Biology subjects

Al-Shahrour, F.

Publications and source records attributed to Al-Shahrour, F..

15 recordsLinked to original sources

bioRxiv2026

Clonucopya: An end-to-end workflow bridging tumor clonal architecture and drug prioritization

Motivation: Intra-tumor heterogeneity limits the effectiveness of anticancer treatments, as distinct clonal populations may respond differently to therapy. Although subclonal inference from sequencing data is well established, translating clonal architecture into actionable drug recommendations remains a major bottleneck. Results: We present Clonucopya, an end-to-end Snakemake workflow that integrates subclonal inference (PyClone-VI, PhyClone) with drug prioritization (PanDrugs2) to link tumor clonal architecture directly to candidate drugs. From genome sequencing data, Clonucopya reconstructs tumor phylogenies, quantifies clone-level prevalence across samples, and ranks FDA/EMA-approved and experimental therapeutic candidates against the somatic mutations detected in each clone. Outputs include clonality plots, per-clone variant and drug tables, and a summary ranking drugs by clonal coverage to highlight broadly active therapeutic candidates. We assess Clonucopya's utility through a real-world longitudinal, multi-region use case, revealing clinically actionable clonal dynamics across tumor progression.

bioinformatics↗

bioRxiv2026

NGFR-driven suppression of antigen presentation limits CD8+ T cell immunity and response to checkpoint blockade

Immune checkpoint blockade has revolutionized cancer therapy; however, numerous tumors remain resistant by adopting cellular states that impede immune recognition. In this study, we identify the nerve growth factor receptor (NGFR) as a regulator of immune evasion in head and neck squamous cell carcinoma (HNSCC). Genetic ablation of Ngfr resulted in impaired tumor growth in immunocompetent MOC2 HNSCC, while pharmacological inhibition with THX-B reduced primary tumor growth and spontaneous metastatic dissemination. Single-cell profiling of MOC2 tumors demonstrated that Ngfr loss redirected tumor cells away from invasive EMT-like states and enhanced antigen-processing and presentation programs. This was accompanied by increased presentation of tumor antigens and expansion of effector CD8+ T-cells in vivo. Functionally, CD8+ T-cell depletion, Batf3 deficiency, and JAK1/2 inhibition restored the growth of Ngfr-deficient tumors, indicating that NGFR loss exposes tumors to CD8+ T-cell-mediated control through a JAK-associated antigen-presentation program. Notably, NGFR blockade sensitized otherwise resistant MOC2 tumors to anti-PD1 therapy, and the combination of THX-B with anti-PD1 significantly improved tumor control and survival. In human HNSCC, spatial profiling revealed that NGFR+ tumor regions exhibited reduced HLA-DR expression and limited CD3+ T-cell infiltration. Notably, an NGFR-associated antigen-presentation signature stratified survival and response in HNSCC patients undergoing immune checkpoint blockade. Interestingly, this signature was also linked to improved outcomes in melanoma patients. We also observed a significant increase in the effector CD8+ T-cell fraction in melanoma NGFR KO tumors linked to a significant decrease in tumor growth. These findings position NGFR as a regulator of tumor immune visibility and support NGFR inhibition as a strategy to enhance immunotherapy response.

cancer biology↗

bioRxiv2026

A single-cell atlas linking intratumoral states to therapeutic vulnerabilities across cancers

Intratumoral heterogeneity (ITH) is a major determinant of therapeutic failure, yet its impact on drug response across cancers remains incompletely understood. Here, we present the Therapeutic Cancer Cell Atlas (TCCA), a pan-cancer single-cell resource integrating [~]1.8 million transcriptomes from 537 patients and 183 cancer cell lines spanning 34 tumor types. By combining single-cell transcriptomics with copy-number alteration inference and computational drug-response prediction, we systematically map therapeutic heterogeneity at subclonal resolution across cancers. Using this framework, we identify ten recurrent therapeutic clusters that capture conserved and context-specific drug vulnerabilities across tumor lineages. Notably, therapeutic heterogeneity is largely decoupled from genomic and transcriptomic diversity and instead arises from distinct functional transcriptional programs and tumor microenvironment (TME) states. Integration with transcriptional metaprograms and TME archetypes reveals how stress responses, proliferative states, lineage programs, and immune context shape drug sensitivity beyond tissue of origin. We further demonstrate the translational relevance of TCCA by linking therapeutic clusters to patient outcomes and validating predicted vulnerabilities using pharmacogenomic datasets, including clinically actionable examples in aggressive tumor subtypes. Together, TCCA provides a multidimensional atlas connecting subclonal states, microenvironmental context, and drug response, offering a scalable framework to guide therapeutic prioritization, drug repurposing, and combination strategies in precision oncology.

bioinformatics↗

bioRxiv2025

MIF-induced CD74+ microglia/macrophages are clinically relevant disease-associated subpopulations in brain metastasis and other CNS disorders

The upregulation of CD74, a chaperone involved in MHC-II antigen processing 1,2, has been broadly reported in virtually all brain disorders analyzed by single-cell RNA sequencing 3-6. However, its expression is usually interpreted as indicative of antigen presentation. In parallel, CD74 expression has also been described in cancer cells across multiple tumor types, but interestingly in glioma its expression has been mainly identified in the microenvironment. However, the functional contribution of CD74 to disease progression in the brain, and specifically in secondary brain tumors, has not been directly addressed. Here we described that, in contrast to what it has been assumed, the presence of CD74+ microglia/macrophages, which is induced by increased levels of interferon gamma in the brain affected by metastases, does not relate to its canonical pathway. Instead, CD74s alternative function as cytokine receptor is pivotal. Rewired by increasing levels of its ligand MIF, produced by proliferating cancer cells, the CD74 receptor, upon binding to this ligand, translocates to the nucleus activating a NF-{kappa}B-dependent program promoting metastasis progression. A brain metastasis-associated CD74 signature involves a more aggressive progression of the local disease in patients, while it has no clinical correlation with the matched primary tumor. Furthermore, we identified the CD74+ myeloid population in additional brain disorders including Alzheimers disease and multiple sclerosis, which shared a pan-disease non-canonical signature with clinical relevance. The brain-penetrant drug ibudilast, which prevents the binding of MIF to CD74, decreases brain metastases in experimental models in vivo and in patient-derived organotypic cultures ex vivo in a primary tumor-agnostic manner. Our findings suggest that MIF/CD74-induced reprogramming of myeloid cells in brain disorders is a novel vulnerability that could be exploited therapeutically against brain metastases, and possibly other brain disorders, guided by a non-invasive molecular strategy.

cancer biology↗

bioRxiv2024

Spatial Transcriptomics in Breast Cancer Reveals Tumour Microenvironment-Driven Drug Responses and Clonal Therapeutic Heterogeneity

Breast cancer is a heterogeneous disease that has the highest incidence and mortality rate among cancers in women worldwide. Breast cancer patients are stratified into three clinical subtypes with different treatment strategies and prognostic values. The development of targeted therapies against the biomarkers that define these strata constitutes one of the precedents of precision oncology, which aims to provide tailored treatments to cancer patients by targeting the molecular alterations found in each tumour. Although this approach has increased patient outcomes, many treatment failure cases still exist. Drug ineffectiveness and relapse have been associated with the coexistence of several malignant subpopulations with different drug sensitivities within the same lesion, a phenomenon known as intratumor heterogeneity. This heterogeneity has been extensively studied from a tumour-centric view, but recently, it has become evident that the tumour microenvironment plays a crucial role in intratumor heterogeneity. However, few studies consider the tumour-microenvironment interplay and its influence on drug sensitivity. In this work, we predict the sensitivity of 10x Visium spatial transcriptomics data from 9 breast cancer patients to >1,200 drugs and verify different response patterns across the tumour, interphase and microenvironment regions. We uncover a sensitivity continuum from the tumour core to the periphery accompanied by a functional gradient. Moreover, we identify conserved therapeutic clusters with distinct response patterns within the tumour region. We link the specific drug sensitivities of each therapeutic cluster to different ligand-receptor interactions that underpin distinct biological functions. Finally, we demonstrate that genetically identical cancer spots may belong to different therapeutic clusters and that this therapeutic heterogeneity is related to their location at the edge or core of tumour ducts. These results highlight the importance of considering the distance to the tumour core and the microenvironment composition when identifying suitable treatments to target intratumor heterogeneity.

cancer biology↗

bioRxiv2023

The Minimal Dataset for Cancer of the 1+Million Genomes Initiative

For a real impact on healthcare, precision cancer medicine requires accessibility and interoperability of clinical and genomic data across centres and countries. Due to the heterogeneous digitization in Europe and worldwide, the definition of models for standardised data collection and usability becomes mandatory if countries want to work together on this mission. The European Union 1+Million Genomes (1+MG) initiative, supported by the Horizon 2020 Beyond 1 Million Genomes project, aims at outlining data models, guidance, best practices, and technical infrastructures for transnational access to sequenced genomes, including cancer genomes. Within the framework of the cancer-focused Working Group 9, we developed the 1+MG-Minimal Dataset for Cancer (1+MG-MDC)-a data model encompassing 140 items and organized in eight conceptual domains for the collection of cancer-related clinical information and genomics metadata. The 1+MG-MDC, which results from a multidisciplinary effort, leverages pre-existing models and emphasizes the annotation and traceability of multiple aspects relevant to the complex longitudinal path of the cancer disease and its treatment. We strived to make the 1+MG-MDC easy to adopt, yet comprehensive, addressing the needs of both clinicians and researchers. We will periodically revise and update it to ensure it remains fit for purpose. We propose the 1+MG-MDC as a model to create homogeneous databases, which would, in turn, guide discussions on clinical and genomic features with prognostic or therapeutic value and foster real-world data research.

cancer biology↗

bioRxiv2022

The efficacy of chemotherapy is limited by intratumoural senescent cells that persist through the upregulation of PD-L2

Anti-cancer therapies often result in a subset of surviving cancer cells that undergo therapy-induced senescence (TIS). Senescent cancer cells strongly modify the intratumoural microenvironment favoring immunosuppression and, thereby, tumour growth. An emerging strategy to optimise current therapies is to combine them with treatments that eliminate senescent cells. To this end, we undertook an unbiased proteomics approach to identify surface markers contributing to senescent cells immune evasion. Through this approach, we discovered that the immune checkpoint inhibitor PD-L2, but not PD-L1, is upregulated across multiple senescent human and murine cells. Importantly, blockade of PD-L2 strongly synergises with genotoxic chemotherapy, causing remission of solid tumours in mice. We show that PD-L2 inhibition prevents the persistence of chemotherapy-induced senescent cells, which exert cell-extrinsic immunomodulatory actions. In particular, upon chemotherapy, tumours deficient in PD-L2 fail to produce cytokines of the CXCL family, do not recruit myeloid-derived suppressor cells (MDSCs) and are eliminated in a CD8 T cell-dependent manner. We conclude that blockade of PD-L2 improves chemotherapy efficacy by reducing the intratumoural burden of senescent cells and their associated recruitment of immunosuppressive cells. These findings provide a novel strategy to exploit vulnerabilities arising in tumour cells as a result of therapy-induced damage and cellular senescence.

cancer biology↗

bioRxiv2022

PD-L1ATTAC mice reveal the potential of targeting PD-L1 expressing cells in cancer therapy

Antibodies targeting the PD-1 receptor and its ligand PD-L1 have shown impressive responses in some tumors of bad prognosis. We hypothesized that the selective elimination of PD-L1 expressing cells could similarly have antitumoral effects. To address this question, we developed an inducible suicidal knock-in mouse allele of Pd-l1 (PD-L1ATTAC) which allows for the tracking and specific elimination of PD-L1-expressing cells in adult tissues. Elimination of PD-L1 expressing cells from the mouse peritoneum increased the septic response to lipopolysaccharide (LPS), due to an exacerbated inflammatory response to the endotoxin. In addition, mice depleted of PD-L1+ cells were resistant to colon cancer peritoneal allografts, which was associated with a loss of immunosuppresive B cells and macrophages, concomitant with an increase in activated cytotoxic CD8 T cells. Collectively, these results illustrate the usefulness of PD-L1ATTAC mice and provide genetic support to the concept of targeting PD-L1 expressing cells in cancer therapy.

cancer biology↗

bioRxiv2022

Activation of the Integrated Stress Response overcomes multidrug resistance in FBXW7-deficient cells

FBXW7 is one of the most frequently mutated tumor suppressors, the deficiency of which has been associated with resistance to some anticancer therapies. Through bioinformatic analyses and genome-wide CRISPR screens, we here reveal that FBXW7 deficiency leads to multidrug resistance (MDR), to a bigger extent than well-established MDR-drivers such as overexpression of the drug-efflux pump ABCB1. Proteomic data from FBXW7-deficient cancer cells identify the upregulation of mitochondrial function as a hallmark of FBXW7 deficiency, which has been previously linked to an increased resistance to chemotherapy. Accordingly, genetic or chemical targeting of mitochondria is preferentially toxic for FBXW7-deficient cells in vitro and in vivo. Mechanistically, we show that the toxicity associated with therapies that target mitochondrial translation such as the antibiotic tigecycline relates to the activation of the Integrated Stress Response (ISR). Furthermore, while searching for additional drugs that could overcome the MDR of FBXW7-deficient cells, we found that all of them unexpectedly also activated the ISR regardless of their currently accepted mechanism of action. Together, our study reveals that one of the most frequent mutations in cancer reduces the sensitivity to the vast majority of available therapies, and identifies a general principle to overcome such resistance.

cancer biology↗

bioRxiv2021

Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq

We present Beyondcell (https://gitlab.com/bu_cnio/beyondcell/), a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments. Our method calculates an enrichment score in a collection of drug signatures, delineating therapeutic clusters (TCs) within cellular populations. Additionally, Beyondcell determines therapeutic differences among cell populations, and generates a prioritised ranking of the differential sensitivity drugs between chosen conditions to guide drug selection. We performed Beyondcell analysis in four single-cell datasets to validate our score and to demonstrate that TCs can be exploited to target malignant cells both in cancer cell lines and tumour patients.

bioinformatics↗

bioRxiv2020

DREIMT: a drug repositioning database and prioritization tool for immunomodulation.

MotivationDrug immunomodulation modifies the response of the immune system and can be therapeutically exploited in pathologies such as cancer and autoimmune diseases. ResultsDREIMT is a new hypothesis-generation web tool which performs drug prioritization analysis for immunomodulation. DREIMT provides significant immunomodulatory drugs targeting up to 70 immune cells subtypes through a curated database that integrates 4,960 drug profiles and ~2,6K immune gene expression signatures. The tool also suggests potential immunomodulatory drugs targeting user-supplied gene expression signatures. Final output includes drug-signature association scores, FDRs and downloadable plots and results tables. Availabilityhttp://www.dreimt.org Contactfalshahrour@cnio.es; ggomez@cnio.es

bioinformatics↗

bioRxiv2020

A comprehensive and centralized database for exploring omics data in Autoimmune Diseases

Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field. Here, we present ADEx (https://adex.genyo.es), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis.

bioinformatics↗

bioRxiv2019

Global transcriptomic profiling of the bone marrow stromal microenvironment during postnatal development, aging and inflammation

Bone marrow (BM) stromal cells provide the structural and regulatory framework for hematopoiesis and contribute to developmental-stage specific niches, such as those preserving hematopoietic stem cell (HSCs). Despite recent advances in our understanding of stromal composition and function, little is known on the dynamic transcriptional remodeling that this compartment undergoes over time and during adaptation to stress. Similarly, how molecular changes in stroma are linked to age-related modulation of hematopoiesis is poorly understood. Using RNA-sequencing, we performed a longitudinal comparison of the transcriptional profile of four principal mesenchymal and endothelial stromal subsets, namely CXCL12-abundant reticular (CARc), PDGFR-+Sca-1+, sinusoidal (SECs) and arterial endothelial cells (AECs), isolated from early postnatal, adult and aged mice. Our data i) provide molecular fingerprints defining novel, cell-specific anatomical and functional features ii) reveal radical reprogramming of pro-hematopoietic, immune and matrisomic transcriptional programs during the narrow temporal transition from juvenile to adult stages iii) demonstrate that homeostatic aging is characterized by a progressive and pronounced upregulation of pro-inflammatory gene-expression and loss of stromal cell fitness. By profiling in vivo responses of stromal cells to infection-mimicking agents, we finally demonstrate that transcriptomic pathways elicited by sterile inflammation are largely recapitulated during aging, thereby supporting the inflammatory basis of aging-related adaptations of BM hematopoietic function.

immunology↗

bioRxiv2019

Three-dimensional connectivity and chromatin environment mediate the activation efficiency of mammalian DNA replication origins

In mammalian cells, chromosomal replication starts at thousands of origins at which replisomes are assembled and bidirectional DNA synthesis is established. The slowdown of DNA polymerases at endogenous or exogenous obstacles triggers the activation of additional dormant origins whose genomic positions and regulation are not well understood. Here we report a comparative study of origin activity in mouse embryonic stem cells growing in control conditions or in the presence of mild replication stress. While stress-responsive origins can be identified, we find that the majority of them are also active, albeit with lower frequency, in the control population. To gain insights into the molecular and structural determinants of origin efficiency, we have analyzed the genetic and epigenetic features of origins stratified according to their frequency of activation. We have also integrated the linear origin maps into three-dimensional (3D) chromatin interaction networks, revealing a hierarchical organization in which clusters of connected origins are brought together by longer-range chromatin contacts. Origin efficiency is proportional to the number of connections established with other origin-containing fragments. Interacting origins tend to be activated with similar efficiency and share their timing of replication even when located in different topologically associated domains. Our results are consistent with a model in which clusters of origins are arranged in 3D in replication factories. Within each factory, main and dormant origins are functionally defined by a combination of chromatin environment and 3D connectivity.

genomics↗

bioRxiv2018

Unveiling the molecular basis of disease co-occurrence: towards personalized comorbidity profiles

Comorbidity is an impactful medical problem that is attracting increasing attention in healthcare and biomedical research. However, little is known about the molecular processes leading to the development of a specific disease in patients affected by other conditions. We present a disease interaction network inferred from similarities in patients molecular profiles, which significantly recapitulates epidemiologically documented comorbidities, providing the basis for their interpretation at a molecular level. Furthermore, expanding on the analysis of subgroups of patients with similar molecular profiles, our approach discovers comorbidity relations not previously described, implicates distinct genes in such relations, and identifies drugs whose side effects are potentially associated to the observed comorbidities.

bioinformatics↗