This invention introduces a groundbreaking algorithm designed to identify the specific somatic genome alterations (SGAs) driving cancer in individual patients.
Description
This technology addresses the critical need for personalized precision medicine by distinguishing between driver SGAs, which contribute to cancer development, and passenger SGAs, which do not. The algorithm leverages genomic alteration data and gene expression data to pinpoint the driver SGAs, offering a novel, data-driven approach that surpasses current knowledge-based methods.
Applications
• Cancer Diagnostics
• Personalized Medicine
• Genomic Research
Advantages
Its data-driven approach ensures a more accurate and personalized diagnosis by using patient-specific data to identify cancer drivers, unlike current methods that rely on incomplete knowledge of driver SGAs. The algorithm is capable of identifying both known and novel cancer drivers, expanding the potential targets for precision medicine. By integrating various types of genomic data, including somatic mutations and copy number alterations, it provides a comprehensive analysis of the cancer’s genetic landscape. This holistic view enhances the ability to develop targeted therapies, potentially improving patient outcomes and reducing the trial-and-error approach in cancer treatment.
Invention Readiness
The technology is currently at the software development stage, with preliminary validations supporting its predictions. The algorithm has been applied to data from over 4,000 tumors across 16 cancer types, demonstrating its robustness and potential for clinical application. The next steps involve further validation through clinical trials and collaborations with oncology centers to integrate the technology into routine clinical practice. The invention is poised to play a critical role in the emerging field of Genome Pathology, impacting every cancer patient by providing personalized, data-driven insights into their disease.
IP Status
https://patents.google.com/patent/US11990209B2
