Indian Institute of Science study reveals how cancer cells adapt while moving across tissues

A new study from the Indian Institute of Science (IISc) shows how inherent variations in a cancer cell and its interactions with its surroundings mould its migration.

The findings, published in Biophysical Journal, reveal that cancer cells seem to adapt their migratory pattern depending on the physical and biochemical characteristics of their surroundings, called the microenvironment.

“The spread of tumour from the primary cancer site to distant organs, called metastasis, has puzzled scientists for many years – they are only now beginning to pinpoint triggers and mechanisms that drive this process,” IISc said.

How they adapt

The researchers studied two types of ovarian cancer cells – OVCAR-3, which has a well-structured polygonal shape, and SK-OV-3, which has a naturally elongated spindle shape. Both of these cells metastasise and invade tissues. By placing these cells on soft and stiff surfaces that mimic healthy and diseased tissues, the researchers observed how each type adapted its movement on different surfaces.

On soft surfaces, similar to healthy tissue, both cell types moved slowly in random directions. But on stiff surfaces, which mimic the tough, scarred tissue around tumours, the cells are more deformable and respond differently.

“Based on previous literature, I expected stiffness to be an important factor in aggravating cancer cell migration. However, what I did not expect was that the epithelioid ovarian cancer cells (OVCAR-3) were more migratory than the mesenchymal cells (SK-OV-3) on stiffer matrices,” said Madumitha Suresh, former MTech student at the Department of Bioengineering (BE) and first author of the study.

Shape matters

The researchers also observed a unique movement pattern in the OVCAR-3 cells, which they called slip. In most cells, the direction of movement aligns with the shape of the cell, with the cell’s front leading the way. But when the OVCAR-3 cells moved on stiff surfaces, this alignment broke down.

“Their movement became less coordinated with their shape, almost as if they were sliding or slipping instead of moving in a straight line. Motivated by these unexpected results, the researchers sought to understand the process using quantitative approaches,” IISc said.

It added that existing methods for studying how cancer cells move are either mathematical approaches that don’t capture changes over time or complex computer-based approaches, such as machine learning, that are challenging to use.

Collective dynamics

“We aim to extend our study to decipher the collective dynamics of such cancer cells, especially in more complex 3D environments. This will shed fresh light on the pathology of ovarian cancer, a disease that is characterised by rapid metastasis and high morbidity,” said Ramray Bhat, associate professor at the Department of Developmental Biology and Genetics and corresponding author of the study.