Prostate cancer extracellular vesicle digital scoring assay - a rapid noninvasive approach for quantification of disease-relevant mRNAs

Extracellular Vesicles as Liquid Biopsy Biomarkers across the Cancer Journey: From Early Detection to Recurrence

BACKGROUND

Cancer is a dynamic process and thus requires highly informative and reliable biomarkers to help guide patient care. Liquid-based biopsies have emerged as a clinical tool for tracking cancer dynamics. Extracellular vesicles (EVs), lipid bilayer delimited particles secreted by cells, are a new class of liquid-based biomarkers. EVs are rich in selectively sorted biomolecule cargos, which provide a spatiotemporal fingerprint of the cell of origin, including cancer cells.

CONTENT

This review summarizes the performance characteristics of EV-based biomarkers at different stages of cancer progression, from early malignancy to recurrence, while emphasizing their potential as diagnostic, prognostic, and screening biomarkers. We discuss the characteristics of effective biomarkers, consider challenges associated with the EV biomarker field, and report guidelines based on the biomarker discovery pipeline.

SUMMARY

Basic science and clinical trial studies have shown the potential of EVs as precision-based biomarkers for tracking cancer status, with promising applications for diagnosing disease, predicting response to therapy, and tracking disease burden. The multi-analyte cargos of EVs enhance the performance characteristics of biomarkers. Recent technological advances in ultrasensitive detection of EVs have shown promise with high specificity and sensitivity to differentiate early-cancer cases vs healthy individuals, potentially outperforming current gold-standard imaging-based cancer diagnosis. Ultimately, clinical translation will be dictated by how these new EV biomarker-based platforms perform in larger sample cohorts. Applying ultrasensitive, scalable, and reproducible EV detection platforms with better design considerations based upon the biomarker discovery pipeline should guide the field towards clinically useful liquid biopsy biomarkers.

Tumor-derived systems as novel biomedical tools-turning the enemy into an ally

Cancer is a complex illness that presents significant challenges in its understanding and treatment. The classic definition, "a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body," fails to convey the intricate interaction between the many entities involved in cancer. Recent advancements in the field of cancer research have shed light on the role played by individual cancer cells and the tumor microenvironment as a whole in tumor development and progression. This breakthrough enables the utilization of the tumor and its components as biological tools, opening new possibilities. This article delves deeply into the concept of "tumor-derived systems", an umbrella term for tools sourced from the tumor that aid in combatting it. It includes cancer cell membrane-coated nanoparticles (for tumor theranostics), extracellular vesicles (for tumor diagnosis/therapy), tumor cell lysates (for cancer vaccine development), and engineered cancer cells/organoids (for cancer research). This review seeks to offer a complete overview of the tumor-derived materials that are utilized in cancer research, as well as their current stages of development and implementation. It is aimed primarily at researchers working at the interface of cancer biology and biomedical engineering, and it provides vital insights into this fast-growing topic.

Polymerase-Driven Logic Signal Amplification for the Detection of Small Extracellular Vesicle Surface Proteins and the Identification of Breast Cancer

Small extracellular vesicles (sEVs) derived from tumors contain a vast amount of cellular information and are regarded as a potential diagnostic biomarker for noninvasive cancer diagnosis. Nevertheless, it remains challenging to accurately measure sEVs from clinical samples due to the low abundance of these vesicles as well as their phenotypic heterogeneity. Herein, a polymerase-driven logic signal amplification system (PLSAS) was developed for the high-sensitivity detection of sEV surface proteins and breast cancer (BC) identification. Aptamers were introduced to serve as sensing modules to specifically recognize target proteins. By changing the input DNA sequences, two polymerase-driven primer exchange reaction systems were rationally designed for DNA logic computing. This allows for autonomous targeting of a limited number of targets using "OR" and "AND" logic, leading to a significant increase in fluorescence signals and enabling the specific and ultrasensitive detection of sEV surface proteins. In this work, we investigated surface proteins of mucin 1 (MUC1) and the epithelial cell adhesion molecule (EpCAM) as model proteins. When MUC1 or EpCAM proteins were used as single signal input in the "OR" DNA logic system, the detection limit of sEVs was 24 or 58 particles/μL, respectively. And MUC1 and EpCAM proteins of sEVs can be simultaneously detected in the AND logic method, which can significantly reduce the effect of phenotypic heterogeneity of sEVs to distinguish the source of sEVs derived from various mammary cell lines, such as MCF-7, MDA MB 231, SKBR3, and MCF-10A. The approach has achieved high discrimination in serologically tested positive BC samples (AUC 98.1%) and holds significant potential in advancing the early diagnosis and prognostic assessments of BC.

Assessing Breast Cancer Molecular Subtypes Using Extracellular Vesicles' mRNA

Extracellular vesicles (EVs) carry RNA cargo that is believed to be associated with the cell-of-origin and thus have the potential to serve as a minimally invasive liquid biopsy marker for supplying molecular information to guide treatment decisions (i.e., precision medicine). We report the affinity isolation of EV subpopulations with monoclonal antibodies attached to the surface of a microfluidic chip that is made from a plastic to allow for high-scale production. The EV microfluidic affinity purification (EV-MAP) chip was used for the isolation of EVs sourced from two-orthogonal cell types and was demonstrated for its utility in a proof-of-concept application to provide molecular subtyping information for breast cancer patients. The orthogonal selection process better recapitulated the epithelial tumor microenvironment by isolating two subpopulations of EVs: EVEpCAM (epithelial cell adhesion molecule, epithelial origin) and EVFAPα (fibroblast activation protein α, mesenchymal origin). The EV-MAP provided recovery >80% with a specificity of 99 ± 1% based on exosomal mRNA (exo-mRNA) and real time-droplet digital polymerase chain reaction results. When selected from the plasma of healthy donors and breast cancer patients, EVs did not differ in size or total RNA mass for both markers. On average, 0.5 mL of plasma from breast cancer patients yielded ∼2.25 ng of total RNA for both EVEpCAM and EVFAPα, while in the case of cancer-free individuals, it yielded 0.8 and 1.25 ng of total RNA from EVEpCAM and EVFAPα, respectively. To assess the potential of these two EV subpopulations to provide molecular information for prognostication, we performed the PAM50 test (Prosigna) on exo-mRNA harvested from each EV subpopulation. Results suggested that EVEpCAM and EVFAPα exo-mRNA profiling using subsets of the PAM50 genes and a novel algorithm (i.e., exo-PAM50) generated 100% concordance with the tumor tissue.