NEW YORK – UK startup Wobble Genomics is eyeing the breast cancer early detection market with technology that enables it to capture rare and low-abundance RNA transcripts.
The Edinburgh-based company, which emerged from stealth mode last month, is developing a diagnostic platform for breast cancer using predictive RNA biomarkers it has uncovered. The firm is also generating a database of novel full-length transcripts, which it believes can help garner biological insights for cancer disease monitoring, treatment planning, and drug development.
Richard Kuo, Wobble Genomics' cofounder and CEO, said the company's core technologies include Level-Up, a method to normalize low-abundance RNA molecules in a sample, and Transcriptome Annotation by Modular Algorithms (TAMA), a bioinformatics pipeline optimized for the identification of novel or low-level RNA signals. Kuo developed both methods as a Ph.D. student at the University of Edinburgh.
Level-Up is a multistep thermal cycling workflow that aims to solve a "fundamental problem" for RNA sequencing, Kuo said — the fact that signals from rare RNA molecules, which can be biologically important, are often drowned out by highly abundant RNAs, which are typically expressed by housekeeping genes.
The Level-Up protocol is compatible with any RNA samples after reverse transcription. The method involves heating the cDNA library to denature the molecules and then cooling the sample down "in just the right way" to revert portions of the cDNA to double-stranded molecules, Kuo said.
Because high-abundance cDNA strands are more likely to find their complementary strands during the process, low-level cDNAs tend to remain single-stranded. Kuo said he designed a way to then selectively amplify the single-stranded cDNA, boosting the presence of low-abundance molecules.
Compared to the commonly used depletion-based approach for normalization, Kuo said, one advantage of Level-Up is that the method does not require prior knowledge of the sequence composition of the RNA sample. As such, Level-Up helps to preserve the signal from all RNA molecules and avoids potential off-target effects.
Kuo declined to further comment on the technical details of Level-Up, citing a pending patent application, other than noting that the method "functions off on biochemical kinetics."
The company is typically using about 200 ng of cDNA as starting material for Level-Up, but Kuo said the input amount can go down to 20 ng and "probably below that."
Once normalized, the cDNA library can proceed to sequencing with any platform, Kuo said, adding that Wobble Genomics has been using nanopore sequencing due to its accessibility and long reads for full-length cDNA analysis.
After sequencing, the data can be processed by TAMA, which can analyze low-abundance RNA transcript variants for biomarker discovery and diagnostic applications, Kuo noted. An earlier version of TAMA, which he developed during his Ph.D., is still currently open source and available on GitHub.
"By combining Level-Up with the TAMA software package, we have created this completely new diagnostic platform that allows us to take whole blood samples and then characterize all the full-length RNA, and then use that signal to deconvolve disease and health states," Kuo said.
Wobble Genomics currently has no plans to commercialize Level-Up and TAMA as basic research tools, Kuo noted. Instead, the company only plans to use them clinically.
One such application is breast cancer early detection, Kuo said. Wobble Genomics has been collaborating with Mike Dixon, a professor and consultant surgeon at the University of Edinburgh, on a clinical study to demonstrate the clinical utility of its technologies. This involved full-length RNA sequencing on liquid biopsy samples from 101 breast cancer patients and an age-matched control group of 101 individuals.
Presenting the study results on a poster at the Early Detection of Cancer Conference (EDCC) in San Francisco last month, the company said it was able to identify an average of over 600,000 RNA transcripts per patient, "with the majority of these transcripts being seen for the first time." A subset of them can be harnessed as potential biomarkers "to provide higher accuracy for early-stage cancer diagnostics," the firm noted.
Kuo said Wobble Genomics will also conduct a multisite cancer study beginning next year to analyze samples from a number of NHS sites across the UK. Beyond breast cancer, the company also plans to investigate RNA biomarkers for other cancer types down the road.
Spun out of the Roslin Institute at the University of Edinburgh in the summer of 2021, Wobble Genomics currently has fewer than 20 full-time employees, according to Kuo. At launch, the company received £2.2 million ($2.7 million) in seed funding from Eos Advisory, IQ Capital, and Old College Capital, in addition to over £400,000 in grant funding from Innovate UK and Scottish Enterprise.
Originally, Wobble Genomics obtained an exclusive license for Level-Up from the University of Edinburgh but it now completely owns the technology's IP, Kuo noted.
In December 2023, Wobble Genomics closed another funding round of £8.5 million, led by Mercia Ventures and BGF. Kuo said the company is using the money to continue the development of its diagnostic platform for breast cancer, adding that it might raise additional funding next year.
In addition to demonstrating the clinical utility of its diagnostic platform, Kuo said, Wobble Genomics is working to establish a database of novel transcripts, based on its clinical studies, to help uncover more biological insights for disease treatment and drug discovery.
"We are basically saying we have access to this information that no one has really seen before, and we want to work with people who are experts in different fields to really investigate and understand the value of these data that we're producing," Kuo said.