Great breakthrough in cancer diagnostics

NewsGuard 100/100 Score

An amazingly sensitive method for selective analysis of amino acids, sugars, fatty acids, and other vital compounds has been developed by Russian scientists. This method allows determining even their trace quantities (fractions of nanograms). It is applicable in identifying cancerous cells and diagnostics of cancer at the earliest stage, when traditional diagnostics fail to catch sight of the disease.

Dr. Igor Revel'sky and his colleagues from the Moscow State University have developed method that provides a 100-times increased sensitivity of detecting amino acids and other vital compounds, i.e., a highest precision of their detection. This can be used in controlling the quality of drugs and foods and, prospectively, may become an effective technique of cancer diagnostics that will be more reliable than traditional histology.

The Russian scientists propose to begin with the separation of a complex mixture (e.g., the contents of a cell suspected of cancer). They separate firstly water-soluble substances from the rest of the mixture and, then, treat each of the two obtained fractions with specific reagents. As a result, the analyzed substances become volatile and separable with the use of a gas chromatograph, in which they are diffused along with a carrier gas through a liquid or solid adsorbent for differential adsorption. Each component produces its own peak in chromatogram.

The next challenge is identifying the components and their concentrations. This is rather difficult, as investigated samples contain a great variety of components, and a universal type of detector with a high sensitivity is needed. Such a detector chosen by the Russian scientists is a mass spectrometer. This apparatus is rather expensive and requires special operation skills. It converts molecules into ions and then separates the ions according to their mass-to-charge ratio, which allows identifying atoms and isotopes. The scientists can identify the structure of initial substance using the obtained mass spectra, existing mass spectra data base, and special software.

Finally, it is necessary to recreate the original mixture composition. This process can be compared with doing a puzzle, where a picture needs to be assembled from separate pieces. In the chemical analysis, the number of pieces and pictures is never known by analyst, so, it is a rather complicated task. Information to be processed is contained in the mass spectra of components of studied mixture.

Dr. Sobolevsky, colleague of Dr. Revel'sky, has explained us the applicability of their method. It allows detecting a wide range of substances, which can be used in food quality control and for research purposes. Actually, this method has an exceptional sensitivity and selectivity. It gives a unique possibility for studying the composition of different cell components. Particularly, the scientists have revealed significant differences between the composition of amino acids in a cell culture of adenocarcinoma of human colon and their composition in healthy cells of connective tissue. We continue our research now, but it is clear already that a cancerous cell can be distinguished from a healthy cell by the composition of amino acids. This promises a great breakthrough in cancer diagnostics.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Insilico Medicine's AI-driven approach yields promising PTPN2/N1 inhibitor for cancer immunotherapy