Ultrasensitive and High‐Resolution Protein Spatially Decoding Framework for Tumor Extracellular Vesicles

Abstract

Proteins localized on the surface or within the lumen of tumor‐derived extracellular vesicles (EVs) play distinct roles in cancer progression. However, quantifying both populations of proteins within EVs has been hampered due to the limited sensitivity of the existing protein detection methods and inefficient EV isolation techniques. In this study, the eSimoa framework, an innovative approach enabling spatial decoding of EV protein biomarkers with unmatched sensitivity and specificity is presented. Using the luminal eSimoa pipeline, the absolute concentration of luminal RAS or KRASG12D proteins is released and measured, uncovering their prevalence in pancreatic tumor‐derived EVs. The pulldown eSimoa pipeline measured absolute protein concentrations from low‐abundance EV subpopulations. The eSimoa assays detected EVs in both PBS and plasma samples, confirming their applicability across diverse clinical sample types. Overall, the eSimoa framework offers a valuable tool to (1) detect EVs at concentrations as low as 105 EV mL−1 in plasma, (2) quantify absolute EV protein concentrations as low as fM, and (3) decode the spatial distribution of EV proteins. This study highlights the potential of eSimoa in identifying disease‐specific EV protein biomarkers in clinical samples with minimal pre‐purification, thereby driving advancements in clinical translation.

Before Translating Extracellular Vesicles into Personalized Diagnostics and Therapeutics: What We Could Do

“…While advanced super-resolution microscopy methods have emerged to overcome these challenges, , they still have limitations, including extensive EV labeling and purification procedures and limited sensitivity. Therefore, to address these technical gaps, single-EV or “digital” EV profiling methods − have been developed, offering improved sensitivity, throughput, multiplexing capacities, and requiring minimal prepurification steps. For example, Lin et al developed a dual-target aptamer detection probe specific for EpCAM and PD-L1, enabling a quantitative proximity ligation assay (PLA) to assess PD-L1 expression on tumor-derived EVs .…”

“…To advance EVs’ diagnostic and therapeutic potential in cancer research, our team has pioneered innovative digital EV profiling approaches to decode these EV protein biomarkers at single EV resolution, collectively known as the eSimoa framework (Figure ). This framework seamlessly integrates EV isolation with ultrasensitive single-molecule array (Simoa) protein detection technology . Simoa, one of the digital ELISA methods, is renowned for its unrivaled sensitivity, capable of quantifying proteins at attomolar concentrations, representing a million-fold improvement over existing methods .…”

“…Simoa, one of the digital ELISA methods, is renowned for its unrivaled sensitivity, capable of quantifying proteins at attomolar concentrations, representing a million-fold improvement over existing methods . The significance of this work lies in its potential to advance the field of EV research toward personalized diagnostics and therapeutics, highlighted as a Front Cover Story in Advanced Science . The eSimoa framework (Figure ) consists of three complementary and orthogonal pipelines: surface eSimoa, luminal eSimoa, and surface-luminal eSimoa (pulldown eSimoa).…”

“…These advancements could lead to more efficient analyses with smaller sample sizes and reduced assay times. Our eSimoa framework (Figure ) not only provides a novel tool for studying cancer-specific EV protein biomarkers in clinical samples with minimal prepurification steps, but also enables comprehensive profiling and quantification of surface and luminal EV proteins, providing a detailed landscape of their spatial distribution within tumor EVs. The application of Simoa technology in EV-related cancer research is still nascent, with only seven previous studies identified. ,− However, with its “best-in-class” ultrasensitivity and ability to greatly simplify the EV research workflow, the eSimoa framework stands out as a promising tool in the emerging EV field.…”

Addressing Heterogeneity in direct analysis of Extracellular Vesicles and analogues using Membrane-Sensing Peptides as Pan-Affinity Probes

“…The unparalleled sensitivity of this digital detection platform, integrated into the high-throughput Simoa® instruments, favoured its diffusion in clinical centers for monitoring of biomarkers in the field of neurological diseases, cancer and other chronic diseases. Recently, SiMoA significant clinical potential have been largely documented in EV analysis 36, 37, 38, 39 .…”