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–Large study program encompassing over 10,000 samples across three independent cohorts validates a large class of novel oncRNAs and the utility of AI-based oncRNA profiling for predicting cancer tissue-of-origin–
–Poster presentation at the 2022 Annual Meeting of the American Association for Cancer Research (AACR), New Orleans, LA–
Palo Alto, CA — Exai Bio, a next-generation liquid biopsy company, is presenting today data from its scientific research program on the discovery and validation of tumor-specific, orphan non-coding RNAs (oncRNAs), and the validation of artificial intelligence (AI) profiling of oncRNAs to accurately detect cancers of diverse tissue origins. With these capabilities, Exai Bio is positioned to develop blood tests for early detection and monitoring of residual disease of many commonly seen cancers.
Exai Bio’s technology is based on its unique, proprietary repertoire of oncRNAs, which are an abundant class of small non-coding RNA sequences that are actively secreted only by cancer cells and not normal tissues. As such, oncRNAs can provide a robust disease signal with high sensitivity, low background and, as a result, high specificity, giving the Exai Bio oncRNA platform several advantages over currently employed mutational or epigenomic analyses of circulating tumor-derived DNA.
In a poster entitled, “Discovery and validation of orphan noncoding RNA profiles across multiple cancers in TCGA and two independent cohorts,” Exai Bio is presenting a new study of more than 10,000 samples (7,942 cancer and 3,021 normal samples) from three large independent cancer cohorts. As a first step, Exai Bio identified a large class of distinct oncRNAs that were significantly present in six key cancer types, using samples from The Cancer Genome Atlas (TCGA). These six cancers (breast, colorectal, gastric, kidney, liver, and lung) represent the majority of cancer mortality worldwide.
Next, the oncRNAs from this library were independently validated in two unique IndivuType cohorts, containing 2,245 and 1,252 cancer samples, respectively, and over half of oncRNAs in the library were validated in at least one of the IndivuType cohorts.
Finally, Exai Bio developed artificial intelligence (AI) algorithms in the TCGA cohort for predicting the tissue-of-origin of a cancer sample by analyzing its oncRNA profile. The algorithm was validated and had high accuracy (>91%) in each IndivuType cohort, showing that cancer tissues-of-origin are identifiable based on oncRNA profiles alone.
These results demonstrate that oncRNAs are a unique and generalizable feature of cancers that may be applied to improve the care of cancer patients. Exai Bio is focused on early cancer detection for multiple types of cancer, including the 28 cancer types explored in the TCGA cohort, for which it has identified a proprietary library of more than 250,000 novel oncRNAs. The Exai program aims to build on the current data to translate these findings into a liquid biopsy test with broad utility for early detection of cancer and monitoring of minimal residual disease.
Patrick Arensdorf, Chief Executive Officer, Exai Bio, commented, “We’re proud of the scientific rigor we are applying to the development and validation of an RNA-based liquid biopsy approach for early cancer detection. The evidence reported today demonstrates that Exai Bio’s oncRNA platform is biologically valid, clinically oriented and highly accurate in its ability to predict cancer tissue-of-origin. These results build upon our initial discoveries of tumor-specific oncRNAs in neoadjuvant breast cancer patients and validate the presence of further specific oncRNAs across multiple tumor types. We look forward to translating these findings and advancing the development of our RNA-based liquid biopsy diagnostics platform for early cancer detection and minimal disease monitoring.”
Details of the AACR 2022 poster presentation:
Title: Discovery and validation of orphan noncoding RNA profiles across multiple cancers in TCGA and two independent cohorts
Track: PO.BCS01.05 – Applications of Bioinformatics to Cancer Biology 2
Abstract/Poster: 3353
Authors: Jeffrey Wang, Helen Li, Lisa Fish, Kimberly H. Chau, Patrick Arensdorf, Hani Goodarzi, Babak Alipanahi
Presenter: Jeffrey Wang
Date & Time: April 12, 2022 (1:30 PM – 5:00 PM)
Location: Exhibit Halls, Section 27
Posters will be available on-demand on the AACR website for attendees (www.aacr.org) beginning at 12:00 PM CDT on April 8, 2022 until July 13, 2022. Upon release at AACR, the poster will be accessible on the publications page of Exai Bio’s website.
Exai Bio is a next-generation liquid biopsy company. Its mission is to enable a world where cancer can be detected early, diagnosed accurately, treated in a personalized and targeted way, and ultimately cured. The company’s proprietary RNA and artificial intelligence-based liquid biopsy technology delivers clinical insights into cancer biology to enable the earliest, most accurate diagnosis of cancer.
For more information:
info@exai.bio