Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine

In this study, we investigated drug profile of 24 anticancer drugs tested against a large number of cell lines in order to understand the relation between drug resistance and altered genomic features of a cancer cell line. We detected frequent mutations, high expression and high copy number variatio...

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Bibliographic Details
Published in:Scientific reports 2016-03, Vol.6 (1), p.23857-23857, Article 23857
Main Authors: Gupta, Sudheer, Chaudhary, Kumardeep, Kumar, Rahul, Gautam, Ankur, Nanda, Jagpreet Singh, Dhanda, Sandeep Kumar, Brahmachari, Samir Kumar, Raghava, Gajendra P. S.
Format: Article
Language:English
Subjects:
38
45/91
631/114/1305
631/114/2398
631/67/69
Antineoplastic Agents - pharmacology
Antineoplastic drugs
Antitumor agents
Cancer
Cell Line, Tumor
Copy number
DNA Copy Number Variations
Drug resistance
Drug Resistance, Neoplasm - genetics
Gene Expression Regulation, Neoplastic
Genomics
Humanities and Social Sciences
Humans
Hydroxamic Acids - pharmacology
Indoles - pharmacology
Models, Genetic
multidisciplinary
Neoplasm Proteins - genetics
Organ Specificity
Precision Medicine
Science
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Summary:In this study, we investigated drug profile of 24 anticancer drugs tested against a large number of cell lines in order to understand the relation between drug resistance and altered genomic features of a cancer cell line. We detected frequent mutations, high expression and high copy number variations of certain genes in both drug resistant cell lines and sensitive cell lines. It was observed that a few drugs, like Panobinostat, are effective against almost all types of cell lines, whereas certain drugs are effective against only a limited type of cell lines. Tissue-specific preference of drugs was also seen where a drug is more effective against cell lines belonging to a specific tissue. Genomic features based models have been developed for each anticancer drug and achieved average correlation between predicted and actual growth inhibition of cell lines in the range of 0.43 to 0.78. We hope, our study will throw light in the field of personalized medicine, particularly in designing patient-specific anticancer drugs. In order to serve the scientific community, a webserver, CancerDP, has been developed for predicting priority/potency of an anticancer drug against a cancer cell line using its genomic features ( http://crdd.osdd.net/raghava/cancerdp/ ).
ISSN:2045-2322
2045-2322
DOI:10.1038/srep23857