Machine learning and bioinformatic analyses link the cell surface receptor transcript levels to the drug response of breast cancer cells and drug off-target effects.
Breast cancer responds variably to anticancer therapies, often leading to significant off-target effects. This study proposes that the variability in tumour responses and drug-induced adverse events is linked to the transcriptional profiles of cell surface receptors (CSRs) in breast tumours and norm...
| Main Authors: | Musalula Sinkala, Krupa Naran, Dharanidharan Ramamurthy, Neelakshi Mungra, Kevin Dzobo, Darren Martin, Stefan Barth |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2024-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0296511&type=printable |
Similar Items
-
Mutational landscape of cancer-driver genes across human cancers
by: Musalula Sinkala
Published: (2023-08-01) -
Integrated molecular characterisation of the MAPK pathways in human cancers reveals pharmacologically vulnerable mutations and gene dependencies
by: Musalula Sinkala, et al.
Published: (2021-01-01) -
Bioinformatics and Genomic Analyses of the Suitability of Eight Riboswitches for Antibacterial Drug Targets
by: Nikolet Pavlova, et al.
Published: (2022-08-01) -
Identification of Molecular Signatures and Candidate Drugs in Vascular Dementia by Bioinformatics Analyses
by: Jun Shu, et al.
Published: (2022-02-01) -
Role of immune cell infiltration and small molecule drugs in adhesive capsulitis: Novel exploration based on bioinformatics analyses
by: Hailong Liu, et al.
Published: (2023-02-01)