NEW YORK – Exai Bio, a company recently spun out of the University of California San Francisco based on work in the lab of Hani Goodarzi, is working to develop blood-based tests for cancer early detection and potentially other applications, enabled by genome-wide analysis of small non-coding RNAs.
Formed about six months ago and funded by a $67.5 million Series A financing last December, Exai recently shared data at the American Association for Cancer Research annual meeting from a study of more than 10,000 samples. Researchers were able to validate an AI-based approach to determine a cancer’s tissue-of-origin based on these transcriptomic signals, something crucial for multi-cancer screening assays.
“The liquid biopsy space has been mostly focused on DNA,” Exai CEO Patrick Arensdorf said in an interview. “It may be moving from mutations or methylation or fragmentomics. But it all shares the same analyte, which fundamentally is a scarce commodity in blood.”
“What we’re looking at is further downstream at the transcriptome … RNA that is actively secreted from cells as opposed to DNA that only is released when cells turn over and die,” he said.
More specifically, the firm’s approach takes advantage of a specific class of molecules, which it has dubbed orphan non-coding RNA (oncRNA). “These are the ones that we’ve found are most valuable … the ones that have no real expression in normal cells, but we see them in cancer cells,” Arensdorf said.
At AACR, Exai presented a poster describing its analysis of a combined cohort of cancers and controls using data from The Cancer Genome Atlas and Indivumed.
The authors reported that they identified 144,695 distinct oncRNAs across six tumor types — breast, colorectal, gastric, kidney, liver, and lung cancers — and were able to validate 51,208 of them in two independent cohorts.
They then developed an artificial intelligence model using oncRNA profiles to predict cancer tissue-of-origin, which had over 90 percent accuracy when applied to the two validation cohorts.
Arensdorf said the company is also expecting to publish a number of other studies in the near future, including data across multiple solid tumors identifying tumor-specific oncRNAs. These are “individual fingerprints that allow us to get both origin as well as subtypes, ” he said, “and it really lets us get at that underlying biology.”
Sequencing blood-borne RNA is not proprietary in itself but Arensdorf said that Exai is at a significant first-mover advantage with regard to the oncRNAs that are at the core of its approach.
“We’re looking at segments that haven’t even been annotated in the literature before, so we have a large bioinformatics lead,” he said. “We have really created a lexicon and a dictionary for the non-coding RNAs that no one else has yet.”
Another advantage is that the company builds on years spent on optimizing sample prep to be able to increase the efficiency and eliminate biases in analyzing RNA on a genome-wide scale.
“People have been very focused on using RNA in gene expression more than anything and not really looking at the entire rest of the genome … [but] 98 percent of the genome is non-coding,” Arensdorf said.
“Traditional sample preps are focused on molecules greater than 200 nucleotides … …….