Researchers use Google search engine algorithm to find cancer biomarkers
Improving outcome prediction for cancer patients by network-based ranking of marker genes
- Date : 25 May 2012
- Topic : Personalised medicine
The strategy used by Google to decide which pages are relevant for a search query can also be used to determine which proteins in a patient's cancer are relevant for the disease progression. Researchers from Dresden University of Technology, Germany, have used a modified version of Google's PageRank algorithm to rank about 20 000 proteins by their genetic relevance to the progression of pancreatic cancer. In their study, published in PLoS Computational Biology, they found seven proteins that can help to assess how aggressive a patient's tumour is and guide the clinician to decide if that patient should receive chemotherapy or not.
Modified Google's PageRank algorithm
The researcher's own version of the Google algorithm has been used in this study to find new cancer biomarkers. Biomarkers can help to detect cancer earlier in body fluids or directly in the cancer tissue obtained in an operation or biopsy. Finding these biomarkers is often difficult and time consuming. Another problem is that markers found in different studies for the same types of cancer almost never overlap.
This problem has been circumvented using the Google strategy, which takes into account the content of a web page and also how these pages are connected via hyper-links. With this strategy as the model, the authors made use of the fact that proteins in a cell are connected through a network of physical and regulatory interactions; the 'protein Facebook' so to speak.
According to Christof Winter, the paper's first author, once they added the network information in the analysis, biomarkers became more reproducible. Using this network information and the Google Algorithm, a significant overlap was found with an earlier study from the University of North Carolina. There, a connection was made with a protein which can assess aggressiveness in pancreatic cancer.
Although the new biomarkers seem to mark an improvement over currently used diagnostic tools, they are far from perfect and still need to be validated in a larger follow-up study before they can be used in clinical practice. It remains an open problem to turn these insights into novel drugs which slow down cancer progression. A first step in th
is direction is the group's cooperation with the Dresden-based biotech company RESprotect, who are running a clinical trial on a pancreas cancer drug. TU Dresden is a leading German university, whose Centre for Regenerative Therapies was awarded excellence status in the German excellence initiative. The work was a cooperation between the bioinformatics group of Prof. Michael Schroeder and the medical groups of Dr Christian Pilarsky and Prof. Robert Grützmann.
Funding was provided by the Roland Ernst Stiftung für Gesundheitswesen, MeDDrive TU Dresden, the EU project Ponte and the German projects GoOn, Format, and GeneCloud. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The authors have declared that no competing interests exist.
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