Advanced Medical Imaging, Genetic Analysis Could Improve Cancer Care

Incorporating genetic and cellular analysis of tumors with how they appear in medical images could help improve brain cancer treatment, showing that cells inside and surrounding a tumor play a major role in cancer development, according to a study published in the journal PLOS ONE.

Patients with brain cancer often have fast-growing tumors that are among the most difficult to treat, remove, and monitor. Because of the way brain tumors infiltrate surrounding healthy brain tissue, it’s challenging for surgeons to remove all of the cancer without causing potential damage to a patient’s memory and ability to function.

Additionally, because of the tiny blood vessels that surround the brain, only small molecules can enter, which limits the types of drugs that could help shrink brain tumors. Each patient’s brain tumor cells are also different, which can make treatment even more difficult.

To improve brain cancer treatment, researchers from the Translational Genomics Research Institute (TGen) correlated the genetic and protein fingerprints of brain cancer cells with how those cells and surrounding cells looked using MRI.

Currently, the process of characterizing tumors at the molecular level involves grinding up many cells from a biopsy and extracting DNA, RNA, and other genomic materials so that the tumor can be sequenced, and researchers can know which genes might be causing the cancer. However, scientists can’t tell how cancer cells may have interacted with other nearby cells.

Even with single-cell sequencing, researchers have no context as to what cells were adjacent to the individual diseased cells they analyze.

“The resolution of MRI can’t ‘see’ individual cell differences. But we were able to find evidence for correlations between genetic and cellular changes. We can see the consequences of specific genetic changes in brain cancer tumors that show up on a medical image,” said Dr. Michael Berens, Professor and Director of TGen’s Cancer and Cell Biology Division, head of the institute’s Glioma Research Lab, and one of the study’s lead authors.

Knowing individual cell differences could help surgeons determine how much tissue must be removed to extract the cancer, the dosage and frequency a radiologist might use to treat the cancer, and what specific drugs may be best suited for each patient at different points in time.

The team deployed an advanced imaging tool called Multiplex immunofluorescence imaging (MxIF), which is used to repeatedly stain tumor samples with antibodies attached to fluorescent dyes. The method allows cell level quantification of over 60 cell biomarkers in a single sample.

For this study, the group analyzed more than 100,000 cells in brain tumor cases, using MxIF to discover the differences between two types of brain tumors based on mutations in the gene IDH1.

“Using this platform, we can visualize and analyze various cell types and cell states present in the tumor tissue as well as how they interact with each other and their microenvironment. Visualizing the microenvironment, especially, is key to understanding tumor behavior and the response to therapy, which has been difficult to analyze with conventional methods,” said Dr. Anup Sood, a senior scientist at GE Global Research, and also a lead author of the study.

“The platform’s unique capabilities, which allows deeper insights into cancer, were the result of a more than decade’s long effort by a multidisciplinary team of more than 50 chemists, biologists, software and hardware engineers, computer scientists, statisticians with key industrial and academic partners.” 

The research demonstrates how combining genetic analysis with advanced medical imaging could drastically improve cancer care and treatment.

“This study is a bridge between genetic sequencing, single-cell analysis and high-resolution medical imaging,” said Berens.

“By literally focusing on how tumors look on the outside, as well as spelling out their DNA cell characteristics on the inside, we believe we can provide physicians, oncologists, radiologists, surgeons and others with timely information about how to best attack each patient’s cancer.”

In future research, the team will use the technology on a large group of patients to ensure that it works.

“The more cell-level data we analyze, the more we learn about tumor biology, cell-to-cell interactions, immune response and how tumors progress,” said Dr. Fiona Ginty, another GE senior scientist and the study’s senior author.

“Further, with the integration of cellular, medical imaging and genomic data, we gain a more holistic understanding of why certain tumor types progress more rapidly, and others are more slow-growing, and ultimately which drugs a patient may respond to.”