Breast cancer is heterogeneous in genetic composition. To improve treatments for this disease, Scientists have developed a classification system called IntClust that classifies it into 10 different subtypes.

Cancer arises from genetic changes in somatic cells. As known through research and observation, breast cancer is not one single disease -the mutations in the genes that cause varied cancers are not similar, and this is why tumors respond differently to treatment and grow at different rates. Currently, there are 2 key markers that clinicians use to predict response to treatments.

Spotting advances in tumor genetics and creating a system to diagnose tumor types is a primary objective of cancer scientists. For this purpose, researchers have developed the IntClust system, which uses genomic technology to more accurately pinpoint which type of breast cancer a patient has, and therefore what treatment would be most appropriate.

To validate this system, researchers examined the 997 tumor samples and 7,544 samples from public databases, along with the genomic and clinical data(such as data from the Cancer Genome Atlas). They respectively utilized IntClust system and two main systems in use today- PAM50 (five subtypes) and SCMGENE(four subtypes).

The research, published in the journal Genome Biology, shows that IntClust was at least as good at predicting patients’ prognosis and response to treatment as the existing systems. With clinical significance, IntClust system identified a previously unnoticed subgroup of tumors in just 3.1% of women with very poor survival rates, which appeared to be resistant to treatment. Identifying the genomic signatures for this group could flag up these high risk cancers early, and having the genomic data for these could aid in the investigation of new avenues to treat this type of cancer.

Reference:

Genome-driven integrated classification of breast cancer validated in over 7,500 samples. Genome Biology, 2014; 15 (8)