphocyte infiltration and their association with time to recurrence (TTR). Prognostic factors were included in machine learning analysis to evaluate their ability to predict individual relapse risk. Tumors from recurrent patients (N = 38) exhibited greater proportion of CNAs compared with non-recurrent (N = 46) (mean 31.3% vs. 23%, respectively; P = 0.014), which was confirmed in an independent cohort. Candidate chromosome-specific aberrations included the gain of the chromosome arm 13q (P = 0.02; HR, 2.67) and loss of heterozygosity at 17q22-q24.3 (P = 0.05; HR, 2.69), both associated with shorter TTR. CNA load positively correlated with intratumor heterogeneity (R = 0.52; P < 0.0001), indicating ongoing chromosomal instability. Consistently, subclonal copy-number heterogeneity was associated with elevated risk of relapse (P = 0.028; HR, 2.20), which we did not observe for subclonal mutations. The clinico-genomic model rated an area under the curve of 0.83, achieving a 10% incremental gain compared to clinicopathological markers. In conclusion, tumor aneuploidy and copy-number heterogeneity were predictive of a poor outcome in early-stage colon cancer, and improved discriminative performance in comparison to clinicopathological data.

genomics↗

bioRxiv2018

CNApp: a web-based tool for integrative analysis of genomic copy number alterations in cancer

Somatic copy number alterations (CNAs) are a hallmark of cancer. Although CNA profiles have been established for most human tumor types, their precise role in tumorigenesis as well as their clinical and therapeutic relevance remain largely unclear. Thus, computational and statistical approaches are required to thoroughly define the interplay between CNAs and tumor phenotypes. Here we developed CNApp, a user-friendly web tool that offers sample- and cohort-level computational analyses, allowing a comprehensive and integrative exploration of CNAs with clinical and molecular variables. By using purity-corrected segmented data from multiple genomic platforms, CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to a pan-cancer dataset of 10,635 genomes from TCGA showing that CNA patterns classify cancer types according to their tissue-of-origin, and that broad and focal CNA scores positively correlate in samples with low amounts of whole-chromosome and chromosomal arm-level imbalances. Moreover, using the hepatocellular carcinoma cohort from the TCGA repository, we demonstrate the reliability of the tool in identifying recurrent CNAs, confirming previous results. Finally, we establish machine learning-based models to predict colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and specific genomic imbalances. In summary, CNApp facilitates data-driven research and provides a unique framework for the first time to comprehensively assess CNAs and perform integrative analyses that enable the identification of relevant clinical implications. CNApp is hosted at http://cnapp.bsc.es.

genomics↗