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Nanopore direct RNA sequencing finds cancer's 'fingerprint' to improve early detection

Cancer 'fingerprint' can improve early detection

Artistic concept of an 'epitranscriptomic' fingerprint. Credit: Queralt Tolosa/Centro de Regulación Genómica

Different types of cancer have unique molecular "fingerprints" which are detectable in early stages of the disease and can be picked up with near-perfect accuracy by small, portable scanners in just a few hours, according to a study published today in the journal Molecular Cell.

The discovery by researchers at the Centre for Genomic Regulation (CRG) in Barcelona sets the foundation for creating new, non-invasive diagnostic tests that detect different types of cancer faster and earlier than currently possible.

The study centers around the ribosome, the protein factories of a cell. For decades, ribosomes were thought to have the same blueprint across the human body. However, researchers discovered a hidden layer of complexity—tiny chemical modifications which vary between different tissues, developmental stages, and disease.

"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," says ICREA Research Professor Eva Novoa, lead author of the study and researcher at the CRG. "These subtle differences can tell us a lot about health and disease."

Ribosomes are made of proteins and a special type of RNA molecule called ribosomal RNA (rRNA). rRNA molecules are the target of chemical modifications, affecting the ribosome's function. "95% of human RNA is ribosomal RNA. They are very prevalent in our cells," adds Dr. Novoa.

The researchers looked for all types of chemical modifications across human and mouse rRNA from many different tissues including the brain, heart, liver, and testis. They discovered that each tissue has a unique pattern of rRNA modifications—which they call an "epitranscriptomic fingerprint."

"The fingerprint on a ribosome tells us where a cell comes from," says Dr. Ivan Milenkovic, first author of the study. "It's like each tissue leaves its address on a tag in case its cells end up in the lost and found."

The team found different sets of fingerprints in diseased tissue samples from patients with cancer, particularly in the lung and testis. "The cancer cells are 'hypomodified," meaning they constantly lose some of these chemical marks," says Dr. Milenkovic. "We thought this could be a powerful biomarker," he adds.

The study looked at lung cancer more closely. The researchers obtained normal and diseased tissues from 20 patients with stage I or stage II lung cancer and confirmed that the rRNA from cancer cells is hypomodified. They used the data to train an algorithm which can classify the samples based solely on data from this unique molecular fingerprint.

The test achieved near-perfect accuracy in distinguishing between lung cancer and healthy tissue. "Most lung cancers aren't diagnosed until late stages of development. Here we could detect it much earlier than usual, which could one day help buy patients valuable time," says Dr. Milenkovic.

The study was possible thanks to a new technology called nanopore direct RNA sequencing, which permits the direct analysis of rRNA molecules with all its modifications. "It allows us to see the modifications as they are, in their natural context," says Dr. Novoa.

Before the advent of nanopore sequencing, conventional techniques would process RNA molecules in such a way that it would remove the chemical modifications before researchers could study them.

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"Scientists typically got rid of ribosomal RNAs because they saw it as redundant information that would get in the way of our experiments. 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," says Dr. Novoa.

The advantage of nanopore sequencing is that it relies on small, portable sequencing devices that can fit in the palm of a hand. Researchers can insert biological samples into the machine, which captures and scans RNA molecules in real time.

The study could distinguish cancer and normal cells by scanning as few as 250 RNA molecules obtained from tissue samples. This is a fraction of what a typical nanopore sequencing device is capable of. "It is feasible to develop a rapid, highly accurate test that looks for cancer's ribosomal fingerprint using minimal amounts of tissue," says Dr. Novoa.

In the long term, the researchers want to create a diagnostic method which can detect cancer's fingerprint in circulating RNA in the blood. This would be a less invasive approach because it would only require a blood sample rather than taking tissue samples from patients.

The authors of the study caution that more work is needed before the approach can be used for clinical benefits. "We're just scratching the surface," says Dr. Milenkovic. "We need larger studies to validate these biomarkers across diverse populations and cancer types."

One of the big questions yet to explore is why the modifications change in cancer in the first place. If rRNA modifications are helping cells produce proteins that promote uncontrolled growth and survival, researchers could identify the mechanisms responsible for adding or removing the modifications, potentially leading to new ways of reversing harmful changes.

"We are slowly but surely unraveling this complexity," says Dr. Novoa. "It's only a matter of time before we can start understanding the language of the cell," she concludes.

More information: Ivan Milenkovic et al. Epitranscriptomic rRNA fingerprinting reveals tissue-of-origin and tumor-specific signatures, Molecular Cell (2024). DOI: 10.1016/j.molcel.2024.11.014. www.cell.com/molecular-cell/fu … 1097-2765(24)00919-5

Provided by Center for Genomic Regulation

Citation: Nanopore direct RNA sequencing finds cancer's 'fingerprint' to improve early detection (2024, December 10) retrieved 10 December 2024 from https://phys.org/news/2024-12-nanopore-rna-sequencing-cancer-fingerprint.html

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