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3-D Cultures Grown from Patients' Tumors may Help Personalize Drug Screening

by Vishnuprasad on May 12 2015 11:29 PM

3-D Cultures Grown from Patients
Three-dimensional cultures derived from the tumors of cancer patients closely replicate properties of the original tumors, reveals a new study.
According to the scientists at Wellcome Trust Sanger Institute, UK, these ‘organoids’ are amenable to large-scale drug screens for the detection of genetic changes associated with drug sensitivity.

The drug screening can pave the way for personalized treatment approaches that could optimize clinical outcomes in cancer patients. "This is the first time that a collection of cancer organoids, or a living biobank, has been derived from patient tumors. We believe that these organoids are an important new tool in the arsenal of cancer biologists and may ultimately improve our ability to develop more effective cancer treatments," says Mathew Garnett, a geneticist at the Institute.

In the new study, the scientists grew 22 organoids from 20 patients with colorectal cancer and then sequenced genomic DNA isolated from these cultures.

The genetic mutations in the cultures closely matched those in the corresponding tumor biopsies and agreed well with previous large-scale analyses of colorectal cancer mutations. These findings confirm that the cultures faithfully capture the genomic features of the tumors from which they are derived as well as much of the genomic diversity associated with colorectal cancer.

The scientist screened the responses of the organoids to 83 cancer drugs. Given their diverse genetic profiles, the organoids displayed a range of sensitivities to the drugs.

The researchers identified previously reported associations between specific mutations and resistance to particular drugs. The organoids also showed a novel gene-drug association, indicating that the subset of cancer patients with RNF43 mutations would strongly benefit from a drug that inhibits a protein called porcupine.

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"At some point in the future, this approach may be suitable for modeling individual patient response to cancer therapies to inform clinical treatment," Garnett says. The study was published in the Cell.

Source-Medindia


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