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High-throughput RNAi screen for essential genes and drug synergistic combinations in colorectal cancer
- Source :
- Scientific Data
- Publication Year :
- 2017
-
Abstract
- Metastatic colorectal cancer is a leading cause of cancer death. However, current therapy options are limited to chemotherapy, with the addition of anti-EGFR antibodies for patients with RAS wild-type tumours. Novel drug targets, or drug combinations that induce a synergistic response, would be of great benefit to patients. The identification of genes that are essential for cell survival can be undertaken using functional genomics screens. Furthermore, performing such screens in the presence of a targeted agent would allow the identification of combinations that result in a synthetic lethal interaction. Here, we present a dataset containing the results of a large scale RNAi screen (815 genes) to detect essential genes as well as synergistic combinations with targeted therapeutic agents using a panel of 27 colorectal cancer cell lines. These data identify genes that are essential for colorectal cancer cell survival as well as synthetic lethal treatment combinations using novel computational approaches. Moreover, this dataset could be utilised in combination with genomic profiling to identify predictive biomarkers of response.
- Subjects :
- 0301 basic medicine
Drug
Statistics and Probability
Data Descriptor
Cell biology
Colorectal cancer
medicine.medical_treatment
media_common.quotation_subject
Computational biology
Biology
Library and Information Sciences
Bioinformatics
Education
03 medical and health sciences
RNA interference
Cell Line, Tumor
medicine
Biomarkers, Tumor
Humans
Gene
media_common
Cancer
Chemotherapy
Genes, Essential
Drug Synergism
medicine.disease
Corrigenda
3. Good health
Computer Science Applications
030104 developmental biology
biology.protein
RNA Interference
Antibody
Statistics, Probability and Uncertainty
Colorectal Neoplasms
Functional genomics
Information Systems
Subjects
Details
- ISSN :
- 20524463
- Volume :
- 4
- Database :
- OpenAIRE
- Journal :
- Scientific data
- Accession number :
- edsair.doi.dedup.....fa39be4f38f48ec87679579768982998