When working with patients concerned about their cancer risk, doctors will often recommend a manual exam that involves checking the skin for rigid lumps. This common technique is a widespread and effective procedure, but that guidance on what to look for — a mass that is tough or hard to the touch — actually exposes an important contradiction in the medical field about how tumors work.
In fact, tumors may feel hard from the outside, but research has shown that individual cells within the tissue aren’t uniformly rigid, and can even vary in softness across the tumor. However, cancer researchers didn’t understand how a tumor could be both rigid and soft at the same time, until now.
Northeastern physics researchers published a paper this August answering that question. The idea that different cells within a tumor can have different softness is called mechanical heterogeneity, and Xinzhi Li, a fifth-year physics Ph.D. student at Northeastern, applied a well-established model to study its effects.
“Our idea is, how to use some models to simulate this heterogeneity and study the effects of heterogeneity on the mechanics,” Li said. “How does this variability affect the collective behavior of the system?”
He found that when cells with varying softness were spread evenly throughout the tumor, it did not create the rigid mass that doctors have observed in real tumors. But when the softer cells were organized very specifically in a chain-like structure, the overall mass would remain rigid, despite the extremely soft individual cells.
Li did this work in the lab of Max Bi, an assistant professor of physics at Northeastern, where they focus on a relatively new scientific area called biophysics, or soft-matter physics. Instead of working on traditional physics topics, such as quantum mechanics or nanomaterials, a lot of the projects center on biomedical applications.
Bi said the cells seem to be communicating somehow and intentionally organizing themselves in these chains to create the overall rigid mass.
“It’s like somehow they’re talking, except the talking is not through chemical means, they’re not secreting chemicals,” Bi said. “It’s more mechanical, it’s transmission of forces. They’re talking via pulling and pushing each other.”
Li’s 2-D model views a cell as a polygon, where each cell presses up against the other cells to form tight junctions between them. Because the cells are touching, they exert mechanical force on each other based on their differing softness. The way each particular tumor behaves in the body has a lot to do with its proportion of rigid and soft cells.
Bi said another important finding centers on the tendency of malignant, cancerous tumors spread throughout the body.
“One thing that is really important and that’s often missed by a lot of cancer researchers is how easy it is to mechanically invade,” Bi said. “What is the fraction of rigid cells needed in order for cells to invade, and when they begin to invade, how do they do it?”
When Bi talks about the fraction of rigid cells, he refers to this video, a simulation using Li’s model that looks at the percentage of rigid cells in a tumor and how that affects how the cancer spreads. There, the number at the top of each box relates to the percentage of rigid cells in that example, and the moving green cell represents how easily a tumor can invade into normal tissue.
Although Bi stressed that the paper’s results are purely theoretical, he hopes to test the findings in partnership with cancer researchers.
He said if scientists could increase the rigidity of individual cells within the tumor, it could prevent the tumor from spreading elsewhere in the body. One possible way of studying that involves culturing healthy and cancerous cells together, called a co-culture, and developing a way to control them.
“A possible way to prevent them from invading is if you can somehow increase the percentage of rigid cells, and that would physically stop them from invading,” Bi said. “If we’re able to get this study about cell mixtures and co-cultures going, we can test that directly.”
Until then, Bi said Li’s model is applicable for many topics within this area of research — clearly, bringing physics to biology can teach scientists a lot.