GENERICO.ruScienceA new method for predicting survival in lung cancer has been proposed in Russia

A new method for predicting survival in lung cancer has been proposed in Russia

MOSCOW, October 16Russian scientists have developed a model that allows them to predict the survival of patients with lung adenocarcinoma, the most common form of cancer of this organ, and select effective treatment, the Russian Science Foundation (RSF) reported.
The model is based on an analysis of the level of protein molecules that control the quality of mitochondria – the “energy stations” of living cells that ensure respiration and normal functioning of all body tissues. When their work is disrupted, various pathological processes, chronic diseases and cancer occur. Therefore, cells have mechanisms that maintain the normal state of mitochondria. These mechanisms, in turn, are controlled by special regulatory proteins. Therefore, by the level of these molecules in cells, one can assess how mitochondria work.
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Employees of the Institute of Molecular Biology named after V.A. Engelhardt (IMB, Moscow) and Moscow State University named after M.V. Lomonosov, as part of a project supported by a grant from the Russian Science Foundation, assessed the level of proteins that control the quality of mitochondria in normal and tumor tissue in 80 patients with lung adenocarcinoma. This subtype of lung cancer typically occurs in nonsmokers and is usually diagnosed quite late, making treatment success highly dependent on correct prognosis.

Based on the obtained molecular data, as well as information on the age, gender and stage of the disease of the patients, the authors built a prognostic model that assessed the chances of patients to live for the next year, three and five years. Using mathematical methods, the researchers proved that the forecasting accuracy of the new model is 20% higher than currently available models.

For comparison, forecasts that take into account only the tumor stage have a significantly lower probability. Thus, the proposed approach will allow doctors to more effectively predict the outcome of the disease and personalize treatment for patients with lung adenocarcinoma, the authors of the work believe.
“We were able to divide patients into different risk groups and predict their survival. The model demonstrated significantly better predictive value than other known models built, for example, only taking into account tumor stage. In the future, we plan to expand our model by adding new markers, and also further test it by including a significantly larger number of patients in the analysis,” said Alexey Zamaraev, a project participant, researcher at the Institute of Biomedicine and the Laboratory for the Study of Apoptosis Mechanisms at Moscow State University.


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