Seeing all scales at once with Yang Liu

Cancer is a multiscale disease. It begins with errors and mutations at the molecular level that cause major changes in the way cells multiply and interact with their local environment and allow tumors to grow. The details differ from patient to patient, and they must all be understood to develop a complete picture.

 

The problem is that observations at different scales have required different technologies. Characterizing the way DNA is folded in a cell’s nucleus is an entirely different problem from that of imaging a tumor in tissue. Various instruments have been needed, each with unique technical trade-offs; they can offer only partial insights, leaving gaps in our understanding of the complex cellular networks involved in cancer.

Bioengineering professors Yang Liu and Hongqiang Ma have engineered a single instrument called the “Omni-Mesoscope” for resolving cancer features at all scales. It combines powerful optical instrumentation with advanced image-processing algorithms to capture all scales simultaneously in one data set.

“All these things – the tumor environment, the interactions between cells, even how DNA is packed into a cell nucleus – are aspects of the same system, but with sizes ranging from millimeters to tens of nanometers,” Liu said. “Typical microscopes cover large areas but don’t yield high resolutions, while recent ‘super-resolution microscopy’ techniques show molecular details but only a few at a time. The Omni-Mesoscope does both: it collects high-resolution data over large areas and processes it to show small-scale cellular features over those areas.”

The first thing Liu needed to develop was an optical instrument capable of capturing images over large swaths of tissue while having sufficient precision to deduce cellular features. Her group turned to astronomy for inspiration, using the same high-pixel-count sensors found in wide-field optical telescopes.

“We have the same problem as astronomers: capturing many different objects at as high a resolution as possible,” she said. “The difference is they’re looking up while we’re zooming in to the microscale. This meant we could take advantage of technology already developed for astronomy and apply it in cancer imaging.”

The next step was determining how to remove the noise that invariably shows up in high-precision data and account for any instrument imperfections. Liu’s group used a method based on deconvolution, a traditional mathematical approach, but they are also experimenting with AI to “correct” images.

“Our instrument’s greatest strength is its ability to capture dynamic multiscale information, spanning from the systems level to the molecular level, within large cell populations while preserving their original spatial context,” Liu said. This provides a holistic view of both cell-cell interactions and the molecular attributes of individual cells.”

The Omni-Mesoscope was used to identify a previously unknown means by which cancerous cells resist chemotherapy. On rare occasions, the cells that survive become polypoidal and develop multiple nuclei, which the sensor detected when analyzing remnants after therapy. The phenomenon makes the cells drug-resistant and opens the possibility for relapse in the form of more aggressive growth.

“Most cancer cells do not survive chemotherapy, which means the ones that do are quite difficult to detect and study,” Liu explained. “But detecting and characterizing such rare events is a prime application for the Omni-Mesoscope. It observed many cells and allowed us to pinpoint the few polypoidal ones, giving insight into an unknown mechanism for drug resistance that we can now address.”

Such an instrument is possible because of automation. It allows the smooth integration of image focusing, changing of imaging modes, sample environment monitoring and data processing in a single sensor.

“That we can incorporate everything into one powerful instrument for cancer imaging highlights the impact of engineering,” Liu said. “While all the components existed, each originally designed for different purposes, we approached the challenge with out-of-the-box thinking to imagine and construct an integrated system with entirely new functionality, providing new possibilities in cancer imaging.”

Yang Liu is a professor of bioengineering in the Department of Bioengineering at Illinois Grainger Engineering. She also holds an appointment in the Department of Electrical and Computer Engineering at Illinois Grainger Engineering. She is a member of the Cancer Center at Illinois and the Beckman Institute for Advanced Science and Technology at Illinois.

Honqiang Ma is a research assistant professor of bioengineering in the Department of Bioengineering at Illinois Grainger Engineering.

Read more about how Illinois Grainger engineers are fighting cancer.