New 'drug sensitivity encyclopaedias' will aid global cancer research

In collaboration with the Press Association

Two new studies have matched the genetic profiles of hundreds of different cancer 'cell lines' - lab grown cancer cells routinely used by researchers - to how they respond to different cancer drugs.

The studies appear in the latest edition of the journal Nature.

They reveal hundreds of associations between faults in cancer genes and sensitivity to anticancer drugs, and could help towards improved clinical trials and better targeted treatments.

In the first study, scientists from Novartis and the Broad Institute in the US catalogued the genetic and molecular profiles of almost 1,000 human cancer cell lines used in drug research and development.

For about half the cell lines they also matched this information with how the cells responded to a collection of 24 anticancer drugs, to identify genetic signatures that predict if a cancer is sensitive to a particular drug.

The team have also published their data in an online research tool called The Cancer Cell Line Encyclopaedia (CCLE).

Cancer cell lines are widely used in cancer research. They are derived from tumour tissue and grown indefinitely under controlled conditions in the laboratory.

The researchers say the CCLE will "catalyse discoveries throughout the cancer research community" and "guide clinical trials", by giving a much clearer idea of which tumours are most likely to respond to particular drugs before using them in clinical trials.

Professor Levi Garraway, from the Broad Institute, said: "Knowing that kind of information very early might help to improve the success rate of drug development, compared to a genetically 'agnostic' approach that includes any patient with advanced cancer without knowledge of a genetic profile."

In the second study, scientists from Massachusetts General Hospital in the US and the Wellcome Trust Sanger Institute in the UK screened over 600 cancer cell lines with 130 drugs.

Their data are also available online for other researchers to use, and will be updated every few months as they get more information about other cell lines and drugs.

One of the key discoveries from their initial data is that cells from a childhood bone cancer, Ewing's sarcoma, respond to a drug that is currently used in the treatment of breast and ovarian cancers. The lowered toxicity of this treatment may mean it is a safer alternative therapy for children and young adults with this aggressive cancer.

"Advances in next-generation sequencing technologies are already being translated into the large-scale detection of cancer gene mutations in the clinic," said Dr Ultan McDermott, senior author from the Sanger Institute, who is also funded by Cancer Research UK.

"There is a compelling need to identify, in a systematic fashion, whether observed mutations affect the likelihood of a patient's response to a given drug treatment. We have therefore developed a unique online open-access resource for the research and medical community that can be used to optimise the clinical application of cancer drugs as well as the design of clinical trials of investigational compounds being developed as treatments."

Professor Charles Swanton, a Cancer Research UK expert, said the databases will be an "invaluable resource" and will provide "extremely useful intelligence to cancer researchers and those working in cancer drug development".

He added: "They're the product of a huge amount of work, and will be extremely useful in helping researchers firm up their ideas before testing drugs in the clinic. For example, part of my team's work involves trying to find ways to target cancers that contain certain genetic abnormalities. Data from these papers could help us identify new routes to achieve this, by looking for cell lines with these abnormalities and their drug sensitivities.

"This new resource will help speed up cancer research and may well begin to guide further developments in stratified cancer medicine".

Copyright Press Association 2012

References

  • Barretina, J. et al. (2012). The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity Nature, 483 (7391), 603-307 DOI: 10.1038/nature11003
  • Garnett, M. et al. (2012). Systematic identification of genomic markers of drug sensitivity in cancer cells Nature, 483 (7391), 570-575 DOI: 10.1038/nature11005