From Astronomy to Pathology: Platform Enables Tumor Imaging

Combining astronomic image analysis and sky-mapping with tumor imaging enables researchers to guide targeted cancer immunotherapy, according to a new study published in Science.

Researchers from the Mark Foundation Center for Advanced Genomics and Imaging at Johns Hopkins University along with the Bloomberg~Kimmel Institute for Cancer Immunotherapy developed AstroPath, a platform that combines astronomy and pathology to predict which cancers will respond to which immunotherapies.

"This platform has the potential to transform how oncologists will deliver cancer immunotherapy. For the last 40 years, pathology analysis of cancer has examined one marker at a time, which provides limited information. Leveraging new technology, including instrumentation to image up to 12 markers simultaneously, the AstroPath imaging algorithms provide 1,000 times the information content from a single biopsy than is currently available through routine pathology," said Drew Pardoll, MD, PhD, director of the Bloomberg~Kimmel Institute for Cancer Immunotherapy, in a press release.

"This facilitates precision cancer immunotherapy-- identifying the unique features of each patient's cancer to predict who will respond to a given immunotherapy, such as [anti-programmed cell death-1], and who will not. In doing so, it also advances diagnostic pathology from uniparameter to multiparameter assays."

In an analysis of tumor biopsies from melanoma patients, researchers applied astronomical algorithms to pathology, swapping stars and galaxies for cancer cells and applying the same practices, the study stated.

Immunofluorescent imaging of cancer biopsies allows researchers to see many cellular proteins at once and identify patterns and biomarkers. Six markers were mapped in total, with tumor tissue from 98 melanoma patients receiving anti-programmed cell death-1 therapy, or anti-PD-1.

Because only some patients respond well to anti-PD-1 therapy, it saves a lot of time if the platform can predict the effectiveness of the treatment for a specific patient’s cancer.

The database for the Sloan Digital Sky Survey was the basis for AstroPath. Using multiplex immunofluorescence technology (mIF), AstroPath tags each protein with different-colored fluorescent molecules. The celestial object mapping algorithms show researchers how the tumor cells interact with the tissues surrounding it.

"The spatial arrangements of different kinds of cells within tumors are important," said Janis Taube, MD, MSc, a leader of the research team, professor of dermatology and co-director of the tumor Microenvironment Laboratory at the Bloomberg~Kimmel Institute in the press release.

"Cells are giving each other go/no-go signals based on direct contacts as well as locally secreted factors. Quantifying the proximities between cells expressing specific proteins has the potential to reveal whether these geographic interactions are likely transpiring and what interactions may be responsible for inhibiting immune cells from killing the tumor."

The research has the potential to provide more effective immunotherapies to cancer patients and identify telling biomarkers that can guide treatment.

"Big data is changing science. There are applications everywhere, from astronomy to genomics to oceanography," explained Alexander Szalay, PhD, one of the research team’s leaders and director of the Institute for Data Intensive Engineering and Science at Johns Hopkins University.

"Data-intensive scientific discovery is a new paradigm. The technical challenge we face is how to get consistent, reproducible results when you collect data at scale? AstroPath is a step towards establishing a universal standard."