Size-exclusion chromatography combined with DIA-MS enables deep proteome profiling of extracellular vesicles from melanoma plasma and serum

Melanoma, a type of skin cancer, poses a significant challenge in diagnosis and treatment. While extracellular vesicles (EVs) have emerged as important players in melanoma progression, their potential as clinical biomarkers has been hindered by technical limitations. However, a recent study offers a promising solution by providing a streamlined workflow to identify EV proteins in blood samples with unprecedented depth and accuracy.

Traditionally, profiling blood-derived EV proteins has been challenging due to the complexity of protocols and the need for large sample inputs. In this study, researchers from the University of Zurich introduce a novel approach called SEC-DIA-MS, which combines size-exclusion chromatography (SEC) with deep-proteomic profiling using data-independent acquisition (DIA).

Using as little as 200 µL of plasma per patient, researchers successfully identified and quantified 2896 EV-associated proteins in a cohort of healthy donors and melanoma patients. This represents a remarkable 3.5-fold increase in depth compared to previous studies. Additionally, by depleting the 14 most abundant proteins from plasma and serum, researchers doubled the number of protein group identifications versus native blood samples.

Study workflow and overall protein identification

Fig. 1

a Study outline. Plasma and serum samples were collected from a cohort composed of age- and gender-matched healthy donors (n = 3), stage III (n = 3), and stage IV (n = 3) melanoma patients yielding 18 samples in total. For all 18 samples, three different blood compartments (native, depleted, and EVs) of plasma and serum were analyzed by mass spectrometry yielding 54 samples in total. b EV isolation workflow from 200 µL of plasma or serum by size exclusion chromatography and subsequent quality control by nano-flow cytometry (Nano FC). c Generation of a protein atlas for different blood compartments. Protein groups were determined in three different blood compartments (native, depleted, and EVs) of plasma and serum, respectively. For each plasma and serum compartment proteins from healthy donor, stage III and stage IV melanoma patients were quantified. d Venn diagram of total protein group identifications of blood compartments across all analyzed patients. Note that the protein group identifications of native, depleted, and EV compartment show similar overlaps in plasma and serum samples. e Number of protein groups identified in plasma-derived EVs in previous melanoma studies and our study

The analysis revealed that the EV proteome differed significantly from unenriched plasma and serum, and could effectively distinguish between samples from healthy donors and those from melanoma patients. Importantly, known melanoma markers such as MCAM, TNC, and TGFBI were found to be upregulated in melanoma EVs but not in depleted melanoma plasma, underscoring the specific information contained within EVs.

Furthermore, the study uncovered that EVs were significantly enriched in intact membrane proteins and proteins related to SNARE protein interactions and T-cell biology, providing valuable insights into the molecular mechanisms underlying melanoma progression.

In conclusion, this innovative EV-based proteomic workflow offers increased sensitivity and specificity in identifying potential biomarkers for melanoma. With further validation and application to larger cohorts, this approach holds great promise for improving the diagnosis, prognosis, and treatment of melanoma, as well as other medical conditions.

Lattmann E, Räss L, Tognetti M, Gómez JMM, Lapaire V, Bruderer R, Reiter L, Feng Y, Steinmetz LM, Levesque MP. (2024) Size-exclusion chromatography combined with DIA-MS enables deep proteome profiling of extracellular vesicles from melanoma plasma and serum. Cell Mol Life Sci 81(1):90. [article]

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