A team based at the University of Cape Town has discovered that each of six cancer types (breast, colon, lung, kidney, ovarian and brain) has a unique genetic expression pattern, which can be used for accurate early diagnosis and targeted treatment.
Professor Kevin Naidoo, the SA research chair in scientific computing in the Department of Chemistry at UCT, and Dr Jahanshah Ashkani, also of the UCT chemistry department, made the discovery. Using statistical classification algorithms on massive tumour gene expression data, the UCT researchers found that the gene expression pattern of a patient can be used to accurately classify cancer types. This then lays the ground for developing an early diagnosis. The expression patterns may further be used to identify variations within each of the cancer types, which can then guide specialised patient treatment.
The discovery of a cancer-type carbohydrate-related gene signature led the team to a genomic classification of cancer types. Their work, published in the current issue of Scientific Reports, describes the statistical analysis of 1 893 patients' tumour gene expression data from The Cancer Genome Atlas. This analysis was made possible through the use of computational big data analytics – the examination of large data sets containing a variety of data types – to reveal, in this case, the hidden expression patterns of each cancer type.
The team identified genes that regulate the glycosyltransferase (GT) enzymes which are responsible for modifying the structures of complex carbohydrates that coat the surfaces of tumour cells. By extracting and analysing only 210 GT gene expression profiles from each of the 1 893 full tumour genome sets (each displaying the expressions of more than 20 000 genes), the team found patterns in the data that led to their discovery of a gene expression classification of cancer types.
An early cancer diagnostic is critical for patient survival, as most cancers can be cured if discovered in their early stages. The ability to identify distinct subtypes of cancer opens the door to further research, which will guide the choice of specialised treatment to significantly enhance a patient's chances of survival. This complements the shift towards personalised medicine approaches that deliver specialised oncotherapy to patients following diagnosis.
Professor Naidoo is now leading a multi-laboratory collaboration that includes scientists in the divisions of pathology and human genetics at UCT's medical campus and the Centre for Proteomics and Genomic Research. Their work entails the analysis of blood samples of South African patients. They hope to develop a low-cost gene expression tool for breast cancer, which will form the basis of a routinely used early diagnostic.
This discovery demonstrates the importance of computational big data analytics in biomedical sciences and the developing field of precision medicine.
Photo Professor Kevin Naidoo.
Read more on www.nature.com:
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
Please view the republishing articles page for more information.