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Optical metabolic imaging of a human pancreas organoid
June 3, 2020

Detecting cellular diversity to sharpen personalized cancer treatments

Written By: Tom Ziemer


Individual cancer patients possess their own unique biological quirks, variations that can guide treatment plans.

 Melissa Skala
Melissa Skala

Inside each patient, individual cells can also differ, even within the same organ and among the same cell type—and those differences can determine which cells respond to or resist drugs. By better understanding cellular heterogeneity, physicians could further hone personalized treatment strategies.

Melissa Skala, a University of Wisconsin-Madison associate professor of biomedical engineering, and collaborators have used an approach called optical metabolic imaging (OMI) to effectively assess that heterogeneity and related treatment responses in organoids created with tissues from patients with breast cancer and pancreatic cancer.

In a paper published online in May 2020 in the journal Frontiers in Oncology, the researchers showed that data from the technique reliably predicted treatment responses in those patients—meaning it could potentially be used to screen drugs to develop regimens tailored to individuals.

“We can assess single-cell response in intact samples, so that’s what differentiates this from other methods,” says Skala, who’s also an investigator at the Morgridge Institute for Research and a member of the Carbone Cancer Center. “It’s providing a way to then take heterogeneity into account when designing and testing therapies so that you can address this issue in humans.”

OMI is a microscopy technique that measures the natural fluorescence of two coenzymes, nicotinamide adenine dinucleotide and flavin adenine dinucleotide, that are involved in metabolism in all cells.

“You don’t need to add any fluorescent dyes or labels to the cells, which could affect how they behave,” says Joe Sharick, the paper’s first author and a Skala lab alumnus who’s now a postdoctoral scholar at Ohio State University.

By measuring and combining several data points from OMI, Skala’s group is able to quantify the metabolic states of individual cells, revealing the heterogeneity that could better inform treatments.

“Different cells are going to have completely different microenvironments,” says Sharick. “Some cells, in order to adapt to different microenvironments, might evolve completely different metabolic strategies to survive.”

OMI is predominantly used in cancer research at the moment, though it’s been applied to diagnosis as well. Skala’s lab, in collaboration with Dustin Deming, an oncologist and associate professor in the UW-Madison School of Medicine and Public Health, previously published a study in which OMI was used to design a patient’s treatment. Deming and Skala are currently working on a paper featuring more patients.

Other UW-Madison authors on the paper included Skala lab members Christine Walsh and Dan Pham and researchers from the School of Medicine and Public Health, including Associate Professors Mark Burkard and Kristina Matkowskyj and Assistant Professor Stephanie McGregor. Collaborators at Vanderbilt University and the Medical College of Wisconsin also contributed. For a full list of authors and funding sources for the work, see the paper.