• Study published in Journal of Extracellular Vesicles validates platform for new class of liquid biopsy: multiomic disease biology of living cells from a chosen tissue, starting with the liver
• Platform underpins FDA Breakthrough Device-designated EvoLiver™ and precision medicine programs with pharmaceutical partners

Mursla Bio, a precision medicine and diagnostics company built on tissue-specific extracellular vesicles (TS-EVs), today announced publication of a peer-reviewed study in the Journal of Extracellular Vesicles (impact factor 21.7), the founding journal of the International Society for Extracellular Vesicles. This validates the TS-EV platform for a new class of liquid biopsy: the multiomic disease biology of living cells in a chosen tissue, read from blood, starting with the liver.

In this study, which builds on work first released as a preprint in June 2025, Mursla Bio’s NEXPLOR technology selectively enriched hepatocyte-derived EVs (h-EVs) over EVs from other tissues (lung, kidney, breast, adipose and muscle) and from the blood cells that dominate plasma. The multiomic content of h-EVs was analyzed against bulk EV preparations of the same clinical plasma samples, each under 2 mL, from patients with hepatocellular carcinoma (HCC) or cirrhosis and from healthy donors.

H-EVs accessed a different part of the hepatocyte proteome, identifying 57% more proteins than those bulk EVs, with better reproducibility. Bulk EVs were dominated by the plasma proteins the liver secretes, such as albumin, while h-EVs were enriched in the internal machinery of hepatocytes: membrane, cytosolic and mitochondrial proteins, including EV-defining markers¹. The h-EV fraction revealed 86 proteins uniquely detected or significantly increased in liver disease against healthy donors, compared with 4 unique proteins and no significant differential signal in bulk EVs. These 86 reflected what cirrhosis and HCC shared: fibrosis, disordered fat metabolism and inflammation. Comparing HCC with cirrhosis, the h-EV fraction resolved HCC-defining proteins, and a wider set of proteins that cohered as a network. Paired bulk EVs yielded neither.

Small-RNA sequencing supported a similar conclusion in a second molecular layer. In the same comparison, the h-EV fraction yielded fewer differentially expressed microRNAs than paired bulk EVs, yet only the h-EV microRNAs mapped to HCC signaling, while the bulk set mapped to a more generalized inflammatory response. The same h-EVs were present in the bulk EV preparation, suggesting that the lack of tissue specificity holding back microRNAs as liquid biopsy biomarkers² could be overcome.

The NEXPLOR technology described in the manuscript is a core component of Mursla Bio’s broader TS-EV platform. The hepatocyte panel is Mursla Bio’s first; the discovery and orthogonal validation route behind it is designed to extend to other tissues, and further panels are in development.

The platform has wide applications across clinical diagnostics, from disease surveillance to molecular residual disease (MRD), and precision medicine, including patient stratification, pharmacodynamic biomarkers and companion diagnostics.

Dr Tomás Dias, Chief Scientific Officer of Mursla Bio, said: “EVs are released by virtually every tissue into the bloodstream. They carry health and disease markers that can be traced back to their origin, much as a tissue biopsy would. To our knowledge, this is the most comprehensive validation to date of a platform for tissue-specific EV isolation from human plasma.”

Pierre Arsène, Founder and CEO of Mursla Bio, added: “Much of liquid biopsy has focused on measuring more analytes. Our thesis is that biological context matters as much as analytical depth. That is the foundation of EvoLiver and of the precision medicine programs we are building with pharma partners.”

1. Tissue-specific isolation of hepatocyte extracellular vesicles from human plasma enables tissue-resolved proteomic and miRNA profiling, Journal of Extracellular Vesicles, 2026; 15:e70372. https://doi.org/10.1002/jev2.70372
2. MicroRNAs in oncology: a translational perspective in the era of AI, Nature Reviews Clinical Oncology, 2026.

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