They are creating mathematical equations that describe the shape and motion of single cells for laboratory analysis.
Though this research is in its early stages, it represents an entirely new way of identifying cell abnormalities, including cancer. It could one day be useful in gauging future stages of a disease -- for example, by detecting whether cancer cells are aggressive and likely to spread throughout the body, or metastasize.
In a paper published online in the Bulletin of Mathematical Biology, researchers describe a mathematical model which analyzes image sequences of single, live cells to determine abnormalities manifested in their shape and behavior. A brain tumor cell was one of the cell types they analyzed in the study.
Huseyin Coskun, visiting assistant professor of mathematics at Ohio State and leader of the project, described their novel approach as a first step toward developing mathematical tools for diagnosing cell abnormalities and for giving potential prognoses.
Because the technique would allow doctors to view how cancer cells behave under different physical or chemical conditions, it could also be used to test different treatment strategies for each individual patient -- such as determining the most efficient dose of chemotherapeutic agents or radiation -- or even to test entirely new treatments.
In addition, Coskun sees his technique as a tool for also pathologists, who typically look at photographs of biopsied cells to identify cancer and judge how advanced the cancer may be.
“A pathologist can diagnose cancer, but as far as predicting the future, they don’t have many tools at their disposal -- particularly if a cancer is in its early stages,” Coskun said. “That’s why I believe that one of the most important applications of this research is profiling cancer cells. Given a cell’s motion and its morphological changes, we want to be able to determine what’s happening inside the cell. If it looks like a cancer cell, and a particularly aggressive one, we would like to quantify how likely it is that the cancer cells will invade the body.”In a very basic sense, diagnosing a “sick” cell such as a cancer cell by its appearance, motion, and behavior is analogous to diagnosing a sick human, he said. “When we get sick, our behavior changes. We may stay in bed, sleep a lot -- maybe we are coughing or sneezing. These are basic symptoms that a doctor will consider to determine if we’re sick. Abnormalities oftentimes manifest themselves as behavioral changes in all living organisms. Therefore, a careful analysis of and profiling the behavioral patterns of single cells could provide valuable information.”
Living cells often change shape, expand, or contract, and Coskun believes that he and his colleagues can create unique “personality profiles” of cancer cells.
Coskun and his colleague, Hasan Coskun, assistant professor of mathematics at Texas A&M University-Commerce, used a branch of physics called continuum mechanics to derive equations that describe cells’ appearance and behavior. They compared their model outcomes to findings from past cancer studies, which indicated that cancer cells are more deformable than normal cells.
The researchers discovered that their model results agree with those experimental findings.
Obtaining data from live cell image sequences to use as an input in the mathematical models is not easy. For this, Coskun collaborated with Hakan Ferhatosmanoglu, an associate professor, and his then-student, Ahmet Sacan, both of computer science and engineering at Ohio State. They created open source software called CellTrack to extract data from movies of cell motion.
Given a movie of live cells under the microscope, CellTrack tracks individual cells, extracts data that can be used in the mathematical models, and provides other useful statistical information about the motion.
Huseyin Coskun acknowledged the current limits of his methodology. The researchers were able to show that their mathematical models can be applied to analyze single cell motion and obtain useful information. They were also able to hypothesize a biological explanation for very complex mechanism of cell motion based on their mathematical model outcomes. But he and his partners need many more high-resolution movies of healthy cells and cancer cells to build upon this initial work. That’s why Coskun is setting up collaborations with medical researchers at Ohio State and other universities.
Coskun believes that mathematical techniques such as his are becoming more common in the biomedical sciences because they allow researchers to perform studies that would be too difficult, time-consuming or expensive in real life. He hopes his technique could be used to answer emerging questions in cell biology.Contact: Huseyin Coskun, (614) 292-5131; firstname.lastname@example.org
Huseyin Coskun | EurekAlert!
Cryo-electron microscopy achieves unprecedented resolution using new computational methods
24.03.2017 | DOE/Lawrence Berkeley National Laboratory
How cheetahs stay fit and healthy
24.03.2017 | Forschungsverbund Berlin e.V.
Astronomers from Bonn and Tautenburg in Thuringia (Germany) used the 100-m radio telescope at Effelsberg to observe several galaxy clusters. At the edges of these large accumulations of dark matter, stellar systems (galaxies), hot gas, and charged particles, they found magnetic fields that are exceptionally ordered over distances of many million light years. This makes them the most extended magnetic fields in the universe known so far.
The results will be published on March 22 in the journal „Astronomy & Astrophysics“.
Galaxy clusters are the largest gravitationally bound structures in the universe. With a typical extent of about 10 million light years, i.e. 100 times the...
Researchers at the Goethe University Frankfurt, together with partners from the University of Tübingen in Germany and Queen Mary University as well as Francis Crick Institute from London (UK) have developed a novel technology to decipher the secret ubiquitin code.
Ubiquitin is a small protein that can be linked to other cellular proteins, thereby controlling and modulating their functions. The attachment occurs in many...
In the eternal search for next generation high-efficiency solar cells and LEDs, scientists at Los Alamos National Laboratory and their partners are creating...
Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are less stable. Now researchers at the Technical University of Munich (TUM) have, for the first time ever, produced a composite material combining silicon nanosheets and a polymer that is both UV-resistant and easy to process. This brings the scientists a significant step closer to industrial applications like flexible displays and photosensors.
Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are...
Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to simulate these confined natural conditions in artificial vesicles for the first time. As reported in the academic journal Small, the results are offering better insight into the development of nanoreactors and artificial organelles.
Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to...
20.03.2017 | Event News
14.03.2017 | Event News
07.03.2017 | Event News
24.03.2017 | Materials Sciences
24.03.2017 | Physics and Astronomy
24.03.2017 | Physics and Astronomy