Biology subjects

Ruano, I.

Publications and source records attributed to Ruano, I..

9 recordsLinked to original sources

bioRxiv2026

MET inhibition exploits conserved regulatory dependencies in malignant rhabdoid tumors

Malignant rhabdoid tumors (MRTs) are lethal, yet genomically simple childhood cancers characterised by universal SWI/SNF dysregulation. Despite this shared molecular framework, the regulatory programs sustaining MRTs and how they wire actionable dependencies, remain poorly defined. Here, we integrated single-cell multi-omic profiling and spatial transcriptomics across anatomically and molecularly diverse MRTs, generating a comprehensive multimodal MRT dataset at single-cell resolution. We leveraged this resource to identify candidate tumor-specific dependencies, which were subsequently functionally validated in vitro and in vivo in matched patient-derived models. We found that distinct malignant subpopulations are spatially patterned in complex environmentally shaped topologies, consistent with reciprocal interactions with stromal and immune compartments contributing to intratumoral transcriptional diversity. We identified recurrent transcriptional metaprograms conserved across patients and molecular subtypes, including a previously undescribed shared core rhabdoid program, as well as a metaprogram characterized by extracellular matrix interactions, and preferentially localized in tumor-stroma intermixed neighborhoods, supporting identification of niche conditioning cues. Mechanistically, we identified regulatory wiring driving these metaprograms, with the core shared rhabdoid programme coordinated by a circuit centred on TCF12, ZNF148 and CHD2. Guided by target nominations from our integrated analyses, we performed a curated drug screen using patient-derived MRT models and validated HGF/MET signaling as a selective vulnerability in extrarenal rhabdoid tumors. Pharmacologic MET inhibition was cytotoxic in sensitive models and induced a complete response in vivo using a clinically approved compound. Importantly, MET expression in primary tumors correlated with response, supporting biomarker-guided patient stratification for immediate clinical translation. Collectively, our findings define the molecular architecture of MRTs, reveal conserved regulatory programs beyond anatomical and molecular subtypes, and highlight a targetable signaling axis with immediate translational potential, establishing a framework for precision therapy in this lethal pediatric malignancy.

cancer biology↗

bioRxiv2026

On technical biases in imaging spatial transcriptomics

Imaging spatial transcriptomics (iST) has revolutionized our ability to contextualize gene expression within intact tissue architectures at single-cell and subcellular resolution. However, these platforms introduce complex technical biases that span the entire measurement pipeline -- from sample preparation to data acquisition to quantification. Here, we categorize these biases into experimental (e.g., sample preservation and spatial sampling) and computational sources (e.g., z-stack registration and field-of-view stitching). Using public datasets, we demonstrate how different biases can compound and manifest, and propose a unified count modeling framework to formalize these sources of variation. Finally, we call for a more integrated understanding of iST data origins and greater knowledge sharing within and across sectors to support the prospective development of more robust experimental design and reliable downstream analysis.

bioinformatics↗

bioRxiv2025

A transcriptional map of human tonsil architecture:beyond the sum of (single cell) parts

The tonsil is a highly compartmentalized organ in which different microanatomical structures orchestrate designated (immune) functions. We use this already well-studied tissue to survey spatial molecular imaging data (CosMx SMI) for studying immune responses in native tissue context; and, to demonstrate the advantages of SMI for faithfully recapitulating cellular composition in direct comparison with single-cell RNA sequencing. While SMI data still poses many analytical challenges and lacks standardization, we established a versatile analysis pipeline focused on the profitable particularities of these data: considering organization (microenvironment), interactions (signaling), and function (higher-order structures) across scales. Specifically, we resolve ~ 2M cells into 52 subpopulations across immune and, in particular, structural compartments. Various spatial niches partition tonsillar tissue into architecturally and functionally distinct regions, which we characterize through cell-cell colocalization and communication analyses, while performing various non-standard analyses at the level of spatial features. These topological readouts may help elucidate where certain immunological processes occur (e.g., class switch recombination); and, where signaling pathways are active (e.g., TNF and galectin, which have been implicated in diverse lymphomas). In all, we provide an analytical framework for Spatial Immunology, and showcase alternative views that such techniques and concomitant computational approaches can bring on tissue composition and architecture.

immunology↗

bioRxiv2025

In Situ Inference of Copy Number Variations in Image-Based Spatial Transcriptomics

Copy number variations (CNVs) drive cancer progression. So far, spatial CNV inference has relied on whole transcriptome-based sequencing technologies. However, advances in image-based spatial transcriptomics (iST) now enable high-plex gene measurement in situ. Here, we introduce an approach that adapts CNV inference to iST data, enabling spatial mapping of malignant clones and the tumor microenvironment, at single-cell resolution. Additionally, we assess how panel size and detection efficiency influence CNV inference.

bioinformatics↗

bioRxiv2025

Tracing colorectal malignancy transformation from cell to tissue scale

The transformation of normal intestinal epithelium into colorectal cancer (CRC) involves coordinated changes across molecular, cellular, and architectural scales; yet, how these layers integrate remains poorly resolved. Here, we survey colorectal tumorigenesis by combining whole-transcriptome spatial molecular imaging (WTx CosMx SMI) with single-nucleus RNA-sequencing (snPATHO-seq) and digital histopathology on colon samples containing reference mucosa, adenomas and carcinomas, as well as a metastatic lymph node. Leveraging (discrete) histological annotations and (continuous) data-driven trajectories, we quantify the dynamics of cellular density, heterogeneity, function and signaling along the reference-adenoma-carcinoma axis, which is concordant in its spatial and molecular definition. This combination of analytical approaches across different data views let us chart tissue transformation across dimensions (physical/transcriptional) and scales (cell/tissue). We resolve [~]3.5 million cells into 43 epithelial, immune, and stromal subpopulations that exhibit a bi-furcating tumor evolution: On the one hand, LGR5+ stem-like epithelial cells are enriched in highly homogeneous proliferative tumor cores. On the other hand, MMP7+ fetal-like states are restricted to immunosuppressive invasive fronts, rich in cancer-associated fibroblasts (CAFs) and tumor-associated macrophages. These subpopulations form concentric spatial layers that organize transformed regions, and their compound aligns with histological malignancy. We further define transition crypts - single colonic crypts with divided histological and transcriptional makeup - that arise from rare crypt fusion or abrupt transformation events. Finally, we trace MMP7+ fetal-like tumor cell states and concomitant myofibroblast-like FAP+ CAFs to lymphovascular invasion sites and matched lymph node metastases, thereby recapitulating invasive programs at single-cell resolution and across sites. In all, we present single cell- and WTx-resolved spatial data that are among the first of their kind. These open up spatial-centric, out-of-the-box analytical avenues to resolve the molecular, cellular and architectural dynamics that attend tissue transformation during CRC onset, progression and dissemination.

cancer biology↗

bioRxiv2025

Decoding the immune response in leptomeningeal disease through single-cell sequencing of cerebrospinal fluid

AbstractAssessing anti-tumor immune responses and immune microenvironments in central nervous system (CNS) neoplasms, such as brain tumors and leptomeningeal disease (LMD), provides prognostic insights and predictive biomarkers. Liquid biopsy of the cerebrospinal fluid (CSF) represents a promising minimally-invasive approach, but its ability to reflect immune responses against tumors remains unclear. Here, we used single-cell sequencing of CSF cells and spatial transcriptomics of CNS lesions to compare and contrast LMD patients with CNS lymphoma (CNSL), glioblastoma (GB) and brain metastases (BrM), to neuroinflammatory CNS disorders. We identified disease-specific CSF environments, reflecting parenchymal tumor microenvironment features. CNSL showed robust T cell responses, while BrM and GB were dominated by both blood-derived and tissue-resident myeloid cells. Longitudinal CSF sampling unveiled mechanisms of disease progression and therapy resistance, highlighting the potential of CSF liquid biopsies for uncovering disease biology, discovering cellular biomarkers and developing personalized therapies for CNS neoplasms.

immunology↗

bioRxiv2024

Spatial Flux Balance Analysis reveals tissue-of-origin and spatially dependent metabolic rewiring in renal and colorectal cancer

1To fully understand how cancer metabolism differs between primary tumors and metastases, resolving cell metabolism with spatial precision is essential. Yet, spatial fluxomics lags behind advancements in spatial transcriptomics. To address this gap, we generated high-resolution spatial transcriptomics datasets from paired primary colorectal tumors and liver metastases, designed to capture metabolic adaptations across distinct tumor sites. Concurrently, we developed the Spatial Flux Balance Analysis (spFBA) computational framework to leverage them. Since broad metabolic differences between tumors and healthy tissues are established, we first validated spFBA on a publicly available renal cancer dataset, including tumor-normal interface samples. spFBA detected cancer metabolic hallmarks, like enhanced glucose uptake and metabolic growth, but with unprecedented resolution, revealing lactate production with sustained oxygen consumption at the tumor interface and with reduced respiration in the core. Next, applying spFBA to our colorectal cancer dataset, we provided biological insights, confirming that metastases mimic the metabolic traits of their tissue of origin. Additionally, our approach uncovered the first in vivo evidence of lactate-consuming cancer cells, marking a significant advance in understanding cancer metabolism. spFBA stands out as a powerful approach to unravel the spatial metabolic complexity of cancer and beyond, leveraging the expanding landscape of spatial transcriptomics datasets.

systems biology↗

bioRxiv2024

HYL001, a new potent TGFβ signaling inhibitor that is efficacious against microsatellite stable CRC metastasis in combination with immune checkpoint therapy in mice

Blockade of the TGF{beta} signalling pathway has emerged from preclinical studies as a potential treatment to enhance the efficacy of immune checkpoint inhibition in advanced colorectal cancer (CRC) and several other types of cancer. However, clinical translation of first-generation inhibitors has known little success. Here, we report the synthesis and characterization of HYL001, a potent inhibitor of TGF{beta} receptor 1 (ALK5), that is approximately 9 times more efficacious than the structurally related compound galunisertib, while maintaining a favourable safety profile. HYL001 in combination with immune checkpoint blockade (anti-PD1) eradicates liver metastases generated in mice by microsatellite stable, aggressive colorectal cancer tumours at doses where galunisertib is ineffective. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/593510v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1909963org.highwire.dtl.DTLVardef@4644d2org.highwire.dtl.DTLVardef@1506d80org.highwire.dtl.DTLVardef@14504b7_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2022

Induction of senescence renders cancer cells highly immunogenic

Cellular senescence is a stress response that activates innate immunity. However, the interplay between senescent cells and the adaptive immune system remains largely unexplored. Here, we show that senescent cells display enhanced MHC class I (MHC-I) antigen processing and presentation. Immunization of mice with senescent syngeneic fibroblasts generates CD8 T cells reactive against both normal and senescent fibroblasts, some of them targeting senescence-associated MHC-I-peptides. In the context of cancer, we demonstrate that senescent cancer cells trigger strong anti-tumor protection mediated by antigen-presenting cells and CD8 T cells. This response is superior to the protection elicited by cells undergoing immunogenic cell death. Finally, induction of senescence in patient-derived cancer cells exacerbates the activation of autologous tumor-reactive CD8 tumor-infiltrating lymphocytes (TILs) with no effect on non-reactive TILs. Our study indicates that immunization with senescent cancer cells strongly activates anti-tumor immunity, and this can be exploited for cancer therapy. STATEMENT OF SIGNIFICANCEOur study shows that senescent cells are endowed with a high immunogenic potential, superior to the gold standard of immunogenic cell death. The induction of senescence in cancer cells can be exploited to develop efficient and protective CD8-dependent anti-tumor immune responses.

cancer biology↗