Cancer Mechanics: How Physical Cues Influence Cell Migration, Metastasis, and Treatment

The green represents collagen while areas of red represent breast cancer cells. From the research of Bo Sun

Cancer cells are a product of their environment. The surrounding cells, extracellular matrix, and other features influence disease progression and spread of cancer cells to other parts of the body. Chemical cues like the presence of nutrients and oxygen have been studied for decades, but more recently, researchers have turned their attention to equally important physical cues.

New research on the tumor mechanical microenvironment will be presented at the 2020 American Physical Society March Meeting in Denver. Highlights include a study that looks at how the anisotropy of the extracellular matrix affects cancer cell migration, a novel optical tweezer-based tool that probes mechanical cues, and a model to find the best place within a tumor to inject a chemotherapy drug.

Mechanical Cues Drive Metastasis

Oregon State University researcher Bo Sun will present his findings on the complex interactions between cancer cell migration and the extracellular matrix, a 3D network of collagen, proteins, and other molecules that support the surrounding cells. Specifically, he will discuss the anisotropy of the extracellular matrix, and how a particular alignment of collagen fibers can create a cancer cell superhighway of sorts.

“For most research in the field so far, a dominant paradigm is that rigidity of the tissue environment is the dominant factor that guides cell migration. The cell wants to move to a more rigid region compared to a soft region,” said Sun. “We’re seeing that a different type of physical property, anisotropy of the environment, is more efficient in terms of guiding cell migration.”

For instance, collagen fibers aligned circumferentially around the tumor causes the cancer cells to become trapped by this alignment, whereas fibers arranged radially provide a frictionless highway for cells to migrate outward. Studying the way cells move in their environment–and what factors drive that movement–has implications for understanding how cancer cells infiltrate new areas of the body.

Probing Tissues with Optical Tweezers

Biophysicist Kandice Tanner has repurposed a tool to measure the mechanical cues that may influence how tumor cells disseminate to different organs. The optical tweezer-based technique can probe the physical properties of cells in living animals with microscale resolution.

“Previously, characterization of mechanical properties of tissues, cells, and extracellular matrix hydrogels were mainly obtained using bulk rheological or nanometer scale techniques such as atomic force microscopy and primarily for in vitro systems,” said Tanner, an investigator at the National Cancer Institute, part of the National Institutes of Health. “These techniques are useful to assess material properties but do not possess the resolution that is needed to resolve length scales that are compatible with the micron-size protrusions used by cells to respond to external cues.”

Tanner and her colleagues employed the technique to measure the viscoelastic properties of tissue in living zebrafish and 3D culture models of breast cancer progression. For the latter project, they used optical trap-based active microrheology to map internal cellular and external extracellular matrix mechanics with near simultaneity. They found that, unlike healthy cells, breast tumor cells do not match their mechanical properties to the surrounding microenvironment.

“As cancer cells migrate from their original primary tumor, they encounter many physical cues before establishing new lesions in different organs such as the patient’s bones, brain, liver, or lungs,” said Tanner. “We believe that by decoding the role of the physical cues, we can understand why some tumor cells are able to colonize one organ versus the other.”

Modeling Cancer Drug Response

Cancer treatment relies heavily on trial and error, which can lead to unnecessary toxicity and cost. Models that predict how a cancer drug will diffuse throughout the tumor offer a possible solution for oncologists. Aminur Rahman develops these kinds of mechanistic models of drug response as a method for oncologists to choose the most effective treatment before administering any medication.

“Our mechanistic models are able to produce dose-response curves that oncologists would see from cell line and drug data pairs,” said Rahman, a post-doctoral researcher at Texas Tech University. “We realized that perhaps this research could be used for computer-aided treatment strategies.”

He will present the results of multiple projects in a poster presentation. The first investigates a model of drug distribution after injection directly into a solid tumor and its effect on cancer cell death. While the model assumes the tumor is spherical and homogeneous, brain tumors in particular tend to be highly inhomogeneous and anisotropic. The second study develops a more sophisticated computational model for inhomogeneous-anisotropic drug diffusion using real-world diffusion tensor MRI data.

“Because of the tumor’s inhomogeneity and anisotropy, the center might not be the best place to inject drugs,” said Rahman. “We looked at different injection sites, and it was not necessary the center that would do the trick. In such cases, having a model would help an oncologist know where to inject the drug.”

The Nematic Feedback Between Cancer Cells and the Extracellular Matrix
TIME/DATE/PLACE: 8:00 AM, Monday, March 2, 2020, Room: 403

The Role of Tissue Biophysics in Organ Selectivity in Metastasis
TIME/DATE/PLACE: 9:24 AM, Monday, March 2, 2020, Room: 403
CONTACT: Kandice Tanner,

Physics-Based Models and Simulations of Cancer Drug Response in Solid Tumors
TIME/DATE/PLACE: 2:00 PM, Monday, March 2, 2020, Room: Exhibit Hall C/D
CONTACT: Aminur Rahman,



The 2020 APS March Meeting is Canceled
Due to rapidly escalating health concerns relating to the spread of the coronavirus disease (COVID-19), the 2020 APS March Meeting in Denver, CO, has been canceled.

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