Statistical methods for transcriptomics: From microarrays to RNA-seq

La transcriptómica estudia el nivel de expresión de los genes en distintas condiciones experimentales para tratar de identificar los genes asociados a un fenotipo dado así como las relaciones de regulación entre distintos genes. Los datos ómicos se caracterizan por contener información de miles de variables en una muestra con pocas observaciones. Las tecnologías de alto rendimiento más comunes para medir el nivel de expresión de miles de genes simultáneamente son los microarrays y, más recientemente, la secuenciación de RNA (RNA-seq). Este trabajo de tesis versará sobre la evaluación, adaptación y desarrollo de modelos estadísticos para el análisis de datos de expresión génica, tanto si ha sido estimada mediante microarrays o bien con RNA-seq. El estudio se abordará con herramientas univariantes y multivariantes, así como con métodos tanto univariantes como multivariantes.Tarazona Campos, S. (2014). Statistical methods for transcriptomics: From microarrays to RNA-seq [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48485TESISPremios Extraordinarios de tesis doctorale

RGmatch: matching genomic regions to proximal genes in omics data integration

© The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.[EN] Background: The integrative analysis of multiple genomics data often requires that genome coordinates-based signals have to be associated with proximal genes. The relative location of a genomic region with respect to the gene (gene area) is important for functional data interpretation; hence algorithms that match regions to genes should be able to deliver insight into this information. Results: In this work we review the tools that are publicly available for making region-to-gene associations. We also present a novel method, RGmatch, a flexible and easy-to-use Python tool that computes associations either at the gene, transcript, or exon level, applying a set of rules to annotate each region-gene association with the region location within the gene. RGmatch can be applied to any organism as long as genome annotation is available. Furthermore, we qualitatively and quantitatively compare RGmatch to other tools. Conclusions: RGmatch simplifies the association of a genomic region with its closest gene. At the same time, it is a powerful tool because the rules used to annotate these associations are very easy to modify according to the researcher’s specific interests. Some important differences between RGmatch and other similar tools already in existence are RGmatch’s flexibility, its wide range of user options, compatibility with any annotatable organism, and its comprehensive and user-friendly output.The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under the grant agreement 306000 and the MINECO (Economy and Competitiveness Ministry) BIO2012-40244 grant.Furió Tarí, P.; Conesa, A.; Tarazona Campos, S. (2016). RGmatch: matching genomic regions to proximal genes in omics data integration. BMC Bioinformatics. 17((Suppl 15)). https://doi.org/10.1186/s12859-016-1293-1S129317(Suppl 15)Shu W, Chen H, Bo X, Wang S. Genome-wide analysis of the relationships between DNaseI HS, histone modifications and gene expression reveals distinct modes of chromatin domains. Nucleic Acids Res. 2011;39:7428–43.Song L, Zhang Z, Grasfeder LL, Boyle AP, Giresi PG, Lee B-K, et al. Open chromatin defined by DNaseI and FAIRE identifies regulatory elements that shape cell-type identity. Genome Res. 2011;21:1757–67.He HH, Meyer CA, Chen MW, Jordan VC, Brown M, Liu XS. Differential DNase I hypersensitivity reveals factor-dependent chromatin dynamics. Genome Res. 2012;22:1015–25.Natarajan A, Yardimci GG, Sheffield NC, Crawford GE, Ohler U. Predicting cell-type-specific gene expression from regions of open chromatin. Genome Res. 2012;22:1711–22.Wang Y-M, Zhou P, Wang L-Y, Li Z-H, Zhang Y-N, Zhang Y-X. Correlation between DNase I hypersensitive site distribution and gene expression in HeLa S3 cells. PLoS One. 2012;7:e42414.Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38:576–89.Mclean CY, Bristor D, Hiller M, Clarke SL, Schaar BT, Lowe CB, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat Biotechnol. 2010;28:495–501.Ji H, Jiang H, Ma W, Johnson DS, Myers RM, Wong WH, Ji H, Jiang H, Ma W, Johnson DS, Myers RM, Wong WH. An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nat Biotechnol. 2008;26:1293–300.Wang B, Cunningham JM, Yang X. Seq2pathway: an R/Bioconductor package for pathway analysis of next-generation sequencing data. Bioinformatics. 2015;31:3043.Yu G, Wang L-G, He Q-Y. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics. 2015;31:2382–3

Impact of Age on Inflammation-Based Scores among Patients Diagnosed with Stage III Non-Small Cell Lung Cancer

[EN] Background: Inflammatory and nutritional indexes are prognostic factors in non-small cell lung cancer (NSCLC). Furthermore, a low grade of chronic inflammation has been described in the older population (inflammaging). We aimed to evaluate the neutrophil-to-lymphocyte ratio (NLR), the Prognostic Nutritional Index (PNI), the advanced lung cancer inflammation index (ALI), the platelet-to-lymphocyte ratio (PLR), and the Glasgow Prognostic Score (GPS) in young and older patients diagnosed with locally advanced NSCLC to determine if significant differences between these groups exist.Methods:We conducted a retrospective study analyzing the impact of age on the NLR, PNI, ALI, PLR, and GPS among patients diagnosed with stage III NSCLC at Hospital Universitario Doctor Peset between 2010 and 2015.Results:We included 124 patients (84 young, 40 older patients). The median hemoglobin level and leukocyte count were lower in the older patients (p= 0.0158 andp= 0.001, respectively). A higher median C-reactive protein level was also found in this group (p= 0.0095). Regarding specific inflammatory indexes, the PNI, comprising inflammatory and nutritional parameters, was lower among the older patients (p= 0.0463). The median NLR, ALI, and PLR were similar in both age groups. Moreover, no differences between the age groups were found in the percentage of patients showing high versus low NLR (cutoff point, 5) or ALI (cutoff point, 18) or in the different GPS groups.Conclusions:The baseline PNI, hemoglobin level, and lymphocyte count were lower among the older patients; furthermore, CRP was higher, possibly, because of a more prominent inflammatory status in older patients with lung cancer. No other immunological or nutritional analytical variables were different between the age groups.Palomar-Abril, V.; Soria-Comes, T.; Tarazona Campos, S.; Martín Ureste, M.; Giner-Bosch, V.; Maestu-Maiques, IC. (2020). Impact of Age on Inflammation-Based Scores among Patients Diagnosed with Stage III Non-Small Cell Lung Cancer. Oncology. 98(8):528-533. https://doi.org/10.1159/000506204S52853398

La intensificación "Análisis Inteligente de Datos": una experiencia de Aprendizaje Basado en Proyectos

[EN] The Universitat Politècnica de València and its Faculty of Business Administration and Management have created a new intensification, named, "Intelligent Data Analysis", that provides the student with sufficient knowledge to integrate data analysis in the sometimes routine tasks of a company.The statistical, computer and ICT-related skills obtained through the Business Administration and Management degree are enhanced with more advanced statiscal models for multivariate data analysis and with R language programming, which is very suitable for such data analysis. All these skills are acquired under the Project-Based Learning methodology.This project's main achievement has been the coordination between the different subjects of the intensification to use the same software, which has resulted in a continuity for the way in which students work with RStudio, R, and Rmakdown. This has provided them a high level of management and integration of data analysis in the students’ work routines which will later aid them to become more qualified professionals.[ES] La Universitat Politècnica de Valencia y, en concreto, su Facultad de Administración y Dirección de Empresas ha decidido crear una nueva intensificación llamada "Análisis Inteligente de Datos" que proporciona al estudiante conocimientos suficientes para integrar el análisis de datos en las tareas en ocasiones rutinarias de la empresa. Las habilidades estadísticas, informáticas y relacionadas con las TIC que pueden obtenerse en el grado en Administración y Dirección de Empresas, se potencian con modelos estadísticos más avanzados para el análisis de datos multivariantes y con la programación en lenguaje R, que es muy adecuado para el análisis de datos. Todas las habilidades mencionadas se adquieren bajo la metodología de Aprendizaje Basado en Proyectos. El principal logro del presente proyecto ha sido la coordinación entre asignaturas de la intensificación a través de la utilización del mismo software, ya que ello ha supuesto una continuidad en la forma de trabajar del alumno con RStudio, R y Rmarkdown. Todo ello ha redundado en un alto nivel de manejo e integración del análisis de datos en las rutinas de trabajo de los estudiantes que les ayudará a convertirse posteriormente en profesionales más cualificados.Este trabajo ha sido financiado con un proyecto de la convocatoria Aprendizaje + Docencia: Proyectos de Innovación y Mejora educativa (PIME/20-21/200) de la Universitat Politècnica de València.Debón Aucejo, AM.; Tarazona Campos, S.; Doménech I De Soria, J.; Polo Garrido, F. (2021). La intensificación "Análisis Inteligente de Datos": una experiencia de Aprendizaje Basado en Proyectos. En IN-RED 2021: VII Congreso de Innovación Edicativa y Docencia en Red. Editorial Universitat Politècnica de València. 962-969. https://doi.org/10.4995/INRED2021.2021.13725OCS96296

Tumor microenvironment-targeted poly-L-glutamic acid-based combination conjugate for enhanced triple negative breast cancer treatment

[EN] The intrinsic characteristics of the tumor microenvironment (TME), including acidic pH and overexpression of hydrolytic enzymes, offer an exciting opportunity for the rational design of TME-drug delivery systems (DDS). We developed and characterized a pH-responsive biodegradable poly-L-glutamic acid (PGA)-based combination conjugate family with the aim of optimizing anticancer effects. We obtained combination conjugates bearing Doxorubicin (Dox) and aminoglutethimide (AGM) with two Dox loadings and two different hydrazone pH sensitive linkers that promote the specific release of Dox from the polymeric backbone within the TME. Low Dox loading coupled with a short hydrazone linker yielded optimal effects on primary tumor growth, lung metastasis (-90% reduction), and toxicological profile in a preclinical metastatic triple-negative breast cancer (TNBC) murine model. The use of transcriptomic analysis helped us to identify the molecular mechanisms responsible for such results including a differential immunomodulation and cell death pathways among the conjugates. This data highlights the advantages of targeting the TME, the therapeutic value of polymer-based combination approaches, and the utility of -omits-based analysis to accelerate anticancer DDS.The authors would like to thank Dr. Stuart P. Atkinson for his collaboration in manuscript preparation and English revision, and Irene Borreda for essential immunohistological support. This work has been supported by the European Research Council (grant ERC-CoG-2014-648831 "MyNano") and the Spanish Ministry of Science and Innovation (CTQ2010-18195, SAF2013-44848-R, BES-2008-006801, IPT-2012-0712-010000, Programa I3, and BIO2015-71658-R). LBN is funded through a University of South Florida-Helmsley Foundation award. FHL is funded through NIH grant. Part of the equipment employed in this work has been funded by Generalitat Valenciana and co-financed with FEDER funds (PO FEDER of Comunitat Valenciana 2014-2020).Arroyo-Crespo, JJ.; Armiñán, A.; Charbonnier, D.; Balzano-Nogueira, L.; Huertas-López, F.; Martí, C.; Tarazona Campos, S.... (2018). Tumor microenvironment-targeted poly-L-glutamic acid-based combination conjugate for enhanced triple negative breast cancer treatment. Biomaterials. 186:8-21. https://doi.org/10.1016/j.biomaterials.2018.09.02382118

Pathway network inference from gene expression data

This article has been published as part of BMC Systems Biology Volume 8 Supplement 2, 2014: Selected articles from the High-Throughput Omics and Data Integration Workshop. The full contents of the supplement are available online at http://www.biomedcentral.com/bmcsystbiol/supplements/8/S2.[EN] Background: The development of high-throughput omics technologies enabled genome-wide measurements of the activity of cellular elements and provides the analytical resources for the progress of the Systems Biology discipline. Analysis and interpretation of gene expression data has evolved from the gene to the pathway and interaction level, i.e. from the detection of differentially expressed genes, to the establishment of gene interaction networks and the identification of enriched functional categories. Still, the understanding of biological systems requires a further level of analysis that addresses the characterization of the interaction between functional modules. Results: We present a novel computational methodology to study the functional interconnections among the molecular elements of a biological system. The PANA approach uses high-throughput genomics measurements and a functional annotation scheme to extract an activity profile from each functional block -or pathway- followed by machine-learning methods to infer the relationships between these functional profiles. The result is a global, interconnected network of pathways that represents the functional cross-talk within the molecular system. We have applied this approach to describe the functional transcriptional connections during the yeast cell cycle and to identify pathways that change their connectivity in a disease condition using an Alzheimer example. Conclusions: PANA is a useful tool to deepen in our understanding of the functional interdependences that operate within complex biological systems. We show the approach is algorithmically consistent and the inferred network is well supported by the available functional data. The method allows the dissection of the molecular basis of the functional connections and we describe the different regulatory mechanisms that explain the network’s topology obtained for the yeast cell cycle data.This work has been supported by the FP7 STATegra project, grant 306000, by CONICET (National Research Council of Argentina), grant PIP112-2009-0100322, and by Universidad Nacional del Sur (Bahía Blanca, Argentina), grant PGI 24/N032. The publication costs for this article were funded by the FP7 STATegra project, grant 306000.Ponzoni, I.; Nueda, MJ.; Tarazona Campos, S.; Gotz, S.; Montaner, D.; Dussaut, JS.; Dopazo, J.... (2014). Pathway network inference from gene expression data. BMC Systems Biology. 8(2):1-17. https://doi.org/10.1186/1752-0509-8-S2-S7S1178

Influence of ecological infrastructures on the increase of biodiversity and conservation of beneficial arthropods in citrus orchards

[EN] We performed a study in nineteen citrus plots representative of the agricultural landscape of the municipality of Altea (100 km south of Valencia, in eastern Spain) in order to determine the influence of ecological infrastructures on biodiversity and conservation of beneficial arthropods. The landscape was dominated by small citrus orchards mixed with low density urban areas, a consequence of touristic urban pressure. We have considered five factors: pest management system (zero residues vs. conventional), size of the plot, distance to nearest natural habitat, presence/absence of cover crop, and presence/absence of other non-citrus fruits in the plot. Four of the five factors showed a positive influence on biodiversification and conservation of beneficials: small plot size, short distance to natural habitat, presence of vegetation cover and presence of other fruits. These are the factors to promote in order to develop biological strategies alternative to traditional pesticide use in the management of citrus pests. Only the factor “pest management system” does not show a significant influence on biodiversity or on abundance of biological control agents.Laborda Cenjor, R.; Bertomeu Cucart, S.; Sanchez Domingo, A.; Xamani Monserrat, P.; Tarazona Campos, S.; Ibañez, J.; García Prats, A.... (2013). Influence of ecological infrastructures on the increase of biodiversity and conservation of beneficial arthropods in citrus orchards. En Integrated Control in Citrus Fruit Crops. International Organization for Biological and Integrated Control of Noxious Animals and Plants, West Palearctic Regional Section (IOBC-WPRS). 111-115. http://hdl.handle.net/10251/54941S11111

Enseñanza no presencial de la estadística a través del uso de herramientas web

El aprendizaje de la estadística requiere no sólo de la comprensión de conceptos teóricos, sino también de su aplicación a casos prácticos y del manejo de software para el análisis de datos. Es por ello que, en general, la enseñanza presencial de esta disciplina suele favorecer el aprendizaje del alumno. Este estudio describe la metodología y los resultados obtenidos en el primer año de funcionamiento de una asignatura de estadística on-line: Métodos Estadísticos, que abarca Estadística Descriptiva, Distribuciones de Probabilidad, Inferencia Básica, ANOVA y Modelos de Regresión. Esta asignatura está incluida en el curso específico de adaptación al grado en Ingeniería Agroalimentaria y del Medio Rural de la UPV para titulados en Ingeniería Técnica Agrícola. Se utilizó la plataforma web de la UPV (Poliformat) para poner el material de la asignatura a disposición de los alumnos, para realizar exámenes online, para depositar los informes de los problemas resueltos mediante el software estadístico Statgraphics, o bien para las consultas de los alumnos. El uso de estas herramientas junto con el material proporcionado y un control continuado del progreso del alumno facilitó la obtención de unos resultados excepcionales en la evaluación final, a pesar de tratarse de alumnos que, en su mayoría, no estaban familiarizados con el uso de Internet, compaginaban los estudios con su actividad laboral y carecían de hábitos de estudio al haber finalizado sus estudios más de cinco años antes

Variable Selection for Multifactorial Genomic Data

[EN] Dimension reduction techniques are used to explore genomic data. Due to the large number of variables (genes) included in this kind of studies, variable selection methods are needed to identify the most responsive genes in order to get a better interpretation of the results or to conduct more specific experiments. These methods should be consistent with the amount of signal in the data. For this purpose, we introduce a novel selection strategy called minAS and also adapt other existing strategies, such us Gamma approximation, resampling techniques, etc. All of them are based on studying the distribution of statistics measuring the importance of the variables in the model. These strategies have been applied to the ASCA-genes analysis framework and more generally to dimension reduction techniques as PCA. The performance of the different strategies was evaluated using simulated data. The best performing methods were then applied on an experimental dataset containing the transcriptomic profiles of human embryonic stem cells cultured under different oxygen concentrations. The ability of the methods to extract relevant biological information from the data is discussedThis work was partially funded by Spanish Ministry of Science and Innovation [grants BIO2008-05266-E and DPI2008-06880-C03-03/DPI] and by Universidad Politecnica de Valencia [UPV-PAID 05-09]. The English revision of this paper was funded by the Universidad Politecnica de Valencia.Tarazona Campos, S.; Prado-López, S.; Dopazo, J.; Ferrer Riquelme, AJ.; Conesa, A. (2012). Variable Selection for Multifactorial Genomic Data. Chemometrics and Intelligent Laboratory Systems. 110(1):113-122. https://doi.org/10.1016/j.chemolab.2011.10.012S113122110

Dynamic evaluation of neutrophil-to-lymphocyte ratio as prognostic factor in stage III non-small cell lung cancer treated with chemoradiotherapy

[EN] Purpose Locally advanced non-small cell lung cancer (LA-NSCLC) is frequently treated with chemoradiotherapy (CRT). Despite the efforts, long-term outcomes are poor, and novel therapies have been introduced to improve results. Biomarkers are needed to detect early treatment failure and plan future follow-up and therapies. Our aim is to evaluate the role of dynamics of neutrophil-to-lymphocyte ratio (NLR) in patients with locally advanced NSCLC treated with CRT. Methods We retrospectively reviewed patients diagnosed with LA-NSCLC receiving definitive CRT at our center from 2010 to 2015. Baseline and post-treatment NLR were collected from our center database. NLR was dichotomized (threshold = 4) and patients were divided into two groups based on the variation from baseline to post-treatment NLR. The prognostic role and association with response were examined with logistic regression and multivariate Cox regression model, respectively. Results Ninety-two patients were included. Our analysis shows that NLR after treatment is associated with response to treatment [OR in the multivariate analysis 4.94 (1.01-24.48); p value = 0.048]. Furthermore, NLR and ECOG are independent prognostic factors for progression-free survival (PFS) and overall survival (OS). Specifically, PFS was 25.79 months for the good prognosis group and 12.09 for the poor prognosis group [HR 2.98 (CI 95% = 1.74-5.10), p < 0.001]; and OS was 42.94 months and 18.86 months, respectively [HR 2.81 (CI 95% = 1.62-4.90), p < 0.001]. Conclusion Dynamics of NLR have a prognostic value in stage III NSCLC treated with definitive CRT. Pre- and post-CRT NLR should be evaluated in prospective clinical trials involving consolidation treatment with immunotherapy.Palomar-Abril, V.; Soria-Comes, T.; Tarazona Campos, S.; Ureste, MM.; Giner-Bosch, V.; Maiques, ICM. (2020). 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