Identification of molecular prognostic and therapy resistance signatures in paediatric sarcomas

Research area

 |  sarcomas

Keywords

 |  childhood and adolescent sarcomas, Ewing sarcoma, next generation sequencing, bioinformatics

Suitability

 |  PhD/Doctorate, Honours

Contact supervisors at any time

Associate Professor Jason Cain
e: jason.cain@hudson.org.au

Dr Leanne Super

Project description

Sarcomas are a rare type of cancer that originate in the connective tissue of the body, including fat, muscle, bone, and cartilage. Sarcoma’s can develop anywhere in the body and are among the most common types of solid tumours in children. Most predominant in the paediatric and adolescent populations are sarcomas arising in the bone (osteosarcoma, Ewing’s sarcoma) and muscle (rhabdomyosarcoma). Incorporation of neoadjuvant chemotherapy has increased 5-year survival rates from 10% to ~70% for patients with localised disease. However, ~20% of patients present with metastases at diagnosis and a further 25%-50% will develop metastatic disease during their treatment. Despite aggressive multimodal treatments including polychemotherapy and surgery, cure rates for patients with metastatic or relapsed disease are poor, with a 5-year survival rate of <20% and represent a significant clinical challenge. Moreover, current standard-of-care treatments often result in lifelong morbidity. To date there is no reliable way to predict which patients will respond to therapy, and which are at high risk of disease recurrence, highlighting the urgent need for patient risk stratification.

We will utilized a defined clinical patient cohort of sarcoma patients treated at Victorian paediatric institutions since 1996. Samples will be acquired for multiomic analysis and data correlated to clinical responses and outcomes.

Collectively, the harmonisation of miltiomic data from a defined cohort of childhood sarcoma patients will provide important information on the mechanisms of tumour progression and therapy resistance as well as identify prognostic biomarkers and biomarkers of predictive response to therapy. This would pave the way for stratification of patients and potential personalised clinical management to improve outcomes and limit long term effects.

Please email me directly with enquiries: jason.cain@hudson.org.au