Next-Gen RNA-Based Liquid Biopsy Platform Detects Multiple Cancer Types at Earliest Stages

A novel RNA- and AI-based platform has demonstrated the ability to detect multiple cancer types at the earliest stages using a single, standard blood sample.

The universal platform developed by Exai Bio (Palo Alto, CA, USA) has diverse applications across numerous cancer care scenarios, including screening, early detection, monitoring, molecular residual disease analysis, and therapy selection. The platform employs RNA sequencing to distinguish a new class of small, non-coding RNAs linked to cancer, known as orphan non-coding RNAs (oncRNAs). The RNA composition of the transcriptome delivers a more dynamic and exhaustive perspective of actionable cancer biology than the DNA content of the genome. The abundance of oncRNAs in the blood of cancer patients and their relative scarcity in those without cancer makes oncRNA-based tests remarkably sensitive and specific.

Image: Exai is developing blood tests that have both high accuracy and cancer biology insights (Photo courtesy of Freepik)

Exai has identified hundreds of thousands of unique oncRNAs through studies involving over 16,000 patients, creating a vast catalog that paves the way for developing innovative RNA-based tests for early cancer detection. Exai utilizes artificial intelligence (AI) and machine learning (ML) to analyze the multitude of oncRNAs found in cancer patients' blood by identifying distinct, cancer-specific patterns. Exai has proven that these oncRNA patterns can be used to detect various types and subtypes of cancer, predict the original tissue of cancer, and identify cancer in its earliest stages.

In Exai’s multi-cancer early detection (MCED) study, eight types of cancer - lung, stomach, pancreas, kidney, colorectal, breast, prostate, and the bladder - were analyzed, reflecting the majority of the societal cancer burden. The study showed successful detection of stage I breast and prostate cancers, both of which have been extremely difficult to identify at early stages using other blood-based methods. When a cancer signal was identified in the test group, Exai's platform was able to pinpoint the origin tissue with 88% accuracy for the top predicted cancer type and 95% accuracy considering the top two predictions, demonstrating the power of its unique generative AI technology. This new MCED data lend further support to the increasing evidence that Exai's platform is versatile, and capable of application across numerous tumor types and clinical uses, all through the use of standard blood samples.

“These results demonstrate that Exai’s RNA- and AI-based platform can detect stage I cancer at very high sensitivity across multiple cancers while also maintaining the high specificity which is required for real-world clinical utility,” said Patrick Arensdorf, chief executive officer of Exai Bio. “Exai is developing blood tests that have both high accuracy and cancer biology insights to improve cancer care.”

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