HMN 2026: What is oncRNA From discovery to liquid biopsy

After being described in 2018, researchers knew they had something interesting with T3p, a single small RNA found in breast cancer but absent from normal tissue. The molecule took the team on a six-year journey to systematically map orphan non-coding RNAs (oncRNAs) across all major cancer types, understand which ones actually drive disease, and demonstrate their utility in monitoring patients through simple blood tests.

In a paper published in Cell Reports Medicine, the researchers show how they went from mining cancer genome data to building machine learning classifiers, developing large-scale functional screens in mice, and finally validating these RNAs as blood-based biomarkers in nearly 200 breast cancer patients.

Orphan RNAs exist everywhere in cancer

The first major finding was that what they saw in breast cancer wasn’t unique. The researchers systematically analyzed small RNA sequencing data from The Cancer Genome Atlas across 32 cancer types and found approximately 260,000 of these cancer-specific small RNAs—oncRNAs—distributed across every cancer examined.

The appearance of these RNAs isn’t random and each cancer type produces a distinct pattern of oncRNA expression. For example, lung cancer cells express a different set of oncRNAs than breast cancers. These patterns can be leveraged by machine learning models to classify cancer type identities with 90.9% accuracy. The team validated these patterns in an independent cohort of 938 tumors, achieving 82.1% accuracy.

Variations also exist within specific cancers: Basal breast tumors produce different oncRNA patterns than luminal tumors, indicating there may be subdivisions that aren’t yet known. This suggests that these molecules are telling us something fundamental about cancer cell state. In other words, patterns of oncRNA presence and absence serve as “digital molecular barcodes” that capture cancer cell identity, from cancer type to subtype and even cellular states.

Some oncRNAs actually drive cancer

While this new set of cancer biomarkers turns out to be very useful, the team was also interested in knowing whether cancer cells can adopt some of these cancer emergent RNA species to engineer new oncogenic pathways.

To find out, the team created large-scale screening libraries encoding roughly 400 oncRNAs across breast, colon, lung, and prostate tumors and introduced them into cancer cells using lentiviral vectors. For half, they overexpressed the oncRNAs. For the other half, they used “Tough Decoy” constructs to knock them down. The team then injected these cells into mice and looked for which oncRNAs gave cells a competitive advantage during tumor growth.

About 5% showed clear phenotypes in xenograft mouse models. The researchers validated two breast cancer oncRNAs in detail. One promoted epithelial-mesenchymal transition, a critical process for cancer progression and metastasis. The other activated E2F target genes, driving proliferation. Both significantly increased tumor growth and metastatic colonization in independent cell line models.

When the team looked back at patient tumor data, they found that tumors expressing these same oncRNAs showed similar pathway modulations. Seeing the same biological patterns in TCGA samples and their own models gave them confidence in their results.

They’re secreted into blood

Most clinically exciting is that cancer cells release these RNAs into the bloodstream, and tracking them can tell you how patients are doing.

The researchers profiled cell-free RNA from 25 cancer cell lines across nine tissue types and found that about 30% of oncRNAs are actively secreted. To validate, they analyzed serum from 192 breast cancer patients in the I-SPY 2 neoadjuvant chemotherapy trial, collecting blood before and after treatment and calculated the change in total oncRNA burden (?oncRNA below).

That simple metric was remarkably predictive. Patients with high residual oncRNA after chemotherapy had nearly four-fold worse overall survival. This remained true even when they controlled for standard clinical measures like pathologic complete response and residual cancer burden.

This was a moonshot. They knew these RNAs showed up in blood, but whether they’d be informative in actual patient samples was unknown. The fact that they needed only 1 milliliter of serum and still got a strong signal was surprising.

This addresses a real clinical problem: monitoring minimal residual disease in breast cancer with markers such as cell-free DNA is challenging because tumors don’t shed much DNA, especially in early stages. RNA-based monitoring might offer a way forward because cancer cells actively secrete RNA rather than passively shedding DNA.

What’s next?

There are still big open biological and clinical questions. How exactly do these functional oncRNAs work? Are they interacting with proteins? With other RNAs? Could oncRNA dynamics be used in real-time to guide treatment decisions? Could it catch cancer recurrence earlier? Could they help clinicians better stratify patients to guide treatment? These will require deeper study and larger, prospective trials to answer.

But the core findings that oncRNAs provide cancer-specific signals in blood are already moving toward translation. The team is closely involved with a biotech company, Exai Bio (Hani is a co-founder), to develop oncRNA-based diagnostics, and the company has been building AI models and diverse datasets for cancer detection and classification.

Any good translational work really does take a village, but when you’re processing tens of thousands of samples computationally, it’s easy to lose sight of the fact that each one represents a patient’s story. These samples come from people who enrolled in trials, gave their blood, and participated in research hoping it would help others. Being able to honor that through rigorous science is what motivates the whole team.

The researchers think oncRNAs represent a new class of cancer-emergent molecules that function as both drivers and biomarkers. The team hope that this open-source resource opens new directions for the field.

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