RESUMEN
Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell malignancy worldwide. Molecular classifications have tried to improve cure rates. We prospectively examined and correlated the mutational landscape with the clinical features and outcomes of 185 Mexican patients (median age 59.3 years, 50% women) with newly diagnosed DLBCL. A customized panel of 79 genes was designed, based on previous international series. Most patients had ECOG performance status (PS) < 2 (69.2%), advanced-stage disease (72.4%), germinal-center phenotype (68.1%), and double-hit lymphomas (14.1%). One hundred and ten (59.5%) patients had at least one gene with driver mutations. The most common mutated genes were as follows: TP53, EZH2, CREBBP, NOTCH1, and KMT2D. The median follow-up was 42 months, and the 5-year relapse-free survival (RFS) and overall survival (OS) rates were 70% and 72%, respectively. In the multivariate analysis, both age > 50 years and ECOG PS > 2 were significantly associated with a worse OS. Our investigation did not reveal any discernible correlation between the presence of a specific mutation and survival. In conclusion, using a customized panel, we characterized the mutational landscape of a large cohort of Mexican DLBCL patients. These results need to be confirmed in further studies.
Asunto(s)
Proteína Potenciadora del Homólogo Zeste 2 , Linfoma de Células B Grandes Difuso , Mutación , Humanos , Linfoma de Células B Grandes Difuso/genética , Linfoma de Células B Grandes Difuso/mortalidad , Femenino , Persona de Mediana Edad , Masculino , México/epidemiología , Anciano , Adulto , Proteína Potenciadora del Homólogo Zeste 2/genética , Anciano de 80 o más Años , Estudios Prospectivos , Receptor Notch1/genética , Proteína de Unión a CREB/genética , Proteína p53 Supresora de Tumor/genética , Proteínas de Neoplasias/genética , Adulto Joven , Pronóstico , Adolescente , Proteínas de Unión al ADNRESUMEN
BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) is the most transmissible ß-coronavirus in history, affecting all population groups. Immunocompromised patients, particularly cancer patients, have been highlighted as a reservoir to promote accumulation of viral mutations throughout persistent infection. CASE PRESENTATION: We aimed to describe the clinical course and SARS-CoV-2 mutation profile for 102 days in an immunocompromised patient with non-Hodgkin's lymphoma and COVID-19. We used RT-qPCR to quantify SARS-CoV-2 viral load over time and whole-virus genome sequencing to identify viral lineage and mutation profile. The patient presented with a persistent infection through 102 days while being treated with cytotoxic chemotherapy for non-Hodgkin's lymphoma and received targeted therapy for COVID-19 with remdesivir and hyperimmune plasma. All sequenced samples belonged to the BA.1.1 lineage. We detected nine amino acid substitutions in five viral genes (Nucleocapsid, ORF1a, ORF1b, ORF13a, and ORF9b), grouped in two clusters: the first cluster with amino acid substitutions only detected on days 39 and 87 of sample collection, and the second cluster with amino acid substitutions only detected on day 95 of sample collection. The Spike gene remained unchanged in all samples. Viral load was dynamic but consistent with the disease flares. CONCLUSIONS: This report shows that the multiple mutations that occur in an immunocompromised patient with persistent COVID-19 could provide information regarding viral evolution and emergence of new SARS-CoV-2 variants.
Asunto(s)
COVID-19 , Linfoma no Hodgkin , Humanos , SARS-CoV-2/genética , COVID-19/diagnóstico , Esparcimiento de Virus , Infección Persistente , Linfoma no Hodgkin/complicaciones , Linfoma no Hodgkin/tratamiento farmacológico , Huésped InmunocomprometidoRESUMEN
Background: Iodide transport defect is an uncommon cause of dyshormonogenic congenital hypothyroidism due to homozygous or compound heterozygous pathogenic variants in the SLC5A5 gene, which encodes the sodium/iodide symporter (NIS), causing deficient iodide accumulation in thyroid follicular cells, thus impairing thyroid hormonogenesis. Methods:SLC5A5 gene variants were compiled from public databases and research articles exploring the molecular bases of congenital hypothyroidism. Using a dataset of 198 missense NIS variants classified as either benign or pathogenic, we developed and validated a machine learning-based NIS-specific variant classifier to predict the impact of missense NIS variants. Results: We generated a manually curated dataset containing 7793 unique SLC5A5 variants. As most databases compiled exome sequencing data, variant mapping revealed an increased density of variants in SLC5A5 coding exons. Based on allele frequency (AF) analysis, we established an AF threshold of 1:10,000 above which a variant should be considered benign. Most pathogenic NIS variants were located in the protein-coding region, as most patients were genetically diagnosed by using a candidate gene strategy limited to this region. Significantly, we evidenced that 94.5% of missense NIS variants were classified as of uncertain significance. Therefore, we developed an NIS-specific variant classifier to improve the prediction of pathogenicity of missense variants. Our classifier predicted the clinical outcome of missense variants with high accuracy (90%), outperforming state-of-the-art pathogenicity predictors, such as REVEL, PolyPhen-2, and SIFT. Based on the excellent performance of our classifier, we predicted the mutational landscape of NIS. The analysis of the mutational landscape revealed that most missense variants located in transmembrane segments are frequently pathogenic. Moreover, we predicted that â¼28% of all single-nucleotide variants that could cause missense NIS variants are pathogenic, thus putatively leading to congenital hypothyroidism if present in homozygous or compound heterozygous state. Conclusions: We reported the first NIS-specific variant classifier aiming at improving the interpretation of missense NIS variants in clinical practice. Deciphering the mutational landscape for every protein involved in thyroid hormonogenesis is a relevant task for a deep understanding of the molecular mechanisms causing dyshormonogenic congenital hypothyroidism.