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New computational test predicts ovarian cancer survival

Scientists have developed a new automated way of predicting the survival chances from ovarian cancer from routine biopsy samples, by looking at the cells in the environment around tumours.

The technique could be developed into a computer-assisted prediction tool for use in hospitals, allowing doctors to identify patients could benefit from different types of treatment.

Researchers from The Institute of Cancer Research, London, analysed digitised sections of biopsied tumour samples from 91 patients with late-stage ovarian cancer.

They aimed to understand how different cell types are distributed around tumours by developing new automated imaging software that can identify up to 100 different cell features and analyse millions of cells in a tumour within an hour.

Patients with a higher ratio of a particular cell type known as stromal cells in the area around ovarian tumours were found to be more likely to develop more severe disease – with a 15 per cent chance of surviving for five years following surgery.

Calculating the ratios of different cell types could allow doctors to prescribe therapies that target features specific to an individual’s tumour – for instance new treatments in development that block the interactions between cancer and stromal cells.

The researchers also found that a high ratio of immune cells around a tumour indicated better survival rates. Women with this kind of immune reaction could benefit from some of the new immunotherapies that remove the breaks from the immune system.

Patients with a low stromal cell ratio combined with a high immune cell ratio were found to have a 70 per cent chance of surviving 10 years, compared with only a 22 per cent 10-year survival chance for the rest of the patients in the study.

The study was published in the journal Scientific Reports and funded by the ICR, the Wellcome Trust and the NIHR Biomedical Research Centre at The Royal Marsden and the ICR.

Dr Yinyin Yuan, Team Leader in Computational Pathology and Integrative Genomics at the ICR, said: “Our study has shown that the microenvironment around ovarian tumours can have a significant impact on the severity of the disease. Finding a way to identify women who are most at risk, and to match patients to the best available treatment, could save lives.

 “Our new approach could be implemented into hospitals as low-cost markers relatively easily, complementing other methods for identifying patients with more or less aggressive cancers, so they can be treated accordingly.”

“There have already been successes in targeting the tumour micro-environment in ongoing clinical trials in a number of cancer types, including immunotherapies. Developing these strategies for ovarian cancer – and identifying women most likely to benefit from them – could transform the way patients are treated in future.”


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