Meningiomas are the most common brain tumor. Although they are typically cured by surgery, up to 20% recur. Moreover, surgery is often difficult to perform depending on where in the skull the meningioma arises. Therefore, we need additional treatment options. Unfortunately, we do not have good medications to treat these tumors. Like other cancers, meningiomas arise as a result of successive mutations in their DNA. As a cell divides, it must make copies of its DNA for its daughter cells. Mutations represent mistakes in this copying process. If these mutations disrupt the internal controls of a meningioma precursor cell, leading it to grow in an uncontrolled and inexorable manner, it will develop into a meningioma.

One way to develop effective treatments for meningioma is to identify the mutations that led to those cancers and figure out their implications. This method has worked for certain types of leukemia, lung cancer, melanoma, and other cancer types, in part by accomplishing two goals. First, by determining how these mutations disrupt the internal controls of meningioma cells, we can fashion new treatments that reverse the mutations’ disruptive effects. Second, by understanding which mutations an individual meningioma has, we may be able to predict how it will behave. For instance, we may be able to identify those 20% of patients whose meningiomas are likely to recur, and give them additional treatment up front to minimize this likelihood.

The mutations that lead to meningioma can occur anywhere in the genome. In principle, the only way to detect  these mutations is to reconstruct the entire genome of a meningioma and compare it to the normal genome of the same patient. Until recently, this has been prohibitively expensive—indeed, The Human Genome Project cost $3 billion and reconstructed only a single human genome. Moreover, to identify the important mutations in meningioma, we must reconstruct many meningiomas and normal genomes and identify the mutations that recur most often. Fortunately, recent technical advances have led to plummeting sequencing costs, making it possible to reconstruct entire cancer and normal genomes at reasonable cost. We have been involved in national and international efforts to reconstruct the genomes of several cancer types. We have also developed the analytic methods to detect the differences between cancer genomes and normal genomes and determine which of these differences are important.

In this project, we will perform similar analyses in meningioma, to comprehensively assess the genomes of four meningiomas and their normal counterparts, and identify all the mutations that led to these meningiomas. We anticipate that this knowledge will lead to a fundamental understanding of how meningiomas arise and will enable the development of targeted treatments that reverse the effects of the mutations that lead to meningioma.