Title | Liquid Biopsy Proteomics in Ophthalmology. |
Publication Type | Journal Article |
Year of Publication | 2024 |
Authors | Wolf, Julian, Franco Joel A., Yip Rui, Dabaja Mohamed Ziad, Velez Gabriel, Liu Fei, Bassuk Alexander G., Mruthyunjaya Prithvi, Dufour Antoine, and Mahajan Vinit B. |
Journal | J Proteome Res |
Volume | 23 |
Issue | 2 |
Pagination | 511-522 |
Date Published | 2024 Feb 02 |
ISSN | 1535-3907 |
Keywords | Artificial Intelligence, Biopsy, Humans, Liquid Biopsy, Ophthalmology, Proteins, Proteomics |
Abstract | Minimally invasive liquid biopsies from the eye capture locally enriched fluids that contain thousands of proteins from highly specialized ocular cell types, presenting a promising alternative to solid tissue biopsies. The advantages of liquid biopsies include sampling the eye without causing irreversible functional damage, potentially better reflecting tissue heterogeneity, collecting samples in an outpatient setting, monitoring therapeutic response with sequential sampling, and even allowing examination of disease mechanisms at the cell level in living humans, an approach that we refer to as TEMPO (Tracing Expression of Multiple Protein Origins). Liquid biopsy proteomics has the potential to transform molecular diagnostics and prognostics and to assess disease mechanisms and personalized therapeutic strategies in individual patients. This review addresses opportunities, challenges, and future directions of high-resolution liquid biopsy proteomics in ophthalmology, with particular emphasis on the large-scale collection of high-quality samples, cutting edge proteomics technology, and artificial intelligence-supported data analysis. |
DOI | 10.1021/acs.jproteome.3c00756 |
Alternate Journal | J Proteome Res |
PubMed ID | 38171013 |
PubMed Central ID | PMC10845144 |
Grant List | P30 EY026877 / EY / NEI NIH HHS / United States R01 EY030151 / EY / NEI NIH HHS / United States R01 EY031360 / EY / NEI NIH HHS / United States R01 EY031952 / EY / NEI NIH HHS / United States |