Data from the Paris-based MOSCATO-01 study, presented at the Molecular Analysis for Personalised Therapy (MAP) conference, show that patients with advanced cancer who had their treatment tailored to their genetic makeup had around 30 percent longer before their cancer started growing again compared to the progression-free survival observed with previous treatments.
Patients taking part in the trial had a wide range of solid tumours (lung, breast, head and neck, genito-urinary, gastro-intestinal, and a variety of rare cancers), and all had already tried at least three cancer therapies. The researchers identified 411 patients with an actionable target, and 199 were treated with an ad hoc targeted therapy.
“The primary objective of the MOSCATO trial was to demonstrate that incorporating high-throughput gene sequencing and using it to make therapeutic decisions could improve the clinical outcome for at least 25 percent of advanced/metastatic cancer patients. Final results showed that 33 percent of patients had an improved survival,” said Professor Jean Charles Soria, principal investigator of the trial from the Gustave Roussy Cancer Campus.
“This is the first demonstration that comprehensive genomic analysis could improve the clinical outcome for cancer patients,” he noted.
“This positive result is particularly remarkable because the MOSCATO trial specifically excluded patients with well-established actionable targets for which approved and marketed targeted drugs are available (i.e. lung cancer with EGFR mutation, or ALK translocation, B-RAF mutant melanoma, GIST with KIT mutations or breast cancer with HER2 amplification),” added Professor Fabrice André, Head of the INSERM U981 research laboratory, and co-designer of the trial.
The MAP conference is a joint initiative between Cancer Research UK, UNICANCER and ESM.
“This is an exciting time for precision medicine and personalised treatment,” said Dr Rowena Sharpe, head of precision medicine at Cancer Research UK. “It’s fantastic to see continued effort going into this area and it’s important that we make the most of the data that we already have.”
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