The concept of testing blood or urine to find markers that help diagnose or treat disease holds great promise. But as technology has improved to allow researchers to examine tiny fragments of RNA for that purpose, one major problem has hindered its potential.

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"Different people are using different methods to sequence small RNA, and sometimes getting different results. If it keeps going on like that, it will be hard for the field to make progress," says Muneesh Tewari, M.D., Ph.D., professor of internal medicine and biomedical engineering at Michigan Medicine.

Tewari's lab led a group of nine labs across the United States and the Netherlands, brought together through the National Institutes of Health, that sought to solve the problem of inconsistent testing methods.

The consortium examined nine different methods for RNA sequencing to understand and standardize the best way to sequence small RNAs. The goal was to create a process that could be reproduced from one lab to the next.

Liquid biopsy involves detecting DNA- or RNA-based markers associated with a specific disease that are present in blood, urine or other body fluids. RNA sequencing is focused primarily on small RNA outside the cells, such as microRNA. These short RNA molecules can become altered in diseases such as cancer, providing a clue to help spot disease in its earliest stages.

But blood and urine contain only a tiny amount of RNA outside of cells, making it challenging to sequence.

Which is why consistency in testing procedure is crucial.

"Liquid biopsy for RNA is an exciting new field for diagnostics. But the field needed this kind of consortium to come together, because of the challenge of different methods leading to results that are not reproducible," Tewari says.

He also notes a strength of this work is in bringing together varied expertise, from molecular biologists to computational and bioinformatics specialists.

Variations seen among tests

For this study, published in Nature Biotechnology, researchers prepared samples identically and sent them across the country for each of the nine labs to analyze.

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Each lab used multiple testing protocols to sequence four different samples, including a plasma sample and three synthetic RNA samples. Altogether, they tested nine different sequencing protocols, including four commercially available kits and five protocols developed by the labs.

Combined, the data yielded more than 5 billion sequencing reads.

And the disparities were highly evident: "We realized that not only different methods produce different results, but also any small change within a given protocol can introduce an important degree of variation," says lead study author Maria D. Giraldez, M.D., Ph.D., a postdoctoral research fellow in Tewari's lab.

"In order to compare results across labs, it is key to use a common and highly standardized protocol."

Researchers found that different methods used for sequencing produced different — and often inaccurate — estimates of how abundant any individual marker was. The methods developed by the consortium labs improved the accuracy of these estimates.

Establishing uniform standards

When RNA sequencing was used to compare the relative amounts of individual microRNAs between different samples, however, all the methods produced accurate and reproducible estimates.

"We found there was not a lot of variability if you used the same protocol across multiple labs," says study author Ryan Spengler, Ph.D., a postdoctoral fellow in Tewari's lab. "This means, if you want to coordinate a study between different labs, the key is to keep to the same protocol — whatever it is. Then, you can compare your results."

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The analysis lays a foundation to help researchers create standard procedures around their protocols while positioning the field of RNA sequencing and liquid biopsies to move forward.

Researchers have made the synthetic reference material available, which means other researchers across the country can run their tests and compare results to what the consortium of labs found.

Meanwhile, Tewari's lab is continuing to work on improving the methodology to be more useful for discovering biomarkers.