The challenge
Osteosarcoma is a type of bone cancer that commonly occurs in teenagers and people over 60 years old. It often starts with vague symptoms, like pain in an arm or leg, which can lead to a delay in diagnosis, sometimes taking over three months.
This delay can make the cancer harder to treat and may be one reason why survival rates haven’t improved much since the 1980s.
How will this project tackle this challenge?
The team aim to develop new tests to detect osteosarcoma-related substances in a blood sample that could help to identify osteosarcoma earlier. Blood tests for other cancer types detect cancer DNA in the blood, however as osteosarcoma often has very complex genetic characteristics, this approach is unlikely to work well. Instead, the team are focusing on detecting osteosarcoma specific markers including RNA, proteins or cells which could be more reliable.
The research will use both tissue and blood samples from osteosarcoma patients. By analysing these samples, they’ll look for specific markers (proteins, RNA and cells) that indicate the presence of osteosarcoma. This ‘discovery’ dataset of markers will then be made freely available to the international osteosarcoma community to explore and continually build on.
The team will then use a mix of computer algorithms (artificial intelligence) and cost analysis to refine the initial ‘discovery’ dataset until it becomes a reliable and affordable diagnostic tool. This tool will then undergo further testing to confirm its accuracy.
What this means for people affected by sarcoma
Ultimately, the goal is to create a reliable and translatable blood test for osteosarcoma that can facilitate an earlier diagnosis. This will mean patients can begin treatment as soon as possible. It will also lay the groundwork for similar tests for other types of sarcoma, benefiting many patients in the future.