Màster Universitari en Anàlisi de Dades Òmiques

Prediction of tumor patterns through the integration of clinical and transcriptomics data

2026-03-30T07:59:12Z

Prediction of tumor patterns through the integration of clinical and transcriptomics data Moreno Fernández-Aliseda, Claudia Cancer remains a leading cause of mortality worldwide, largely due to its remarkable heterogeneity and the lack of robust molecular classifiers that can capture the complexity of tumor biology beyond histopathological criteria. Despite major advances in molecular oncology, most transcriptomic studies have focused primarily on global gene expression, overlooking other regulatory layers such as promoter activity, alternative splicing, or tumor microenvironment composition. This perspective limits the discovery of biomarkers and constrains the development of predictive tools for precision oncology. Here, we present tumorProfiler, a modular analytical framework that integrates multiple transcriptomic dimensions, including promoter activity, alternative splicing (Percent Spliced-In, PSI) and gene expression, into predictive models for tumor classification. Using high-quality RNA-seq data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) cohort (n = 305 donors), we systematically characterized differential promoter activity, exon inclusion patterns, gene deregulation, and immune–stromal profiles across ten tumor types and intra-organ progression subtypes. Six supervised learning models were constructed, combining interpretable machine learning algorithms such as Random Forest with automated frameworks for benchmarking. Our results reveal that promoter activity and gene expression consistently outperform splicing events and cell composition in multiclass tumor prediction, achieving high accuracy and generalization capacity (AUC > 0.95; OOB error < 7%). While splicing events-based models captured biologically meaningful variation, their predictive power was more limited. Importantly, variable importance analyses highlighted a reduced subset of promoters, splicing events, and genes as candidate biomarkers with potential translational relevance. Altogether, this work demonstrates that transcriptomic regulation in cancer operates through complementary layers of molecular information, each contributing differently to tumor identity and progression. By integrating these layers, tumorProfiler provides a flexible and interpretable platform for patient stratification, biomarker discovery, and the design of precision therapies. Although currently a computational proof of concept, its modular design and discovery potential open avenues for experimental validation and future clinical translation. Curs 2024-2025; Tutora: Meritxell Pujolassos Tanyà

Population structure and spatial distribution of mycobacterium tuberculosis in Catalonia

2025-11-28T11:36:17Z

Population structure and spatial distribution of mycobacterium tuberculosis in Catalonia Leonov, Vadim Abstract Motivation: Even though Catalonia is a low-incidence area for tuberculosis (TB) transmission, high migration flow can make it a focal point for various Mycobacterium tuberculosis complex (MTBC) lineages. This study analyzed the population structure, geographical distribution, and hotspot locations of MTBC lineages/sublineages in Catalo-nia. Methods: Whole-genome sequencing (WGS) of 791 clinical MTBC strains enabled the construction of a Maximum Likelihood phylogenetic tree based on employing the General Time Reversible evolutionary model with gamma distribution for nucleotide substitution, and strains were typed into lineages and sublineages according to specific SNPs profiles. A logistic regression model was employed to analyze clinical phenotype associated with dominant MTBC lineages. The global Fisher’s exact test evaluated the distribution of lineages, including the assessment of migration factors. Post hoc Fisher’s exact test assessed the linkage between the country of origin and MTBC line-age. SatScan analysis identified hotspot areas for MTBC lineages across the study region. Results: WGS analysis revealed seven MTBC lineages in Catalonia: L4 (82.9%), L3 (6.8%), L2 (3.4%), L1 (2.6%), L6 (1.4%), M. bovis (1.9%), and L5 (0.3%). Within predominant Lineage 4, L4.1.2/Haarlem, L4.3/LAM, and L4.10/PGG3 sublineages were most prevalent. The L1/EAI, L2/Beijing, and L3/CAS exhibited localized distributions and adhered to the migrant community, while the L4.1.2/Haarlem, L4.3/LAM, and L4.10/PGG3 are almost ubiquitous in Catalonia. The L3/CAS and L4.10/PGG3 were significantly associated with extrapulmonary TB, while L4.1.2/Haarlem was linked with sputum smear-positive TB cases. Recent migrants from India and Pakistan showed a significantly higher risk of L3/CAS. Overall, the L4/Euro-American predominantly spreads among Spanish-born patients and long-term migrants with Senegalese and Moroccan migrants having 1.1- and 1.2-fold higher risks for L4.1.2/Haarlem and L4.10/PGG3 respectively. Migrants from Argentina, Venezuela, Senegal, Morocco, and Roma-nia demonstrated significant associations with L4.3/LAM, with aORs of 2.4, 2.4, 2.0, 1.6, and 1.1, respectively. Hotspots with multiple MTBC lineages involvement were identified in 9 counties Vallès Occidental, Barcelonès, Baix Llobregat, Garraf. Alt Penedès, Maresme, Moianès, Vallès Oriental, and Baix Camp, underscoring the need for targeted public health interventions. The L4.10/PGG3 exhibits a high propensity to form clusters compared to other lineages in Catalonia. Conclusion: In Catalonia, the L4/Euro-American dominates, particularly L4.1.2/Haarlem, L4.3/LAM, and L4.10/PGG3, each with distinct epidemiological profiles. Spatial analysis pinpointed transmission hotspots, high-lighting regional variability in MTBC lineage distribution. Targeted public health interventions are crucial in these high-risk areas and among certain migrant populations to mitigate TB transmission dynamics. Curs 2023-2024

Interferon-stimulated gene expression in HIV-1 inoculated macrophages and healthy Langerhans cells: The impact of macrophage polarization and Langerhans cell maturation

2025-11-28T11:34:39Z

Interferon-stimulated gene expression in HIV-1 inoculated macrophages and healthy Langerhans cells: The impact of macrophage polarization and Langerhans cell maturation Dormans, Thijs Abstract Background: Antigen presenting cells (APCs) have been extensively studied for their role in human immunodeficiency virus type 1 (HIV-1) infection. HIV-1 is readily recognized by APCs, which subsequently exert a strong antiviral response through induced expression of interferon-stimulated genes (ISGs). Cellular activating processes in APCs can influence the extent of this antiviral response and may alter susceptibility to HIV-1 infection. In this study, we investigated the effect of distinctive activation processes on ISG expression in two types of APC: macrophage polarization and Langerhans cell maturation. Methods: Microarray-based differential gene expression (DGE) analysis was performed to study the effects of M1, M2a and M2 macrophage polarization on ISG expression upon HIV-1 inoculation. Furthermore, we performed RNA-seq of immature and mature Langerhans cells. DGE analysis and weighted gene co-expression network analysis (WGCNA) were performed, comparing ISG expression between immature and mature Langerhans cells derived from healthy donors in absence of HIV-1. Results: HIV-1 inoculation of macrophages led to polarization state-specific gene expression changes: M1 and M2c showed a relatively large and partly overlapping change in ISG expression, whereas M2a remained largely transcriptionally refractive, which was opposite of what was observed in absence of HIV-1. Differential expression of TIMP1 and PLAUR was validated in an independent macrophage set. Mature Langerhans cells were found to differ greatly in their gene expression compared to immature Langerhans cells and intersection of DGE-WGCNA results revealed several maturity state driver ISGs. Conclusion: These findings enhance our understanding of the effects of macrophage polarization and Langerhans cell differentiation on ISG expression and outline various candidate genes for further exploration of their role in HIV-1 pathogenesis. Curs 2023-2024

Genetic risk factors associated with ischemic stroke and etiological subtypes

2025-11-28T11:35:58Z

Genetic risk factors associated with ischemic stroke and etiological subtypes Boldo Cobo, Paula Abstract Background: Ischemic stroke is a multifactorial pathology caused by an interruption of the blood flow to the brain, causing the brain not to receive oxygen and nutrients. Although research has advanced in identifying genetic factors linked to IS, there is a notable gap in studies centered on the Spanish population, which remains underrepresented. Methods and Results: We conducted a genome-wide association study (GWAS) on a Spanish repli-cation cohort of 3,882 individuals (457 IS cases and 3,425 controls), derived from a larger primary cohort of 9,081 individuals (3,493 IS cases and 5,588 controls). A meta-analysis combining both cohorts was performed, followed by functional annotation, gene-based, and gene-set analyses. We identified a replicated locus associated with ischemic stroke, rs7092141-C (beta (SE) = 0.04 (0.019), p = 0.027). Our metanalysis identified three loci with genome-wide significance: rs184652834-G, rs76757388-A, and rs7092141-C. Additionally, eight loci showed nominal significance in the replica-tion cohort, which was also significant in the main cohort, involving genes such as ANKH, LATS2, and GPR158. Gene-set analyses highlighted suggestive pathways, including the G protein-coupled receptor signaling pathway (p-value =4.37×10-3), activation of NOXA and mitochondrial translocation pathway (p-value =3.18×10-3), and diseases: endometriosis (p-value =1.74×10-4) and coronary artery (p-value =2.33×10-2). Conclusion: Our findings underscore the importance of conducting genetic studies in specific popu-lations like the Spanish cohort. The identified loci and suggestive pathways provide a foundation for further research into the genetic mechanisms underlying ischemic stroke, which may ultimately lead to improved prevention and treatment strategies. Curs 2023-2024