March 01, 2012
Text: Nils Ehrenberg
Although the human body consists of a scarcely conceivable 10 to 100 billion cells, it only takes a few diseased cells to cause cancer. Minor damage in the DNA as a result of exposure to UV light or tobacco smoke can switch off a cell’s natural growth limits: the cell then starts to divide uncontrollably and, in the worst-case scenario, overgrow healthy tissue in the form of tumours, which eventually destroy vital organs.
It was long believed that only changes in the DNA itself play a crucial role in the emergence of cancer. However, it is now clear that the biochemical “coat” of the DNA strand also has an important role to play, as a cell’s genetic material is modified by a large number of chemical attachments. DNA methylation, in particular, plays a central role in gene regulation: small hydrocarbon attachments thus decide whether a gene is “active” or “silenced”, namely whether it can be read off or not.
Defects in DNA methylation result in altered gene activity in the cell which can contribute to tumour formation. In addition, the methylation patterns of tumour cells differ clearly from those of healthy tissue cells. “This is the precise point where our research begins,” says Thomas Lengauer from the Max Planck Institute for Informatics in Saarbrücken, who, together with Christoph Bock, leads the Computational Epigenetics Research Group in Professor Lengauer’s Department of Computational Biology and Applied Algorithmics.
The scientists rummage through vast collections of genetic data for suspicious methylation patterns using software programs they develop themselves. “Many of these patterns only arise in very specific types of cancer, so we can use them in clinical diagnosis as biomarkers, that is to say as indicators for the corresponding form of the disease,” says Thomas Lengauer. The scientists rely on close cooperation with hospitals and biotechnology laboratories for their work. The tissue samples from cancer patients are processed in the laboratory and the genetic material they contain is cut into numerous small snippets. The solution is then processed using microarrays (DNA chips) or using new-generation sequencing processes. “Eventually you get a kind of map of the epigenome, which comprises all of the biochemical markings layered on top the actual DNA sequence,” explains Thomas Lengauer.
The subsequent mathematical analyses by the Saarbrücken-based researchers are carried out exclusively in the computer. Ingenious algorithms and statistical processes screen the sea of epigenome data for patterns that only arise in certain forms of cancer and are absent in healthy patients – a task that requires a lot of careful programming. Because, unlike the genome, which is almost identical in all of the body’s cells, the DNA’s chemical coat is a real chameleon. “There are around 200 different types of tissue in the human body, each with different epigenomes. These also change with advancing age and in the presence of disease,” says Thomas Lengauer. “We have to take all of these variations into account in our programs to ensure that only differences relevant to cancer are considered important.”
And all of this effort is proving worthwhile. Working in collaboration with the Universitätsklinikum Bonn, the scientists in Saarbrücken developed an epigenetic biomarker for malignant glioblastoma, the most common form of malignant brain tumour. “Chemotherapy is only effective in around one quarter of affected patients,” explains Christoph Bock, who also leads a research group at the Research Center for Molecular Medicine in Vienna. “In these patients, a particular gene called MGMT is methylated, that is silenced. In its active state, this gene controls a repair mechanism in the cancer cells. In patients with active MGMT, the DNA damage arising during chemotherapy, which causes diseased cells to die, would be reversed and the treatment fails.” With the help of the new biomarker, the hospital can now identify in advance of treatment those patients for whom debilitating chemotherapy is actually worthwhile. The researchers subsequently systematised the time-consuming manual procedure for the identification of this biomarker and developed a corresponding software program. Using this software, other innovative biomarkers for cancer can now be identified considerably faster.