Molecular CSI: How cancer ‘fingerprints’ could yield diagnoses earlier than ever

BARCELONA — In the cellular world’s version of CSI, scientists have discovered that our cells leave behind telltale “fingerprints” that could blow the cover on cancer’s stealthy operation. The breakthrough comes not from DNA, as you might expect, but from the humble ribosome – the cell’s protein-making powerhouse that we’ve overlooked for decades. These molecular signatures, unique to different tissues and altered in cancer, could potentially identify tumors using just a tiny sample of tissue and a portable device no bigger than the palm of your hand.

The discovery, reported by researchers at the Centre for Genomic Regulation in Barcelona, centers around ribosomes — the microscopic machines that manufacture all the proteins our bodies need to function. While scientists have long viewed ribosomes as identical workers in our cellular factories, this new research reveals they carry distinct chemical markers that vary between different types of tissues and change when cells become cancerous.

“Our ribosomes are not all the same,” explains Eva Maria Novoa, the study’s lead author, in a statement. “They are specialized in different tissues and carry unique signatures that reflect what’s happening inside our bodies.”

Researchers add that it’s akin to each tissue type, leaving its own molecular return address on its cellular machinery.

To understand the significance of this finding, imagine each ribosome as a complex machine made partly of RNA – a molecular cousin of DNA. These RNA molecules can be decorated with over 220 different chemical modifications, like adding methyl groups or converting one building block to another. The presence and pattern of these modifications can fine-tune how the ribosome works, similar to how tiny adjustments to a machine’s parts can alter its performance.

The research team used cutting-edge technology called nanopore direct RNA sequencing to examine these modification patterns across different mouse tissues (brain, heart, liver, and testis) at various developmental stages from embryo to adult. Think of the technology as a molecular scanner that can read the chemical structure of RNA molecules as they pass through microscopic pores, detecting even subtle modifications in their composition.

The results published in the journal Molecular Cell were striking: each tissue type had its own distinct pattern of RNA modifications – a unique molecular fingerprint. Even more intriguing, when the researchers examined matched pairs of normal and cancerous tissue from 20 lung cancer patients, they found that cancer tissues showed consistently different modification patterns compared to healthy tissues from the same patients.

Perhaps most remarkably, the team discovered they could accurately identify cancer samples using just 250 RNA molecules – a tiny fraction of what’s typically needed for other diagnostic techniques. This has enormous implications for early cancer detection, particularly for diseases like lung cancer, where early diagnosis is crucial but often challenging.

“95% of human RNA is ribosomal RNA. They are very prevalent in our cells,” adds Dr. Novoa, highlighting why these molecules make excellent diagnostic targets.

The abundance of ribosomal RNA, traditionally seen as a nuisance in genetic studies, may actually be a major advantage for diagnostic purposes.

The team termed their approach “epitranscriptomic fingerprinting,” a method that could revolutionize how we identify the tissue origin of cancer samples and detect cancer itself. The technique works with small, portable sequencing devices, opening the possibility of quick, accurate cancer testing that could be performed in clinical settings.

In a twist of scientific irony, what researchers once considered cellular “background noise” may become a powerful tool in the fight against cancer.

“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,” Dr. Novoa notes.