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Researchers Develop Mathematical Model to Forecast Metastatic Breast Cancer Survival Rates

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Key Points

  • Breast cancer patients die when tumors have colonized an average of four metastatic sites, the study found. Women had the poorest chances of long-term survival if they had more than two initial metastatic locations; they fared much better if migrating tumor cells first landed on one organ.
  • Roughly 35% of breast cancer patients developed first metastasis to the bone, while less than 5% contracted their first metastasis in the brain. The 5-year survival of the bone group is more than 90%, whereas the brain group had survival characteristics of 20% or less.
  • Bone, chest wall, and mammary lymph nodes were “spreader” sites in the patients sampled. Lungs, distant lymph nodes, and liver were “sponge” sites.

University of Southern California (USC) researchers have developed a mathematical model to forecast metastatic breast cancer survival rates using techniques usually reserved for weather prediction, financial forecasting, and surfing the Web.

For decades, medical schools have taught doctors that the best way to treat cancer and metastatic progression is to memorize a list of tumors and their typical migration patterns.

“This is akin to back in the days when weather reporting depended solely on a barometer and experience,” said Jorge Nieva, MD, Associate Professor of Clinical Medicine at the Keck School of Medicine of USC. “Medical students are taught very fundamental cancer progression patterns. What the modeling does is it brings the sort of complexity of modern-day weather forecasting to trying to understand where tumors go, when they go, and how they get to that location. This type of mathematical modeling is wholeheartedly different from what most medical students learn today.”

Study Details

The study, published by Newton et al in npj Breast Cancer, looked at 25 years of data regarding 446 breast cancer patients at Memorial Sloan Kettering Cancer Center. It focused on a subgroup of women who were diagnosed with localized disease, but later relapsed with metastatic disease.

The model shows that cancer metastasis is neither random nor unpredictable. Survival depends significantly on the location of the first metastatic site or “spatiotemporal patterns.” The path of metastasis varies depending on tumor makeup and treatment decisions.

“There's nothing like this in the cancer world; there's nothing really like this in the disease progression community, even though the techniques are well-developed in other contexts,” said Paul Newton, PhD, Professor of Aerospace and Mechanical Engineering in the USC Viterbi School of Engineering. “Our long-term goal is to build comprehensive predictive computational simulations of metastatic cancer. Ultimately, what we want to do is tailor those models to individual patients using their individual characteristics.”

The framework combines scattered data points doctors are already collecting in order to produce an understandable, comprehensive cancer map. The system design is comparable to information Google collects to predict Web surfing patterns and to determine PageRank.

“If somebody is reading about breast cancer on Wikipedia, the likelihood that she is going to jump to a lung cancer page or a bone cancer page is much higher than the likelihood of her jumping to the Costco website,” said Dr. Newton, who is also a Professor at the Norris Comprehensive Cancer Center in the Keck School of Medicine of USC, as well as Professor of Mathematics. “These probabilities of jumping from one page to another are not all equal. Where you jump to next depends strongly on where you currently are. This observation lies at the heart of our model.”

Study Findings

Breast cancer patients die when tumors have colonized an average of four metastatic sites, the study found. Women had the poorest chances of long-term survival if they had more than two initial metastatic locations; they fared much better if migrating tumor cells first landed on one organ.

Roughly 35% of breast cancer patients developed first metastasis to the bone, while less than 5% contracted their first metastasis in the brain, Dr. Newton said. The 5-year survival of the bone group is more than 90%, whereas the brain group had survival characteristics of 20% or less, he said.

The study's results led the researchers to further define the words “spreaders” and “sponges” to describe metastasis, a nomenclature that eventually could inform medical teams how best to deliver personalized therapy plans.

“A spreader is a site that is likely the source of new disease,” said Peter Kuhn, PhD, Dean’s Professor of Biological Sciences and Professor of Medicine, Biomedical Engineering, and Aerospace and Mechanical Engineering at USC. “Hence, you need to avoid spreaders, or eliminate the disease if it shows up at a spreader site. At a sponge site, one might just manage or stabilize. Of course if you could eliminate all of it, you would. But if you have multiple metastasis, one would attempt to stabilize the sponge but eliminate the spreader.”

Bone, chest wall, and mammary lymph nodes were spreader sites in the patients sampled. Lungs, distant lymph nodes, and liver were sponge sites.

The future of cancer care could be squads consisting of a biologist, a mathematician, a physicist, and a computer programmer to complement the current medical teams, Dr. Newton said.

“Over the next 5 to 10 years, there's going to be a big change in the way medical schools and oncologists think about disease,” he said. “I could easily see a situation 10 years down the road where a patient comes in with a particularly difficult disease. The oncologists in charge will put together a team of researchers to develop a model to forecast disease progression and determine best treatment options that they would then implement.”

An interactive website containing the study's diagrams is available here.

The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.


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