Cedars-Sinai Cancer researchers are paving the way in cancer treatment with the development of a groundbreaking precision medicine and artificial intelligence tool known as the Molecular Twin Precision Oncology Platform.
This innovative platform has shown remarkable potential in identifying biomarkers that surpass current standard tests for predicting pancreatic cancer survival, indicating a major leap forward in personalized cancer therapy.
The Molecular Twin platform, developed at Cedars-Sinai, stands out for its versatility and potential for widespread application.
Dan Theodorescu, MD, Ph.D., director of Cedars-Sinai Cancer and the senior author of the study, emphasized that this technology is not just limited to pancreatic cancer but can be applied to any tumor type.
Its groundbreaking nature lies in its ability to create effective tests accessible even in locations without advanced resources and technology, thus broadening the reach of precision medicine.
The study focused on pancreatic ductal adenocarcinoma, a common and aggressive form of pancreatic cancer.
Researchers analyzed blood and tissue samples from 74 patients, integrating a vast array of 6,363 biological data points, including genetic and molecular information. This comprehensive approach resulted in a model that accurately predicted disease survival in 87% of patients.
The team further employed AI to refine the data, achieving nearly similar accuracy with just 589 data points. Remarkably, they identified blood proteins as the single best predictor of pancreatic cancer survival.
This research marks a significant advancement over the existing FDA-approved pancreatic cancer test, CA 19-9.
The findings were validated using independent datasets from The Cancer Genome Atlas, Massachusetts General Hospital, and Johns Hopkins University, underscoring the reliability and potential of the Molecular Twin platform.
Arsen Osipov, MD, the study’s first author, highlighted the urgent need for developing biomarkers in pancreatic cancer treatment.
The Molecular Twin platform, launched in 2021, promises to meet this need, not only for pancreatic cancer but across various cancer types.
Jennifer Van Eyk, Ph.D., an expert in protein study, pointed out the critical role of proteins in predicting patient survival.
While genetic information is crucial for understanding cancer risk and subtyping, proteins serve as the body’s first responders once cancer develops, offering valuable insights into a patient’s response to treatment.
The future of the Molecular Twin platform is expansive.
Researchers plan to enrich it with data from additional patients and incorporate diverse types of data, including medical imaging, gut microbiome samples, tumor microenvironment analysis, and physical activity feedback from wearable devices.
This comprehensive data pool is expected to uncover biomarkers for various cancer types, potentially leading to new treatments and the ability to identify and prevent cancer in at-risk patients before it even develops.
In conclusion, the Molecular Twin Precision Oncology Platform represents a significant stride in the fight against cancer.
By harnessing the power of precision medicine and AI, Cedars-Sinai Cancer investigators are opening new frontiers in personalized cancer treatment, offering hope for improved survival rates and quality of life for cancer patients worldwide.
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The research findings can be found in Nature Cancer.
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