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1.
Nat Med ; 27(7): 1280-1289, 2021 07.
Artículo en Inglés | MEDLINE | ID: mdl-34017137

RESUMEN

Patients with cancer have high mortality from coronavirus disease 2019 (COVID-19), and the immune parameters that dictate clinical outcomes remain unknown. In a cohort of 100 patients with cancer who were hospitalized for COVID-19, patients with hematologic cancer had higher mortality relative to patients with solid cancer. In two additional cohorts, flow cytometric and serologic analyses demonstrated that patients with solid cancer and patients without cancer had a similar immune phenotype during acute COVID-19, whereas patients with hematologic cancer had impairment of B cells and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific antibody responses. Despite the impaired humoral immunity and high mortality in patients with hematologic cancer who also have COVID-19, those with a greater number of CD8 T cells had improved survival, including those treated with anti-CD20 therapy. Furthermore, 77% of patients with hematologic cancer had detectable SARS-CoV-2-specific T cell responses. Thus, CD8 T cells might influence recovery from COVID-19 when humoral immunity is deficient. These observations suggest that CD8 T cell responses to vaccination might provide protection in patients with hematologic cancer even in the setting of limited humoral responses.


Asunto(s)
Linfocitos T CD8-positivos/inmunología , COVID-19/inmunología , Neoplasias Hematológicas/inmunología , Neoplasias/inmunología , Anciano , Anticuerpos Antivirales/inmunología , Linfocitos B/inmunología , COVID-19/complicaciones , COVID-19/mortalidad , Estudios de Cohortes , Femenino , Neoplasias Hematológicas/complicaciones , Humanos , Inmunidad Celular/inmunología , Inmunidad Humoral/inmunología , Inmunofenotipificación , Modelos Logísticos , Masculino , Persona de Mediana Edad , Análisis Multivariante , Neoplasias/complicaciones , Modelos de Riesgos Proporcionales , Estudios Prospectivos , SARS-CoV-2 , Tasa de Supervivencia
2.
Res Sq ; 2021 Feb 02.
Artículo en Inglés | MEDLINE | ID: mdl-33564756

RESUMEN

Cancer patients have increased morbidity and mortality from Coronavirus Disease 2019 (COVID-19), but the underlying immune mechanisms are unknown. In a cohort of 100 cancer patients hospitalized for COVID-19 at the University of Pennsylvania Health System, we found that patients with hematologic cancers had a significantly higher mortality relative to patients with solid cancers after accounting for confounders including ECOG performance status and active cancer status. We performed flow cytometric and serologic analyses of 106 cancer patients and 113 non-cancer controls from two additional cohorts at Penn and Memorial Sloan Kettering Cancer Center. Patients with solid cancers exhibited an immune phenotype similar to non-cancer patients during acute COVID-19 whereas patients with hematologic cancers had significant impairment of B cells and SARS-CoV-2-specific antibody responses. High dimensional analysis of flow cytometric data revealed 5 distinct immune phenotypes. An immune phenotype characterized by CD8 T cell depletion was associated with a high viral load and the highest mortality of 71%, among all cancer patients. In contrast, despite impaired B cell responses, patients with hematologic cancers and preserved CD8 T cells had a lower viral load and mortality. These data highlight the importance of CD8 T cells in acute COVID-19, particularly in the setting of impaired humoral immunity. Further, depletion of B cells with anti-CD20 therapy resulted in almost complete abrogation of SARS-CoV-2-specific IgG and IgM antibodies, but was not associated with increased mortality compared to other hematologic cancers, when adequate CD8 T cells were present. Finally, higher CD8 T cell counts were associated with improved overall survival in patients with hematologic cancers. Thus, CD8 T cells likely compensate for deficient humoral immunity and influence clinical recovery of COVID-19. These observations have important implications for cancer and COVID-19-directed treatments, immunosuppressive therapies, and for understanding the role of B and T cells in acute COVID-19.

3.
J Mol Diagn ; 19(5): 682-696, 2017 09.
Artículo en Inglés | MEDLINE | ID: mdl-28802831

RESUMEN

Kinase gene fusions are important drivers of oncogenic transformation and can be inhibited with targeted therapies. Clinical grade diagnostics using RNA sequencing to detect gene rearrangements in solid tumors are limited, and the few that are available require prior knowledge of fusion break points. To address this, we have analytically validated a targeted RNA sequencing assay (OSU-SpARKFuse) for fusion detection that interrogates complete transcripts from 93 kinase and transcription factor genes. From a total of 74 positive and 36 negative control samples, OSU-SpARKFuse had 93.3% sensitivity and 100% specificity for fusion detection. Assessment of repeatability and reproducibility revealed 96.3% and 94.4% concordance between intrarun and interrun technical replicates, respectively. Application of this assay on prospective patient samples uncovered OLFM4 as a novel RET fusion partner in a small-bowel cancer and led to the discovery of a KLK2-FGFR2 fusion in a patient with prostate cancer who subsequently underwent treatment with a pan-fibroblast growth factor receptor inhibitor. Beyond fusion detection, OSU-SpARKFuse has built-in capabilities for discovery research, including gene expression analysis, detection of single-nucleotide variants, and identification of alternative splicing events.


Asunto(s)
Biomarcadores de Tumor , Neoplasias/diagnóstico , Neoplasias/genética , Proteínas de Fusión Oncogénica/genética , Proteínas Quinasas/genética , Análisis de Secuencia de ARN/métodos , Análisis de Secuencia de ARN/normas , Empalme Alternativo , Línea Celular Tumoral , Perfilación de la Expresión Génica , Humanos , Hibridación Fluorescente in Situ , Polimorfismo de Nucleótido Simple , Proteínas Proto-Oncogénicas c-ret/genética , Control de Calidad , Receptor Tipo 2 de Factor de Crecimiento de Fibroblastos/genética , Reproducibilidad de los Resultados , Reacción en Cadena de la Polimerasa de Transcriptasa Inversa , Sensibilidad y Especificidad , Análisis de Secuencia de ADN , Flujo de Trabajo
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