Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Connect with me

Sylvana Hassanieh

MSc, BSc

PhD student

PhD student-CRUK scholar- Clarendon scholar- focusing on clinical colorectal cancer and chemotherapy resistance


I did my bachelor in science at the American University of Beirut in medical laboratory diagnostics then my master degree in medicine and molecular genetics. I was a research student at MGH cancer center - Harvard Medical school where I worked on DNA repair and cancer ( Prof. Raul Mostoslavsky group). 

Research Focus

I work under the supervision of Prof. Tim Maughan on colorectal cancer (CRC) which is the third most common cancer in the world. The standard of care for stage III CRC is surgery followed by adjuvant chemotherapy/radiotherapy, while stage IV is combination chemotherapy with the possibility of antibody therpay. One of the most common approved chemotherapeutic regimens is the administration of 5-fluorouracil (5FU) combined with oxaliplatin as it improves outcome compared to single agent 5FU. However, not all patients benefit from oxaliplatin and some also show high toxicity events, usually neuropathy which may become chronic. 

My PhD project aims at creating a biomarker to predict which patients may be sensitive or resistant to oxaliplatin to aid treatment decision. To that end, I use multiomic data of 385 CRC patients from  the FOCUS clinical trial randomised to FU with or without oxaliplatin. Two different approaches have been taken to interrogate the data: (1) hypothesis driven analysis of candidates as potential biomarkers and (2) derivation of a predictive model from the transcriptome for further validation.

Key publications

More publications