New 3D technique uncovers early signs of pancreatic cancer

Tissue processing workflow and cohorts for CODA 3D modeling and sequencing. Credit: Nature (2024).

Researchers at the Johns Hopkins Kimmel Cancer Center have developed a groundbreaking 3D technique to identify tiny, precancerous lesions in the pancreas.

These lesions, called pancreatic intraepithelial neoplasias (PanINs), can lead to one of the deadliest forms of pancreatic cancer.

Published in the journal Nature, this research offers the most detailed 3D map of these precancerous lesions in the human pancreas.

This discovery is a significant step toward early detection of pancreatic ductal adenocarcinoma (PDAC) and other types of pancreatic cancer.

“Pancreatic cancer is relatively rare, so we were surprised to find a lot of precancerous PanINs in what seemed like normal pancreas tissue,” says Dr. Laura Wood, one of the senior authors of the study. “This research raises new questions about how cancer starts in the pancreas and what happens as people age.”

The study was co-led by Dr. Alicia Braxton, a postdoctoral fellow, and Dr. Ashley Kiemen, an assistant professor of pathology, both from Johns Hopkins University.

PanINs are very small and hard to detect with standard radiology exams. This often means that by the time pancreatic cancer is diagnosed, it has already reached an advanced stage and spread to other organs.

Traditional methods of examining tissue involve slicing it thinly, staining it, and looking at it under a microscope. This 2D approach gives a limited view of PanINs, making it difficult to understand where they come from and how they lead to cancer.

To get a better look at PanINs, the researchers developed a 3D technique. They sliced and stained tissue from 38 normal pancreatic samples onto hundreds of 2D slides. Then, they used a machine-learning tool called CODA to analyze and reconstruct these slides into 3D images.

The 3D images revealed complex networks of PanINs, with an average of 13 PanINs per cubic centimeter of tissue. Some samples had as many as 31 PanINs per cubic centimeter. Patients with PDAC in other parts of their pancreas tended to have more PanINs, although the difference was not statistically significant.

The researchers also used 3D-guided microdissection and DNA sequencing to study eight samples in more detail. They found that the PanINs were genetically distinct from each other and were driven by different gene mutations. One common mutation involved the KRAS gene, which is found in most pancreatic cancers.

This discovery—that multiple precancerous lesions can arise from independent mutations—has not been seen in other organs before. “Now that we know these PanINs exist, we can work on targeting them, such as through the KRAS gene,” says Dr. Wood.

Although CODA is not yet ready for clinical use, it has the potential to be applied to any tissue, disease, or model organism. “This is just the beginning,” says Dr. Kiemen. “We need to continue investigating what this means for other organs. If normal tissue has many PanINs, how do we determine which ones are relevant to disease?”

Dr. Wood adds, “One of the best ways to help people with cancer is through prevention. Understanding the early stages of cancer through detailed 3D maps is a crucial first step. Until you look in 3D, you don’t know what you’re missing.”

This new 3D technique offers hope for earlier detection and better prevention of pancreatic cancer, potentially saving many lives in the future.

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