Google search algorithm helps track spread of cancer cells

So, following Google’s example with search results, the researchers split the sites where the lung cancer spread to into two groups: first order and second order. In first order sites, tumor cells would most likely reach them by traveling directly from the lung. Tumors are more likely to reach second order sites by colonizing a first order site and then spreading to the second order location.

Using this approach, the researchers were able to estimate the average times it takes the cancer to spread to different parts of the body. The lymph nodes were the quickest to be affected by metastasizing lung cancer cells, with the adrenal gland and liver following close behind.

At the other end of the spectrum, lung cancer cells take so long to spread to the bladder and uterus that an individual with lung cancer would probably have died before those sites can be affected.

Unfortunately, the researchers’ dataset didn’t include records of the times when doctors noticed each new tumor. But the researchers could see how many tumors existed in each new site, input that information into the model, and calculate each progression.

“What we’re trying to do now is use this baseline model and make it patient specific, or at least subgroup specific to make more targeted predictions,” Newton said.

The researchers will also play with the model, searching for novel ways of reducing a cancer’s likeliness of spreading, for example, by isolating a key site in the

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