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Researchers from the University of Miami (UM) and the University ofHeidelberg in Germany have developed a mathematical model tounderstand and predict the progress of a tumor, from its earlystages to metastasis, in hopes of creating highly personalizedtreatment strategies for patients who have cancer . The findings are published in Nature's new online journal Scientific Reports . When a tumor forms in the landscape of the human body, one of twothings may happen: the tumor can halt its growth and lie dormant orit can grow nourished by a network of underlying vessels thatexpands as the tumor develops. The vessels also provide a way forthe cancerous cells to travel to other parts of the body, settleand grow - a process called metastasis. The study reveals a hidden connection between the tumor and thenutrient supplying vessels. The method outlines paths of futuretumor expansion and identifies specific points in the vessels thatcan be targeted to control the growth, explains Neil Johnson,Ph.D., professor of physics, director of the Complexity ResearchGroup at UM College of Arts and Sciences and co-principalinvestigator of the study. "Cancer is a disease of many scales. There are the individualcells, the cells that group together to form the tumor, thevasculature and finally metastasis. By including information abouthow the tumor grows in response to its nutrients, and how thegrowth of the tumor feeds back the nutrient supply itself, ourmodel moves us one step closer to predicting the future evolutionof a patient's tumor," Johnson says. "It opens up a path towardpersonalized treatment and intervention." One interesting aspect of the model is that it's based on thedistribution of feeding vessels in a tumor section. Since thevessels both feed and are fed by the tumor, estimates of growthcharacteristics for a patient's tumor can be made. This type ofestimate can potentially be applied to a better design of treatmentschedules for cancer patients, explains Joseph D. Rosenblatt, M.D.,interim director of Sylvester Comprehensive Cancer Center, at UMMiller School of Medicine and co-principal investigator of thestudy. "This method could be used to predict growth rates in the humansetting and model effects of agents that specifically targetsupporting processes that sustain the tumor," Rosenblatt says. "Ourmodel may be useful in designing treatment intervals and dosageschedules based on more accurate assessment of growth dynamics andthe interdependence of tumor growth and blood vessel formation." By analyzing images of tumor sections for distribution of tumorcells and tumor vasculature, the researchers created a simple modelthat predicts the most likely course of the disease, explains SehyoChoe, post-doctoral research fellow at the Division of TheoreticalBioinformatics at the German Cancer Research Center in Germany andat the Institute for Pharmacy and Molecular BiotechnologyUniversity of Heidelberg; and co-principal investigator of thestudy. "Our model implements local differences of a tumor directlyextracted from in vivo images, and the parameters are directlymeasurable for each cancer," Choe says. "By doing so, we believe weare one step closer to eventually building a model that will beable to describe a likely corridor of progression of a cancer,based on real-time information of a specific patient from imagesand other patient specific data." Additional References Citations. I am an expert from glogift.com, while we provides the quality product, such as China Silicone Rubber Mat , China Silicone Cup Cover, Healthy Wristbands,and more.
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