A recent study published in Molecular Cell has revealed a unique molecular “fingerprint” present in cancer cells, detectable through rapid and non-invasive methods. Researchers at the Centre for Genomic Regulation (CRG) in Barcelona utilized nanopore direct RNA sequencing to identify chemical modifications on ribosomal RNA (rRNA) that differentiate healthy and cancerous tissues. This discovery could pave the way for earlier cancer diagnoses using portable devices.
Ribosomal RNA Holds Diagnostic Potential
Ribosomes were once thought to be identical across tissues. The study, led by Eva Novoa, a researcher at CRG, challenges this notion, demonstrating that rRNA—the major component of ribosomes—undergoes chemical modifications that vary by tissue and disease state.
"Our ribosomes are not all the same. They are specialized in different tissues and carry unique signatures that reflect what's happening inside our bodies," stated Novoa. These modifications, collectively described as an “epitranscriptomic fingerprint,” act as a molecular identifier for tissues and diseases.
Focusing on cancer, the researchers analyzed rRNA from various tissues, including the brain, heart, and lungs. They found that cancer cells often exhibit “hypomodified” rRNA, meaning they lack some chemical marks typically found in healthy cells.
High Accuracy in Lung Cancer Detection
The study examined tissue samples from 20 patients with early-stage lung cancer, confirming that rRNA hypomodification distinguishes cancer cells from healthy ones. Using this data, the team developed an algorithm capable of classifying samples based solely on their rRNA fingerprints.
The test delivered outstanding accuracy in separating lung cancer from healthy samples. “Most lung cancers aren’t diagnosed until late stages of development,” said Ivan Milenkovic, the study’s first author. “Here we could detect it much earlier than usual, which could one day help buy patients valuable time.”
Nanopore Sequencing Enables Real-Time Analysis
Central to these findings is nanopore direct RNA sequencing, a technology that allows researchers to examine rRNA and its modifications in their natural state. Traditional sequencing techniques often discard or alter rRNA, making nanopore sequencing particularly transformative.
“Scientists typically got rid of ribosomal RNAs because they saw it as redundant information that would get in the way of our experiments,” stated Novoa. “Fast forward a few years, we’ve taken this data out of the junkyard and turned it into a gold mine, especially when information about chemical modifications is captured. It’s an incredible turnaround.”
Nanopore sequencing is not only precise but also portable. The devices, small enough to fit in the palm of a hand, analyze biological samples in real-time. This efficiency means that scanning as few as 250 RNA molecules from a tissue sample is sufficient for detection—well within the capacity of typical nanopore devices.
Toward Less Invasive Diagnostics
While the current study relies on tissue samples, the researchers envision a future where circulating RNA from a blood sample could be used to detect cancer. This less invasive approach would be a significant advancement in diagnostics.
However, more research is needed before such methods can enter clinical practice. “We're just scratching the surface," cautioned Milenkovic. "We need larger studies to validate these biomarkers across diverse populations and cancer types."
Understanding rRNA Modifications
Beyond diagnostics, the study raises intriguing questions about the biological role of rRNA modifications. If these changes contribute to cancer cell survival or proliferation, targeting the mechanisms responsible could open avenues for therapeutic intervention.
“We are slowly but surely unraveling this complexity,” explained Novoa. “It’s only a matter of time before we can start understanding the language of the cell.”
Publication Details
Milenkovic I, Cruciani S, Llovera L, et al. Epitranscriptomic rRNA fingerprinting reveals tissue-of-origin and tumor-specific signatures. Molecular Cell. 2024;109(11):1097-2765. doi:10.1016/j.molcel.2024.11.014.