Group Publications

@article{pmid42302479,

title = {Discovery and analytical assessment of urinary miRNA biomarkers for cervical cancer using advanced small RNA sequencing},

author = {Mengfei Xu and Mariano A Molina and Cristina Gómez-Martín and Maaike M H S Dekker and Saba Ghasemi and Johan de Rooij and D Michiel Pegtel and Nienke E van Trommel and Renske D M Steenbergen},

doi = {10.1016/j.tranon.2026.102857},

issn = {1936-5233},

year  = {2026},

date = {2026-09-01},

journal = {Transl Oncol},

volume = {71},

pages = {102857},

abstract = {Cervical cancer is primarily caused by persistent infection with high-risk human papillomavirus (hrHPV), which alters host RNA expression, including regulatory microRNAs (miRNAs). Because urine is emerging as a convenient biosource for cancer detection, we evaluated the feasibility of urinary miRNAs as non-invasive biomarkers for cervical cancer. We optimized miRNA isolation from whole urine and urine fractions using commercial RNA extraction kits, spike-in controls, and digital nanoplate PCR. Following identification of optimal conditions, IsoSeek small RNA sequencing was performed to profile miRNA expression in urine from women with cervical cancer (n = 20) and age-matched controls (n = 20). Differentially expressed candidates were then analytically confirmed by RT-qPCR. The Norgen RNA isolation kit applied to whole urine provided the most robust miRNA recovery. Sequencing identified significantly altered urinary levels of hsa-miR-143-3p and hsa-miR-204-3p in cervical cancer. The ratio of these miRNAs showed strong discriminatory performance for detecting cervical cancer using IsoSeek (AUC = 0.93) and remained robust after RT-qPCR analysis in the same cohort (AUC = 0.84). These findings support the feasibility of using urinary miRNA profiling for non-invasive biomarker discovery and highlight the hsa-miR-143-3p/hsa-miR-204-3p ratio as a promising candidate marker for cervical cancer detection.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41484049,

title = {Untargeted breathomics identifies metabolic signatures of immune activity, intestinal integrity, and fatigue in systemic lupus erythematosus},

author = {Ioannis Parodis and Martina Iacubino and Lorenzo Rocco and Dionysis Nikolopoulos and Leonardo Palazzo and Liam Grimmett and Matt Kerr and Chiara Bellocchi and Barbara Vigone and Alessandro Santaniello and Guillermo Barturen and Alexandre E Voskuyl and Marta E Alarcón-Riquelme and Lorenzo Beretta},

doi = {10.1016/j.ard.2025.12.005},

issn = {1468-2060},

year  = {2026},

date = {2026-05-01},

journal = {Ann Rheum Dis},

volume = {85},

number = {5},

pages = {848--857},

abstract = {OBJECTIVES: Systemic lupus erythematosus (SLE) is a complex autoimmune disease with pronounced clinical heterogeneity and symptom burden. Despite growing knowledge of SLE biology, sensitive noninvasive biomarkers for monitoring disease activity remain lacking. This study aimed to characterise the breath metabolome in SLE and to explore associations between volatile organic compounds (VOCs) and clinical features, including disease activity and fatigue.nnMETHODS: Exhaled breath was collected from 30 SLE patients and 30 matched healthy controls using the ReCIVA Breath Sampler and analysed by thermal desorption gas chromatography-mass spectrometry. VOCs were identified using high-resolution libraries and classified by confidence levels. Associations with clinical and patient-reported outcomes were evaluated, including disease activity indices, fatigue scores, Definition Of Remission In SLE remission, and Lupus Low Disease Activity State.nnRESULTS: Of 1433 detected VOCs, 539 exhibited levels over background and were considered breath-derived. Distinct breathomic signatures discriminated patients from controls and stratified patients by SLE activity and fatigue burden. Five VOC clusters were identified. Methyl acetate was inversely associated with disease activity and fatigue, suggesting a role in immune homeostasis. A cluster of branched alkenes and alcohols was associated with active disease and greater fatigue, aligning with oxidative stress and lipid peroxidation. Nitrogen-containing heterocycles displayed U-shaped patterns across disease states, potentially reflecting varying intestinal permeability.nnCONCLUSIONS: This is the first study to characterise the breath metabolome in SLE. VOC signatures reflected immunometabolic perturbations, oxidative stress, and gut barrier integrity. Breathomics may provide a noninvasive means to monitor disease activity and symptom burden in SLE.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41448992,

title = {Transcriptomic stratification predicts response to rituximab, abatacept, or the association of hydroxychloroquine and leflunomide in 3 randomised controlled clinical trials of Sjögren's disease},

author = {Baptiste Chevet and Valérie Devauchelle-Pensec and Elena Pontarini and Valentin Baloche and Michele Bombardieri and Simon J Bowman and Michael Barnes and Antoine G Sreih and Jinqi Liu and Sheila Kelly and Antonia Christodoulou and Philippe Moingeon and Laurence Laigle and Perrine Soret and Christelle Le Dantec and Jacques-Olivier Pers and Marta E Alarcon-Riquelme and Guillermo Barturen and Xavier Mariette and Joel van Roon and Raphaèle Seror and Gaetane Nocturne and Divi Cornec and Nathan Foulquier and },

doi = {10.1016/j.ard.2025.11.017},

issn = {1468-2060},

year  = {2026},

date = {2026-05-01},

journal = {Ann Rheum Dis},

volume = {85},

number = {5},

pages = {873--879},

abstract = {OBJECTIVES: Sjögren's disease (SjD) is clinically and biologically heterogeneous, and no immunomodulatory drug has yet demonstrated efficacy in phase 3 trials. We previously identified 4 transcriptomic endotypes in SjD patients using whole-blood RNA sequencing. We hypothesised that these endotypes may predict differential therapeutic responses.nnMETHODS: We analysed clinical, biological, and transcriptomic data from 3 randomised controlled trials evaluating hydroxychloroquine-leflunomide (HCQ-LEF; n = 18; RepurpSS-I trial), rituximab (RTX; n = 56; TRACTISS trial), and abatacept (n = 117). Patients were assigned to the 4 endotypes using semisupervised uniform manifold approximation and projection combined with a support vector machine model. Demographics, disease activity, and therapeutic response, as defined by the Sjögren Tool for Assessing Response index, were compared across clusters in both pooled and individual trial analyses.nnRESULTS: Of 170 patients, 81, 24, 80, and 6 were classified into clusters 1 to 4, respectively. European Alliance of Associations for Rheumatology (EULAR) Sjögren's Syndrome Patient Reported Index scores were comparable across clusters, while the EULAR Sjögren's Syndrome Disease Activity Index was significantly higher in clusters 3 and 4 vs clusters 1 and 2 (P = .003). In pooled analyses, patients in cluster 1 had significantly greater response rates with active treatment vs placebo (61.5% vs 32.6%: P = .016), with a similar trend in the RTX trial. In contrast, patients in cluster 3 benefitted from HCQ-LEF, whereas cluster 2 (healthy-like patients) showed no significant response to any therapy.nnCONCLUSIONS: Transcriptomic stratification of SjD patients revealed differential responses to HCQ-LEF and RTX. Notably, healthy-like patients exhibited minimal treatment response, suggesting they may be unsuitable candidates for future therapeutic trials.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41885389,

title = {Small and Large Extracellular Vesicles in Circulation of Diffuse Large B-Cell Lymphoma Patients Originate From Different Cell Types of the Tumor Microenvironment},

author = {Filippo Maltoni and Steven Wang and Mischa F B Steketee and Cristina A Gómez-Martín and Esther E E Drees and Federica Morelli and Leontien Bosch and Monique van Eijndhoven and Gert Jan Timmers and Ilse Houtenbos and Josée M Zijlstra and Xiaofei Ye and Qiang Pan-Hammarström and Martine E D Chamuleau and Pier Luigi Zinzani and Yongsoo Kim and Lucia Catani and Dirk Michiel Pegtel},

doi = {10.1002/jev2.70259},

issn = {2001-3078},

year  = {2026},

date = {2026-04-01},

journal = {J Extracell Vesicles},

volume = {15},

number = {4},

pages = {e70259},

abstract = {Malignant and non-malignant cells within the tumor microenvironment (TME) actively secrete extracellular vesicles (EVs) that may mediate intercellular communication or enter the blood stream. Circulating EVs in Diffuse Large B-Cell Lymphoma (DLBCL) patients are a promising source of liquid biopsy biomarkers; however, whether different cellular components of the TME preferentially secrete small (S-) and/or large (L-) EVs is still unknown. With an established density-gradient separation protocol and tunable resistive pulse sensing analysis, we demonstrate that DLBCL cells in culture produce 100-1000-fold higher numbers of S-EVs (50-200 nm) compared with L-EVs (200-1000 nm) and very large EVs (>1000 nm). In contrast, the plasma from DLBCL patients contains comparable concentrations of S- and L-EVs, consistent with various cellular origins. Small RNA sequencing showed minor differences in miRNA content between plasma S- and L-EVs; however, messenger RNA sequencing revealed stark differences in cargo between EV-size subtypes and between healthy donors and patients. Deconvolution analysis with single-cell sequencing data from 17 DLBCL tumor tissues as reference using the Statescope algorithm indicated that circulating S-EVs from malignant cells outnumber the L-EVs. In contrast, TME macrophage-, T cell-, and natural killer-derived L-EVs outnumber S-EVs. Together, these findings suggest that circulating S- and L-EVs can originate from distinct cellular compartments within the DLBCL TME, representing complementary biological information. These observations have important implications for the development of EV-based liquid biopsy strategies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Barturen2026,

title = {Impaired Sertoli-Spermatogonia interactions contribute to oligospermia and infertility in F1 captive-bred male Solea senegalensis},

author = {Guillermo Barturen and Diego Robledo and Francisca Robles and Rose Ruiz Daniels and Maialen Carballeda and Dorinda Torres-Sabino and Rafael Navajas-Pérez and Paulino Martínez and Carmelo Ruiz-Rejón and Roberto De la Herrán},

doi = {10.1016/j.aquaculture.2025.743593},

issn = {0044-8486},

year  = {2026},

date = {2026-03-30},

journal = {Aquaculture},

volume = {615},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42212163,

title = {Assessing the translational relevance of specific molecular pathways in spontaneous lupus mouse models},

author = {María Rivas-Torrubia and María Morell and Zuzanna Makowska and Jorge Kageyama and Anne Bosshard and Julius Lindblom and Maria Orietta Borghi and Eleonore Bettacchioli and  and  and Ioannis Parodis and Lorenzo Beretta and Concepción Marañón and Jacques-Olivier Pers and Ralf Lesche and Fiona McDonald and Marta E Alarcón-Riquelme and Guillermo Barturen},

doi = {10.3389/fimmu.2026.1823650},

issn = {1664-3224},

year  = {2026},

date = {2026-01-01},

journal = {Front Immunol},

volume = {17},

pages = {1823650},

abstract = {BACKGROUND: Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by loss of self-tolerance, causing inflammation and tissue damage in multiple organs. Although animal models have advanced our understanding of SLE's molecular basis, recent regulatory changes and longstanding concerns regarding reproducibility and translatability have renewed the need to critically evaluate how these models mirror human disease. Understanding pathway-level similarities and differences between mouse models and human disease is essential, given the marked clinical and molecular heterogeneity of SLE.nnMETHODS: Four spontaneous SLE mouse models were studied: MRL  , NZB/W, BXSB., and Tlr7.Tg6. Transcriptome sequencing from blood, spleen, and kidney; flow cytometry from the spleen; and cytokines and autoantibody measurement in plasma were performed at four time points. Similar molecular datasets from the human PRECISESADS SLE cohort were used for the integration.nnRESULTS: The study identified specific molecular pathways driving the phenotype in each mouse model and established a framework describing the dynamics of these phenotype-associated molecular signatures, thereby facilitating the selection of time points of interest for future mouse-oriented experimental designs. In addition, by comparing these pathways with those observed in human SLE, we identified the most similar ones and their relationship with disease activity, providing crucial insight into their translational relevance. Importantly, disease severity across models was linked to both the extent and timing of molecular dysregulations. As expected, MRL  showed the most aggressive phenotype with early immune activation and apoptosis dysregulation, while Tlr7.Tg6 presented late-onset signatures associated with interferon and inflammation. Shared molecular features with human SLE included interferon responses, T and B cell depletion, and neutrophil activation. Integration analysis revealed distinct, yet overlapping, immune pathways between models and species, with some signatures such as age-associated B cells and double-negative memory T cells being model-specific but potentially relevant to early disease processes.nnCONCLUSIONS: These findings provide a valuable framework for future SLE research and reinforce the utility of mouse models for studying specific molecular pathways related to human SLE pathogenesis and heterogeneity. The integration of longitudinal mouse and human molecular information highlights the models that best recapitulate key aspects of human disease, offering guidance for the study of specific immunopathological mechanisms or therapeutic targets.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40701862,

title = {Differential molecular signatures in response to CD19-CAR T cell therapy compared with conventional pharmacotherapy in systemic lupus erythematosus},

author = {Panagiotis Garantziotis and Lorenzo Beretta and Julius Lindblom and Georgia-Savina Moysidou and Dionysis Nikolopoulos and Ricardo Grieshaber-Bouyer and Melanie Hagen and Christina Bergmann and Andreas Wirsching and Aline Bozec and  and Matthias Schneider and Guillermo Barturen and George Bertsias and Dimitrios T Boumpas and Marta E Alarcón-Riquelme and Andreas Mackensen and Georg Schett and Ioannis Parodis},

doi = {10.1016/j.ard.2025.06.2132},

issn = {1468-2060},

year  = {2026},

date = {2026-01-01},

journal = {Ann Rheum Dis},

volume = {85},

number = {1},

pages = {153--163},

abstract = {OBJECTIVES: Early trials of CD19-chimeric antigen receptor (CAR) T cell therapy in systemic lupus erythematosus (SLE) show promise, but the molecular mechanisms underlying its disease-modifying effects remain unclear. We aimed to compare biological profiles and alterations following CD19-CAR T cell versus standard pharmacotherapy in SLE.nnMETHODS: Pseudo-bulk gene expression derived from single-cell RNA sequencing of peripheral blood mononuclear cells from 7 SLE patients before and after CD19-CAR T cell therapy was compared with whole-blood transcriptome data from 30 SLE patients in remission on standard pharmacotherapy and 31 SLE patients before and 6 months after treatment with rituximab, belimumab, or cyclophosphamide. Pathway analysis was conducted using Functional Analysis of Individual Microarray Expression and gene set enrichment analysis.nnRESULTS: CD19-CAR T cell-induced remission was characterised by marked suppression of complement activation, type I interferon, DNA damage response (DDR), and cell death pathways compared with remission following conventional pharmacotherapy, alongside an upregulation of lipid metabolism pathways. Compared with rituximab and belimumab, CD19-CAR T cell therapy induced greater downregulation of type I/II interferon, DDR, and chemokine pathways. Compared with cyclophosphamide, CD19-CAR T cell therapy induced greater suppression of interferon, mitochondrial, and mammalian target of rapamycin signalling pathways.nnCONCLUSIONS: CD19-CAR T cell therapy induces substantial suppression of key immunological pathways involved in SLE, including complement activation and type I interferon responses, accompanied by a metabolic reprogramming. Molecular profiles of remission after CD19-CAR T cell therapy differ from those induced by conventional SLE pharmacotherapy, suggesting more profound CD19-CAR T cell-induced biological alterations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42146897,

title = {An Integrative Framework Identifies Cooperative Targeting of Host Pathways by Tick Salivary miRNAs},

author = {José María Medina and Guillermo Barturen and Michail Kotsyfakis and Michael Hackenberg},

doi = {10.34133/csbj.0106},

issn = {2001-0370},

year  = {2026},

date = {2026-01-01},

journal = {Comput Struct Biotechnol J},

volume = {35},

number = {1},

pages = {0106},

abstract = {Ticks are ectoparasites that modulate host responses to sustain prolonged blood feeding, and in , salivary microRNAs (miRNAs) represent promising candidates for manipulating host gene expression. Using phylogenetic footprinting combined with cooperative targeting analysis, we predicted deeply conserved miRNA-mRNA interactions that appear to contribute to tick lifecycle completion and tick's ability to parasitize diverse vertebrate hosts. Our analysis suggests that conserved tick miRNAs may mimic host miRNAs by exploiting shared target sites on host transcripts, potentially influencing regulatory circuits active during tick feeding and cross-kingdom communication. We identified 12 core tick salivary miRNAs-highly expressed and enriched in conserved target sites-predicted to cooperatively target 22 human genes, several of which are associated with processes relevant to parasitism establishment. These predicted cooperative interactions involve hub genes such as PDGFRA and NRG1, which are components of MAPK and PI3K-AKT pathways that regulate immune defense, tissue repair, and sensory responses. Our results suggest that  miRNAs could potentially influence host homeostasis through cooperative targeting mechanisms, and they introduce a broadly applicable framework that leverages evolutionary conservation to detect meaningful cross-species miRNA-mRNA interactions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40672966,

title = {Dysregulation of innate and adaptive lymphoid immunity may have implications for symptom attribution and predict responses to targeted therapies in neuropsychiatric systemic lupus erythematosus},

author = {Julius Lindblom and Guillermo Barturen and Lorenzo Beretta and Daniel Toro-Domínguez and Elena Carnero-Montoro and Maria Orietta Borghi and Jessica Castillo and Ellen Iacobaeus and Yvonne Enman and  and Chandra Mohan and Marta E Alarcón-Riquelme and Dionysis Nikolopoulos and Ioannis Parodis},

doi = {10.1016/j.jtauto.2025.100296},

issn = {2589-9090},

year  = {2025},

date = {2025-12-01},

journal = {J Transl Autoimmun},

volume = {11},

pages = {100296},

abstract = {OBJECTIVES: To gain insights into the pathogenesis of neuropsychiatric systemic lupus erythematosus (NPSLE) and identify potential drug targets through investigation of whole-blood human transcriptome.nnMETHODS: We analysed differentially expressed genes in peripheral blood from active central nervous system (CNS) lupus (n = 26) and active non-neuropsychiatric SLE (n = 38) patients versus healthy controls (n = 497) from the European PRECISESADS project (NTC02890121). We further explored dysregulated gene modules in active CNS lupus and their correlation with serological markers. Lastly, we performed regulatory network and druggability analysis.nnRESULTS: Unsupervised weighted gene co-expression network analysis (WGCNA) revealed 23 dysregulated gene modules and two subgroups of active CNS lupus. The interferon gene module was prominently upregulated in subgroup 1, while the B cell, T cell, and cytotoxic/natural killer (NK) cell modules were downregulated. Subgroup 2 showed less marked dysregulation patterns. Subgroup 1 had lower estimated proportions of lymphoid cell subsets and proportionally more patients positive for anti-dsDNA antibodies compared to subgroup 2, pointing to molecularly distinct subgroups or misclassification of subgroup 2.  prediction algorithms demonstrated a greater anticipated response to anifrolumab, C3 inhibitors, and calcineurin inhibitors for patients in CNS lupus subgroup 1 compared with subgroup 2.nnCONCLUSIONS: Gene dysregulation patterns related to innate and adaptive lymphoid immunity separated active CNS lupus patients into two distinct subgroups with differential anticipated response to type I interferon, C3, and calcineurin inhibition. Our study provides a conceptual framework for precision medicine in NPSLE and implications for overcoming the major clinical challenge of attributing neuropsychiatric features to SLE versus other causes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40415615,

title = {Identifying Predictive Biomarkers of Response in Patients With Rheumatoid Arthritis Treated With Adalimumab Using Machine Learning Analysis of Whole-Blood Transcriptomics Data},

author = {Chuan Fu Yap and Nisha Nair and Ann W Morgan and John D Isaacs and Anthony G Wilson and Kimme Hyrich and Guillermo Barturen and María Riva-Torrubia and Marta Gut and Ivo Gut and Marta E Alarcón Riquelme and Anne Barton and Darren Plant},

doi = {10.1002/art.43255},

issn = {2326-5205},

year  = {2025},

date = {2025-12-01},

journal = {Arthritis Rheumatol},

volume = {77},

number = {12},

pages = {1663--1672},

abstract = {OBJECTIVE: Tumornecrosis factor inhibitors (TNFi) have significantly improved rheumatoid arthritis (RA) management, yet variability in patient response remains a substantial challenge, with approximately 40% of patients discontinuing TNFi due to nonresponse or adverse effects. This study aimed to identify biomarkers predictive of adalimumab treatment response using whole-blood transcriptomics, leveraging machine learning models for data mining observed by targeted statistical analysis.nnMETHODS: A cohort of patients with RA starting TNFi therapy (n = 100) was assessed for treatment response at 6 months, with RNA sequencing performed on baseline (pretreatment) and 3-month follow-up samples. Machine learning classifiers were built to identify predictive biomarkers for treatment outcomes. This was observed by a network analysis on the biomarkers to elucidate the most influential biomarker, which was subsequently confirmed through survival analysis.nnRESULTS: Differential gene expression analysis in 97 samples passing quality control identified 84 genes associated with treatment response. Random forest classifiers achieved high predictive accuracy with area under the receiver operating characteristic curves up to 0.86, identifying genes contributing to treatment outcomes. Network analysis further elucidated gene interactions, highlighting marginal zone B And B1 cell-specific protein 1 (MZB1) as a novel biomarker not captured by machine learning alone. MZB1's role in B cell development and antibody production was associated with antidrug antibody formation, impacting treatment efficacy.nnCONCLUSION: This study advances the understanding of transcriptomic alterations in RA treatment and enhances our understanding of treatment response mechanisms. Although the gene signatures identified require independent replication, the study serves as a starting point to pave the way for personalized therapeutic strategies in patients commencing TNFi therapy in RA.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41167980,

title = {Mesenchymal Colorectal Cancers Secrete Vesicles With Unique Cargo That Can Be Used for Liquid Biopsy Based Diagnostics},

author = {Paris J Asif and Lauri H Borghuis and Sander R van Hooff and Anita E Grootemaat and Monique A J van Eijndhoven and Johan de Rooij and Nils J Groenewegen and Jennifer Perez Boza and Onno Kranenburg and Inne H M Borel Rinkes and Cristina Gómez-Martín and Hans F M Pruijt and Nicole N van der Wel and Arezo Torang and Tineke E Buffart and D Michiel Pegtel and Jan Paul Medema},

doi = {10.1002/jev2.70171},

issn = {2001-3078},

year  = {2025},

date = {2025-11-01},

journal = {J Extracell Vesicles},

volume = {14},

number = {11},

pages = {e70171},

abstract = {Tumour-derived extracellular vesicles (TEVs) play a crucial role in cancer progression, metastasis and therapy resistance but their distinct profiles across different cancer stages and molecular subtypes remain underexplored. This study initially analysed TEVs from all CMS subtypes in colorectal cancer (CRC) cells and continued focusing on the epithelial (CMS2) and mesenchymal (CMS4) subtypes using six cell lines and clinical samples. Investigation of the cargo of vesicles secreted by the two subtypes revealed significant differences in mRNA, miRNA, and protein profiles between the two subtypes. Notably, CMS2 predominantly secreted smaller, Tetraspanin-8 (TSPAN8) enriched EVs, while CMS4 produced both larger and smaller EVs, enriched in TSPAN4. This underscores the complexity of vesicle heterogeneity between these subtypes. Additionally, we assessed miRNA profiles from plasma-derived bulk TEVs in CRC patients. Our integrative analysis identified a subtype-specific miRNA signature, indicating that TEVs from CMS2 and CMS4 cells can be detected in circulation and may serve as potential diagnostic tool for CRC.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41118569,

title = {Knowing is not enough; we must apply: the case for rigorous microRNA annotation standards},

author = {Michael Hackenberg and Panagiotis Kalogeropoulos and Kevin J Peterson and Marc R Friedländer and Bastian Fromm},

doi = {10.1093/nar/gkaf1049},

issn = {1362-4962},

year  = {2025},

date = {2025-10-01},

journal = {Nucleic Acids Res},

volume = {53},

number = {19},

abstract = {MicroRNAs are by far the most extensively studied and best-characterized class of small RNAs. This depth of knowledge may partly explain the persistent eagerness in the field to classify new sequences as microRNAs-since labeling a molecule as such often implies immediate functional insight and biological relevance. However, this enthusiasm has led to the publication and deposition of thousands of spurious microRNA entries in public repositories, increasing the risk of misinterpretation-particularly when these sequences are linked to human disease. To address this, we present a concise, four-part checklist for evaluating putative microRNAs, based on structural, genomic, functional, and expression-related criteria. Applying it to "Mir-690" and nine other examples, which are not listed in the curated microRNA database MirGeneDB, but highly cited, we find no support for their classification as microRNAs. They fail to meet core microRNA annotation criteria, lack structural features, conservation of targets, and reproducible or microRNA-typical expression evidence. Our findings underscore the need for heightened scrutiny and standardized validation in microRNA research. The checklist we provide offers a practical tool for authors, editors, reviewers, and readers to critically assess microRNA claims-particularly when such sequences are proposed as biomarkers or therapeutic targets in translational studies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40961943,

title = {Circulating extracellular vesicle isomiR signatures predict therapy response in patients with multiple myeloma},

author = {Cristina Gómez-Martín and Esther E E Drees and Monique A J van Eijndhoven and Nils J Groenewegen and Steven Wang and Sandra A W M Verkuijlen and Jan R T van Weering and Ernesto Aparicio-Puerta and Leontien Bosch and Kris A Frerichs and Christie P M Verkleij and Marie J Kersten and Josée M Zijlstra and Daphne de Jong and Catharina G M Groothuis-Oudshoorn and Michael Hackenberg and Johan R de Rooij and Niels W C J van de Donk and D Michiel Pegtel},

doi = {10.1016/j.xcrm.2025.102358},

issn = {2666-3791},

year  = {2025},

date = {2025-10-01},

journal = {Cell Rep Med},

volume = {6},

number = {10},

pages = {102358},

abstract = {Multiple myeloma (MM) is a plasma cell neoplasm characterized by high inter- and intra-patient clonal heterogeneity, leading to high variability in therapeutic responses. Minimally invasive biomarkers that predict response may help personalize treatment decisions. IsoSeek, a single-nucleotide resolution small RNA sequencing method can profile thousands of microRNAs (miRNAs) and their variants (isomiRs) from patient plasma-purified extracellular vesicles (EVs). Machine learning-generated miRNA/isomiR classifiers accurately predict therapeutic response in relapsed/refractory MM (RRMM) patients receiving daratumumab-containing regimens, achieving an area-under-the-curve of 0.98 (95% confidence interval [CI]:0.94-1.00). A classifier signature with the plasma cell-selective miR-148-3p, predicts durable response (≥6 months), progression-free (hazard ratio [HR]: 33.09, 95% CI: 4.2-262, p < 0.001), and overall survival (HR: 3.81, 95% CI: 1.05-13.99, p < 0.05). Targetome analysis connects the prognostic classifier to established MM drug targets BCL2 and MYC suggesting biological relevance. Thus, EV-isomiR sequencing in MM patients offers a tumor-naïve alternative to an invasive bone-marrow biopsy for predicting treatment outcome.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40903491,

title = {Discovery of core genes for systemic lupus erythematosus via genome-wide aggregated trans-effects analysis},

author = {Andrii Iakovliev and Olivia Castellini-Pérez and Buddhiprabha Erabadda and  and  and Javier Martín and Guillermo Barturen and Paul M McKeigue and Elena Carnero-Montoro and Marta E Alarcón-Riquelme and Athina Spiliopoulou},

doi = {10.1038/s41435-025-00352-4},

issn = {1476-5470},

year  = {2025},

date = {2025-10-01},

journal = {Genes Immun},

volume = {26},

number = {5},

pages = {497--508},

abstract = {The "omnigenic" hypothesis postulates that the polygenic effects of common variants on a typical complex trait coalesce on relatively few core genes through trans-effects on their expression. Our aim was to identify core genes for systemic lupus erythematosus (SLE) by testing for association with genome-wide aggregated trans-effects (GATE) scores for gene expression in a large genetic dataset (5267/4909 SLE cases/controls). SLE was strongly associated with upregulation of expression of eight interferon-stimulated genes driven by shared trans-effects. We estimate that trans-effects on interferon signaling account for 9% of the total genetic effect on SLE risk. Outside this pathway, GATE analysis detected twenty putative core genes for SLE. Direct protein measurements for these genes were strongly associated with SLE in UK Biobank. Two putative core genes (TNFRSF17, TNFRSF13B) encode receptors (BCMA, TACI) expressed on B cells; their ligands (BAFF, APRIL) are targeted by drugs licensed or in development for SLE. Four genes (PDCD1, LAG3, TNFRSF9, CD27) encode receptors that have been characterized as immune checkpoints, and three (CD5L, SIGLEC1, CXCL13) are biomarkers of SLE disease activity. These results provide genetic support for existing drug targets in SLE (interferon signaling, BAFF/APRIL signaling) and identify other possible therapeutic targets including immune checkpoint receptors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41148977,

title = {Genome Divergence Based on Entropic Segmentation of DNA},

author = {Pedro A Bernaola-Galván and Pedro Carpena and Cristina Gómez-Martín and José L Oliver},

doi = {10.3390/e27101019},

issn = {1099-4300},

year  = {2025},

date = {2025-09-01},

journal = {Entropy (Basel)},

volume = {27},

number = {10},

abstract = {The concept of a genome signature broadly refers to characteristic patterns in DNA sequences that enable the identification and comparison of species or individuals, often without requiring sequence alignment. Such signatures have applications ranging from forensic identification of individuals to cancer genomics. In comparative genomics and evolutionary biology, genome signatures typically rely on statistical properties of DNA that are species-specific and carry phylogenetic information reflecting evolutionary relationships. We propose a novel genome signature based on the compositional structure of DNA, defined by the distributions of strong/weak, purine/pyrimidine, and keto/amino ratios across DNA segments identified through entropic segmentation. We observe that these ratio distributions are similar among closely related species but differ markedly between distant ones. To quantify these differences, we employ the Jensen-Shannon distance-a symmetric and robust measure of distributional dissimilarity-to define a genome-to-genome distance metric, termed Segment Compositional Distance (D). Our results demonstrate a clear correlation between D and species divergence times, and also that this metric captures a strong phylogenetic signal. Our method employs a genome-wide approach rather than tracking specific mutations; thus, D offers a coarse-grained perspective on genome compositional evolution, contributing to the ongoing discussion surrounding the molecular clock hypothesis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40374430,

title = {New IgG and IgA autoantibody specificities against DNA-binding and RNA-binding proteins discriminate systemic lupus erythematosus from health and non-lupus autoimmunity-could anti-LIN28A enhance precision in diagnostics?},

author = {Ioannis Parodis and Denis Lagutkin and Julius Lindblom and Helena Idborg and Lorenzo Beretta and Maria Orietta Borghi and  and Janique M Peyper and Guillermo Barturen and Per-Johan Jakobsson and Marta E Alarcón-Riquelme and Natalia Sherina and Dionysis Nikolopoulos},

doi = {10.1016/j.ard.2025.04.003},

issn = {1468-2060},

year  = {2025},

date = {2025-07-01},

journal = {Ann Rheum Dis},

volume = {84},

number = {7},

pages = {1180--1194},

abstract = {OBJECTIVES: In response to the urgent unmet needs of heterogeneity, unpredictability, and diagnostic delay in systemic lupus erythematosus (SLE), we aimed to identify and validate new immunoglobulin (Ig)G and IgA autoantibody specificities.nnMETHODS: Using a KoRectly EXpressed technology-based microarrays (i-Ome Discovery; Sengenics), we screened for circulating IgG and IgA autoantibodies against 1609 proteins in 2 independent cohorts (discovery: NTC02890121; validation: NCT02890134) comprising patients with SLE (n = 199 and n = 30), primary Sjögren's disease (n = 115 and n = 31), and systemic sclerosis (n = 115 and n = 24), and healthy controls (HCs; n = 111 and n = 84), respectively.nnRESULTS: We identified and validated 5 IgG (anti-Lin-28 homolog A [LIN28A], anti-HNRNPA2B1, anti-HMG20B, anti-HMGB2, and anti-alpha-globin transcription factor CP2 [TFCP2]) and 4 IgA (anti-LIN28A, anti-HMG20B, anti-SUB1, and anti-TFCP2) autoantibodies that demonstrated high specificity for SLE (0.91-0.94), along with consistent and robust positivity (0.22-0.69) in differentially abundant autoantibody (daAAb) analysis between SLE and comparator groups. IgG and IgA anti-LIN28A levels varied over a 14-month follow-up in the validation cohort of newly diagnosed patients with SLE and exhibited metrics that outperformed those of traditional autoantibody markers such as anti-double-stranded DNA. Clustering of patients with SLE based on autoantibody positivity (levels above the HC median plus 2 IQRs in the discovery cohort) status revealed 1 subgroup demonstrating seroreactivity against multiple antigens, 3 exhibiting varying reactivity, and 1 showing no reactivity. In pathway analysis, daAAb targets pointed to DNA-binding and RNA-binding and transcription functions.nnCONCLUSIONS: Novel autoantibodies validated in this study may enhance diagnostics and molecular characterisation in SLE. The prominent IgA seroreactivity implicates important roles of mucosal tissues in SLE autoimmunity, warranting further investigation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40348637,

title = {Novel IgG and IgA autoantibodies validated in two independent cohorts are associated with disease activity and determine organ manifestations in systemic lupus erythematosus: implications for anti-LIN28A, anti-HMGN5, anti-IRF5, and anti-TGIF1},

author = {Julius Lindblom and Denis Lagutkin and Natalia Sherina and Helena Idborg and Lorenzo Beretta and Maria Orietta Borghi and  and Janique M Peyper and Guillermo Barturen and Per-Johan Jakobsson and Marta E Alarcón-Riquelme and Dionysis Nikolopoulos and Ioannis Parodis},

doi = {10.1016/j.ard.2025.04.008},

issn = {1468-2060},

year  = {2025},

date = {2025-07-01},

journal = {Ann Rheum Dis},

volume = {84},

number = {7},

pages = {1164--1179},

abstract = {OBJECTIVES: This study aimed to identify and validate novel autoantibodies that reflect global and organ-specific disease activity in systemic lupus erythematosus (SLE).nnMETHODS: Plasma samples were screened for IgG and IgA seroreactivity against 1609 protein autoantigens using a microarray (i-Ome Discovery; Sengenics). We determined differentially abundant autoantibodies (daAAbs) in patients with SLE vs healthy controls within a discovery (n = 196 vs n = 110; NTC02890121) and an independent validation cohort (n = 30 vs n = 83; NCT02890134) from the European PRECISESADS project. Validated daAAbs were analysed in relation to global and organ-specific disease activity using linear and logistic regression, along with daAAb target pathway enrichment analysis.nnRESULTS: We validated 89 IgG and 66 IgA daAAbs. IgG anti-LIN28A, IgG anti-HMGN5, and both isotypes for anti-IRF5 and anti-TGIF1 were associated with a SLE disease activity index 2000 score of ≥10, negatively associated with lupus low disease activity state, and highly prevalent in subgroups with active disease across organ manifestations. IgG anti-LIN28A levels exceeded the cutoff for positivity in 53% of patients with central nervous system (CNS) involvement, a prevalence higher than that observed for anti-double-stranded DNA (20%) and 47% of patients with renal activity. A cluster of IgG and IgA daAAbs against RNA-binding proteins, including anti-LIN28A, was linked to CNS involvement. IgA anti-FOSL2 was elevated uniquely in patients with musculoskeletal activity. Enriched pathways involving DNA binding and repair showed considerable overlap across manifestations.nnCONCLUSIONS: Novel IgG and IgA autoantibodies, including IgG anti-LIN28A, IgG anti-HMGN5, IgG and IgA anti-IRF5, and IgG and IgA anti-TGIF1 were associated with SLE disease activity and highly abundant across organ manifestations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40407596,

title = {Small RNA Landscape of Platelet Dust: Platelet-Derived Extracellular Vesicles from Patients with Non-Small-Cell Lung Cancer},

author = {Mafalda Antunes-Ferreira and Ilias Glogovitis and Diogo Fortunato and Silvia D'Ambrosi and Mariona Colom Saborit and Galina Yahubyan and Vesselin Baev and Michael Hackenberg and Natasa Zarovni and Thomas Wurdinger and Danijela Koppers-Lalic},

doi = {10.3390/ncrna11030038},

issn = {2311-553X},

year  = {2025},

date = {2025-05-01},

journal = {Noncoding RNA},

volume = {11},

number = {3},

abstract = { Platelet-derived Extracellular Vesicles, or "Platelet Dust" (PD), are reported as the most-abundant extracellular vesicles in plasma. However, the PD molecular content, especially the small RNA profile, is still poorly characterized. This study aims to characterize PD and other extracellular vesicles (EVs) in patients with non-small-cell lung cancer (NSCLC), focusing on their small RNA signatures and diagnostic potential.  The EVs were isolated directly from the plasma of healthy donors and patients with NSCLC using the surface markers CD9, CD63, CD81 (overall EVs), and CD61 (PD). Small RNA sequencing was then performed to comprehensively profile the miRNAs.  Our analysis revealed distinct small RNA profiles in the EVs and the PD from the patients with NSCLC. The EVs (CD9-, CD63-, and CD81-positive) showed the enrichment of four miRNAs and the depletion of ten miRNAs, while the PD (CD61-positive) exhibited a more complex profile, with nineteen miRNAs enriched and nine miRNAs depleted in the patients with NSCLC compared to those of the healthy controls.  This exploratory study enhances our understanding of miRNA composition within different plasma vesicle populations, shedding light on the biology of plasma vesicles and their contents. Furthermore, utilizing an extracellular vesicle isolation method with potential clinical applicability offers the prospect of improved cancer characterization and detection by selecting the most informative subpopulation of plasma vesicles.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40210974,

title = {Strong evidence for the evolution of decreasing compositional heterogeneity in SARS-CoV-2 genomes during the pandemic},

author = {José L Oliver and Pedro Bernaola-Galván and Pedro Carpena and Francisco Perfectti and Cristina Gómez-Martín and Silvia Castiglione and Pasquale Raia and Miguel Verdú and Andrés Moya},

doi = {10.1038/s41598-025-95893-z},

issn = {2045-2322},

year  = {2025},

date = {2025-04-01},

journal = {Sci Rep},

volume = {15},

number = {1},

pages = {12246},

abstract = {The rapid evolution of SARS-CoV-2 during the pandemic was characterized by the fixation of a plethora of mutations, many of which enable the virus to evade host resistance, likely altering the virus' genome compositional structure (i.e., the arrangement of compositional domains of varying lengths and nucleotide frequencies within the genome). To explore this hypothesis, we summarize the evolutionary effects of these mutations by computing the Sequence Compositional Complexity (SCC) in random stratified datasets of fully sequenced genomes. Phylogenetic ridge regression of SCC against time reveals a striking downward evolutionary trend, suggesting the ongoing adaptation of the virus's genome structure to the human host. Other genomic features, such as strand asymmetry, the effective number of K-mers, and the depletion of CpG dinucleotides, each linked to the virus's adaptation to its human host, also exhibit decreasing phylogenetic trends throughout the pandemic, along with strong phylogenetic correlations to SCC. We hypothesize that viral CpG depletion (throughout C➔U changes), promoted by directional mutational pressures exerted on the genome by the host antiviral defense systems, may play a key role in the decrease of SARS-CoV-2 genome compositional heterogeneity, with specific adaptation to the human host occurring as a form of genetic mimicry. Overall, our findings suggest a decelerating evolution of reduced compositional complexity in SCC, whereas the number of K-mers and the depletion of CpG dinucleotides are still increasing. These results indicate a genome-wide evolutionary trend toward a more symmetric and homogeneous genome compositional structure in SARS-CoV-2, which is partly still ongoing.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39468422,

title = {A Strong Dysregulated Myeloid Component in the Epigenetic Landscape of Systemic Sclerosis: An Integrated DNA Methylome and Transcriptome Analysis},

author = {Javier Martínez-López and Lourdes Ortiz-Fernandez and Elkyn Estupiñán-Moreno and Martin Kerick and Eduardo Andrés-León and Laura C Terron-Camero and Elena Carnero-Montoro and Guillermo Barturen and Lorenzo Beretta and Isabel Almeida and  and Marta E Alarcón-Riquelme and Esteban Ballestar and Marialbert Acosta-Herrera and Javier Martín},

doi = {10.1002/art.43044},

issn = {2326-5205},

year  = {2025},

date = {2025-04-01},

journal = {Arthritis Rheumatol},

volume = {77},

number = {4},

pages = {439--449},

abstract = {OBJECTIVE: Nongenetic factors influence systemic sclerosis (SSc) pathogenesis, underscoring epigenetics as a relevant contributor to the disease. We aimed to unravel DNA methylation abnormalities associated with SSc through an epigenome-wide association study.nnMETHODS: We analyzed DNA methylation data from whole-blood samples in 179 patients with SSc and 241 unaffected individuals to identify differentially methylated positions (DMPs) with a false discovery rate (FDR) <0.05. These results were further integrated with RNA sequencing data from the same patients to assess their functional consequence. Additionally, we examined the impact of DNA methylation changes on transcription factors and analyzed the relationship between alterations of the methylation and gene expression profile and serum proteins levels.nnRESULTS: This analysis yielded 525 DMPs enriched in immune-related pathways, with leukocyte cell-cell adhesion being the most significant (FDR = 4.91 × 10), prioritizing integrins as they were exposed by integrating methylome and transcriptome data. Furthermore, through this integrative approach, we observed an enrichment of neutrophil-related pathways, highlighting this myeloid cell type as a relevant contributor in SSc pathogenesis. In addition, we uncovered novel profibrotic and proinflammatory mechanisms involved in the disease. Finally, the altered epigenetic and transcriptomic signature revealed an increased activity of CCAAT/enhancer-binding protein transcription factor family in SSc, which is crucial in the myeloid lineage development.nnCONCLUSION: Our findings uncover the impaired epigenetic regulation of the disease and its impact on gene expression, identifying new molecules for potential clinical applications and improving our understanding of SSc pathogenesis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40138719,

title = {DGCR8 haploinsufficiency leads to primate-specific RNA dysregulation and pluripotency defects},

author = {Ana Colomer-Boronat and Lisanne I Knol and Guillermo Peris and Laura Sanchez and Silvia Peluso and Pablo Tristan-Ramos and Ana Gazquez-Gutierrez and Priscilla Chin and Katrina Gordon and Guillermo Barturen and Robert E Hill and Francisco J Sanchez-Luque and Jose Luis Garcia-Perez and Alasdair Ivens and Sara Macias and Sara R Heras},

doi = {10.1093/nar/gkaf197},

issn = {1362-4962},

year  = {2025},

date = {2025-03-01},

journal = {Nucleic Acids Res},

volume = {53},

number = {6},

abstract = {The 22q11.2 deletion syndrome (22qDS) is a human disorder where the majority of clinical manifestations originate during embryonic development. 22qDS is caused by a microdeletion in one chromosome 22, including DGCR8, an essential gene for microRNA (miRNA) production. However, the impact of DGCR8 hemizygosity on human development is still unclear. In this study, we generated two human pluripotent cell models containing a single functional DGCR8 allele to elucidate its role in early development. DGCR8+/- human embryonic stem cells (hESCs) showed increased apoptosis as well as self-renewal and differentiation defects in both the naïve and primed states. The expression of primate-specific miRNAs was largely affected, due to impaired miRNA processing and chromatin accessibility. DGCR8+/- hESCs also displayed a pronounced reduction in human endogenous retrovirus class H (HERVH) expression, a primate-specific retroelement essential for pluripotency maintenance. The reintroduction of miRNAs belonging to the primate-specific C19MC cluster as well as the miR-371-3 cluster rescued the defects of DGCR8+/- cells. Mechanistically, downregulation of HERVH by depletion of primate-specific miRNAs was mediated by KLF4. Altogether, we show that DGCR8 is haploinsufficient in humans and that miRNAs and transposable elements may have co-evolved in primates as part of an essential regulatory network to maintain stem cell identity.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40777011,

title = {Optimized network inference for immune diseased single cells},

author = {Elena Merino Tejero and Dwain Jude Vaz and Guillermo Barturen and María Rivas-Torrubia and Marta E Alarcón-Riquelme and Walter Kolch and David Matallanas},

doi = {10.3389/fimmu.2025.1597862},

issn = {1664-3224},

year  = {2025},

date = {2025-01-01},

journal = {Front Immunol},

volume = {16},

pages = {1597862},

abstract = {INTRODUCTION: Mathematical models are powerful tools that can be used to advance our understanding of complex diseases. Autoimmune disorders such as systemic lupus erythematosus (SLE) are highly heterogeneous and require high-resolution mechanistic approaches. In this work, we present ONIDsc, a single-cell regulatory network inference model designed to elucidate immune-related disease mechanisms in SLE.nnMETHODS: ONIDsc enhances SINGE's Generalized Lasso Granger (GLG) causality model used in Single-cell Inference of Networks using Granger ensembles (SINGE) by finding the optimal lambda penalty with cyclical coordinate descent. We benchmarked ONIDsc against existing models and found it consistently outperforms SINGE and other methods when gold standards are generated from chromatin immunoprecipitation sequencing (ChIP-seq) and ChIP-chip experiments. We then applied ONIDsc to three large-scale datasets, one from control patients and the two from SLE patients, to reconstruct networks common to different immune cell types.nnRESULTS: ONIDsc identified four gene transcripts: matrix remodelling-associated protein 8 (MXRA8), nicotinamide adenine dinucleotide kinase (NADK), RNA Polymerase III Subunit GL (POLR3GL) and Ultrabithorax Domain Protein 11 (UBXN11) in CD4+ T-lymphocytes, CD8+ Regulatory T-Lymphocytes, CD8+ T-lymphocytes 1 and Low Density Granulocytes that were present in SLE patients but absent in controls.nnDISCUSSION: These genes were significantly related to nicotinate metabolism, ribonucleic acid (RNA) transcription, protein phosphorylation and the Rho family GTPase (RND) 1-3 signaling pathways, previously associated with immune regulation. Our results highlight ONIDsc's potential as a powerful tool for dissecting physiological and pathological processes in immune cells using high-dimensional single-cell data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39838418,

title = {Genome sequences of four Ixodes species expands understanding of tick evolution},

author = {Alexandra Cerqueira de Araujo and Benjamin Noel and Anthony Bretaudeau and Karine Labadie and Matéo Boudet and Nachida Tadrent and Benjamin Istace and Salima Kritli and Corinne Cruaud and Robert Olaso and Jean-François Deleuze and Maarten J Voordouw and Caroline Hervet and Olivier Plantard and Aya Zamoto-Niikura and Thomas Chertemps and Martine Maïbèche and Frédérique Hilliou and Gaëlle Le Goff and Jindřich Chmelař and Vilém Mazák and Mohamed Amine Jmel and Michalis Kotsyfakis and José María Medina and Michael Hackenberg and Ladislav Šimo and Fotini A Koutroumpa and Patrick Wincker and Petr Kopáček and Jan Perner and Jean-Marc Aury and Claude Rispe},

doi = {10.1186/s12915-025-02121-1},

issn = {1741-7007},

year  = {2025},

date = {2025-01-01},

journal = {BMC Biol},

volume = {23},

number = {1},

pages = {17},

abstract = {BACKGROUND: Ticks, hematophagous Acari, pose a significant threat by transmitting various pathogens to their vertebrate hosts during feeding. Despite advances in tick genomics, high-quality genomes were lacking until recently, particularly in the genus Ixodes, which includes the main vectors of Lyme disease.nnRESULTS: Here, we present the genome sequences of four tick species, derived from a single female individual, with a particular focus on the European species Ixodes ricinus, achieving a chromosome-level assembly. Additionally, draft assemblies were generated for the three other Ixodes species, I. persulcatus, I. pacificus, and I. hexagonus. The quality of the four genomes and extensive annotation of several important gene families have allowed us to study the evolution of gene repertoires at the level of the genus Ixodes and of the tick group. We have determined gene families that have undergone major amplifications during the evolution of ticks, while an expression atlas obtained for I. ricinus reveals striking patterns of specialization both between and within gene families. Notably, several gene family amplifications are associated with a proliferation of single-exon genes-most strikingly for fatty acid elongases and sulfotransferases.nnCONCLUSIONS: The integration of our data with existing genomes establishes a solid framework for the study of gene evolution, improving our understanding of tick biology. In addition, our work lays the foundations for applied research and innovative control targeting these organisms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39794699,

title = {BiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics data},

author = {Cristian Iperi and Álvaro Fernández-Ochoa and Guillermo Barturen and Jacques-Olivier Pers and Nathan Foulquier and Eleonore Bettacchioli and Marta Alarcón-Riquelme and  and Divi Cornec and Anne Bordron and Christophe Jamin},

doi = {10.1186/s12859-024-06022-y},

issn = {1471-2105},

year  = {2025},

date = {2025-01-01},

journal = {BMC Bioinformatics},

volume = {26},

number = {1},

pages = {8},

abstract = {BACKGROUND: Interpreting biological system changes requires interpreting vast amounts of multi-omics data. While user-friendly tools exist for single-omics analysis, integrating multiple omics still requires bioinformatics expertise, limiting accessibility for the broader scientific community.nnRESULTS: BiomiX tackles the bottleneck in high-throughput omics data analysis, enabling efficient and integrated analysis of multiomics data obtained from two cohorts. BiomiX incorporates diverse omics data, using DESeq2/Limma packages for transcriptomics, and quantifying metabolomics peak differences, evaluated via the Wilcoxon test with the False Discovery Rate correction. The metabolomics annotation for Liquid Chromatography-Mass Spectrometry untargeted metabolomics is additionally supported using the mass-to-charge ratio in the CEU Mass Mediator database and fragmentation spectra in the TidyMass package. Methylomics analysis is performed using the ChAMP R package. Finally, Multi-Omics Factor Analysis (MOFA) integration identifies shared sources of variation across omics data. BiomiX also generates statistics, report figures and integrates EnrichR and GSEA for biological process exploration and subgroup analysis based on user-defined gene panels enhancing condition subtyping. BiomiX fine-tunes MOFA models, to optimize factors number selection, distinguishing between cohorts and providing tools to interpret discriminative MOFA factors. The interpretation relies on innovative bibliography research on Pubmed, which provides the articles most related to the discriminant factor contributors. Furthermore, discriminant MOFA factors are correlated with clinical data, and the top contributing pathways are explored, all with the aim of guiding the user in factor interpretation.nnCONCLUSIONS: The analysis of single-omics and multi-omics integration in a standalone tool, along with MOFA implementation and its interpretability via literature, represents significant progress in the multi-omics field in line with the "Findable, Accessible, Interoperable, and Reusable" data principles. BiomiX offers a wide range of parameters and interactive data visualization, allowing for personalized analysis tailored to user needs. This R-based, user-friendly tool is compatible with multiple operating systems and aims to make multi-omics analysis accessible to non-experts in bioinformatics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39673268,

title = {MirGeneDB 3.0: improved taxonomic sampling, uniform nomenclature of novel conserved microRNA families and updated covariance models},

author = {Alexander W Clarke and Eirik Høye and Anju Angelina Hembrom and Vanessa Molin Paynter and Jakob Vinther and Łukasz Wyrożemski and Inna Biryukova and Alessandro Formaggioni and Vladimir Ovchinnikov and Holger Herlyn and Alexandra Pierce and Charles Wu and Morteza Aslanzadeh and Jeanne Cheneby and Pedro Martinez and Marc R Friedländer and Eivind Hovig and Michael Hackenberg and Sinan Uğur Umu and Morten Johansen and Kevin J Peterson and Bastian Fromm},

doi = {10.1093/nar/gkae1094},

issn = {1362-4962},

year  = {2025},

date = {2025-01-01},

journal = {Nucleic Acids Res},

volume = {53},

number = {D1},

pages = {D116--D128},

abstract = {We present a major update of MirGeneDB (3.0), the manually curated animal microRNA gene database. Beyond moving to a new server and the creation of a computational mirror, we have expanded the database with the addition of 33 invertebrate species, including representatives of 5 previously unsampled phyla, and 6 mammal species. MirGeneDB now contains entries for 21 822 microRNA genes (5160 of these from the new species) belonging to 1743 microRNA families. The inclusion of these new species allowed us to refine both the evolutionary node of appearance of a number of microRNA genes/families, as well as MirGeneDB's phylogenetically informed nomenclature system. Updated covariance models of all microRNA families, along with all smallRNA read data are now downloadable. These enhanced annotations will allow researchers to analyze microRNA properties such as secondary structure and features of their biogenesis within a robust phylogenetic context and without the database plagued with numerous false positives and false negatives. In light of these improvements, MirGeneDB 3.0 will assume the responsibility for naming conserved novel metazoan microRNAs. MirGeneDB is part of RNAcentral and Elixir Norway and is publicly and freely available at mirgenedb.org.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39623153,

title = {Revisiting the heterogeneity of interferon-related autoimmune diseases},

author = {Guillermo Barturen and Marta E Alarcón-Riquelme},

doi = {10.1038/s41584-024-01196-4},

issn = {1759-4804},

year  = {2025},

date = {2025-01-01},

journal = {Nat Rev Rheumatol},

volume = {21},

number = {1},

pages = {7--8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39633268,

title = {Pheno-Ranker: a toolkit for comparison of phenotypic data stored in GA4GH standards and beyond},

author = {Ivo C Leist and María Rivas-Torrubia and Marta E Alarcón-Riquelme and Guillermo Barturen and Precisesads Clinical Consortium and Ivo G Gut and Manuel Rueda},

doi = {10.1186/s12859-024-05993-2},

issn = {1471-2105},

year  = {2024},

date = {2024-12-01},

journal = {BMC Bioinformatics},

volume = {25},

number = {1},

pages = {373},

abstract = {BACKGROUND: Phenotypic data comparison is essential for disease association studies, patient stratification, and genotype-phenotype correlation analysis. To support these efforts, the Global Alliance for Genomics and Health (GA4GH) established Phenopackets v2 and Beacon v2 standards for storing, sharing, and discovering genomic and phenotypic data. These standards provide a consistent framework for organizing biological data, simplifying their transformation into computer-friendly formats. However, matching participants using GA4GH-based formats remains challenging, as current methods are not fully compatible, limiting their effectiveness.nnRESULTS: Here, we introduce Pheno-Ranker, an open-source software toolkit for individual-level comparison of phenotypic data. As input, it accepts JSON/YAML data exchange formats from Beacon v2 and Phenopackets v2 data models, as well as any data structure encoded in JSON, YAML, or CSV formats. Internally, the hierarchical data structure is flattened to one dimension and then transformed through one-hot encoding. This allows for efficient pairwise (all-to-all) comparisons within cohorts or for matching of a patient's profile in cohorts. Users have the flexibility to refine their comparisons by including or excluding terms, applying weights to variables, and obtaining statistical significance through Z-scores and p-values. The output consists of text files, which can be further analyzed using unsupervised learning techniques, such as clustering or multidimensional scaling (MDS), and with graph analytics. Pheno-Ranker's performance has been validated with simulated and synthetic data, showing its accuracy, robustness, and efficiency across various health data scenarios. A real data use case from the PRECISESADS study highlights its practical utility in clinical research.nnCONCLUSIONS: Pheno-Ranker is a user-friendly, lightweight software for semantic similarity analysis of phenotypic data in Beacon v2 and Phenopackets v2 formats, extendable to other data types. It enables the comparison of a wide range of variables beyond HPO or OMIM terms while preserving full context. The software is designed as a command-line tool with additional utilities for CSV import, data simulation, summary statistics plotting, and QR code generation. For interactive analysis, it also includes a web-based user interface built with R Shiny. Links to the online documentation, including a Google Colab tutorial, and the tool's source code are available on the project home page: https://github.com/CNAG-Biomedical-Informatics/pheno-ranker .},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39115426,

title = {Tumor-Secreted Extracellular Vesicles Counteract Therapy Response by Triggering Inflammatory Mesenchymal Stem Cell Development},

author = {Crescenzo Massaro and Hilal N Sensoy and Manon Mulders and Celine De Schrijver and Cristina Gómez-Martín and Juan Simon Nieto and Tonny Lagerweij and Alisha Atmopawiro and Jennifer Pérez-Boza and Maarten Bebelman and Leontien Bosch and Simone Foderaro and Mafalda Neves Ferreira and Monique A J van Eijndhoven and Jan R T van Weering and Carmela Dell'Aversana and Lucia Altucci and Cemile Dilara Savci-Heijink and Niels W C J van de Donk and Cristina Giorgio and Laura Brandolini and Marcello Allegretti and Dirk Michiel Pegtel and Serena Rubina Baglio},

doi = {10.1158/1078-0432.CCR-23-4097},

issn = {1557-3265},

year  = {2024},

date = {2024-10-01},

journal = {Clin Cancer Res},

volume = {30},

number = {20},

pages = {4714--4728},

abstract = {PURPOSE: Therapy resistance is a major clinical hurdle in bone cancer treatment and seems to be largely driven by poorly understood microenvironmental factors. Recent evidence suggests a critical role for a unique subpopulation of mesenchymal stem cells with inflammatory features (iMSC), though their origin and function remained unexplored. We demonstrate that cancer-secreted extracellular vesicles (EV) trigger the development of iMSCs, which hinder therapy response in vivo, and set out to identify strategies to counteract their function.nnEXPERIMENTAL DESIGN: The role of iMSCs in therapy resistance was evaluated in an orthotopic xenograft mouse model of osteosarcoma. EV-induced alterations of the MSC transcriptome were analyzed and compared with single-cell RNA sequencing data of biopsies from patients with osteosarcoma and multiple myeloma. Functional assays identified EV components driving iMSC development. We assessed the efficacy of clinical drugs in blocking iMSC-induced resistance in vivo.nnRESULTS: We found that iMSCs are induced by interaction with cancer EVs and completely abrogate the antimetastatic effect of TGFβ signaling inhibition. Importantly, EV-induced iMSCs faithfully recapitulate the inflammatory single-cell RNA signature of stromal cells enriched in biopsies from patients with multiple myeloma and osteosarcoma. Mechanistically, cancer EVs act through two distinct mechanisms. EV-associated TGFβ induces IL6 production, whereas the EV-RNA cargo enhances TLR3-mediated chemokine production. We reveal that simultaneous blockade of downstream EV-activated pathways with ladarixin and tocilizumab disrupts metastasis formation and overcomes iMSC-induced resistance.nnCONCLUSIONS: Our observations establish iMSCs as major contributors to drug resistance, reveal EVs as triggers of iMSC development, and highlight a promising combination strategy to improve therapy response in patients with bone cancer.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39013887,

title = {Molecular subtypes explain lupus epigenomic heterogeneity unveiling new regulatory genetic risk variants},

author = {Olivia Castellini-Pérez and Elena Povedano and Guillermo Barturen and Manuel Martínez-Bueno and Andrii Iakovliev and Martin Kerick and Raúl López-Domínguez and Concepción Marañón and Javier Martín and Esteban Ballestar and  and  and María Orietta Borghi and Weiliang Qiu and Cheng Zhu and Srinivas Shankara and Athina Spiliopoulou and Emanuele de Rinaldis and Elena Carnero-Montoro and Marta E Alarcón-Riquelme},

doi = {10.1038/s41525-024-00420-0},

issn = {2056-7944},

year  = {2024},

date = {2024-07-01},

journal = {NPJ Genom Med},

volume = {9},

number = {1},

pages = {38},

abstract = {The heterogeneity of systemic lupus erythematosus (SLE) can be explained by epigenetic alterations that disrupt transcriptional programs mediating environmental and genetic risk. This study evaluated the epigenetic contribution to SLE heterogeneity considering molecular and serological subtypes, genetics and transcriptional status, followed by drug target discovery. We performed a stratified epigenome-wide association studies of whole blood DNA methylation from 213 SLE patients and 221 controls. Methylation quantitative trait loci analyses, cytokine and transcription factor activity - epigenetic associations and methylation-expression correlations were conducted. New drug targets were searched for based on differentially methylated genes. In a stratified approach, a total of 974 differential methylation CpG sites with dependency on molecular subtypes and autoantibody profiles were found. Mediation analyses suggested that SLE-associated SNPs in the HLA region exert their risk through DNA methylation changes. Novel genetic variants regulating DNAm in disease or in specific molecular contexts were identified. The epigenetic landscapes showed strong association with transcription factor activity and cytokine levels, conditioned by the molecular context. Epigenetic signals were enriched in known and novel drug targets for SLE. This study reveals possible genetic drivers and consequences of epigenetic variability on SLE heterogeneity and disentangles the DNAm mediation role on SLE genetic risk and novel disease-specific meQTLs. Finally, novel targets for drug development were discovered.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38735509,

title = {Integration of multi-omics analysis reveals metabolic alterations of B lymphocytes in systemic lupus erythematosus},

author = {Cristian Iperi and Álvaro Fernández-Ochoa and Jacques-Olivier Pers and Guillermo Barturen and Marta Alarcón-Riquelme and  and Rosa Quirantes-Piné and Isabel Borrás-Linares and Antonio Segura-Carretero and Divi Cornec and Anne Bordron and Christophe Jamin},

doi = {10.1016/j.clim.2024.110243},

issn = {1521-7035},

year  = {2024},

date = {2024-07-01},

journal = {Clin Immunol},

volume = {264},

pages = {110243},

abstract = {OBJECTIVE: To link changes in the B-cell transcriptome from systemic lupus erythematosus (SLE) patients with those in their macroenvironment, including cellular and fluidic components.nnMETHODS: Analysis was performed on 363 patients and 508 controls, encompassing transcriptomics, metabolomics, and clinical data. B-cell and whole-blood transcriptomes were analysed using DESeq and GSEA. Plasma and urine metabolomics peak changes were quantified and annotated using Ceu Mass Mediator database. Common sources of variation were identified using MOFA integration analysis.nnRESULTS: Cellular macroenvironment was enriched in cytokines, stress responses, lipidic synthesis/mobility pathways and nucleotide degradation. B cells shared these pathways, except nucleotide degradation diverted to nucleotide salvage pathway, and distinct glycosylation, LPA receptors and Schlafen proteins.nnCONCLUSIONS: B cells showed metabolic changes shared with their macroenvironment and unique changes directly or indirectly induced by IFN-α signalling. This study underscores the importance of understanding the interplay between B cells and their macroenvironment in SLE pathology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38899167,

title = {Interferon and B-cell Signatures Inform Precision Medicine in Lupus Nephritis},

author = {Ioannis Parodis and Julius Lindblom and Daniel Toro-Domínguez and Lorenzo Beretta and Maria O Borghi and Jessica Castillo and Elena Carnero-Montoro and Yvonne Enman and Chandra Mohan and Marta E Alarcón-Riquelme and Guillermo Barturen and Dionysis Nikolopoulos and },

doi = {10.1016/j.ekir.2024.03.014},

issn = {2468-0249},

year  = {2024},

date = {2024-06-01},

journal = {Kidney Int Rep},

volume = {9},

number = {6},

pages = {1817--1835},

abstract = {INTRODUCTION: Current therapeutic management of lupus nephritis (LN) fails to induce long-term remission in over 50% of patients, highlighting the urgent need for additional options.nnMETHODS: We analyzed differentially expressed genes (DEGs) in peripheral blood from patients with active LN ( = 41) and active nonrenal lupus ( = 62) versus healthy controls (HCs) ( = 497) from the European PRECISESADS project (NTC02890121), and dysregulated gene modules in a discovery ( = 26) and a replication ( = 15) set of active LN cases.nnRESULTS: Replicated gene modules qualified for correlation analyses with serologic markers, and regulatory network and druggability analysis. Unsupervised coexpression network analysis revealed 20 dysregulated gene modules and stratified the active LN population into 3 distinct subgroups. These subgroups were characterized by low, intermediate, and high interferon (IFN) signatures, with differential dysregulation of the "B cell" and "plasma cells/Ig" modules. Drugs annotated to the IFN network included CC-motif chemokine receptor 1 (CCR1) inhibitors, programmed death-ligand 1 (PD-L1) inhibitors, and irinotecan; whereas the anti-CD38 daratumumab and proteasome inhibitor bortezomib showed potential for counteracting the "plasma cells/Ig" signature.  analysis demonstrated the low-IFN subgroup to benefit from calcineurin inhibition and the intermediate-IFN subgroup from B-cell targeted therapies. High-IFN patients exhibited greater anticipated response to anifrolumab whereas daratumumab appeared beneficial to the intermediate-IFN and high-IFN subgroups.nnCONCLUSION: IFN upregulation and B and plasma cell gene dysregulation patterns revealed 3 subgroups of LN, which may not necessarily represent distinct disease phenotypes but rather phases of the inflammatory processes during a renal flare, providing a conceptual framework for precision medicine in LN.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38373843,

title = {Molecular characterisation of lupus low disease activity state (LLDAS) and DORIS remission by whole-blood transcriptome-based pathways in a pan-European systemic lupus erythematosus cohort},

author = {Ioannis Parodis and Julius Lindblom and Guillermo Barturen and Rafaela Ortega-Castro and Ricard Cervera and Jacques-Olivier Pers and Fernanda Genre and Falk Hiepe and Maria Gerosa and László Kovács and Ellen De Langhe and Silvia Piantoni and Georg Stummvoll and Carlos Vasconcelos and Barbara Vigone and Torsten Witte and  and Marta E Alarcón-Riquelme and Lorenzo Beretta},

doi = {10.1136/ard-2023-224795},

issn = {1468-2060},

year  = {2024},

date = {2024-06-01},

journal = {Ann Rheum Dis},

volume = {83},

number = {7},

pages = {889--900},

abstract = {OBJECTIVES: To unveil biological milieus underlying low disease activity (LDA) and remission versus active systemic lupus erythematosus (SLE).nnMETHODS: We determined differentially expressed pathways (DEPs) in SLE patients from the PRECISESADS project (NTC02890121) stratified into patients fulfilling and not fulfilling the criteria of (1) Lupus LDA State (LLDAS), (2) Definitions of Remission in SLE remission, and (3) LLDAS exclusive of remission.nnRESULTS: We analysed data from 321 patients; 40.8% were in LLDAS, and 17.4% in DORIS remission. After exclusion of patients in remission, 28.3% were in LLDAS. Overall, 604 pathways differed significantly in LLDAS versus non-LLDAS patients with an false-discovery rate-corrected p (q)<0.05 and a robust effect size (dr)≥0.36. Accordingly, 288 pathways differed significantly between DORIS remitters and non-remitters (q<0.05 and dr≥0.36). DEPs yielded distinct molecular clusters characterised by differential serological, musculoskeletal, and renal activity. Analysis of partially overlapping samples showed no DEPs between LLDAS and DORIS remission. Drug repurposing potentiality for treating SLE was unveiled, as were important pathways underlying active SLE whose modulation could aid attainment of LLDAS/remission, including toll-like receptor (TLR) cascades, Bruton tyrosine kinase (BTK) activity, the cytotoxic T lymphocyte antigen 4 (CTLA-4)-related inhibitory signalling, and the nucleotide-binding oligomerization domain leucine-rich repeat-containing protein 3 (NLRP3) inflammasome pathway.nnCONCLUSIONS: We demonstrated for the first time molecular signalling pathways distinguishing LLDAS/remission from active SLE. LLDAS/remission was associated with reversal of biological processes related to SLE pathogenesis and specific clinical manifestations. DEP clustering by remission better grouped patients compared with LLDAS, substantiating remission as the ultimate treatment goal in SLE; however, the lack of substantial pathway differentiation between the two states justifies LLDAS as an acceptable goal from a biological perspective.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38515664,

title = {Assessing the complementary information from an increased number of biologically relevant features in liquid biopsy-derived RNA-Seq data},

author = {Stavros Giannoukakos and Silvia D'Ambrosi and Danijela Koppers-Lalic and Cristina Gómez-Martín and Alberto Fernandez and Michael Hackenberg},

doi = {10.1016/j.heliyon.2024.e27360},

issn = {2405-8440},

year  = {2024},

date = {2024-03-01},

journal = {Heliyon},

volume = {10},

number = {6},

pages = {e27360},

abstract = {Liquid biopsy-derived RNA sequencing (lbRNA-seq) exhibits significant promise for clinic-oriented cancer diagnostics due to its non-invasiveness and ease of repeatability. Despite substantial advancements, obstacles like technical artefacts and process standardisation impede seamless clinical integration. Alongside addressing technical aspects such as normalising fluctuating low-input material and establishing a standardised clinical workflow, the lack of result validation using independent datasets remains a critical factor contributing to the often low reproducibility of liquid biopsy-detected biomarkers. Considering the outlined drawbacks, our objective was to establish a workflow/methodology characterised by: 1. Harness the rich diversity of biological features accessible through lbRNA-seq data, encompassing a holistic range of molecular and functional attributes. These components are seamlessly integrated via a Machine Learning-based Ensemble Classification framework, enabling a unified and comprehensive analysis of the intricate information encoded within the data. 2. Implementing and rigorously benchmarking intra-sample normalisation methods to heighten their relevance within clinical settings. 3. Thoroughly assessing its efficacy across independent test sets to ascertain its robustness and potential utility. Using ten datasets from several studies comprising three different sources of biological material, we first show that while the best-performing normalisation methods depend strongly on the dataset and coupled Machine Learning method, the rather simple Counts Per Million method is generally very robust, showing comparable performance to cross-sample methods. Subsequently, we demonstrate that the innovative biofeature types introduced in this study, such as the Fraction of Canonical Transcript, harbour complementary information. Consequently, their inclusion consistently enhances prediction power compared to models relying solely on gene expression-based biofeatures. Finally, we demonstrate that the workflow is robust on completely independent datasets, generally from different labs and/or different protocols. Taken together, the workflow presented here outperforms generally employed methods in prediction accuracy and may hold potential for clinical diagnostics application due to its specific design.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37858475,

title = {IsoSeek for unbiased and UMI-informed sequencing of miRNAs from low input samples at single-nucleotide resolution},

author = {Monique A J van Eijndhoven and Chantal Scheepbouwer and Ernesto Aparicio-Puerta and Michael Hackenberg and D Michiel Pegtel},

doi = {10.1016/j.xpro.2023.102645},

issn = {2666-1667},

year  = {2023},

date = {2023-12-01},

journal = {STAR Protoc},

volume = {4},

number = {4},

pages = {102645},

abstract = {Besides canonical microRNAs (miRNAs), sequence-based variations called isomiRs have biological relevance and diagnostic potential; however, accurate calling of these post-transcriptional modifications is challenging, especially for low input samples. Here, we present IsoSeek, a sequencing protocol that reduces ligation and PCR amplification bias and improves the accuracy of miRNA detection in low input samples. We describe steps for using randomized adapters combined with unique molecular identifiers (UMI), library quantification, and sequencing, followed by detailed procedures for data processing and analysis. For complete details on the use and execution of this protocol, please refer to C. Gómez-Martín et al. (2023) and Van Eijndhoven et al. (2021)..},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37712701,

title = {HSV-1 miRNAs are post-transcriptionally edited in latently infected human ganglia},

author = {Andreja Zubković and Cristina Gomes and Adwait Parchure and Mia Cesarec and Antun Ferenčić and Filip Rokić and Hrvoje Jakovac and Abigail L Whitford and Sara A Dochnal and Anna R Cliffe and Dražen Cuculić and Angela Gallo and Oliver Vugrek and Michael Hackenberg and Igor Jurak},

doi = {10.1128/jvi.00730-23},

issn = {1098-5514},

year  = {2023},

date = {2023-10-01},

journal = {J Virol},

volume = {97},

number = {10},

pages = {e0073023},

abstract = {Herpes simplex virus 1 is an important human pathogen that has been intensively studied for many decades. Nevertheless, the molecular mechanisms regulating its establishment, maintenance, and reactivation from latency are poorly understood. Here, we show that HSV-1-encoded miR-H2 is post-transcriptionally edited in latently infected human tissues. Hyperediting of viral miRNAs increases the targeting potential of these miRNAs and may play an important role in regulating latency. We show that the edited miR-H2 can target ICP4, an essential viral protein. Interestingly, we found no evidence of hyperediting of its homolog, miR-H2, which is expressed by the closely related virus HSV-2. The discovery of post-translational modifications of viral miRNA in the latency phase suggests that these processes may also be important for other non-coding viral RNA in the latency phase, including the intron LAT, which in turn may be crucial for understanding the biology of this virus.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37509327,

title = {Interferon-Alpha Decreases Cancer Stem Cell Properties and Modulates Exosomes in Malignant Melanoma},

author = {María Belén García-Ortega and Ernesto Aparicio and Carmen Griñán-Lisón and Gema Jiménez and Elena López-Ruiz and José Luis Palacios and Gloria Ruiz-Alcalá and Cristina Alba and Antonio Martínez and Houria Boulaiz and Macarena Perán and Michael Hackenberg and José Bragança and Sofia M Calado and Juan A Marchal and María Ángel García},

doi = {10.3390/cancers15143666},

issn = {2072-6694},

year  = {2023},

date = {2023-07-01},

journal = {Cancers (Basel)},

volume = {15},

number = {14},

abstract = {Malignant melanoma (MM) can spread to other organs and is resistant in part due to the presence of cancer stem cell subpopulations (CSCs). While a controversial high dose of interferon-alpha (IFN-α) has been used to treat non-metastatic high-risk melanoma, it comes with undesirable side effects. In this study, we evaluated the effect of low and high doses of IFN-α on CSCs by analyzing ALDH activity, side population and specific surface markers in established and patient-derived primary cell lines. We also assessed the clonogenicity, migration and tumor initiation capacities of IFN-α treated CSCs. Additionally, we investigated genomic modulations related to stemness properties using microRNA sequencing and microarrays. The effect of IFN-α on CSCs-derived exosomes was also analyzed using NanoSight and liquid chromatography (LC-HRMS)-based metabolomic analysis, among others. Our results showed that even low doses of IFN-α reduced CSC formation and stemness properties, and led to a significant decrease in the ability to form tumors in mice xenotransplants. IFN-α also modulated the expression of genes and microRNAs involved in several cancer processes and metabolomics of released exosomes. Our work suggests the utility of low doses of interferon, combined with the analysis of metabolic biomarkers, as a potential clinical approach against the aggressiveness of CSCs in melanoma.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37216599,

title = {NORMSEQ: a tool for evaluation, selection and visualization of RNA-Seq normalization methods},

author = {Chantal Scheepbouwer and Michael Hackenberg and Monique A J van Eijndhoven and Alan Gerber and Michiel Pegtel and Cristina Gómez-Martín},

doi = {10.1093/nar/gkad429},

issn = {1362-4962},

year  = {2023},

date = {2023-07-01},

journal = {Nucleic Acids Res},

volume = {51},

number = {W1},

pages = {W372--W378},

abstract = {RNA-sequencing has become one of the most used high-throughput approaches to gain knowledge about the expression of all different RNA subpopulations. However, technical artifacts, either introduced during library preparation and/or data analysis, can influence the detected RNA expression levels. A critical step, especially in large and low input datasets or studies, is data normalization, which aims at eliminating the variability in data that is not related to biology. Many normalization methods have been developed, each of them relying on different assumptions, making the selection of the appropriate normalization strategy key to preserve biological information. To address this, we developed NormSeq, a free web-server tool to systematically assess the performance of normalization methods in a given dataset. A key feature of NormSeq is the implementation of information gain to guide the selection of the best normalization method, which is crucial to eliminate or at least reduce non-biological variability. Altogether, NormSeq provides an easy-to-use platform to explore different aspects of gene expression data with a special focus on data normalization to help researchers, even without bioinformatics expertise, to obtain reliable biological inference from their data. NormSeq is freely available at: https://arn.ugr.es/normSeq.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37372134,

title = {Compositional Structure of the Genome: A Review},

author = {Pedro Bernaola-Galván and Pedro Carpena and Cristina Gómez-Martín and Jose L Oliver},

doi = {10.3390/biology12060849},

issn = {2079-7737},

year  = {2023},

date = {2023-06-01},

journal = {Biology (Basel)},

volume = {12},

number = {6},

abstract = {As the genome carries the historical information of a species' biotic and environmental interactions, analyzing changes in genome structure over time by using powerful statistical physics methods (such as entropic segmentation algorithms, fluctuation analysis in DNA walks, or measures of compositional complexity) provides valuable insights into genome evolution. Nucleotide frequencies tend to vary along the DNA chain, resulting in a hierarchically patchy chromosome structure with heterogeneities at different length scales that range from a few nucleotides to tens of millions of them. Fluctuation analysis reveals that these compositional structures can be classified into three main categories: (1) short-range heterogeneities (below a few kilobase pairs (Kbp)) primarily attributed to the alternation of coding and noncoding regions, interspersed or tandem repeats densities, etc.; (2) isochores, spanning tens to hundreds of tens of Kbp; and (3) superstructures, reaching sizes of tens of megabase pairs (Mbp) or even larger. The obtained isochore and superstructure coordinates in the first complete T2T human sequence are now shared in a public database. In this way, interested researchers can use T2T isochore data, as well as the annotations for different genome elements, to check a specific hypothesis about genome structure. Similarly to other levels of biological organization, a hierarchical compositional structure is prevalent in the genome. Once the compositional structure of a genome is identified, various measures can be derived to quantify the heterogeneity of such structure. The distribution of segment G+C content has recently been proposed as a new genome signature that proves to be useful for comparing complete genomes. Another meaningful measure is the sequence compositional complexity (SCC), which has been used for genome structure comparisons. Lastly, we review the recent genome comparisons in species of the ancient phylum Cyanobacteria, conducted by phylogenetic regression of SCC against time, which have revealed positive trends towards higher genome complexity. These findings provide the first evidence for a driven progressive evolution of genome compositional structure.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37323569,

title = {Reassessment of miRNA variant (isomiRs) composition by small RNA sequencing},

author = {Cristina Gómez-Martín and Ernesto Aparicio-Puerta and Monique A J van Eijndhoven and José M Medina and Michael Hackenberg and D Michiel Pegtel},

doi = {10.1016/j.crmeth.2023.100480},

issn = {2667-2375},

year  = {2023},

date = {2023-05-01},

journal = {Cell Rep Methods},

volume = {3},

number = {5},

pages = {100480},

abstract = {IsomiRs, sequence variants of mature microRNAs, are usually detected and quantified using high-throughput sequencing. Many examples of their biological relevance have been reported, but sequencing artifacts identified as artificial variants might bias biological inference and therefore need to be ideally avoided. We conducted a comprehensive evaluation of 10 different small RNA sequencing protocols, exploring both a theoretically isomiR-free pool of synthetic miRNAs and HEK293T cells. We calculated that, with the exception of two protocols, less than 5% of miRNA reads can be attributed to library preparation artifacts. Randomized-end adapter protocols showed superior accuracy, with 40% of true biological isomiRs. Nevertheless, we demonstrate concordance across protocols for selected miRNAs in non-templated uridyl additions. Notably, NTA-U calling and isomiR target prediction can be inaccurate when using protocols with poor single-nucleotide resolution. Our results highlight the relevance of protocol choice for biological isomiRs detection and annotation, which has key potential implications for biomedical applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36996699,

title = {Distinct gene dysregulation patterns herald precision medicine potentiality in systemic lupus erythematosus},

author = {Julius Lindblom and Daniel Toro-Domínguez and Elena Carnero-Montoro and Lorenzo Beretta and Maria Orietta Borghi and Jessica Castillo and Yvonne Enman and  and Chandra Mohan and Marta E Alarcón-Riquelme and Guillermo Barturen and Ioannis Parodis},

doi = {10.1016/j.jaut.2023.103025},

issn = {1095-9157},

year  = {2023},

date = {2023-04-01},

journal = {J Autoimmun},

volume = {136},

pages = {103025},

abstract = {OBJECTIVES: We aimed at investigating the whole-blood transcriptome, expression quantitative trait loci (eQTLs), and levels of selected serological markers in patients with SLE versus healthy controls (HC) to gain insight into pathogenesis and identify drug targets.nnMETHODS: We analyzed differentially expressed genes (DEGs) and dysregulated gene modules in a cohort of 350 SLE patients and 497 HC from the European PRECISESADS project (NTC02890121), split into a discovery (60%) and a replication (40%) set. Replicated DEGs qualified for eQTL, pathway enrichment, regulatory network, and druggability analysis. For validation purposes, a separate gene module analysis was performed in an independent cohort (GSE88887).nnRESULTS: Analysis of 521 replicated DEGs identified multiple enriched interferon signaling pathways through Reactome. Gene module analysis yielded 18 replicated gene modules in SLE patients, including 11 gene modules that were validated in GSE88887. Three distinct gene module clusters were defined i.e., "interferon/plasma cells", "inflammation", and "lymphocyte signaling". Predominant downregulation of the lymphocyte signaling cluster denoted renal activity. By contrast, upregulation of interferon-related genes indicated hematological activity and vasculitis. Druggability analysis revealed several potential drugs interfering with dysregulated genes within the "interferon" and "PLK1 signaling events" modules. STAT1 was identified as the chief regulator in the most enriched signaling molecule network. Drugs annotated to 15 DEGs associated with cis-eQTLs included bortezomib for its ability to modulate CTSL activity. Belimumab was annotated to TNFSF13B (BAFF) and daratumumab was annotated to CD38 among the remaining replicated DEGs.nnCONCLUSIONS: Modulation of interferon, STAT1, PLK1, B and plasma cell signatures showed promise as viable approaches to treat SLE, pointing to their importance in SLE pathogenesis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36902312,

title = {Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection},

author = {Silvia D'Ambrosi and Stavros Giannoukakos and Mafalda Antunes-Ferreira and Carlos Pedraz-Valdunciel and Jillian W P Bracht and Nicolas Potie and Ana Gimenez-Capitan and Michael Hackenberg and Alberto Fernandez Hilario and Miguel A Molina-Vila and Rafael Rosell and Thomas Würdinger and Danijela Koppers-Lalic},

doi = {10.3390/ijms24054881},

issn = {1422-0067},

year  = {2023},

date = {2023-03-01},

journal = {Int J Mol Sci},

volume = {24},

number = {5},

abstract = {Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36810209,

title = {ALL-tRNAseq enables robust tRNA profiling in tissue samples},

author = {Chantal Scheepbouwer and Ernesto Aparicio-Puerta and Cristina Gomez-Martin and Heleen Verschueren and Monique van Eijndhoven and Laurine E Wedekind and Stavros Giannoukakos and Nathalie Hijmering and Lisa Gasparotto and Hilde T van der Galien and Roos S van Rijn and Eleonora Aronica and Robby Kibbelaar and Vivi M Heine and Pieter Wesseling and David P Noske and W Peter Vandertop and Daphne de Jong and D Michiel Pegtel and Michael Hackenberg and Tom Wurdinger and Alan Gerber and Danijela Koppers-Lalic},

doi = {10.1101/gad.350233.122},

issn = {1549-5477},

year  = {2023},

date = {2023-03-01},

journal = {Genes Dev},

volume = {37},

number = {5-6},

pages = {243--257},

abstract = {Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36979375,

title = {Genome-Wide Analysis of microRNA Expression Profile in Roots and Leaves of Three Wheat Cultivars under Water and Drought Conditions},

author = {Cristina Gómez-Martín and Hui Zhou and José María Medina and Ernesto Aparicio-Puerta and Bujun Shi and Michael Hackenberg},

doi = {10.3390/biom13030440},

issn = {2218-273X},

year  = {2023},

date = {2023-02-01},

journal = {Biomolecules},

volume = {13},

number = {3},

abstract = {Wheat is one of the most important food sources on Earth. MicroRNAs (miRNAs) play important roles in wheat productivity. To identify wheat miRNAs as well as their expression profiles under drought condition, we constructed and sequenced small RNA (sRNA) libraries from the leaves and roots of three wheat cultivars (Kukri, RAC875 and Excalibur) under water and drought conditions. A total of 636 known miRNAs and 294 novel miRNAs were identified, of which 34 miRNAs were tissue- or cultivar-specific. Among these, 314 were significantly regulated under drought conditions. miRNAs that were drought-regulated in all cultivars displayed notably higher expression than those that responded in a cultivar-specific manner. Cultivar-specific drought response miRNAs were mainly detected in roots and showed significantly different drought regulations between cultivars. By using wheat degradome library, 6619 target genes were identified. Many target genes were strongly enriched for protein domains, such as MEKHLA, that play roles in drought response. Targeting analysis showed that drought-downregulated miRNAs targeted more genes than drought-upregulated miRNAs. Furthermore, such genes had more important functions. Additionally, the genes targeted by drought-downregulated miRNAs had multiple interactions with each other, while the genes targeted by drought-upregulated miRNAs had no interactions. Our data provide valuable information on wheat miRNA expression profiles and potential functions in different tissues, cultivars and drought conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36689184,

title = {sRNAtoolbox: Dockerized Analysis of Small RNA Sequencing Data in Model and Non-model Species},

author = {Cristina Gómez-Martín and Ernesto Aparicio-Puerta and Michael Hackenberg},

doi = {10.1007/978-1-0716-2982-6_13},

issn = {1940-6029},

year  = {2023},

date = {2023-01-01},

journal = {Methods Mol Biol},

volume = {2630},

pages = {179--213},

abstract = {The current versions of the microRNA databases MiRgeneDB, miRBase, and PmiREN contain annotations for a total of 358 different species. Public repositories, however, host small RNA sequencing data for over 800 species. This discrepancy implies that microRNA research is also very active in species that neither have an available high-quality genome assembly nor annotations for microRNAs or other types of noncoding genes. These cases are particularly challenging to analyze because reference sequences need to be collected from different sources and processed and formatted appropriately so that the dedicated small RNA analysis tools can make use of them. In this protocol we describe how small RNA sequencing data can be easily analyzed by means of a dockerized version of the well-established sRNAtoolbox/sRNAbench small RNA tools. We outline the analysis of two publicly available datasets to demonstrate basic aspects like the preparation of the local database, expression profiling, or differential expression analysis as well as more advanced features such as quantification of exogenous RNA content and data analysis in non-model species.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36243964,

title = {isomiRdb: microRNA expression at isoform resolution},

author = {Ernesto Aparicio-Puerta and Pascal Hirsch and Georges P Schmartz and Tobias Fehlmann and Verena Keller and Annika Engel and Fabian Kern and Michael Hackenberg and Andreas Keller},

doi = {10.1093/nar/gkac884},

issn = {1362-4962},

year  = {2023},

date = {2023-01-01},

journal = {Nucleic Acids Res},

volume = {51},

number = {D1},

pages = {D179--D185},

abstract = {A significant fraction of mature miRNA transcripts carries sequence and/or length variations, termed isomiRs. IsomiRs are differentially abundant in cell types, tissues, body fluids or patients' samples. Not surprisingly, multiple studies describe a physiological and pathophysiological role. Despite their importance, systematically collected and annotated isomiR information available in databases remains limited. We thus developed isomiRdb, a comprehensive resource that compiles miRNA expression data at isomiR resolution from various sources. We processed 42 499 human miRNA-seq datasets (5.9 × 1011 sequencing reads) and consistently analyzed them using miRMaster and sRNAbench. Our database provides online access to the 90 483 most abundant isomiRs (>1 RPM in at least 1% of the samples) from 52 tissues and 188 cell types. Additionally, the full set of over 3 million detected isomiRs is available for download. Our resource can be queried at the sample, miRNA or isomiR level so users can quickly answer common questions about the presence/absence of a particular miRNA/isomiR in tissues of interest. Further, the database facilitates to identify whether a potentially interesting new isoform has been detected before and its frequency. In addition to expression tables, isomiRdb can generate multiple interactive visualisations including violin plots and heatmaps. isomiRdb is free to use and publicly available at: https://www.ccb.uni-saarland.de/isomirdb.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36562829,

title = {Comprehensive, integrative genomic analysis of microRNA expression profiles in different tissues of two wheat cultivars with different traits},

author = {Cristina Gómez-Martín and Hui Zhou and José Maria Medina and Ernesto Aparicio-Puerta and Michael Hackenberg and Bujun Shi},

doi = {10.1007/s10142-022-00920-1},

issn = {1438-7948},

year  = {2022},

date = {2022-12-01},

journal = {Funct Integr Genomics},

volume = {23},

number = {1},

pages = {15},

abstract = {Wheat is one of the most important food sources on Earth. MicroRNAs (miRNA) play important roles in wheat productivity. To identify wheat miRNAs, we constructed and sequenced sRNA libraries from leaves and roots of two wheat cultivars (RAC875 and Kukri) with many different traits. Given that available miRNA wheat complement in the plant-specific database PmiREN ( https://pmiren.com ) does not include root tissues and root-associated miRNAs might thus be missing, we performed first the prediction of novel miRNAs using the sRNAbench tool. We found a total of 150 putatively novel miRNA genes with expression of both arms from 289 unique mature sequences and nearly 30% of all miRNA reads in roots corresponded to novel miRNAs. In contrast, this figure in leaves dropped to under 3%, confirming the undersampling of roots in the complement of known miRNAs. By using 120 publicly available wheat datasets, 598 Zea mays small RNA libraries, 64 plant species genomes, wheat degradome library, and functional enrichment analysis, a subset of novel miRNAs were confirmed as bona-fide miRNAs. Of the total 605 miRNAs identified in this study inclusive of 316 known miRNAs, 528 miRNAs were shared by both cultivars, 429 miRNAs were shared by both root tissues and 329 miRNAs were shared by both leaf tissues. In addition, 32 miRNAs were specific to Kukri while 45 miRNAs were specific to RAC875. These miRNAs had diverse functions, such as regulation of gene transcription, protein translation, energy metabolism, and cell cycle progression. Our data provide a genome-wide miRNA expression profile in these two wheat cultivars and help functional studies of wheat genomics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36499112,

title = {Decoding Gene Expression Signatures Underlying Vegetative to Inflorescence Meristem Transition in the Common Bean},

author = {Ana M González and Ricardo Lebrón and Fernando J Yuste-Lisbona and Cristina Gómez-Martín and Ana Ortiz-Atienza and Michael Hackenberg and José L Oliver and Rafael Lozano and Marta Santalla},

doi = {10.3390/ijms232314783},

issn = {1422-0067},

year  = {2022},

date = {2022-11-01},

journal = {Int J Mol Sci},

volume = {23},

number = {23},

abstract = {The tropical common bean ( L.) is an obligatory short-day plant that requires relaxation of the photoperiod to induce flowering. Similar to other crops, photoperiod-induced floral initiation depends on the differentiation and maintenance of meristems. In this study, the global changes in transcript expression profiles were analyzed in two meristematic tissues corresponding to the vegetative and inflorescence meristems of two genotypes with different sensitivities to photoperiods. A total of 3396 differentially expressed genes (DEGs) were identified, and 1271 and 1533 were found to be up-regulated and down-regulated, respectively, whereas 592 genes showed discordant expression patterns between both genotypes.  homologues of DEGs were identified, and most of them were not previously involved in  floral transition, suggesting an evolutionary divergence of the transcriptional regulatory networks of the flowering process of both species. However, some genes belonging to the photoperiod and flower development pathways with evolutionarily conserved transcriptional profiles have been found. In addition, the flower meristem identity genes  and , as well as , were identified as markers to distinguish between the vegetative and reproductive stages. Our data also indicated that the down-regulation of the photoperiodic genes seems to be directly associated with promoting floral transition under inductive short-day lengths. These findings provide valuable insight into the molecular factors that underlie meristematic development and contribute to understanding the photoperiod adaptation in the common bean.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35947992,

title = {Scoring personalized molecular portraits identify Systemic Lupus Erythematosus subtypes and predict individualized drug responses, symptomatology and disease progression},

author = {Daniel Toro-Domínguez and Jordi Martorell-Marugán and Manuel Martinez-Bueno and Raúl López-Domínguez and Elena Carnero-Montoro and Guillermo Barturen and Daniel Goldman and Michelle Petri and Pedro Carmona-Sáez and Marta E Alarcón-Riquelme},

doi = {10.1093/bib/bbac332},

issn = {1477-4054},

year  = {2022},

date = {2022-09-01},

journal = {Brief Bioinform},

volume = {23},

number = {5},

abstract = {OBJECTIVES: Systemic Lupus Erythematosus is a complex autoimmune disease that leads to significant worsening of quality of life and mortality. Flares appear unpredictably during the disease course and therapies used are often only partially effective. These challenges are mainly due to the molecular heterogeneity of the disease, and in this context, personalized medicine-based approaches offer major promise. With this work we intended to advance in that direction by developing MyPROSLE, an omic-based analytical workflow for measuring the molecular portrait of individual patients to support clinicians in their therapeutic decisions.nnMETHODS: Immunological gene-modules were used to represent the transcriptome of the patients. A dysregulation score for each gene-module was calculated at the patient level based on averaged z-scores. Almost 6100 Lupus and 750 healthy samples were used to analyze the association among dysregulation scores, clinical manifestations, prognosis, flare and remission events and response to Tabalumab. Machine learning-based classification models were built to predict around 100 different clinical parameters based on personalized dysregulation scores.nnRESULTS: MyPROSLE allows to molecularly summarize patients in 206 gene-modules, clustered into nine main lupus signatures. The combination of these modules revealed highly differentiated pathological mechanisms. We found that the dysregulation of certain gene-modules is strongly associated with specific clinical manifestations, the occurrence of relapses or the presence of long-term remission and drug response. Therefore, MyPROSLE may be used to accurately predict these clinical outcomes.nnCONCLUSIONS: MyPROSLE (https://myprosle.genyo.es) allows molecular characterization of individual Lupus patients and it extracts key molecular information to support more precise therapeutic decisions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}