What You Need to Know
Investigators from John Theurer Cancer Center (JTCC), part of the NCI-designated Lombardi Comprehensive Cancer Center at Georgetown University, and Genetic Testing Cooperative Inc. (GTC) published a study demonstrating the reliability of combining next-generation sequencing and artificial intelligence to accurately diagnose subtypes of blood cancers and solid tumors.
This approach has the potential to become a part of routine cancer care and lead to improved patient outcomes.
The study was published in the January 2023 issue of the American Journal of Pathology.
About the Study
The JTCC and GTC researchers investigated a targeted transcriptome and artificial intelligence to diagnose blood cancers and solid tumors.
In this study, RNA samples from 2,606 hematologic neoplasms and 2,038 solid tumors as well as normal bone marrow and lymph node samples were analyzed using next-generation sequencing with a targeted 1,408-gene panel. Twenty subtypes of hematologic neoplasms and 24 subtypes of solid tumors were identified. Machine learning was highly accurate for distinguishing between different diagnoses.
The data indicate that targeted transcriptome analysis combined with artificial intelligence is highly useful for diagnosing and classifying various cancers.
"These results open the door for supplementing and eventually replacing current diagnostic technologies with a new approach that, in addition to more accurate diagnosis, should eventually lead to real-time disease monitoring during therapy to better guide care," explained study co-authors Andre Goy, MD, MS, chairman and executive director of JTCC, and Andrew Pecora, MD, co-chief of the Division of Skin Cancer and Sarcoma at JTCC.