Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data

Many functional analysis tools have been developed to extract functional and mechanistic insight from bulk transcriptome data. With the advent of single-cell RNA sequencing (scRNA-seq), it is in principle possible to do such an analysis for single cells. However, scRNA-seq data has characteristics such as drop-out events and low library sizes. It is thus not clear if functional TF and pathway analysis tools established for bulk sequencing can be applied to scRNA-seq in a meaningful way.To address this question, we perform benchmark studies on simulated and real scRNA-seq data. We include the bulk-RNA tools PROGENy, GO enrichment, and DoRothEA that estimate pathway and transcription factor (TF) activities, respectively, and compare them against the tools SCENIC/AUCell and metaVIPER, designed for scRNA-seq. For the in silico study, we simulate single cells from TF/pathway perturbation bulk RNA-seq experiments. We complement the simulated data with real scRNA-seq data upon CRISPR-mediated knock-out. Our benchmarks on simulated and real data reveal comparable performance to the original bulk data. Additionally, we show that the TF and pathway activities preserve cell type-specific variability by analyzing a mixture sample sequenced with 13 scRNA-seq protocols. We also provide the benchmark data for further use by the community.Our analyses suggest that bulk-based functional analysis tools that use manually curated footprint gene sets can be applied to scRNA-seq data, partially outperforming dedicated single-cell tools. Furthermore, we find that the performance of functional analysis tools is more sensitive to the gene sets than to the statistic used

DEFICIENCY OF MYELOID PHD PROTEINS AGGRAVATES ATHEROGENESIS VIA MACROPHAGE APOPTOSIS AND PARACRINE FIBROTIC SIGNALING Atherogenic effects of myeloid PHD knockdown

AIMS: Atherosclerotic plaque hypoxia is detrimental for macrophage function. Prolyl hydroxylases (PHDs) initiate cellular hypoxic responses, possibly influencing macrophage function in plaque hypoxia. Thus, we aimed to elucidate the role of myeloid PHDs in atherosclerosis. METHODS AND RESULTS: Myeloid-specific PHD knockout (PHDko) mice were obtained via bone marrow transplantation (PHD1ko, PHD3ko) or conditional knockdown through lysozyme M-driven Cre recombinase (PHD2cko). Mice were fed high cholesterol diet for 6–12 weeks to induce atherosclerosis. Aortic root plaque size was significantly augmented 2.6-fold in PHD2cko, and 1.4-fold in PHD3ko compared to controls but was unchanged in PHD1ko mice. Macrophage apoptosis was promoted in PHD2cko and PHD3ko mice in vitro and in vivo, via the hypoxia-inducible factor (HIF) 1α/BNIP3 axis. Bulk and single-cell RNA data of PHD2cko bone marrow-derived macrophages (BMDMs) and plaque macrophages, respectively, showed enhanced HIF1α/BNIP3 signalling, which was validated in vitro by siRNA silencing. Human plaque BNIP3 mRNA was positively associated with plaque necrotic core size, suggesting similar pro-apoptotic effects in human. Furthermore, PHD2cko plaques displayed enhanced fibrosis, while macrophage collagen breakdown by matrix metalloproteinases, collagen production, and proliferation were unaltered. Instead, PHD2cko BMDMs enhanced fibroblast collagen secretion in a paracrine manner. In silico analysis of macrophage-fibroblast communication predicted SPP1 (osteopontin) signalling as regulator, which was corroborated by enhanced plaque SPP1 protein in vivo. Increased SPP1 mRNA expression upon PHD2cko was preferentially observed in foamy plaque macrophages expressing ‘triggering receptor expressed on myeloid cells-2’ (TREM2hi) evidenced by single-cell RNA, but not in neutrophils. This confirmed enhanced fibrotic signalling by PHD2cko macrophages to fibroblasts, in vitro as well as in vivo. CONCLUSION: Myeloid PHD2cko and PHD3ko enhanced atherosclerotic plaque growth and macrophage apoptosis, while PHD2cko macrophages further activated collagen secretion by fibroblasts in vitro, likely via paracrine SPP1 signalling through TREM2hi macrophages

Computational approaches for the identification of putative therapeutic targets for pancreatic ductal adenocarcinoma

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Bioquímica. Fecha de lectura: 13-12-2019Esta tesis tiene embargado el acceso al texto completo hasta el 13-06-2021La investigación contra el cáncer ha conseguido grandes avances en el desarrollo de nuevos tratamientos con mayor eficacia y especificidad. Sin embargo, algunos tipos de cáncer como el adenocarcinoma ductal de páncreas (PDAC, de sus siglas en inglés) todavía presentan dificultades para establecer regímenes farmacológicos efectivos. La biología computacional ha definido el paisaje de mutaciones accionables por fármacos y subtipos de tumores de PDAC con una potencial respuesta diferencial a tratamientos. Los últimos datos de genómica funcional y farmacogenómica en líneas celulares de cáncer ofrecen la oportunidad de identificar nuevas vulnerabilidades terapéuticas. El objetivo principal de esta tesis es la identificación de nuevas dianas con potencial terapéutico en PDAC mediante aproximaciones computacionales. Para ello, el transcriptoma de tumores primarios se diseccionó usando métodos computacionales. Primero, métodos de deconvolución permitieron separar la señal transcripcional de los distintos tipos celulares en el tejido de páncreas. Esto nos ha permitido seleccionar aquellas muestras que son representativas de la enfermedad, y redefinir los subtipos de tumores. Segundo, el agrupamiento jerarquizado de las líneas celulares de cáncer de páncreas junto con los tumores primarios permitió trasladar los datos farmacológicos de sensibilidad a los subtipos de tumores encontrados en los pacientes. De esta manera hemos definido el paisaje de sensibilidad diferencial entre los subtipos para una posible estratificación de los pacientes. Más allá de tratamientos contra el tumor primario, la metástasis representa otra diana terapéutica complementaria ya que es la causa principal de muerte en pacientes. En este contexto, hemos realizado un estudio piloto de medicina personalizada en un tumor altamente metastásico. Hemos secuenciado el transcriptoma de células individuales de un xenoinjerto derivado del tumor de un paciente para caracterizar los programas transcripcionales que gobiernan la metástasis y proponer fármacos que la interrumpan. El reposicionamiento de fármacos basado en la reversión del fenotipo transcripcional nos ha permitido proponer varios inhibidores como posibles tratamientos anti-metastásicos, que más tarde han sido validado en el propio modelo experimental. Finalmente, para hacer accesible los últimos datos de dependencias genéticas en cáncer y su investigación traslacional en terapia contra el cáncer, hemos desarrollado un nuevo método llamado vulcanSpot. VulcanSpot integra los datos masivos de dependencias genéticas con métodos computacionales de prescripción de fármacos utilizando asociaciones de fármacos conocidos y reposicionados para destapar posibles vulnerabilidades terapéuticas en cáncerCancer research has made great advances in developing novel treatments with higher efficacy and specificity. However, some cancer types such as pancreatic ductal adenocarcinoma (PDAC) remain a challenge for the establishment of effective pharmacological regimens. Computational biology has been used to describe the actionable mutational landscape and to discover tumour subtypes in PDAC with potentially differing drug responses. The recently released large-scale functional genomic and pharmacogenomic screenings in cancer cell lines bring the opportunity to uncover novel therapeutic vulnerabilities. The main objective of this thesis is to identify novel therapeutic targets for PDAC using computational approaches. To this end, the transcriptome of primary tumours was dissected using computational methods. First, deconvolution methods were used to separate the transcriptional signal derived from distinct cell types from pancreas tissue. This unlocks the possibility to select those samples that better represent PDAC, and to redefine the tumour subtypes. Second, hierarchical clustering of pancreatic cancer cell lines with primary tumours enabled the translation of drug sensitivity data from cell lines to the tumour subtypes found in patients. Doing so, we have studied the differing drug sensitivity landscape between tumour subtypes for a potential stratification of the patients. Beyond primary tumours, metastasis represents a complementary therapeutic target since it is the main cause of cancer death in patients. In this context, we have carried out a pilot study of precision medicine on a PDAC tumour with high metastatic capacities. We have sequenced the transcriptome of single cells to characterize the main transcriptional programmes governing cell migration and tumour spread, and to computationally prescribe candidate drugs to block metastasis. Drug repositioning approaches based on the reversion of the transcriptional malignant phenotype allowed us to propose several inhibitors as potential anti-metastatic treatments, which were subsequently validated in the experimental model. Finally, to make accessible the latest cancer gene dependency data and its research translation in cancer therapeutics, we have developed a novel method named vulcanSpot. VulcanSpot integrates big data of gene dependencies with computational drug prescription methods based on known and repurposed drugs associations to uncover therapeutic vulnerabilities in cance

The miR-146b-3p/PAX8/NIS regulatory circuit modulates the differentiation phenotype and function of thyroid cells during carcinogenesis

The presence of differentiated thyroid cells in thyroid cancer is critical for the antitumor response to radioactive iodide treatment, and loss of the differentiated phenotype is a key hallmark of iodide-refractory metastatic disease. The role of microRNAs (miRNA) in fine-tuning gene expression has become a major regulatory mechanism by which developmental and pathologic processes occur. In this study, we performed next-generation sequencing and expression analysis of eight papillary thyroid carcinomas (PTC) to comprehensively characterize miRNAs involved in loss of differentiation. We found that only a small set of abundant miRNAs is differentially expressed between PTC tissue and normal tissue from the same patient. In addition, we integrated computational prediction of potential targets and mRNA sequencing and identified a master miRNA regulatory network involved in essential biologic processes such as thyroid differentiation. Both mature products of mir-146b (miR-146b-5p and -3p) were among the most abundantly expressed miRNAs in tumors. Specifically, we found that miR-146b-3p binds to the 3′-untranslated region of PAX8 and sodium/iodide symporter (NIS), leading to impaired protein translation and a subsequent reduction in iodide uptake. Furthermore, our findings show that miR-146b and PAX8 regulate each other and share common target genes, thus highlighting a novel regulatory circuit that governs the differentiated phenotype of PTC. In conclusion, our study has uncovered the existence of a miR-146b-3p/PAX8/NIS regulatory circuit that may be exploited therapeutically to modulate thyroid cell differentiation and iodide uptake for improved treatment of advanced thyroid cancer.This work was supported by Grants BFU2010-16025 and SAF2013-44709-R from the Dirección General de Proyectos de Investigación; RD12/0036/0030 from FIS, Instituto de Salud Carlos III (ISCIII); and S2011/BMD-2328 TIRONET project from the Comunidad de Madrid (Spain) to P. Santisteban; and FIS-ISCIII; PI14/01980 to G. Riesco-Eizaguirre. L. Wert-Lamas and A. Sastre-Perona hold a predoctoral FPI and FPU fellowship, respectively, from the Spanish Government and L.P. Fernández was a JAE.doc postdoctoral from CSIC.Peer reviewe

Cross-regional homeostatic and reactive glial signatures in multiple sclerosis

Multiple sclerosis (MS) is a multifocal and progressive inflammatory disease of the central nervous system (CNS). However, the compartmentalized pathology of the disease affecting various anatomical regions including gray and white matter and lack of appropriate disease models impede understanding of the disease. Utilizing single-nucleus RNA-sequencing and multiplex spatial RNA mapping, we generated an integrated transcriptomic map comprising leukocortical, cerebellar and spinal cord areas in normal and MS tissues that captures regional subtype diversity of various cell types with an emphasis on astrocytes and oligodendrocytes. While we found strong cross-regional diversity among glial subtypes in control tissue, regional signatures become more obscure in MS. This suggests that patterns of transcriptomic changes in MS are shared across regions and converge on specific pathways, especially those regulating cellular stress and immune activation. In addition, we found evidence that a subtype of white matter oligodendrocytes appearing across all three CNS regions adopt pro-remyelinating gene signatures in MS. In summary, our data suggest that cross-regional transcriptomic glial signatures overlap in MS, with different reactive glial cell types capable of either exacerbating or ameliorating pathology

Partial Inhibition of the 6-Phosphofructo-2-Kinase/Fructose-2,6-Bisphosphatase-3 (PFKFB3) Enzyme in Myeloid Cells Does Not Affect Atherosclerosis

Background: The protein 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a key stimulator of glycolytic flux. Systemic, partial PFKFB3 inhibition previously decreased total plaque burden and increased plaque stability. However, it is unclear which cell type conferred these positive effects. Myeloid cells play an important role in atherogenesis, and mainly rely on glycolysis for energy supply. Thus, we studied whether myeloid inhibition of PFKFB3-mediated glycolysis in Ldlr–/–LysMCre+/–Pfkfb3fl/fl (Pfkfb3fl/fl) mice confers beneficial effects on plaque stability and alleviates cardiovascular disease burden compared to Ldlr–/–LysMCre+/–Pfkfb3wt/wt control mice (Pfkfb3wt/wt). Methods and Results: Analysis of atherosclerotic human and murine single-cell populations confirmed PFKFB3/Pfkfb3 expression in myeloid cells, but also in lymphocytes, endothelial cells, fibroblasts and smooth muscle cells. Pfkfb3wt/wt and Pfkfb3fl/fl mice were fed a 0.25% cholesterol diet for 12 weeks. Pfkfb3fl/fl bone marrow-derived macrophages (BMDMs) showed 50% knockdown of Pfkfb3 mRNA. As expected based on partial glycolysis inhibition, extracellular acidification rate as a measure of glycolysis was partially reduced in Pfkfb3fl/fl compared to Pfkfb3wt/wt BMDMs. Unexpectedly, plaque and necrotic core size, as well as macrophage (MAC3), neutrophil (Ly6G) and collagen (Sirius Red) content were unchanged in advanced Pfkfb3fl/fl lesions. Similarly, early lesion plaque and necrotic core size and total plaque burden were unaffected. Conclusion: Partial myeloid knockdown of PFKFB3 did not affect atherosclerosis development in advanced or early lesions. Previously reported positive effects of systemic, partial PFKFB3 inhibition on lesion stabilization, do not seem conferred by monocytes, macrophages or neutrophils. Instead, other Pfkfb3-expressing cells in atherosclerosis might be responsible, such as DCs, smooth muscle cells or fibroblasts

Clonal dynamics monitoring during clinical evolution in chronic lymphocytic leukaemia

Chronic lymphocytic leukaemia is the most prevalent leukaemia in Western countries. It is an incurable disease characterized by a highly variable clinical course. Chronic lymphocytic leukaemia is an ideal model for studying clonal heterogeneity and dynamics during cancer progression, response to therapy and/or relapse because the disease usually develops over several years. Here we report an analysis by deep sequencing of sequential samples taken at different times from the affected organs of two patients with 12- and 7-year disease courses, respectively. One of the patients followed a linear pattern of clonal evolution, acquiring and selecting new mutations in response to salvage therapy and/or allogeneic transplantation, while the other suffered loss of cellular tumoral clones during progression and histological transformation.This work was supported by the Spanish Ministry of Economy and Competence (MINECO): SAF2013-47416-R; ISCIII-MINECO AES-FEDER (Plan Estatal de I + D + I 2008–2011 and 2013–2016) (PI14/00221 (MSB), PIE14/0064 (MSB), PIE15/0081 (MAP), PI16/01294 (MAP), CIBERONC CB16/12/00291 (MAP)), Madrid Autonomous Community, B2017/BMD3778 (MAP, MSB, FA-S), F Hoffmann-La Roche (JAGM); CNIO Bioinformatics Unit work has been supported by Marie-Curie Career Integration Grant CIG334361. J.G.-R. is a recipient of a i-PFIS predoctoral fellowship (IFI14/00003); NM was supported by AECC Scientific Foundation; S.D. was supported by the Torres Quevedo subprogramme (MICINN) under grant agreement PTQ-12-05391. K.T. and J.P.-P. are supported by Severo Ochoa FPI grant doctoral fellowship by the Spanish MINECO. MSB currently holds a Miguel Servet II contract (CPII16/00024) supported by ISCIII-MINECO AES-FEDER (Plan Estatal I + D + I 2013–2016) and the Fundación de Investigación Biomédica Puerta de Hierro