$3.2M NIH Grant Supports Development of New Approach to Target ‘Invisible’ Residual Tumors

$3.2M NIH Grant Supports Development of New Approach to Target ‘Invisible’ Residual Tumors

A $3.2-million grant from the National Institutes of Health has been awarded to the collaborative work between Northeastern University’s Spring Lab and Cellaria into a new method of eliminating the microscopic cancerous tumors left behind by standard therapies.

The approach uses antibody-photosensitizer molecules that make cancer cells susceptible to light-induced destruction. Researchers will mainly focus on ovarian and pancreatic cancer — whose residual microscopic tumors can spread into the abdomen, attacking other organs.

Microscopic clusters of cancer cells missed during cytoreductive surgery (meant to remove the tumor and nearby tissues where the cancer may have spread) often contain resistant cells that escape follow-up chemotherapy and lead to disease recurrence.

Currently, there is a lack of imaging tools capable of detecting or monitoring these residual tumors, as well as limited approaches to address them, leaving patients at a higher risk of relapse.

Bryan Spring, PhD, Spring Lab’s principal investigator, and colleagues have been working extensively to develop a way to address both of these limitations.

In a previous study, they were able to detect, monitor, and eliminate abdominal micrometastases in ovarian cancer mouse models using a tumor-targeted, activatable photoimmunotherapy, integrated with a newly developed microscopic imaging tool.

The new photoimmunotherapy uses a compound comprising an antibody that targets EGFR — a cell-surface receptor protein highly present in ovarian cancer cells — combined with a molecule that becomes fluorescent and toxic after being internalized and processed by cells and in the presence of near-infrared light (invisible to the human eye).

Since cancer cells overproducing the target surface protein take up higher amounts of the compound (called a photocytotoxic immunoconjugate), light-induced cell death occurs predominantly within tumors, leaving healthy cells unaffected.

The approach showed high sensitivity and specificity (93% for both) for tumors as small as 30 micrometers (a small cluster of cells), allowing their selective destruction. In this case, sensitivity refers to the ability to correctly target cancer cells, while specificity concerns the ability to correctly avoid healthy cells.

Therefore, this unique approach not only has the potential to help destroy residual therapy-resistant cancer cells but also provides a way to monitor these microscopic tumors in common sites of recurrence.

In the now-awarded project, titled “Multiplexed and dynamically targeted photoimmunotherapy of heterogeneous, chemoresistant micrometastases guided by online in vivo optical imaging of cell-surface biomarkers,” the researchers aim to further develop this approach to address distinct subtypes of ovarian and pancreatic cancer.

The project is based on a collaboration between the Spring Lab and Cellaria, which allowed the expansion of the lab’s work through Cellaria’s next-generation, patient-derived, customized cancer cell models.

“We’ve demonstrated proof of concept and seen significant interest from clinicians,” Spring, who is also an assistant professor of biomedical physics at Northeastern University, said in a press release.

“However, we initially targeted just a single ovarian cancer biomarker. To capture the [variability] of the disease and efficiently study multiple biomarkers we needed to upgrade our cell models,” he added.

Since developing such models in the lab “would have taken years,” Spring said, the researchers chose to work with Cellaria, which provided quick access to “rigorously characterized cell models for specific molecular subtypes and patient populations.”

“This has really accelerated progress,” Spring said. “The bottom line is that via this collaboration we get to concentrate on our science, rather than the tools we need to support it, which is just as we prefer it.”

By using these models, the researchers plan to determine the best biomarkers of ovarian and pancreatic cancer for targeting therapy-resistant cells and applying their photoimmunotherapy.

With this work, they hope to open new avenues for personalized medicine and provide a way to monitor treatment response of microscopic residual disease.