Researchers at Stanford Medicine have developed an advanced RNA-based blood test that can detect cancers, monitor treatment resistance, and identify tissue injury from non-cancerous conditions.
The test analyses cell-free RNA molecules in the bloodstream, which are byproducts of natural cell death from various tissues and organs, including cancerous tumours.
The research was co-led by Ash Alizadeh and Maximilian Diehn, with contributions from Monica Nesselbush, Bogdan Luca, and Young-Jun Jeon.
Researchers from institutions, including Massachusetts General Hospital, Harvard Medical School, and Memorial Sloan Kettering Cancer Center, also participated in the project.
The team spent over six years developing methods to target messenger RNA in blood.
Their work facilitated the identification of cancers at different stages, tracking resistance to cancer treatments, and monitoring the severity of injury to healthy tissue.
The study detailing the cell-free RNA blood test was recently published in Nature.
The test focuses on messenger RNA, which comprises less than 5% of the cell-free RNA pool and signals which genes are expressed as proteins.
Diehn said: “We have developed a sensitive, versatile new type of liquid biopsy that measures cell-free and circulating-tumour RNA and has the potential to enhance personalised medicine in cancer and non-cancer diseases.
“This approach means that the test can be used to examine blood samples currently in the freezer from a completed clinical trial, for example, and could help find a molecular signature that predicts who responded to a drug and who did not.
“We can save time by using historical samples to discover a biomarker that can then be applied in real time to patients moving forward.”
Researchers concentrated on around 5,000 genes not typically expressed in healthy individuals’ blood, significantly enhancing the test’s accuracy in identifying cancer.
The test detected cancer RNA in 73% of lung cancer cases, including early stages.
Unlike DNA-based tests, the blood test can monitor conditions without genetic mutations, such as certain causes of resistance to cancer treatments.
The team devised molecular and computational strategies to eliminate platelet interference, ensuring accurate results.
Their computational approach allowed the method to work on both newly collected and previously stored blood samples.
Beyond cancer applications, the test detected elevated normal lung RNA levels in patients with acute respiratory distress syndrome, reflecting the severity of lung damage.
It also identified normal lung RNA in healthy smokers, indicating microscopic lung injury.
Alizadeh said: “Analysis of the rare abundance genes lets us focus on the most relevant subset of RNA for detecting disease, just like archaeologists who want to learn about what people ate might focus on a subset of artifacts such as food containers or utensils.
“Unfortunately, a significant fraction of our patients who are being treated for cancer go on to have their therapy stop working, and that resistance is often based on adaptations that do not involve genetic changes, but instead altering how the cells behave or even how the cells look under a microscope.
“Our non-invasive approach has the potential of avoiding surgical biopsies and identifying these common types of resistance earlier before substantial disease burden shows up on scans or presents with symptoms like pain, providing an earlier opportunity to change treatment and improve outcomes.”
