Computer Tech: The Latest Weapon Against Cancer

Scientists Kornelia Polyak and Franziska Michor at the Dana-Farber Cancer Institute have advanced our ability to predict how a patient’s tumor is likely to respond to different therapies through computational modeling. Utilizing a computer model capable of collecting data on the characteristics of many different cancer cells, scientists can now predict whether or not a patients tumor will respond well to chemotherapy. This means doctors can prescribe the most effective and individualized treatment for patients.

There are a variety of cancer cells in tumors that can express their own unique traits. This mix is referred to as tumor heterogeneity. The phenotypes and genotypes of these cells are what determine how tumors change.
Polyak and Michor’s computer model is able to collect data from cancer cells such as genetic and phenotypic traits and also pinpoint the location of the cancer cells within tumors. Using the model, the scientists observed how tumor heterogeneity impact chemotherapy results and how treatment changes heterogeneity of the tumor. A test was done on 47 patients with breast cancer to test the effectiveness of the model. Patients were given biopsies and their tumors were then analyzed by the predictive model. The study found that genetic diversity in cancer cells did not change significantly for patients who did not respond well to treatment and that tumors with higher genetic diversity generally do not react well to chemotherapy. However, one positive outcome was that cells that grow quickly were destroyed after treatment. This means that doctors can use the computer model as a tool to predict which cells are likely to be eliminated due to chemotherapy.

This study was really exciting and reassuring to me because it shows how cancer can be attacked from many different angles. Whether it is through new drugs or a computer model, the fight against cancer can only be won with a widespread arsenal of techniques.

Article: Vanessa Almendro, Yu-Kang Cheng, Amanda Randles, Shalev Itzkovitz, Andriy Marusyk, Elisabet Ametlle, Xavier Gonzalez-Farre, Montse Muñoz, Hege G. Russnes, Åslaug Helland, Inga H. Rye, Anne-Lise Borresen-Dale, Reo Maruyama, Alexander van Oudenaarden, Mitchell Dowsett, Robin L. Jones, Jorge Reis-Filho, Pere Gasco, Mithat Gönen, Franziska Michor and Kornelia Polyak Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity

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