A genomic signature for accurate classification and prediction of clinical outcomes in cancer patients treated with immune checkpoint blockade immunotherapy
Abstract Tumor mutational burden (TMB) is associated with clinical response to immunotherapy, but application has been limited to a subset of cancer patients. We hypothesized that advanced machine-learning and proper modeling could identify mutations that classify patients most likely to derive clin...
Guardado en:
Autores principales: | Mei Lu, Kuan-Han Hank Wu, Sheri Trudeau, Margaret Jiang, Joe Zhao, Elliott Fan |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2020
|
Materias: | |
Acceso en línea: | https://doaj.org/article/e53d57ff3e1b4551bda14782b610fbfc |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
CANCER IMMUNOTHERAPY BASED ON THE BLOCKADE OF IMMUNE CHECKPOINTS
por: A. V. Bogolyubova, et al.
Publicado: (2015) -
Regulation of antitumour CD8 T-cell immunity and checkpoint blockade immunotherapy by Neuropilin-1
por: Marine Leclerc, et al.
Publicado: (2019) -
Photothermal therapy with immune-adjuvant nanoparticles together with checkpoint blockade for effective cancer immunotherapy
por: Qian Chen, et al.
Publicado: (2016) -
Structural basis of checkpoint blockade by monoclonal antibodies in cancer immunotherapy
por: Ju Yeon Lee, et al.
Publicado: (2016) -
Nanosonosensitizer-Augmented Sonodynamic Therapy Combined with Checkpoint Blockade for Cancer Immunotherapy
por: Lin X, et al.
Publicado: (2021)