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Functional cancer genomics

Published on October 29, 2015   44 min

A selection of talks on Biochemistry

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0:00
Hello. I am Roderick Beijersbergen from the Netherlands Cancer Institute in Amsterdam. And I will be talking to you today about functional cancer genomics.
0:10
In the past decade, rapid progress in the ability to analyze full genomes of cancers has pointed out that individual tumors may contain hundreds and thousand of mutations across the entire genome. Some tumors, such as colorectal cancer, lung cancer and melanoma, have frequently even up to a 100,000 mutations. Although the majority of these mutations will not directly affect the coding region of genes, and thus, not lead to abnormal proteins, estimates are that 10 to 100 mutations expressed in coding regions will result in the expression of mutant proteins with aberrant functions. These abnormal proteins and the biological pathways and mechanisms they control play important roles in the development of cancer and response to cancer therapies. It's an enormous challenge for oncology research to map and understand the role of each of these genetic alterations for the diagnosis, prognosis and treatment of cancer. In addition to the large numbers of mutations found in different tumor types, it has also become clear that within one tumor type, for example lung cancer, different mutational spectra can be found in individual patients.
1:19
This slide shows significantly mutated genes in 178 tumors of one type, in this example, squamous cell lung cancer. Although the frequency of the mutations of the tumor suppressor gene TP53 is high, with more than 80 percent mutation frequency, for other genes, even though they are significantly mutated, this mutation rate is much lower. This indicates that among different tumors, different mutations exist, even within one tumor type. This heterogeneity among different tumors, even from the same tumor type, complicates the interpretation and use of this genetic information for the treatment of cancer. However, more in-depth analysis of all the pathways involved, for example, in cell proliferation, growth, and survival, which can be due to different mutations within the same phenotypic outcome can highlight all the pathways and provide potential therapeutic targets for this type of cancer.

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