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For many years, a major question in cancer genomics has been the identification of those variations that can have a functional role in cancer, and distinguish from the majority of genomic changes that have no functional consequences. This is particularly challenging when considering complex chromosomal rearrangements, often composed of multiple DNA breaks, resulting in difficulties in classifying and interpreting them functionally. Despite recent efforts towards classifying structural variants (SVs), more robust statistical frames are needed to better classify these variants and isolate those that derive from specific molecular mechanisms. We present a new statistical approach to analyze SVs patterns from 2392 tumor samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium and identify significant recurrence, which can inform relevant mechanisms involved in the biology of tumors. The method is based on recursive KDE clustering of 152,926 SVs, randomization methods, graph mining techniques and statistical measures. The proposed methodology was able not only to identify complex patterns across different cancer types but also to prove them as not random occurrences. Furthermore, a new class of pattern that was not previously described has been identified.

During the last decade, there has been increasing awareness of the massive number of microorganisms, collectively known as the human microbiota, that are associated with humans. This microbiota outnumbers the host cells by approximately a factor of ten and contains a large repertoire of microbial genome-encoded metabolic processes. The diverse human microbiota and its associated metabolic potential can provide the host with novel functions that can influence host health and disease status in ways that still need to be analyzed. The microbiota varies with age, with features that depend on the body site, host lifestyle and health status. The challenge is therefore to identify and characterize these microbial communities and use this information to learn how they function and how they can influence the host in terms of health and well-being. Here we provide an overview of some of the recent studies involving the human microbiota and about how these communities might affect host health and disease. A special emphasis is given to studies related to tuberculosis, a disease that claims over one million lives each year worldwide and still represents a challenge for control in many countries, including Colombia.

Background The taxonomic and phylogenetic classification based on sequence analysis of the ITS1 genomic region has become a crucial component of fungal ecology and diversity studies. Nowadays, there is no accurate alignment-free classification tool for fungal ITS1 sequences for large environmental surveys. This study describes the development of a machine learning-based classifier for the taxonomical assignment of fungal ITS1 sequences at the genus level. Results A fungal ITS1 sequence database was built using curated data. Training and test sets were generated from it. A Naïve Bayesian classifier was built using features from the primary sequence with an accuracy of 87 % in the classification at the genus level. Conclusions The final model was based on a Naïve Bayes algorithm using ITS1 sequences from 510 fungal genera. This classifier, denoted as Mycofier, provides similar classification accuracy compared to BLASTN, but the database used for the classification contains curated data and the tool, independent of alignment, is more efficient and contributes to the field, given the lack of an accurate classification tool for large data from fungal ITS1 sequences. The software and source code for Mycofier are freely available at https://github.com/ldelgado-serrano/mycofier.git .

The microbial community of a Colombian high mountain hot spring, El Coquito, was analyzed using three different culture-independent assessments of 16S ribosomal RNA genes: clone libraries, pyrosequencing of the V5-V6 hypervariable region, and microarray. This acidic spring had a diverse community composed mainly oí Bacteria that shared characteristics with those from other hot springs and extreme acidic environments. The microbial community was dominated by Proteobacteria, Firmicutes, and Planctomycetes and contained chemotrophic bacteria potentially involved in cycling of ferrous and sulfur-containing minerals and phototrophic organisms, most of which were eukaryotic micro-algae. Despite the presence of a large proportion of novel, unclassified sequences, the taxonomic profiles obtained with each strategy showed similarities at higher taxonomic levels. However, some groups, such as Spirochaetes and Aquificae, were identified using only one methodology, and more taxa were detected with the gene array, which also shared more groups with the pyrosequencing data. Overall, the combined use of different approaches provided a broader view of the microbial community in this acidic hot spring.

Human cancer arises as a result of genomic alterations that transform cells and make them to grow without control and to pathological levels. The characterization of such genomic changes has enabled understanding tumor development and identifying clinical biomarkers for prognosis and therapy. Many of the genomic and epigenomic alterations in cancer can also be observed through the analysis of the transcriptome, which gives a more functional approach. Next-generation sequencing technologies, such as whole-genome sequencing (WGS) and RNA-seq, have provided the opportunity to assess molecular characterization of distinct tumors, leading to the discovery of several molecular aberrations linked to the biology of tumors. These molecular alterations include cancer-driving mutations, complex chromosomal rearrangements, atypical transcriptional profiles, gene fusions, among others.Despite the efforts to generate a comprehensive molecular atlas of tumor biology, there are still many unknown aspects, mainly due to technical and methodological limitations. In particular, regarding the genomic characterization of cancer genomes, structural variation is known to play a crucial role in carcinogenesis as a major component of cancer genome architecture. However, the full spectrum of complex rearrangements is still largely unknown due to the lack of straightforward frameworks that allow their identification, classification, and comprehensive characterization.On the other hand, regarding the transcriptomic characterization in tumor progression, changes in gene expression have been found to be related to metastasis. Nevertheless, the entire landscape of mRNA alterations has not been explored, opening a gap in the discovery of new transcripts, such as fusion transcripts, that might be associated with metastasis and evolve into predictive markers.In this thesis, we address these two limitations through two studies to better characterize structural genomic and transcriptomic alterations that contribute to tumor development.With the particular aim to classify and isolate complex somatic rearrangements in the cancer genome, with a potential molecular mechanism behind, we first investigated the landscape of chromosomal rearrangement from 2,586 tumor genomes across 40 cancer types (from the ICGC-TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium). We developed a novel framework for clustering, classification, and characterization of SV patterns with distribution that match with potential specific molecular mechanisms behind, rather than with random distribution. As a result, we identified complex rearrangements likely triggered by single catastrophic events, such as Chromoplexy or Chromothripsis. Among these, we identified a new pattern that we named Chromotrikona, which involves reciprocal translocations between different chromosomes. These findings contribute to the understanding of the genomic structural processes leading complex genomic reorganizations with impact in cancer.To search for RNA alterations associated with metastasis, we further conducted a study of RNA alterations in metastatic breast cancer, specifically in differential gene expression and fusion transcripts. We collaborated with Dr. De Mattos from IrsiCaixa, analyzing RNA-seq datasets of 82 metastatic breast samples obtained from 10 different patients, to search for evidence that could determine the metastasis in various tissues. Running in parallel, each one of these lines has provided interesting results. In particular, in the context of fusion transcripts, we have generated and applied a comprehensive strategy to identify and characterize transcript fusion events. The study has revealed a new pattern of massive multi-fusions of different transcripts in most of the metastases analyzed. This pattern has been experimentally validated and characterized. Surprisingly, it has been found beyond metastatic samples, being also present in normal breast cells. Although it is not clear the origin and the real nature of this event, we hypothesize that it might occurs at RNA level and be tissue specific. Further analyses will be needed to provide a deeper insight of the impact of this event in human cellular phenotypes.

En las últimas décadas ha incrementado nuestro conocimiento sobre la gran cantidad de microorganismos que conviven con nosotros, comunidades que colectivamente se conocen como la microbiota humana. El número de microorganismos que conforman la microbiota supera el número de células del cuerpo humano por un factor de diez aproximadamente y aporta un gran repertorio de genes y procesos metabólicos. La diversidad de la microbiota humana y su potencial metabólico brindan al hospedero una serie de funciones que complementan sus procesos y a su vez pueden influir sobre la salud del ser humano en formas que apenas se empiezan a conocer. La microbiota varía desde el nacimiento hasta la vejez del individuo, con características que dependen del sitio corporal, del estilo de vida y del estado de salud del hospedero. El reto actual es aprovechar el conocimiento derivado de la identificación y caracterización de estas comunidades microbianas para entender cómo funcionan estos microorganismos y cómo pueden influir de forma positiva o negativa sobre la salud del humano. En este documento ofrecemos una revisión general de algunos estudios recientes sobre la microbiota humana y su posible efecto en el hospedero en términos de salud y bienestar. Igualmente, se mencionan estudios sobre microbiota y su posible asociación con la tuberculosis, una enfermedad que todavía cobra más de un millón de vidas anualmente a nivel mundial y cuyo control todavía representa un gran reto en varios países del mundo, incluido Colombia.

Purpose: Metastatic prostate cancer (mPC) is enriched for homologous recombination repair (HRR) gene alterations; these biomarkers have prognostic and predictive value. Next-generation sequencing (NGS) allows for patient stratification based on these biomarkers, but widespread clinical implementation is still limited. Moreover, not all mutations in HRR genes result in functional HRR loss in the tumor. We investigated the correlation between genomic and functional loss of HRR, using NGS and an optimized RAD51 immunofluorescence (RAD51-IF) assay in mPC clinical biopsies. Experimental design: Observational study including patients with stage IV prostate cancer. Biopsies from either primary tumor or metastatic biopsies underwent NGS (targeted sequencing and/or whole-exome sequencing), and RAD51-IF. Clinical data was extracted from electronic patient records. Results: 219 biopsies from 187 patients were acquired, including primary (151/219) and metastatic (68/219) tumor biopsies collected either in the metastatic hormone-sensitive (169/219) or castration-resistant (50/219) setting. NGS (181 biopsies from 157 patients) showed frequent genomic alterations in TP53 (40%), AR (15%), PTEN (14%), MYC (10%), BRCA2 (9%), ATM (8%) and BRCA1 (2%). Tissue for RAD51 IF was available for 206 samples; of those, 140/206 (68%) were evaluable for RAD51-IF. Based on a previously defined threshold of 10% RAD51-positive cells, 21% samples had RAD51-low results compatible with HRR deficiency (HRD). Sample matched RAD51-IF and genomics data were obtained for 128 biopsies (117 patients): RAD51-IF had a high sensitivity (68%) and specificity (85%) to identify cases with BRCA1/2 alterations. Additionally, the RAD51-IF assay was able to identify restoration of HRR function in selected cases with BRCA2 reversion mutations or BRCA1 expression. Conclusions: RAD51-IF is feasible in routine clinical samples from mPC patients and associates strongly with clinically relevant HRR gene alterations.Competing Interest StatementThe authors have declared no competing interest.

Real-world evidence comparing the efficacy of chimeric antigen receptor (CAR) T-cell therapy against that of the previous standard of care (SOC) for refractory large B-cell lymphoma (LBCL) is scarce. We retrospectively collected data from patients with LBCL according to SCHOLAR-1 criteria treated with commercial CAR T-cell therapy in Spain (204 patients included and 192 treated, 101 with axicabtagene ciloleucel [axi-cel], and 91 with tisagenlecleucel [tisa-cel]) and compared the results with a historical refractory population of patients (n = 81) obtained from the GELTAMO-IPI study. We observed superior efficacy for CAR-T therapy (for both axi-cel and tisa-cel) over pSOC, with longer progression-free survival (PFS) (median of 5.6 vs. 4–6 months, p ≤ 0.001) and overall survival (OS) (median of 15 vs. 8 months, p < 0.001), independently of other prognostic factors (HR: 0.59 (95% CI: 0.44–0.80); p < 0.001] for PFS, and 0.45 [(95% CI: 0.31–0.64)] for OS). Within the CAR-T cohort, axi-cel showed longer PFS (median of 7.3 versus 2.8 months, respectively, p = 0.027) and OS (58% versus 42% at 12 months, respectively, p = 0.048) than tisa-cel. These differences were maintained in the multivariable analysis. On the other hand, axi-cel was independently associated with a higher risk of severe cytokine release syndrome and neurotoxicity. Our results suggest that the efficacy of CAR-T cell therapy is superior to pSOC in the real-world setting. Furthermore, axi-cel could be superior in efficacy to tisa-cel, although more toxic, in this group of refractory patients according to SCHOLAR-1 criteria.