CRISPR/Cas patents and health-related publications in South America.

CRISPR/Cas is being increasingly used for various applications. However, different countries introduce new technologies at different paces and purposes. This study reviews research progress using the CRISPR/Cas system in South America, focusing on health-related applications. The PubMed database was used to identify relevant articles about gene editing with CRISPR/Cas, whereas patents were searched in the Patentscope database. In addition, ClinicalTrials.gov was used to find information on active and recruiting clinical trials. A total of 668 non-duplicated articles (extracted from PubMed) and 225 patents (not all health-related) were found. One hundred ninety-two articles on health-related applications of CRISPR/Cas were analyzed in detail. In 95 out of these, more than 50% of the authors were affiliated with South American institutions. Experimental CRISPR/Cas studies target different diseases, particularly cancer, neurological, and endocrine disorders. Most patents refer to generic applications, but those with clear disease indications are for inborn errors of metabolism, ophthalmological, hematological, and immunological disorders. No clinical trials were found involving Latin American countries. Although research on gene editing in South America is advancing, our data show the low number of national innovations protected by intellectual property in this field.

MatchTope: A tool to predict the cross reactivity of peptides complexed with Major Histocompatibility Complex I.

The therapeutic targeting of the immune system, for example in vaccinology and cancer treatment, is a challenging task and the subject of active research. Several in silico tools used for predicting immunogenicity are based on the analysis of peptide sequences binding to the Major Histocompatibility Complex (pMHC). However, few of these bioinformatics tools take into account the pMHC three-dimensional structure. Here, we describe a new bioinformatics tool, MatchTope, developed for predicting peptide similarity, which can trigger cross-reactivity events, by computing and analyzing the electrostatic potentials of pMHC complexes. We validated MatchTope by using previously published data from in vitro assays. We thereby demonstrate the strength of MatchTope for similarity prediction between targets derived from several pathogens as well as for indicating possible cross responses between self and tumor peptides. Our results suggest that MatchTope can enhance and speed up future studies in the fields of vaccinology and cancer immunotherapy.

Sales of "COVID kit" drugs and adverse drug reactions reported by the Brazilian Health Regulatory Agency / Vendas de "kit-COVID" e reações adversas a esses medicamentos relatadas pela Agência Nacional de Vigilância Sanitária / Ventas de medicamentos del "kit-COVID" y reacciones adversas a los medicamentos notificadas por la Agencia Nacional de Vigilancia Sanitaria

Off-label use of azithromycin, hydroxychloroquine, and ivermectin (the "COVID kit") has been suggested for COVID-19 treatment in Brazil without clinical or scientific evidence of efficacy. These drugs have known adverse drug reactions (ADR). This study aimed to analyze if the sales of drugs in the "COVID kit" are correlated to the reported number of ADR after the COVID-19 pandemic began. Data was obtained from the Brazilian Health Regulatory Agency (Anvisa) website on reported sales and ADRs for azithromycin, hydroxychloroquine, and ivermectin for all Brazilian states. The period from March 2019 to February 2020 (before the pandemic) was compared to that from March 2020 to February 2021 (during the pandemic). Trend adjustment was performed for time series data and cross-correlation analysis to investigate correlation between sales and ADR within the same month (lag 0) and in the following months (lag 1 and lag 2). Spearman's correlation coefficient was used to assess the magnitude of the correlations. After the pandemic onset, sales of all investigated drugs increased significantly (69.75% for azithromycin, 10,856,481.39% for hydroxychloroquine, and 12,291,129.32% for ivermectin). ADR levels of all medications but azithromycin were zero before the pandemic, but increased after its onset. Cross-correlation analysis was significant in lag 1 for all drugs nationwide. Spearman's correlation was moderate for azithromycin and hydroxychloroquine but absent for ivermectin. Data must be interpreted cautiously since no active search for ADR was performed. Our results show that the increased and indiscriminate use of "COVID kit" during the pandemic correlates to an increased occurrence of ADRs.

No Brasil, o uso off label de azitromicina, hidroxicloroquina e ivermectina (o "kit-COVID") foi sugerido para tratar COVID-19 sem que tivéssemos evidências clínicas ou científicas de sua eficácia. Estas drogas têm causado reações adversas (RA) em quem as tomam. Este estudo almejou analisar se a venda dos medicamentos que compõem o "kit-COVID" correlaciona-se com o número relatado de RAs após o início da pandemia da COVID-19. Os dados sobre vendas e RA associados a azitromicina, hidroxicloroquina e ivermectina foram obtidos no site da Agência Nacional de Vigilância Sanitária (Anvisa) para todos os estados brasileiros. Comparamos o período entre março de 2019 e fevereiro de 2020 (antes da pandemia) ao de março de 2020 a fevereiro de 2021 (durante a pandemia). Ajustamos tendências para os dados de séries temporais e as análises de correlação cruzada para investigar a correlação entre vendas e RA em um mesmo mês (lag 0) e nos seguintes (lag 1 e 2). O coeficiente de correlação de Spearman foi utilizado para avaliar a magnitude das correlações. Após o início da pandemia, as vendas de todos os medicamentos investigados aumentaram significativamente (69,75% para azitromicina, 10.856.481,39% para hidroxicloroquina e 12.291.129,32% para ivermectina). Os níveis de RAs de todos os medicamentos (com exceção de azitromicina) eram zero antes da pandemia mas aumentaram após seu início. A análise de correlação cruzada foi significativa no lag 1 para todas as drogas em todo o país. A correlação de Spearman foi moderada para azitromicina e hidroxicloroquina, mas ausente para ivermectina. Os dados devem ser interpretados com cautela, uma vez que não realizamos uma busca ativa por RA. Nossos resultados mostram que o uso aumentado e indiscriminado do "kit-COVID" durante a pandemia se correlaciona com uma ocorrência aumentada de RAs.

Se ha sugerido el uso fuera de lo establecido de azitromicina, hidroxicloroquina e ivermectina (el "kit-COVID") para el tratamiento de la COVID-19 en Brasil sin evidencia clínica o científica de su eficacia. Estos medicamentos tienen reacciones adversas (RAM) conocidas. Este estudio pretendía analizar si las ventas de medicamentos del "kit-COVID" están correlacionadas con el número de reacciones adversas notificadas tras el inicio de la pandemia de COVID-19. Los datos se obtuvieron del sitio web de la Agencia Nacional de Vigilancia Sanitaria (Anvisa) sobre las ventas y las RAM notificadas para la azitromicina, la hidroxicloroquina y la ivermectina para todos los estados brasileños. Se comparó el periodo de marzo de 2019 a febrero de 2020 (antes de la pandemia) con el de marzo de 2020 a febrero de 2021 (durante la pandemia). Se realizó un ajuste de tendencia para los datos de las series de tiempo y un análisis de correlación cruzada para investigar la correlación entre las ventas y la RAM dentro del mismo mes (lag 0) y en los meses siguientes (lag 1 y lag 2). Se utilizó el coeficiente de correlación de Spearman para evaluar la magnitud de las correlaciones. Tras el inicio de la pandemia, las ventas de todos los medicamentos investigados aumentaron significativamente (69,75% para la azitromicina, 10.856.481,39% para la hidroxicloroquina y 12.291.129,32% para la ivermectina). Los niveles de RAM de todos los medicamentos, excepto la azitromicina, eran nulos antes de la pandemia, pero aumentaron tras su inicio. El análisis de correlación cruzada fue significativo en el lag 1 para todos los medicamentos a nivel nacional. La correlación de Spearman fue moderada para la azitromicina y la hidroxicloroquina, pero no para la ivermectina. Los datos deben interpretarse con cautela, ya que no se realizó una búsqueda activa de RAM. Nuestros resultados muestran que el uso creciente e indiscriminado del "kit-COVID" durante la pandemia se correlaciona con una mayor aparición de las RAM.

High infiltration of B cells in tertiary lymphoid structures, TCR oligoclonality, and neoantigens are part of esophageal squamous cell carcinoma microenvironment.

Esophageal squamous cell carcinoma (ESCA) exhibits high intratumoral molecular heterogeneity posing a challenge to cancer therapy. Immune checkpoint blockade therapy has been approved for this disease, but with modest results. RNA-Seq data from paired tumor and surrounding nonmalignant tissue from 14 patients diagnosed with ESCA without previous treatment and from The Cancer Genome Atlas-ESCA cohort were analyzed. Herein, we investigated ESCA immune landscape including mutation-derived neoantigens and immune cell subpopulations. Tumor-associated antigen expression was determined by in silico analyses and confirmed by immunohistochemistry showing that PRAME, CEACAM4, and MAGEA11 proteins are expressed on tumors. Immune checkpoint molecules gene expression was higher in the tumor compared with surrounding nonmalignant tissue, but its expression varies greatly among patients. TCR repertoire and BCR transcripts analysis evidenced low clonal diversity with one TCR clone predicted to be specific for a MAGEA11-derived peptide. A high number of B-cell clones infiltrating the tumors and the abundance of these cells in tertiary lymphoid structures observed in ESCA tumors support B cells as a potential immune modulator in this tumor.

Machine Learning Supports Long Noncoding RNAs as Expression Markers for Endometrial Carcinoma.

Uterine corpus endometrial carcinoma (UCEC) is the second most common type of gynecological tumor. Several research studies have recently shown the potential of different ncRNAs as biomarkers for prognostics and diagnosis in different types of cancers, including UCEC. Thus, we hypothesized that long noncoding RNAs (lncRNAs) could serve as efficient factors to discriminate solid primary (TP) and normal adjacent (NT) tissues in UCEC with high accuracy. We performed an in silico differential expression analysis comparing TP and NT from a set of samples downloaded from the Cancer Genome Atlas (TCGA) database, targeting highly differentially expressed lncRNAs that could potentially serve as gene expression markers. All analyses were performed in R software. The receiver operator characteristics (ROC) analyses and both supervised and unsupervised machine learning indicated a set of 14 lncRNAs that may serve as biomarkers for UCEC. Functions and putative pathways were assessed through a coexpression network and target enrichment analysis.

Analysis of the Cancer Genome Atlas Data Reveals Novel Putative ncRNAs Targets in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the prevalent type of primary liver malignancy. Different noncoding RNAs (ncRNAs) that negatively regulate gene expression, such as the microRNAs and the long ncRNAs (lncRNAs), have been associated with cell invasiveness and cell dissemination, tumor recurrence, and metastasis in HCC. To evaluate which regulatory ncRNAs might be good candidates to disrupt HCC proliferation pathways, we performed both unsupervised and supervised analyses of HCC expression data, comparing samples of solid tumor tissue (TP) and adjacent tissue (NT) of a set of patients, focusing on ncRNAs and searching for common mechanisms that may shed light in future therapeutic options. All analyses were performed using the R software. Differential expression (total RNA and miRNA) and enrichment analyses (Gene Ontology + Pathways) were performed using the package TCGABiolinks. As a result, we improved the set of lncRNAs that could be the target of future studies in HCC, highlighting the potential of FAM170B-AS1 and TTN-AS1.

Interpreting T-Cell Cross-reactivity through Structure: Implications for TCR-Based Cancer Immunotherapy.

Immunotherapy has become one of the most promising avenues for cancer treatment, making use of the patient's own immune system to eliminate cancer cells. Clinical trials with T-cell-based immunotherapies have shown dramatic tumor regressions, being effective in multiple cancer types and for many different patients. Unfortunately, this progress was tempered by reports of serious (even fatal) side effects. Such therapies rely on the use of cytotoxic T-cell lymphocytes, an essential part of the adaptive immune system. Cytotoxic T-cells are regularly involved in surveillance and are capable of both eliminating diseased cells and generating protective immunological memory. The specificity of a given T-cell is determined through the structural interaction between the T-cell receptor (TCR) and a peptide-loaded major histocompatibility complex (MHC); i.e., an intracellular peptide-ligand displayed at the cell surface by an MHC molecule. However, a given TCR can recognize different peptide-MHC (pMHC) complexes, which can sometimes trigger an unwanted response that is referred to as T-cell cross-reactivity. This has become a major safety issue in TCR-based immunotherapies, following reports of melanoma-specific T-cells causing cytotoxic damage to healthy tissues (e.g., heart and nervous system). T-cell cross-reactivity has been extensively studied in the context of viral immunology and tissue transplantation. Growing evidence suggests that it is largely driven by structural similarities of seemingly unrelated pMHC complexes. Here, we review recent reports about the existence of pMHC "hot-spots" for cross-reactivity and propose the existence of a TCR interaction profile (i.e., a refinement of a more general TCR footprint in which some amino acid residues are more important than others in triggering T-cell cross-reactivity). We also make use of available structural data and pMHC models to interpret previously reported cross-reactivity patterns among virus-derived peptides. Our study provides further evidence that structural analyses of pMHC complexes can be used to assess the intrinsic likelihood of cross-reactivity among peptide-targets. Furthermore, we hypothesize that some apparent inconsistencies in reported cross-reactivities, such as a preferential directionality, might also be driven by particular structural features of the targeted pMHC complex. Finally, we explain why TCR-based immunotherapy provides a special context in which meaningful T-cell cross-reactivity predictions can be made.

DockTope: a Web-based tool for automated pMHC-I modelling.

The immune system is constantly challenged, being required to protect the organism against a wide variety of infectious pathogens and, at the same time, to avoid autoimmune disorders. One of the most important molecules involved in these events is the Major Histocompatibility Complex class I (MHC-I), responsible for binding and presenting small peptides from the intracellular environment to CD8(+) T cells. The study of peptide:MHC-I (pMHC-I) molecules at a structural level is crucial to understand the molecular mechanisms underlying immunologic responses. Unfortunately, there are few pMHC-I structures in the Protein Data Bank (PDB) (especially considering the total number of complexes that could be formed combining different peptides), and pMHC-I modelling tools are scarce. Here, we present DockTope, a free and reliable web-based tool for pMHC-I modelling, based on crystal structures from the PDB. DockTope is fully automated and allows any researcher to construct a pMHC-I complex in an efficient way. We have reproduced a dataset of 135 non-redundant pMHC-I structures from the PDB (Cα RMSD below 1 Å). Modelling of pMHC-I complexes is remarkably important, contributing to the knowledge of important events such as cross-reactivity, autoimmunity, cancer therapy, transplantation and rational vaccine design.