UT Health San Antonio creates innovative organoid for advancing understanding of pancreatic cancer 

pancreas

 

Pancreatic ductal adenocarcinoma (PDAC), a certain type of pancreatic cancer, is a ruthless killer with an average five-year survival rate of less than 10%. Most patients are diagnosed at a late stage when the cancer has already spread throughout their bodies. And the problem is only growing worse.

By 2030, pancreatic cancer is expected to surpass colorectal cancer as the second-leading cause of cancer-related death in the United States. While many other types of cancer have seen dramatic improvements in early detection and survival rates, pancreatic cancer remains an ominous outlier with few treatment options.

Credit: Min Yu (Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC),USC Norris Comprehensive Cancer Center, Pancreatic Desmoplasia
Pancreatic cancer cells (nuclei in blue) grow as a sphere encased in membranes (red). By growing cancer cells in the lab, researchers can study factors that promote and prevent the formation of deadly tumors.

A study by scientists at The University of Texas Health Science Center at San Antonio (UT Health San Antonio), published this year in Nature Communications, provides one of the first models to study the progression of normal human pancreatic cells toward tumor cells. Illumination on this process could aid the development of early biomarkers and potential treatment targets for this deadly disease.

Pei Wang, PhD

Pei Wang, PhD, primary investigator of the study, is an associate professor in the Department of Cell Systems and Anatomy at the Joe R. and Teresa Lozano Long School of Medicine. She was recruited to UT Health San Antonio in 2012 for her stem cell expertise and received a Cancer Prevention and Research Institute of Texas award to study pancreatic cancer.

Before it’s too late

“Learning how to prevent cancers from happening or figuring out how to stop them in their early stages is potentially more important than treatment itself,” Wang said. “For pancreatic cancer, the biggest problem is that we find the cancer too late.”

Of four currently available models for studying pancreatic cancer, none provides a path for an early diagnosis strategy. Whereas those models begin with studying progression of the cancer using mice or biopsied tumor cells, Wang’s model begins with normal human organ donor cells that are induced to become cancerous. A model of this early stage of tumorigenic development had previously never been conducted with human cells.

PDAC tumors develop from exocrine glands in the pancreas, which contain acinar and ductal cells. Acinar cells make digestive enzymes that are released into the small intestine to help break down food so it can be used by the body. Ductal cells line the tubes through which the digestive enzymes flow and they secrete bicarbonate-rich fluid that neutralizes stomach acid. Wang began by separating ductal and acinar cells to see if normal cells from human organ donors could become cancerous through the addition of the four most commonly mutated genes in pancreatic cancer.

Bright field images and schematic illustration of established long-term 3D acinar culture.

Both sets of cells went through a dynamic series of transcriptional alterations when transitioning from normal to tumorigenic state. The cultured acinar organoids lost most of their original cell profiles while taking on some ductal cell characteristics, but they did not completely change from one cell type to the other.

H&E staining of xenograft tumors. Each staining was performed in at least 3 tumor sections with 8 fields of views for each. Scale bar: 50 µm.

Despite the transformations, DNA methylation patterns, or the locations on a DNA molecule where methyl groups are added, were unique to each kind of cell, even after the cells turned cancerous. Testing showed the patterns remained stable, and each lineage could be traced to either ductal or acinar cells, respectively. Wang said this suggests that contrary to what was previously believed, pancreatic cancer in humans has the potential to come from both acinar and ductal cells. This means that approaches to pancreatic cancer treatment may need to become more nuanced and additional research must be conducted into the mechanistic properties of tumorigenic pancreatic cells.

Jun Liu, PhD

Assistant professor Jun Liu, PhD, began work on this novel model about 10 years ago at UT Health San Antonio when he was a postdoctoral fellow. Wang says a great deal of progress was also made by postdoctoral fellow Yi Xu, PhD, and graduate students Michael Nipper and Angel Dominguez.

Study benefits

Wang’s model has many benefits over previous PDAC models. When studying a tumor from a patient, it has developed in the individual for decades, potentially meaning there are many factors affecting the disease. By starting with normal cells and forcing mutations in a comparatively short amount of time, Wang said they can see the genesis of the tumor in earlier stages. Also, through this novel PDAC model, the research team identified over 50 genes significantly expressed during early transformation in both ductal and acinar PDAC models. These genes can be further studied as potential early biomarkers of pancreatic cancer.

Wang’s lab continues research using this model to identify potential novel tumor suppressor genes, explore possible drug targets and reveal mechanisms for drug resistance. Wang said she is thrilled that this model is established so other researchers can use it to further pancreatic cancer research. She said it is critical that work continues to discover early detection and treatment options not only for pancreatic cancer, but also for all cancers.

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Read more:

Reconstitution of human PDAC using primary cells reveals oncogenic transcriptomic features at tumor onset

Yi Xu, Michael H. Nipper, Angel A. Dominguez, Zhenqing Ye, Naoki Akanuma, Kevin Lopez, Janice J. Deng, Destiny Arenas, Ava Sanchez, Francis E. Sharkey, Colin M. Court, Aatur D. Singhi, Huamin Wang, Martin E. Fernandez-Zapico, Lu-Zhe Sun, Siyuan Zheng, Yidong Chen, Jun Liu, Pei Wang. First published Jan. 27, 2024, Nature Communications. https://doi.org/10.1038/s41467-024-45097-2



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