Bioinformatics scientist joins battle to treat brain cancer pplied mathematics may not initially appear a likely source of solutions for cancer treatments. But as boundaries of traditional academic disciplines shi in the era of big data and rapid technological advances, novel research horizons are opening up, o ering exciting new avenues to mix and match previously separate elds and uncover fresh insights and potential therapeutic pathways. Computational biologist Prof. WANG Jiguang (Chemical & Biological Engineering and Division of Life Science) is among the dynamic young minds adding an extra dimension to medical research through bioinformatics and mathematics, while also delivering hope to patients su ering from one of the deadliest types of brain cancer: glioblastoma. Prof. Wang and his interdisciplinary Wang Genomics Lab are exploring how to assist the design of treatments through cancer genomics, helped by their breakthrough in identifying the mutation mechanism leading from lower grade glioma to secondary glioblastoma (sGBM) through a specially designed computational model. Glioblastoma, the rare brain cancer that Prof. Wang is tackling, has seen few successful treatments in the past years. The disease, a ecting three to four people among , per year, is invariably fatal as even a er treatment most malign tumors mutate and return again, with patients A Young Faculty 14 IN FOCUS Prof. Wang’s discovery indicated METex14 mutations at the MET oncogene as a major factor behind aggressive progression from lower grade glioma (LGG) to secondary glioblastoma (sGBM). Leading early career computational biologist Prof.Wang Jiguang and his genomics research laboratory are helping to set the pace in understanding an especially aggressive and hard-to-beat disease on average only surviving for to months from diagnosis. Prof. Wang’s discovery indicated METex mutations at the MET oncogene as a major factor behind aggressive progression from lower grade glioma to sGBM. The nding, published in leading journal Cell in , was the result of a collaboration with Beijing Tiantan Hospital scientists. It led on to the identi cation of a drug molecule (PLB- ) as a possible treatment by the Beijing team and a clinical trial that saw tumor shrinkage in two of late-stage cancer patients, furthering knowledge of how to treat sGBM. “Developing computational models on cancer evolution helps predict cancer cells’ future behavior and prioritize treatment options, while precision cancer medicine promises to tailor treatments according to personal cancer mutations,” Prof. Wang noted at the time. In a more recent advance, with ndings published in Nature Communications in , an international team co-led by HKUST, Beijing Neurosurgical Institute, and the Spanish National Cancer Research Center used computational analyses carried out by the Wang Genomics Lab to discover a mechanism to explain why a subgroup of glioma patients develops chemo-resistance to the current treatment for glioma. Such treatment usually comprises a combination of surgery, radiotherapy, and the chemotherapy agent temozolomide (TMZ). The discovery can potentially allow early identi cation of drug-resistant brain cancer patients, with Prof. Wang subsequently collaborating with the Chinese University of Hong Kong and Prince of Wales Hospital to expand samples to local patients. Prof. Wang’s drive to contribute to this area has been spurred on by his visits to hospitals, where he has seen the human cost – to people of all ages, including young children
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