Cancer is a complex, heterogeneous disease defined by abnormal regulation at multiple levels. What makes every cancer unique and complex is the different combinations of genes that mutate, as well as the additional deviant regulation at the RNA, epigenome and protein levels.
Gene mutations at DNA level are a well-studied causative factor in cancer. When the sequence of DNA is deleted, duplicated, or even replaced, it can result in dysfunctional proteins.
Though gene mutations form the core of cancer research, they are not seen as frequently in cancers. Dr. Vogelstein in his 2011 study, defined cancer as driven by a handful of commonly mutated gene “mountains,” but dominated by a much larger number of less frequently mutated gene “hills.”
Personalized Medicine: A Huge Step Toward Understanding Cancer
In this era of personalized medicine, it is possible for one to obtain a snapshot of all the genes that are mutated in each cancer patient and compare that to the patient’s normal germ-line, or sequence of cells that contain genetic material that can be passed to a child, in order to identify mutations that are enriched only in tumors.
If you were to examine the cancer genomes of several patients suffering from the same type of cancer, you would find it surprisingly hard to find a common pattern of mutated genes. Dr. Trey Ideker’s group at UCSD in their latest study devised a very elegant way to classify cancer patients.
Each patient displays a diverse set of mutated genes, but when all the mutated genes from the different patients were overlaid onto biological pathways, one could see specific pathways, presumably affected in those tumors lighting up. By doing so, one can produce various subtypes of patients exhibiting mutations in specific biological pathways.
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