INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance.

BACKGROUND: Implementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification. RESULTS: The routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a "generic" build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis. CONCLUSIONS: The accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).

Molecular Profiling of Axial Spondyloarthritis Patients Reveals an Association between Innate and Adaptive Cell Populations and Therapeutic Response to Tumor Necrosis Factor Inhibitors.

This study aims at identifying molecular biomarkers differentiating responders and non-responders to treatment with Tumor Necrosis Factor inhibitors (TNFi) among patients with axial spondyloarthritis (axSpA). Whole blood mRNA and plasma proteins were measured in a cohort of biologic-naïve axSpA patients (n = 35), pre and post (14 weeks) TNFi treatment with adalimumab. Differential expression analysis was used to identify the most enriched pathways and in predictive models to distinguish responses to TNFi. A treatment-associated signature suggests a reduction in inflammatory activity. We found transcripts and proteins robustly differentially expressed between baseline and week 14 in responders. C-reactive protein (CRP) and Haptoglobin (HP) proteins showed strong and early decrease in the plasma of axSpA patients, while a cluster of apolipoproteins (APOD, APOA2, APOA1) showed increased expression at week 14. Responders to TNFi treatment present higher levels of markers of innate immunity at baseline, and lower levels of adaptive immunity markers, particularly B-cells. A logistic regression model incorporating ASDAS-CRP, gender, and AFF3, the top differentially expressed gene at baseline, enabled an accurate prediction of response to adalimumab in our cohort (AUC = 0.97). In conclusion, innate and adaptive immune cell type composition at baseline may be a major contributor to response to adalimumab in axSpA patients. A model including clinical and gene expression variables should also be considered.

Transcription readthrough is prevalent in healthy human tissues and associated with inherent genomic features.

Transcription termination is a crucial step in the production of conforming mRNAs and functional proteins. Under cellular stress conditions, the transcription machinery fails to identify the termination site and continues transcribing beyond gene boundaries, a phenomenon designated as transcription readthrough. However, the prevalence and impact of this phenomenon in healthy human tissues remain unexplored. Here, we assessed transcription readthrough in almost 3000 transcriptome profiles representing 23 human tissues and found that 34% of the expressed protein-coding genes produced readthrough transcripts. The production of readthrough transcripts was restricted in genomic regions with high transcriptional activity and was associated with inefficient splicing and increased chromatin accessibility in terminal regions. In addition, we showed that these transcripts contained several binding sites for the same miRNA, unravelling a potential role as miRNA sponges. Overall, this work provides evidence that transcription readthrough is pervasive and non-stochastic, not only in abnormal conditions but also in healthy tissues. This suggests a potential role for such transcripts in modulating normal cellular functions.

Differential Gene Expression of Malaria Parasite in Response to Red Blood Cell-Specific Glycolytic Intermediate 2,3-Diphosphoglycerate (2,3-DPG).

Innovative strategies to control malaria are urgently needed. Exploring the interplay between Plasmodium sp. parasites and host red blood cells (RBCs) offers opportunities for novel antimalarial interventions. Pyruvate kinase deficiency (PKD), characterized by heightened 2,3-diphosphoglycerate (2,3-DPG) concentration, has been associated with protection against malaria. Elevated levels of 2,3-DPG, a specific mammalian metabolite, may hinder glycolysis, prompting us to hypothesize its potential contribution to PKD-mediated protection. We investigated the impact of the extracellular supplementation of 2,3-DPG on the Plasmodium falciparum intraerythrocytic developmental cycle in vitro. The results showed an inhibition of parasite growth, resulting from significantly fewer progeny from 2,3-DPG-treated parasites. We analyzed differential gene expression and the transcriptomic profile of P. falciparum trophozoites, from in vitro cultures subjected or not subjected to the action of 2,3-DPG, using Nanopore Sequencing Technology. The presence of 2,3-DPG in the culture medium was associated with the significant differential expression of 71 genes, mostly associated with the GO terms nucleic acid binding, transcription or monoatomic anion channel. Further, several genes related to cell cycle control were downregulated in treated parasites. These findings suggest that the presence of this RBC-specific glycolytic metabolite impacts the expression of genes transcribed during the parasite trophozoite stage and the number of merozoites released from individual schizonts, which supports the potential role of 2,3-DPG in the mechanism of protection against malaria by PKD.

Viral genetic clustering and transmission dynamics of the 2022 mpox outbreak in Portugal.

Pathogen genome sequencing during epidemics enhances our ability to identify and understand suspected clusters and investigate their relationships. Here, we combine genomic and epidemiological data of the 2022 mpox outbreak to better understand early viral spread, diversification and transmission dynamics. By sequencing 52% of the confirmed cases in Portugal, we identified the mpox virus sublineages with the highest impact on case numbers and fitted them into a global context, finding evidence that several international sublineages probably emerged or spread early in Portugal. We estimated a 62% infection reporting rate and that 1.3% of the population of men who have sex with men in Portugal were infected. We infer the critical role played by sexual networks and superspreader gatherings, such as sauna attendance, in the dissemination of mpox virus. Overall, our findings highlight genomic epidemiology as a tool for the real-time monitoring and control of mpox epidemics, and can guide future vaccine policy in a highly susceptible population.

ReporTree: a surveillance-oriented tool to strengthen the linkage between pathogen genetic clusters and epidemiological data.

BACKGROUND: Genomics-informed pathogen surveillance strengthens public health decision-making, playing an important role in infectious diseases' prevention and control. A pivotal outcome of genomics surveillance is the identification of pathogen genetic clusters and their characterization in terms of geotemporal spread or linkage to clinical and demographic data. This task often consists of the visual exploration of (large) phylogenetic trees and associated metadata, being time-consuming and difficult to reproduce. RESULTS: We developed ReporTree, a flexible bioinformatics pipeline that allows diving into the complexity of pathogen diversity to rapidly identify genetic clusters at any (or all) distance threshold(s) or cluster stability regions and to generate surveillance-oriented reports based on the available metadata, such as timespan, geography, or vaccination/clinical status. ReporTree is able to maintain cluster nomenclature in subsequent analyses and to generate a nomenclature code combining cluster information at different hierarchical levels, thus facilitating the active surveillance of clusters of interest. By handling several input formats and clustering methods, ReporTree is applicable to multiple pathogens, constituting a flexible resource that can be smoothly deployed in routine surveillance bioinformatics workflows with negligible computational and time costs. This is demonstrated through a comprehensive benchmarking of (i) the cg/wgMLST workflow with large datasets of four foodborne bacterial pathogens and (ii) the alignment-based SNP workflow with a large dataset of Mycobacterium tuberculosis. To further validate this tool, we reproduced a previous large-scale study on Neisseria gonorrhoeae, demonstrating how ReporTree is able to rapidly identify the main species genogroups and characterize them with key surveillance metadata, such as antibiotic resistance data. By providing examples for SARS-CoV-2 and the foodborne bacterial pathogen Listeria monocytogenes, we show how this tool is currently a useful asset in genomics-informed routine surveillance and outbreak detection of a wide variety of species. CONCLUSIONS: In summary, ReporTree is a pan-pathogen tool for automated and reproducible identification and characterization of genetic clusters that contributes to a sustainable and efficient public health genomics-informed pathogen surveillance. ReporTree is implemented in python 3.8 and is freely available at https://github.com/insapathogenomics/ReporTree .

Development of an amplicon-based sequencing approach in response to the global emergence of mpox.

The 2022 multicountry mpox outbreak concurrent with the ongoing Coronavirus Disease 2019 (COVID-19) pandemic further highlighted the need for genomic surveillance and rapid pathogen whole-genome sequencing. While metagenomic sequencing approaches have been used to sequence many of the early mpox infections, these methods are resource intensive and require samples with high viral DNA concentrations. Given the atypical clinical presentation of cases associated with the outbreak and uncertainty regarding viral load across both the course of infection and anatomical body sites, there was an urgent need for a more sensitive and broadly applicable sequencing approach. Highly multiplexed amplicon-based sequencing (PrimalSeq) was initially developed for sequencing of Zika virus, and later adapted as the main sequencing approach for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Here, we used PrimalScheme to develop a primer scheme for human monkeypox virus that can be used with many sequencing and bioinformatics pipelines implemented in public health laboratories during the COVID-19 pandemic. We sequenced clinical specimens that tested presumptively positive for human monkeypox virus with amplicon-based and metagenomic sequencing approaches. We found notably higher genome coverage across the virus genome, with minimal amplicon drop-outs, in using the amplicon-based sequencing approach, particularly in higher PCR cycle threshold (Ct) (lower DNA titer) samples. Further testing demonstrated that Ct value correlated with the number of sequencing reads and influenced the percent genome coverage. To maximize genome coverage when resources are limited, we recommend selecting samples with a PCR Ct below 31 Ct and generating 1 million sequencing reads per sample. To support national and international public health genomic surveillance efforts, we sent out primer pool aliquots to 10 laboratories across the United States, United Kingdom, Brazil, and Portugal. These public health laboratories successfully implemented the human monkeypox virus primer scheme in various amplicon sequencing workflows and with different sample types across a range of Ct values. Thus, we show that amplicon-based sequencing can provide a rapidly deployable, cost-effective, and flexible approach to pathogen whole-genome sequencing in response to newly emerging pathogens. Importantly, through the implementation of our primer scheme into existing SARS-CoV-2 workflows and across a range of sample types and sequencing platforms, we further demonstrate the potential of this approach for rapid outbreak response.

Distribution and Clinical Significance of HPV16 Variants in Head and Neck Squamous Cell Carcinomas: Data from a Portuguese Cohort and Systematic Review.

INTRODUCTION: Genomic variants of the human papillomavirus type 16 (HPV16) are thought to play differential roles in the susceptibility to head and neck squamous cell carcinomas (HNSCC) and its biological behaviour. This study aimed to establish the prevalence of HPV16 variants in an HNSCC cohort and associate them with clinical pathological characteristics and patient survival. METHODS: We retrieved samples and clinical data from 68 HNSCC patients. DNA samples were available from tumour biopsy at the time of the primary diagnosis. Targeted next-generation sequencing was used to obtain whole-genome sequences, and variants were established based on phylogenetic classification. RESULTS: 74% of samples clustered in lineage A, 5.7% in lineage B, 2.9% in lineage C, and 17.1% in lineage D. Comparative genome analysis revealed 243 single nucleotide variations. Of these, one hundred were previously reported, according to our systematic review. No significant associations with clinical pathological variables or patient survival were observed. The E6 amino acid variations E31G, L83V, and D25E and E7 N29S, associated with cervical cancer, were not observed, except for N29S in a single patient. CONCLUSION: These results provide a comprehensive genomic map of HPV16 in HSNCC, highlighting tissue-specific characteristics which will help design tailored therapies for cancer patients.

Comparative Effectiveness of COVID-19 Vaccines in Preventing Infections and Disease Progression from SARS-CoV-2 Omicron BA.5 and BA.2, Portugal.

We estimated comparative primary and booster vaccine effectiveness (VE) of SARS-CoV-2 Omicron BA.5 and BA.2 lineages against infection and disease progression. During April-June 2022, we implemented a case-case and cohort study and classified lineages using whole-genome sequencing or spike gene target failure. For the case-case study, we estimated the adjusted odds ratios (aORs) of vaccination using a logistic regression. For the cohort study, we estimated VE against disease progression using a penalized logistic regression. We observed no reduced VE for primary (aOR 1.07 [95% CI 0.93-1.23]) or booster (aOR 0.96 [95% CI 0.84-1.09]) vaccination against BA.5 infection. Among BA.5 case-patients, booster VE against progression to hospitalization was lower than that among BA.2 case-patients (VE 77% [95% CI 49%-90%] vs. VE 93% [95% CI 86%-97%]). Although booster vaccination is less effective against BA.5 than against BA.2, it offers substantial protection against progression from BA.5 infection to severe disease.

Identification of biomarkers predictive of metastasis development in early-stage colorectal cancer using network-based regularization.

Colorectal cancer (CRC) is the third most common cancer and the second most deathly worldwide. It is a very heterogeneous disease that can develop via distinct pathways where metastasis is the primary cause of death. Therefore, it is crucial to understand the molecular mechanisms underlying metastasis. RNA-sequencing is an essential tool used for studying the transcriptional landscape. However, the high-dimensionality of gene expression data makes selecting novel metastatic biomarkers problematic. To distinguish early-stage CRC patients at risk of developing metastasis from those that are not, three types of binary classification approaches were used: (1) classification methods (decision trees, linear and radial kernel support vector machines, logistic regression, and random forest) using differentially expressed genes (DEGs) as input features; (2) regularized logistic regression based on the Elastic Net penalty and the proposed iTwiner-a network-based regularizer accounting for gene correlation information; and (3) classification methods based on the genes pre-selected using regularized logistic regression. Classifiers using the DEGs as features showed similar results, with random forest showing the highest accuracy. Using regularized logistic regression on the full dataset yielded no improvement in the methods' accuracy. Further classification using the pre-selected genes found by different penalty factors, instead of the DEGs, significantly improved the accuracy of the binary classifiers. Moreover, the use of network-based correlation information (iTwiner) for gene selection produced the best classification results and the identification of more stable and robust gene sets. Some are known to be tumor suppressor genes (OPCML-IT2), to be related to resistance to cancer therapies (RAC1P3), or to be involved in several cancer processes such as genome stability (XRCC6P2), tumor growth and metastasis (MIR602) and regulation of gene transcription (NME2P2). We show that the classification of CRC patients based on pre-selected features by regularized logistic regression is a valuable alternative to using DEGs, significantly increasing the models' predictive performance. Moreover, the use of correlation-based penalization for biomarker selection stands as a promising strategy for predicting patients' groups based on RNA-seq data.

Development of an amplicon-based sequencing approach in response to the global emergence of human monkeypox virus.

The 2022 multi-country monkeypox (mpox) outbreak concurrent with the ongoing COVID-19 pandemic has further highlighted the need for genomic surveillance and rapid pathogen whole genome sequencing. While metagenomic sequencing approaches have been used to sequence many of the early mpox infections, these methods are resource intensive and require samples with high viral DNA concentrations. Given the atypical clinical presentation of cases associated with the outbreak and uncertainty regarding viral load across both the course of infection and anatomical body sites, there was an urgent need for a more sensitive and broadly applicable sequencing approach. Highly multiplexed amplicon-based sequencing (PrimalSeq) was initially developed for sequencing of Zika virus, and later adapted as the main sequencing approach for SARS-CoV-2. Here, we used PrimalScheme to develop a primer scheme for human monkeypox virus that can be used with many sequencing and bioinformatics pipelines implemented in public health laboratories during the COVID-19 pandemic. We sequenced clinical samples that tested presumptive positive for human monkeypox virus with amplicon-based and metagenomic sequencing approaches. We found notably higher genome coverage across the virus genome, with minimal amplicon drop-outs, in using the amplicon-based sequencing approach, particularly in higher PCR cycle threshold (lower DNA titer) samples. Further testing demonstrated that Ct value correlated with the number of sequencing reads and influenced the percent genome coverage. To maximize genome coverage when resources are limited, we recommend selecting samples with a PCR cycle threshold below 31 Ct and generating 1 million sequencing reads per sample. To support national and international public health genomic surveillance efforts, we sent out primer pool aliquots to 10 laboratories across the United States, United Kingdom, Brazil, and Portugal. These public health laboratories successfully implemented the human monkeypox virus primer scheme in various amplicon sequencing workflows and with different sample types across a range of Ct values. Thus, we show that amplicon based sequencing can provide a rapidly deployable, cost-effective, and flexible approach to pathogen whole genome sequencing in response to newly emerging pathogens. Importantly, through the implementation of our primer scheme into existing SARS-CoV-2 workflows and across a range of sample types and sequencing platforms, we further demonstrate the potential of this approach for rapid outbreak response.

The rare DRB1*04:08-DQ8 haplotype is the main HLA class II genetic driver and discriminative factor of Early-onset Type 1 diabetes in the Portuguese population.

Introduction: Early-onset Type 1 diabetes (EOT1D) is considered a disease subtype with distinctive immunological and clinical features. While both Human Leukocyte Antigen (HLA) and non-HLA variants contribute to age at T1D diagnosis, detailed analyses of EOT1D-specific genetic determinants are still lacking. This study scrutinized the involvement of the HLA class II locus in EOT1D genetic control. Methods: We conducted genetic association and regularized logistic regression analyses to evaluate genotypic, haplotypic and allelic variants in DRB1, DQA1 and DQB1 genes in children with EOT1D (diagnosed at ≤5 years of age; n=97), individuals with later-onset disease (LaOT1D; diagnosed 8-30 years of age; n=96) and nondiabetic control subjects (n=169), in the Portuguese population. Results: Allelic association analysis of EOT1D and LaOT1D unrelated patients in comparison with controls, revealed that the rare DRB1*04:08 allele is a distinctive EOT1D susceptibility factor (corrected p-value=7.0x10-7). Conversely, the classical T1D risk allele DRB1*04:05 was absent in EOT1D children while was associated with LaOT1D (corrected p-value=1.4x10-2). In corroboration, HLA class II haplotype analysis showed that the rare DRB1*04:08-DQ8 haplotype is specifically associated with EOT1D (corrected p-value=1.4x10-5) and represents the major HLA class II genetic driver and discriminative factor in the development of early onset disease. Discussion: This study uncovered that EOT1D holds a distinctive spectrum of HLA class II susceptibility loci, which includes risk factors overlapping with LaOT1D and discriminative genetic configurations. These findings warrant replication studies in larger multicentric settings encompassing other ethnicities and may impact target screening strategies and follow-up of young children with high T1D genetic risk as well as personalized therapeutic approaches.

Polycomb group (PcG) proteins prevent the assembly of abnormal synaptonemal complex structures during meiosis.

The synaptonemal complex (SC) is a proteinaceous scaffold that is assembled between paired homologous chromosomes during the onset of meiosis. Timely expression of SC coding genes is essential for SC assembly and successful meiosis. However, SC components have an intrinsic tendency to self-organize into abnormal repetitive structures, which are not assembled between the paired homologs and whose formation is potentially deleterious for meiosis and gametogenesis. This creates an interesting conundrum, where SC genes need to be robustly expressed during meiosis, but their expression must be carefully regulated to prevent the formation of anomalous SC structures. In this manuscript, we show that the Polycomb group protein Sfmbt, the Drosophila ortholog of human MBTD1 and L3MBTL2, is required to avoid excessive expression of SC genes during prophase I. Although SC assembly is normal after Sfmbt depletion, SC disassembly is abnormal with the formation of multiple synaptonemal complexes (polycomplexes) within the oocyte. Overexpression of the SC gene corona and depletion of other Polycomb group proteins are similarly associated with polycomplex formation during SC disassembly. These polycomplexes are highly dynamic and have a well-defined periodic structure. Further confirming the importance of Sfmbt, germ line depletion of this protein is associated with significant metaphase I defects and a reduction in female fertility. Since transcription of SC genes mostly occurs during early prophase I, our results suggest a role of Sfmbt and other Polycomb group proteins in downregulating the expression of these and other early prophase I genes during later stages of meiosis.

Genetic and microenvironmental intra-tumor heterogeneity impacts colorectal cancer evolution and metastatic development.

Colorectal cancer (CRC) is a highly diverse disease, where different genomic instability pathways shape genetic clonal diversity and tumor microenvironment. Although intra-tumor heterogeneity has been characterized in primary tumors, its origin and consequences in CRC outcome is not fully understood. Therefore, we assessed intra- and inter-tumor heterogeneity of a prospective cohort of 136 CRC samples. We demonstrate that CRC diversity is forged by asynchronous forms of molecular alterations, where mutational and chromosomal instability collectively boost CRC genetic and microenvironment intra-tumor heterogeneity. We were able to depict predictor signatures of cancer-related genes that can foresee heterogeneity levels across the different tumor consensus molecular subtypes (CMS) and primary tumor location. Finally, we show that high genetic and microenvironment heterogeneity are associated with lower metastatic potential, whereas late-emerging copy number variations favor metastasis development and polyclonal seeding. This study provides an exhaustive portrait of the interplay between genetic and microenvironment intra-tumor heterogeneity across CMS subtypes, depicting molecular events with predictive value of CRC progression and metastasis development.

Concerted Regulation of Glycosylation Factors Sustains Tissue Identity and Function.

Glycosylation is a fundamental cellular process affecting human development and health. Complex machinery establishes the glycan structures whose heterogeneity provides greater structural diversity than other post-translational modifications. Although known to present spatial and temporal diversity, the evolution of glycosylation and its role at the tissue-specific level is poorly understood. In this study, we combined genome and transcriptome profiles of healthy and diseased tissues to uncover novel insights into the complex role of glycosylation in humans. We constructed a catalogue of human glycosylation factors, including transferases, hydrolases and other genes directly involved in glycosylation. These were categorized as involved in N-, O- and lipid-linked glycosylation, glypiation, and glycosaminoglycan synthesis. Our data showed that these glycosylation factors constitute an ancient family of genes, where evolutionary constraints suppressed large gene duplications, except for genes involved in O-linked and lipid glycosylation. The transcriptome profiles of 30 healthy human tissues revealed tissue-specific expression patterns preserved across mammals. In addition, clusters of tightly co-expressed genes suggest a glycosylation code underlying tissue identity. Interestingly, several glycosylation factors showed tissue-specific profiles varying with age, suggesting a role in ageing-related disorders. In cancer, our analysis revealed that glycosylation factors are highly perturbed, at the genome and transcriptome levels, with a strong predominance of copy number alterations. Moreover, glycosylation factor dysregulation was associated with distinct cellular compositions of the tumor microenvironment, reinforcing the impact of glycosylation in modulating the immune system. Overall, this work provides genome-wide evidence that the glycosylation machinery is tightly regulated in healthy tissues and impaired in ageing and tumorigenesis, unveiling novel potential roles as prognostic biomarkers or therapeutic targets.

Phylogenomic characterization and signs of microevolution in the 2022 multi-country outbreak of monkeypox virus.

The largest monkeypox virus (MPXV) outbreak described so far in non-endemic countries was identified in May 2022 (refs. 1-6). In this study, shotgun metagenomics allowed the rapid reconstruction and phylogenomic characterization of the first MPXV outbreak genome sequences, showing that this MPXV belongs to clade 3 and that the outbreak most likely has a single origin. Although 2022 MPXV (lineage B.1) clustered with 2018-2019 cases linked to an endemic country, it segregates in a divergent phylogenetic branch, likely reflecting continuous accelerated evolution. An in-depth mutational analysis suggests the action of host APOBEC3 in viral evolution as well as signs of potential MPXV human adaptation in ongoing microevolution. Our findings also indicate that genome sequencing may provide resolution to track the spread and transmission of this presumably slow-evolving double-stranded DNA virus.

Predictive and Therapeutic Implications of a Novel PLCγ1/SHP2-Driven Mechanism of Cetuximab Resistance in Metastatic Colorectal Cancer.

PURPOSE: Cetuximab is an EGFR-targeted therapy approved for the treatment of RAS wild-type (WT) metastatic colorectal cancer (mCRC). However, about 60% of these patients show innate resistance to cetuximab. To increase cetuximab efficacy, it is crucial to successfully identify responder patients, as well as to develop new therapeutic approaches to overcome cetuximab resistance. EXPERIMENTAL DESIGN: We evaluated the value of EGFR effector phospholipase C gamma 1 (PLCγ1) in predicting cetuximab responses, by analyzing progression-free survival (PFS) of a multicentric retrospective cohort of 94 treated patients with mCRC (log-rank test and Cox regression model). Furthermore, we used in vitro and zebrafish xenotransplant models to identify and target the mechanism behind PLCγ1-mediated resistance to cetuximab. RESULTS: In this study, levels of PLCγ1 were found increased in RAS WT tumors and were able to predict cetuximab responses in clinical samples and in vitro and in vivo models. Mechanistically, PLCγ1 expression was found to bypass cetuximab-dependent EGFR inhibition by activating ERK and AKT pathways. This novel resistance mechanism involves a noncatalytic role of PLCγ1 SH2 tandem domains in the propagation of downstream signaling via SH2-containing protein tyrosine phosphatase 2 (SHP2). Accordingly, SHP2 inhibition sensitizes PLCγ1-resistant cells to cetuximab. CONCLUSIONS: Our discoveries reveal the potential of PLCγ1 as a predictive biomarker for cetuximab responses and suggest an alternative therapeutic approach to circumvent PLCγ1-mediated resistance to cetuximab in patients with RAS WT mCRC. In this way, this work contributes to the development of novel strategies in the medical management and treatment of patients with mCRC.

The role of muscle in the susceptibility and progression of axial Spondyloarthritis: The MyoSpA Study Protocol.

BACKGROUND: Axial Spondyloarthritis (axSpA) is a chronic, inflammatory rheumatic disease that affects the axial skeleton, causing pain, stiffness, and fatigue. Genetics and environmental factors such as microbiota and microtrauma are known causes of disease susceptibility and progression. Murine models of axSpA found a decisive role for biomechanical stress as an inducer of enthesitis and new bone formation. Here, we hypothesize that muscle properties in axSpA patients are compromised and influenced by genetic background. OBJECTIVES: To improve our current knowledge of axSpA physiopathology, we aim to characterize axial and peripheral muscle properties and identify genetic and protein biomarker that might explain such properties. METHODS: A cross-sectional study will be conducted on 48 participants aged 18-50 years old, involving patients with axSpA (according to ASAS classification criteria, symptoms duration < 10 years) and healthy controls matched by gender, age, and levels of physical activity. We will collect epidemiological and clinical data and perform a detailed, whole body and segmental, myofascial characterization (focusing on multifidus, brachioradialis and the gastrocnemius lateralis) concerning: a) Physical Properties (stiffness, tone and elasticity), assessed by MyotonPRO®; b) Strength, by a dynamometer; c) Mass, by bioimpedance; d) Performance through gait speed and 60-second sit-to-stand test; e) Histological and cellular/ molecular characterization through ultrasound-guided biopsies of multifidus muscle; f) Magnetic Resonance Imaging (MRI) characterization of paravertebral muscles. Furthermore, we will perform an integrated transcriptomics and proteomics analysis of peripheral blood samples. DISCUSSION: The innovative and multidisciplinary approaches of this project rely on the elucidation of myofascial physical properties in axSpA and also on the establishment of a biological signature that relates to specific muscle properties. This hitherto unstudied link between gene/protein signatures and muscle properties may enhance our understanding of axSpA physiopathology and reveal new and useful diagnostic and therapeutic targets.

Comprehensive Detection of Pseudogenes Transcribed by Readthrough.

Transcription termination is a critical stage for the production of legitimate mRNAs, and consequently functional proteins. However, the transcription machinery can ignore the stop signs and continue elongating beyond gene boundaries, invading downstream neighboring genes. Such phenomenon, designated transcription readthrough, can trigger the expression of pseudogenes usually silenced or lacking the proper regulatory signals. Due to the sequence similarity to parental genes, readthrough transcribed pseudogenes can regulate relevant protein-coding genes and impact biological functions. Here, we describe a computational pipeline that employs already existent bioinformatic tools to detect readthrough transcribed pseudogenes from expression profiles. We also unveil that combining strand-specific transcriptome data and epigenetic profiles can enhance and corroborate the results. By applying such approach to renal cancer biopsies, we show that pseudogenes can be readthrough transcribed as part of unspliced transcripts or processed RNA chimeras. Overall, our pipeline allows us to scrutinize transcriptome profiles to detect a diversity of readthrough events leading to expression of pseudogenes.