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Potential for a More Personalized Approach to Womb Cancer

By Drug Discovery Trends Editor | May 8, 2015

Manchester doctors have helped show that high-risk womb cancer patients can be genetically profiled to allow them to receive more appropriate treatment.

Traditionally, patients with endometrial cancer – cancer of the womb lining – have their disease risk classified using a combination of clinical and tissue characteristics, including their age and the growth and invasion of their tumor.

Around 15-20 percent of patients have high-risk disease, but it is unclear what the best treatment approach is for these patients. Now Manchester researchers have investigated genetic alterations in high-risk endometrial cancer, to see if they could be used to create tumor subtypes.

Richard Edmondson, Professor of Gynaecological Oncology at The University of Manchester and Saint Mary’s Hospital, said: “Previous work, using comprehensive genetic profiling, has suggested that endometrial cancer can be classified into four subtypes. Our study has explored whether it is possible to use a simpler approach to detect subgroups in high risk patients.”

Using routinely available technology, the international TransPORTEC research consortium analysed samples from 116 patients with endometrial cancer to look for genetic variations.

The team, which also included Dr Emma Crosbie and Professor Henry Kitchener from Manchester, found that genetic subtypes existed in their group of patients, and that they could use their classification to predict which patients were more likely to relapse.

In addition, the analysis allowed them to identify distinctive genetic mutations that can be targeted with specific anti-cancer drugs.

“It looks like these cancers classed as ‘high-risk’ in fact vary significantly in outcome. Our results could be used to refine risk assessment for endometrial cancer patients and allow doctors to choose either a less aggressive approach or more targeted treatment for individual patients,” added Professor Edmondson.

Source: Manchester University


Filed Under: Genomics/Proteomics

 

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