Scientists Take an 'Unprecedented Look' at Colorectal Cancer

Colorectal cancer—also known as colon, rectal and bowel cancer—is the third-most common cancer in the United States. The disease is expected to claim about 52,500 lives in 2023, according to American Cancer Society estimates.
There's nothing insignificant about 52,500 deaths, but the number of colorectal cancer-caused fatalities used to be even higher. The mortality rate for this particular cancer has declined steadily over the past few decades thanks to increased rates of screening, advancements in detection and improvements in treatment.
On Jan. 19, a team of researchers at Harvard Medical School unveiled a promising new weapon in the fight against colorectal cancer deaths. The researchers have generated maps of colorectal tumors in never-before-seen detail. Combining histological features with new single-cell imaging technologies, the maps offer insights into the architecture of colorectal cancer structure and how it forms, advances and interacts with other cells. The research was published in Cell journal.
"Our approach provides a molecular window into 150 years of diagnostic pathology and reveals that many of the elements and structures traditionally thought to be isolated are actually interconnected in unexpected ways," said co-senior author Peter Sorger, Ph.D., the Otto Krayer professor of systems pharmacology in the Blavatnik Institute at Harvard Medical School, in a Harvard report. "An analogy is that before, we were just looking at the tail or the foot of the elephant, but now, for the first time, we can start to see the whole elephant at once."
The process of mapping colorectal cancer
The researchers used single-cell molecular imaging data acquired through high-plex cyclic immunofluorescence (CyCIF)—a powerful method for multiplexed immunofluorescence imaging—to generate 2D maps of large areas of colorectal cancer. They wove these maps together to build a 3D atlas of tumors.
"Our maps include information on almost 100 million cells from large pieces of tumors and provide a rather unprecedented look at colorectal cancer," said co-senior author Sandro Santagata, an associate professor of systems biology at Harvard Medical School and associate professor of pathology at Brigham and Women's Hospital, in the report.
"It's a wild, new look at these tumor structures that we never really appreciated before," Santagata said. "Because we can see them in 3D, we have a crisp, clean view of the structures, and we can now study why they are there, how they form and how they shape tumor evolution."
The goal of mapping colorectal cancer
The purpose of these colorectal cancer maps is to advance research and improve diagnosis and treatment. The researchers hope their work will reveal insights into colorectal cancer that can help develop precision medicines.
Precision or personalized medicine involves tailoring treatment to the unique characteristics of a person and their cancer, as opposed to a one-size-fits-all approach designed for an "average" patient. Advances in precision medicine carried out in the past two decades have improved the medical community's understanding of cancer, and the strategy has become increasingly important for colorectal cancer treatments, according to Soger.
"The big translational story here is building the knowledge to make precision medicine practical for most patients," Soger said in the report.
"This is allowing us to extract a whole additional layer of molecular and structural features that we think will provide diagnostic and prognostic information and improve our ability to target these cancers," Santagata added.
The colorectal cancer maps are part of the researchers' larger efforts to create atlases of other cancers as part of the Ludwig Tumor Atlas project. Soger, Santagata and their research team have already mapped early-stage melanoma and next plan to generate maps for breast cancer and brain cancer.