October 3, 2024

New Tools Developed to Improve Pancreatic Cancer Patient Care, Research Team Finds

A research team at Cedars-Sinai Cancer has made significant progress in the field of pancreatic cancer treatment by utilizing precision medicine and artificial intelligence tools. The team has developed the Molecular Twin Precision Oncology Platform, which has proven to be more effective than the standard test in predicting pancreatic cancer survival. This breakthrough could potentially revolutionize patient care for all cancer types.

Pancreatic cancer is known for being particularly difficult to treat, but the Molecular Twin platform has shown promising results in analyzing tumors, including pancreatic cancers. Dr. Dan Theodorescu, director of Cedars-Sinai Cancer, explains that the Molecular Twin technology can be used to create tests that can be deployed in locations with limited access to advanced resources and technology. This would ensure that patients are matched with the most effective therapies and expand the availability of precision medicine.

The research team analyzed blood and tissue samples from 74 patients with pancreatic ductal adenocarcinoma, the most common and aggressive type of pancreatic cancer. They combined over 6,000 biological data points, including genetic and molecular information, to create a model that accurately predicted disease survival in 87% of patients. By utilizing artificial intelligence, the team then streamlined the data and created a model that performed just as well with only 589 points of data. Further analysis revealed that proteins found in the blood were the best predictors of pancreatic cancer survival.

The full and streamlined models, along with the blood-protein test, outperformed the only FDA-approved test for pancreatic cancer, called CA 19-9. The team validated their findings using independent datasets from The Cancer Genome Atlas, Massachusetts General Hospital, and Johns Hopkins University.

The Molecular Twin platform was introduced by Cedars-Sinai in 2021. Dr. Arsen Osipov, program lead in the Pancreatic Cancer Multidisciplinary Clinic and Precision Medicine Program at Cedars-Sinai Cancer, highlights the importance of developing biomarkers to guide pancreatic cancer treatment. With the robust collection of blood and tissue samples from patients with pancreatic cancer, the team was able to test and refine the Molecular Twin platform. As the platform grows with more patients, it will become an even more powerful tool, not only for pancreatic cancer but for all cancers.

Dr. Jennifer Van Eyk, an expert in protein studies and a key member of the Molecular Twin team, emphasizes the significance of proteins in predicting patient survival. While genetic information provides insights into a patient’s risk of developing cancer and the subtype of cancer, this study demonstrates that proteins are the key to accurately predicting patient survival.

The development of the Molecular Twin Precision Oncology Platform marks a significant advancement in pancreatic cancer treatment. By harnessing the power of precision medicine and artificial intelligence, this new tool has the potential to greatly improve patient care and outcomes not only for pancreatic cancer but for all types of cancer. As further research is conducted and the Molecular Twin platform is refined, researchers hope to expand its applications and make it widely accessible to patients worldwide.

*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it

Money Singh
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Money Singh is a seasoned content writer with over four years of experience in the market research sector. Her expertise spans various industries, including food and beverages, biotechnology, chemical and materials, defense and aerospace, consumer goods, etc. 

Money Singh

Money Singh is a seasoned content writer with over four years of experience in the market research sector. Her expertise spans various industries, including food and beverages, biotechnology, chemical and materials, defense and aerospace, consumer goods, etc. 

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