A telegram from your cells

Exosomes are extracellular vesicles, that are involved in physiological processes like coagulation, waste management and intercellular communication. Photo by Getty.

Cedars-Sinai Cancer Investigators Use AI Technology to “Fingerprint” Messages Sent Between Cells, Paving the Way for a New Understanding of Health and Diseas

The body’s cells communicate with each other via biological “telegrams” called extracellular vesicles (EVs). Cedars-Sinai Cancer investigators have created the first system for profiling EVs so that scientists can begin to understand their messages. Their study, published in the peer-reviewed journal ACS Nano, is the first step toward a better understanding of EV biology and the development of new clinical tests to measure disease progression in real time.

“Our hope is to be able to associate different EV fingerprints with different diseases and responses to treatment,” said Dolores Di Vizio, MD, PhD, professor of Urology, co-leader of the Cancer Biology Program at Cedars-Sinai Cancer and co-senior author of the study. “As cancer scientists, we are primarily interested in applying this new technology to the creation of ‘liquid biopsy’ tests for cancer detection. However, because all cells in the body produce EVs, we also envision its future use to identify biomarkers of cardiovascular disease, autoimmune diseases or neurological disorders.”

EVs are made of an outer envelope of fat molecules filled with “cargo” that might include RNA, proteins and lipids. The tiny particles vary greatly in size, with the largest being about one-tenth the width of a human hair.

“Prior to this study, EVs were mainly classified by their size and by how they were generated,” said Andries Zijlstra, PhD, adjunct associate professor of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center and co-senior author of the study. “The goal of this study was to create a technology that could classify EVs based on several of their characteristics and their various combinations.”

EVs are studied using flow cytometry. The particles are separated from a blood sample, then suspended in fluid flowing through a laser beam that measures their physical and chemical characteristics.

To create the new technique of EV fingerprinting, investigators measured 20 different EV characteristics and used machine learning to classify various combinations of membrane composition, cargo, size and method of generation.

“The concept is that cells in different disease states will produce EVs with a unique fingerprint,” Di Vizio said. “For instance, we have prostate cancer cell lines, and each of these lines now has an EV fingerprint associated with it.”

EV Fingerprinting overview

(A) Schematic representation of EV biogenesis through exocytosis and ectocytosis leading to the formation of exosomes and ectosomes, respectively. “EE” early endosome, “MVB” multivesicular body. (B) Extrinsic labeling of EVs using the lipophilic dye, di-8-ANEPPS (di8), and fluorescently conjugated antibody or intrinsic labeling using fluorescent fusion proteins (pHluorin_M153R tagged CD63). (C) Optical triggering on the CellStream uses a time delay integration charge-coupled device (TDI-CCD) to collect measurements (including Intensity, RawMax Pixel, Area, and Aspect Ratio) simultaneously for up to six emission wavelengths (em = 456, 528, 583, 611, 702, and 773). (D) A matrix histogram of measurements for the five emission wavelengths collected for di8 excited at 488 nm demonstrates the multiparametric nature of EV features collected from this lipophilic, environment sensitive dye. (E) Dimensional reduction embedding and clustering of multiparametric EV features using UMAP. (F) Cluster identification was done using HDBSCAN. (G) Representative results of a UMAP density plot comparing two paired samples.

A further advantage of EV fingerprinting is that it can be performed directly from a blood sample without the laborious process of separating out the EVs, Di Vizio said. This means the technology can be used to develop “liquid biopsy” tests that can be used in clinics.

“Our EV fingerprinting method is faster than most liquid biopsy approaches that require the isolation of EVs,” Di Vizio said. “These tests could be used for diagnosis, monitoring progression of disease and response to treatment, and perhaps even predicting patient outcomes.”

Investigators will next explore pairing specific EV fingerprints with specific disease states, beginning with aggressive forms of cancer, Di Vizio said.

“This type of translational science is key to our mission at Cedars-Sinai Cancer,” said Dan Theodorescu, MD, PhD, director of Cedars-Sinai Cancer and the PHASE ONE Foundation Distinguished Chair and Director at the Samuel Oschin Comprehensive Cancer Institute. “By developing practical new testing techniques that allow us to precisely measure the state of a patient’s health, we can promote the concept of ‘precision prevention,’ expand the promise of precision therapy in oncology and save patients’ lives.”

SourceCedars-Sinai

von Lersner AK, Fernandes F, Ozawa PMM, Jackson M, Masureel M, Ho H, Lima SM, Vagner T, Sung BH, Wehbe M, Franze K, Pua H, Wilson JT, Irish JM, Weaver AM, Di Vizio D, Zijlstra A. (2024) Multiparametric Single-Vesicle Flow Cytometry Resolves Extracellular Vesicle Heterogeneity and Reveals Selective Regulation of Biogenesis and Cargo Distribution. ACS Nano 18(15):10464-10484. [article]

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