Development of an in silico transcriptional drug repositioning methodology for immune cell modulation

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Bioquímica. Fecha de lectura: 23-09-2021Cancer research has made great advances during the last decades in the understanding of the mechanisms that govern the course of the disease. One key factor for this advance has been the comprehension of the role of the immune system and its interplay with tumoral cells. Thanks to this, the view of the disease has shifted from a cancerous cell-centric view, towards a more holistic view in which other cells crosstalk with the tumor and determine its course. This paradigm has allowed the discovery, development and approval of compounds with immunomodulatory capabilities. Computational biology has been extensively employed to analyze large-scale datasets to decipher the interplay mechanisms employed by the tumor and its microenvironment. This project aims to explore potential strategies to exploit immune modulation in the context of cancer and other immune-driven diseases. The principal aim of this thesis is the design of a computational framework to allow hypothesis generation of compounds capable of modulating immune cell activity from gene expression signatures. To this end, we have compiled, annotated and curated a large collection of immune gene expression signatures derived from the literature or generated in-house and a collection of drug-induced gene expression profiles from the CMap L1000 consortium. By employing computational methodologies based on GSEA, the signatures and the drug-induced profiles are compared and scored according to their degree of similarity. These scores are then employed to generate an immune signature-drug association database available to query for compounds with potential immunomodulating capabilities. To facilitate the access to the database we have developed DREIMT (Drug REpositioning for IMmune Transcriptome; www.dreimt.org), a web tool from which queries to the database can be performed. Furthermore, DREIMT has a built-in tool to generate hypotheses of immunomodulatory compounds from user-provided immune signatures and a tool to compare a user-provided immune signature to those employed in the databas

Cutaneous Immune Cell-Microbiota Interactions Are Controlled by Epidermal JunB/AP-1

Atopic dermatitis (AD) is a multi-factorial skin disease with a complex inflammatory signature including type 2 and type 17 activation. Although colonization by S. aureus is common in AD, the mechanisms rendering an organism prone to dysbiosis, and the role of IL-17A in the control of S. aureus-induced skin inflammation, are not well understood. Here, we show several pathological aspects of AD, including type 2/type 17 immune responses, elevated IgE, barrier dysfunction, pruritus, and importantly, spontaneous S. aureus colonization in JunBΔep mice, with a large transcriptomic overlap with AD. Additionally, using Rag1-/- mice, we demonstrate that adaptive immune cells are necessary for protection against S. aureus colonization. Prophylactic antibiotics, but not antibiotics after established dysbiosis, reduce IL-17A expression and skin inflammation, examined using Il17a-eGFP reporter mice. Mechanistically, keratinocytes lacking JunB exhibit higher MyD88 levels in vitro and in vivo, previously shown to regulate S. aureus colonization. In conclusion, our data identify JunB as an upstream regulator of microbiota-immune cell interactions and characterize the IL-17A response upon spontaneous dysbiosis.We thank the Wagner lab for helpful suggestions and discussion throughout the evolution of this project, specifically Alvaro Ucero, Nuria Gago, and Liliana Mellor. We thank Vanessa Bermeo and Guillermo Medrano for help with animal husbandry and genotyping. O.U. was funded by the ECTS/Amgen Bone Biology Fellowship (2013-2016) and by the Spanish Ministry of Economy and Competitiveness (SAF2012-39670). B.R. and W.W. were funded by a Jesus-Serra visiting scientist grant. E.F.W. was funded by a European Research Council advanced grant (ERC FCK/2008/37).S

CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data

Cell-cell communication is essential for tissue development, regeneration and function, and its disruption can lead to diseases and developmental abnormalities. The revolution of single-cell genomics technologies offers unprecedented insights into cellular identities, opening new avenues to resolve the intricate cellular interactions present in tissue niches. CellPhoneDB is a bioinformatics toolkit designed to infer cell-cell communication by combining a curated repository of bona fide ligand-receptor interactions with a set of computational and statistical methods to integrate them with single-cell genomics data. Importantly, CellPhoneDB captures the multimeric nature of molecular complexes, thus representing cell-cell communication biology faithfully. Here we present CellPhoneDB v5, an updated version of the tool, which offers several new features. Firstly, the repository has been expanded by one-third with the addition of new interactions. These encompass interactions mediated by non-protein ligands such as endocrine hormones and GPCR ligands. Secondly, it includes a differentially expression-based methodology for more tailored interaction queries. Thirdly, it incorporates novel computational methods to prioritise specific cell-cell interactions, leveraging other single-cell modalities, such as spatial information or TF activities (i.e. CellSign module). Finally, we provide CellPhoneDBViz, a module to interactively visualise and share results amongst users. Altogether, CellPhoneDB v5 elevates the precision of cell-cell communication inference, ushering in new perspectives to comprehend tissue biology in both healthy and pathological states.Comment: 30 pages, 3 figures and 2 tables. Added previously missing figures and tables; Updated the reference for 'An integrated single-cell reference atlas of the human endometrium' pape

DREIMT: a drug repositioning database and prioritization tool for immunomodulation

Motivation Drug immunomodulation modifies the response of the immune system and can be therapeutically exploited in pathologies such as cancer and autoimmune diseases. Results DREIMT 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 4960 drug profiles and ∼2600 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. Availabilityand implementation http://www.dreimt.org. Supplementary information Supplementary data are available at Bioinformatics online.Agencia Estatal de Investigación | Ref. RTI2018-097596-B-I00Instituto de Salud Carlos IIIComunidad de Madrid | Ref. PEJD-2019-PRE/BMD-15732Xunta de Galicia | Ref. ED431C2018/55-GRCJunta de Andalucía | Ref. PI-0173-201

Saa3 is a key mediator of the protumorigenic properties of cancer-associated fibroblasts in pancreatic tumors

Pancreatic ductal adenocarcinoma (PDAC) is characterized by the presence of abundant desmoplastic stroma primarily composed of cancer-associated fibroblasts (CAFs). It is generally accepted that CAFs stimulate tumor progression and might be implicated in drug resistance and immunosuppression. Here, we have compared the transcriptional profile of PDGFRα+ CAFs isolated from genetically engineered mouse PDAC tumors with that of normal pancreatic fibroblasts to identify genes potentially implicated in their protumorigenic properties. We report that the most differentially expressed gene, Saa3, a member of the serum amyloid A (SAA) apolipoprotein family, is a key mediator of the protumorigenic activity of PDGFRα+ CAFs. Whereas Saa3-competent CAFs stimulate the growth of tumor cells in an orthotopic model, Saa3-null CAFs inhibit tumor growth. Saa3 also plays a role in the cross talk between CAFs and tumor cells. Ablation of Saa3 in pancreatic tumor cells makes them insensitive to the inhibitory effect of Saa3-null CAFs. As a consequence, germline ablation of Saa3 does not prevent PDAC development in mice. The protumorigenic activity of Saa3 in CAFs is mediated by Mpp6, a member of the palmitoylated membrane protein subfamily of the peripheral membrane-associated guanylate kinases (MAGUK). Finally, we interrogated whether these observations could be translated to a human scenario. Indeed, SAA1, the ortholog of murine Saa3, is overexpressed in human CAFs. Moreover, high levels of SAA1 in the stromal component correlate with worse survival. These findings support the concept that selective inhibition of SAA1 in CAFs may provide potential therapeutic benefit to PDAC patients.This work was supported by European Research Council Grants ERC-AG/250297-RAS AHEAD and ERC-AG/695566-THERACAN, Spanish Ministry of Economy and Competitiveness Grant SAF2014-59864-R, and Asociación Española contra el Cáncer Grant GC16173694BARB (to M. Barbacid). M.D. was supported by a fellowship from La Caixa International Fellowship Program. M. Barbacid is the recipient of an Endowed Chair from the AXA Research Fund

Saa3 is a key mediator of the protumorigenic properties of cancer-associated fibroblasts in pancreatic tumors

Pancreatic ductal adenocarcinoma (PDAC) is characterized by the presence of abundant desmoplastic stroma primarily composed of cancer-associated fibroblasts (CAFs). It is generally accepted that CAFs stimulate tumor progression and might be implicated in drug resistance and immunosuppression. Here, we have compared the transcriptional profile of PDGFRα + CAFs isolated from genetically engineered mouse PDAC tumors with that of normal pancreatic fibroblasts to identify genes potentially implicated in their protumorigenic properties. We report that the most differentially expressed gene, Saa3, a member of the serum amyloid A (SAA) apolipoprotein family, is a key mediator of the protumorigenic activity of PDGFRα + CAFs. Whereas Saa3-competent CAFs stimulate the growth of tumor cells in an orthotopic model, Saa3-null CAFs inhibit tumor growth. Saa3 also plays a role in the cross talk between CAFs and tumor cells. Ablation of Saa3 in pancreatic tumor cells makes them insensitive to the inhibitory effect of Saa3-null CAFs. As a consequence, germline ablation of Saa3 does not prevent PDAC development in mice. The protumorigenic activity of Saa3 in CAFs is mediated by Mpp6, a member of the palmitoylated membrane protein subfamily of the peripheral membrane-associated guanylate kinases (MAGUK). Finally, we interrogated whether these observations could be translated to a human scenario. Indeed, SAA1, the ortholog of murine Saa3, is overexpressed in human CAFs. Moreover, high levels of SAA1 in the stromal component correlate with worse survival. These findings support the concept that selective inhibition of SAA1 in CAFs may provide potential therapeutic benefit to PDAC patients.This work was supported by European Research Council Grants ERC-AG/250297-RAS AHEAD and ERC-AG/695566-THERACAN, Spanish Ministry of Economy and Competitiveness Grant SAF2014-59864-R, and Asociación Española contra el Cáncer Grant GC16173694BARB (to M. Barbacid). M.D. was supported by a fellowship from La Caixa International Fellowship Program. M. Barbacid is the recipient of an Endowed Chair from the AXA Research Fun

RANK links senescence to stemness in the mammary epithelia, delaying tumor onset but increasing tumor aggressiveness

Rank signaling enhances stemness in mouse and human mammary epithelial cells (MECs) and mediates mammary tumor initiation. Mammary tumors initiated by oncogenes or carcinogen exposure display high levels of Rank and Rank pathway inhibitors have emerged as a new strategy for breast cancer prevention and treatment. Here, we show that ectopic Rank expression in the mammary epithelia unexpectedly delays tumor onset and reduces tumor incidence in the oncogene-driven Neu and PyMT models. Mechanistically, we have found that ectopic expression of Rank or exposure to Rankl induces senescence, even in the absence of other oncogenic mutations. Rank leads to DNA damage and senescence through p16/p19. Moreover, RANK-induced senescence is essential for Rank-driven stemness, and although initially translates into delayed tumor growth, eventually promotes tumor progression and metastasis. We uncover a dual role for Rank in the mammary epithelia: Rank induces senescence and stemness, delaying tumor initiation but increasing tumor aggressiveness

Stratification of radiosensitive brain metastases based on an actionable S100A9/RAGE resistance mechanism

© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Whole-brain radiotherapy (WBRT) is the treatment backbone for many patients with brain metastasis; however, its efficacy in preventing disease progression and the associated toxicity have questioned the clinical impact of this approach and emphasized the need for alternative treatments. Given the limited therapeutic options available for these patients and the poor understanding of the molecular mechanisms underlying the resistance of metastatic lesions to WBRT, we sought to uncover actionable targets and biomarkers that could help to refine patient selection. Through an unbiased analysis of experimental in vivo models of brain metastasis resistant to WBRT, we identified activation of the S100A9-RAGE-NF-κB-JunB pathway in brain metastases as a potential mediator of resistance in this organ. Targeting this pathway genetically or pharmacologically was sufficient to revert the WBRT resistance and increase therapeutic benefits in vivo at lower doses of radiation. In patients with primary melanoma, lung or breast adenocarcinoma developing brain metastasis, endogenous S100A9 levels in brain lesions correlated with clinical response to WBRT and underscored the potential of S100A9 levels in the blood as a noninvasive biomarker. Collectively, we provide a molecular framework to personalize WBRT and improve its efficacy through combination with a radiosensitizer that balances therapeutic benefit and toxicity.info:eu-repo/semantics/publishedVersio

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

Drug immunomodulation modifies the response of the immune system and can be therapeutically exploited in pathologies such as cancer and autoimmune diseases. DREIMT 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 4960 drug profiles and ∼2600 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. http://www.dreimt.org. Supplementary data are available at Bioinformatics online