Mathematics107

2013 RESEARCH NEWS

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Mathematical Probability Model Predicts How Lung Cancer Spreads

The same sort of mathematical model used to predict which websites people are most apt to visit is now showing promise in helping map how lung cancer spreads in the human body. Using a mathematical technique known as Markov chain Monte Carlo modeling, a multi-institutional team of investigators has developed what they believe will be a new tool for gaining important insights about the dissemination patterns of lung cancer.

“The same types of tools that help us understand the spread of information through the web can help us understand the spread of cancer through the human body,” said Paul Newton of the University of Southern California and a member of the Scripps Research Institute Physical Sciences-Oncology Center (Scripps PS-OC). Dr. Newton and his colleagues published their findings in the journal Cancer Research.

The Scripps PS-OC team, which included investigators from the Scripps Research Institute, the University of California, San Diego Moores Cancer Center, and the Memorial Sloan-Kettering Cancer Center, used their modeling approach to show that that metastatic lung cancer does not progress in a single direction from primary tumor site to distant locations, which has been the traditional medical view. Instead, they found that cancer cell movement around the body likely occurs in more than one direction at a time.

Researchers also learned that the first site to which the cells spread can play a key role in the progression of the disease. The study showed that some parts of the body serve as “sponges” that are relatively unlikely to further spread lung cancer cells to other areas of the body. The study identified other areas as “spreaders” for lung cancer cells. For lung cancer, the main spreaders are the adrenal gland and kidney, whereas the main sponges are the regional lymph nodes, liver, and bone.

The study applied the Markov chain model to data from human autopsy reports of 163 untreated lung cancer patients in the New England area dating from 1914 to 1943. The researchers targeted this time period because it predates the use of radiation and chemotherapy, providing the investigators with a clear view of how cancer progresses if left untreated. Among the 163 patients, researchers charted the advancement patterns of 619 different metastases to 27 distinct body sites.

The investigators note that these findings could potentially impact clinical care by helping guide physicians to targeted treatment options that are designed to curtail the spread of lung cancer. For example, if the cancer is found to have moved to a known spreader location, imaging tests and interventions can be quickly considered for focused treatment before the cells may be more widely dispersed.

This work, which is detailed in a paper titled, “Spreaders and sponges define metastasis in lung cancer: A Markov chain Monte Carlo mathematical model,” was supported in part by the National Cancer Institute’s Physical Sciences in Oncology initiative, a program that aims to foster the development of innovative ideas and new fields of study based on knowledge of the biological and physical laws and principles that define both normal and tumor systems. An abstract of this paper is available at the journal’s Web site.
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http://www.tedmed.com/talks/show?id=7349

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