Transcriptome test systems for cancer diagnosis
Team play
"Search" No. 42-2015
A new method of selecting test systems for personalized diagnosis of oncological diseases is presented by Russian scientists in a recent issue of the journal Scientific Reports (Galatenko et al., Highly informative marker sets consisting of genes with low individual degree of differential expression, in open access - VM).
The method of medical diagnostics proposed by a group of authors led by Corresponding member of the Russian Academy of Sciences Alexander Tonevitsky from Moscow State University and the National Medical Research Radiological Center was the result of cooperation between molecular biologists and mathematicians.
Transcriptomic test systems make it possible to draw conclusions about the features of the disease based on data on the activity of certain genes of a tissue sample or blood of a particular patient and, thanks to this, serve as a tool for personalized medicine. The transcriptome on which they are based represents all the RNA molecules of a cell, it is a reflection of all its active genes at a given time. Transcriptomic test systems not only increase the accuracy of diagnosis, but also make it possible to predict the course of the disease and optimize the choice of therapy. For example, thanks to them, it is possible to assess the risk of relapse in 5 or even 10 years based on current features.
Analyzing the expression features of tens of thousands of genes is currently difficult and expensive, and therefore transcriptomic test systems are built on the basis of only a few dozen genes. Usually, genes are chosen as such genes, each of which by itself has the maximum informative value. But Russian scientists have found that genes with high individual informativeness do not necessarily complement each other well, whereas genes with lower informativeness can collectively be highly informative.
In the studies of Tonevitsky and co-authors, samples of breast cancer patients and machine learning methods combined with selective strategies were used to predict the risk of relapse using transcriptome systems, which required the involvement of the resources of the Moscow State University supercomputer center. Thus, scientists have identified pairs and triples of genes that make it possible to ensure the reliability of the risk assessment at least as good as that of foreign commercial test systems (OncotypeDX and MammaPrint).
Commenting on the opening in an interview with Echo of Moscow, one of the authors, Vladimir Galatenko, drew an analogy with a sports team: a team of stars, but without a team game, often loses to a team of weaker, but well-played and well-complementary players. The developed method of searching for the most informative combinations of genes also makes it possible to investigate groups of genes important for a particular pathology that would have been missed by traditional methods of analysis.
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21.10.2015