Fátima Sánchez-Cabo

Bio: Fátima Sánchez-Cabo is an academic researcher from Centro Nacional de Investigaciones Cardiovasculares. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 28, co-authored 93 publications receiving 12405 citations. Previous affiliations of Fátima Sánchez-Cabo include Carlos III Health Institute & University of Manchester.

Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome

Abstract: The role of the adaptive immune response in controlling the growth and recurrence of human tumors has been controversial. We characterized the tumor-infiltrating immune cells in large cohorts of human colorectal cancers by gene expression profiling and in situ immunohistochemical staining. Collectively, the immunological data (the type, density, and location of immune cells within the tumor samples) were found to be a better predictor of patient survival than the histopathological methods currently used to stage colorectal cancer. The results were validated in two additional patient populations. These data support the hypothesis that the adaptive immune response influences the behavior of human tumors. In situ analysis of tumor-infiltrating immune cells may therefore be a valuable prognostic tool in the treatment of colorectal cancer and possibly other malignancies.

Effector Memory T Cells, Early Metastasis, and Survival in Colorectal Cancer

Abstract: Background The role of tumor-infiltrating immune cells in the early metastatic invasion of colorectal cancer is unknown. Methods We studied pathological signs of early metastatic invasion (venous emboli and lymphatic and perineural invasion) in 959 specimens of resected colorectal cancer. The local immune response within the tumor was studied by flow cytometry (39 tumors), low-density-array real-time polymerase-chain-reaction assay (75 tumors), and tissue microarrays (415 tumors). Results Univariate analysis showed significant differences in disease-free and overall survival according to the presence or absence of histologic signs of early metastatic invasion (P<0.001). Multivariate Cox analysis showed that an early conventional pathological tumor–node–metastasis stage (P<0.001) and the absence of early metastatic invasion (P=0.04) were independently associated with increased survival. As compared with tumors with signs of early metastatic invasion, tumors without such signs had increased infiltrates of i...

Unidirectional transfer of microRNA-loaded exosomes from T cells to antigen-presenting cells

Abstract: The immune synapse is an exquisitely evolved means of communication between T cells and antigen-presenting cells (APCs) during antigen recognition. Recent evidence points to the transfer of RNA via exosomes as a novel mode of intercellular communication. Here we show that exosomes of T, B and dendritic immune cells contain microRNA (miRNA) repertoires that differ from those of their parent cells. We investigate whether miRNAs are exchanged during cognate immune interactions, and demonstrate the existence of antigen-driven unidirectional transfer of miRNAs from the T cell to the APC, mediated by the delivery of CD63+ exosomes on immune synapse formation. Inhibition of exosome production by targeting neutral sphingomyelinase-2 impairs transfer of miRNAs to APCs. Moreover, miRNAs transferred during immune synapsis are able to modulate gene expression in recipient cells. Thus, our results support a mechanism of cellular communication involving antigen-dependent, unidirectional intercellular transfer of miRNAs by exosomes during immune synapsis.

Sumoylated hnRNPA2B1 controls the sorting of miRNAs into exosomes through binding to specific motifs.

Abstract: Exosomes are released by most cells to the extracellular environment and are involved in cell-to-cell communication Exosomes contain specific repertoires of mRNAs, microRNAs (miRNAs) and other non-coding RNAs that can be functionally transferred to recipient cells However, the mechanisms that control the specific loading of RNA species into exosomes remain unknown Here we describe sequence motifs present in miRNAs that control their localization into exosomes The protein heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) specifically binds exosomal miRNAs through the recognition of these motifs and controls their loading into exosomes Moreover, hnRNPA2B1 in exosomes is sumoylated, and sumoylation controls the binding of hnRNPA2B1 to miRNAs The loading of miRNAs into exosomes can be modulated by mutagenesis of the identified motifs or changes in hnRNPA2B1 expression levels These findings identify hnRNPA2B1 as a key player in miRNA sorting into exosomes and provide potential tools for the packaging of selected regulatory RNAs into exosomes and their use in biomedical applications

GOplot: an R package for visually combining expression data with functional analysis.

Abstract: UNLABELLED Despite the plethora of methods available for the functional analysis of omics data, obtaining comprehensive-yet detailed understanding of the results remains challenging. This is mainly due to the lack of publicly available tools for the visualization of this type of information. Here we present an R package called GOplot, based on ggplot2, for enhanced graphical representation. Our package takes the output of any general enrichment analysis and generates plots at different levels of detail: from a general overview to identify the most enriched categories (bar plot, bubble plot) to a more detailed view displaying different types of information for molecules in a given set of categories (circle plot, chord plot, cluster plot). The package provides a deeper insight into omics data and allows scientists to generate insightful plots with only a few lines of code to easily communicate the findings. AVAILABILITY AND IMPLEMENTATION The R package GOplot is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/GOplot. The shiny web application of the Venn diagram can be found at: https://wwalter.shinyapps.io/Venn/. A detailed manual of the package with sample figures can be found at https://wencke.github.io/ CONTACT fscabo@cnic.es or mricote@cnic.es.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

Integrating single-cell transcriptomic data across different conditions, technologies, and species.

Abstract: Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

PD-1 Blockade in Tumors with Mismatch-Repair Deficiency

Abstract: BackgroundSomatic mutations have the potential to encode “non-self” immunogenic antigens. We hypothesized that tumors with a large number of somatic mutations due to mismatch-repair defects may be susceptible to immune checkpoint blockade. MethodsWe conducted a phase 2 study to evaluate the clinical activity of pembrolizumab, an anti–programmed death 1 immune checkpoint inhibitor, in 41 patients with progressive metastatic carcinoma with or without mismatch-repair deficiency. Pembrolizumab was administered intravenously at a dose of 10 mg per kilogram of body weight every 14 days in patients with mismatch repair–deficient colorectal cancers, patients with mismatch repair–proficient colorectal cancers, and patients with mismatch repair–deficient cancers that were not colorectal. The coprimary end points were the immune-related objective response rate and the 20-week immune-related progression-free survival rate. ResultsThe immune-related objective response rate and immune-related progression-free survival ...

Extracellular vesicles: exosomes, microvesicles, and friends.

Abstract: Cells release into the extracellular environment diverse types of membrane vesicles of endosomal and plasma membrane origin called exosomes and microvesicles, respectively. These extracellular vesicles (EVs) represent an important mode of intercellular communication by serving as vehicles for transfer between cells of membrane and cytosolic proteins, lipids, and RNA. Deficiencies in our knowledge of the molecular mechanisms for EV formation and lack of methods to interfere with the packaging of cargo or with vesicle release, however, still hamper identification of their physiological relevance in vivo. In this review, we focus on the characterization of EVs and on currently proposed mechanisms for their formation, targeting, and function.