
pmid: 35663013
pmc: PMC9157216
Abstract Circulating extracellular vesicles (EVs) contain molecular footprints from their cell of origin and may provide potential non-invasive access for detection, characterization, and monitoring of numerous diseases. Despite their growing promise, the integrated proteo-transcriptomic landscape of EVs and their donor cells remain poorly understood. To assess their cargo, we conducted small RNA sequencing and mass spectrometry (LC-MS/MS) of EVs isolated from in vitro cancer cell culture and prostate cancer patients’ serum. Here, we report that EVs enrich for distinct molecular cargo, and their proteo-transcriptome is predominantly different from their cancer cell of origin, implicating a coordinated disposal and delivery mechanism. We have discovered that EVs package their cargo in a non-random fusion, as their most enriched RNAs and proteins are not the most abundant cargo from their donor cells. We show that EVs enrich for 4 times more cytoskeletal and 2 times extracellular proteins than their donor cells. While the donor cells carry 10 times more mitochondrial and 3 times nuclear proteins than their EVs. EVs predominantly (40-60%) enrich for small RNA (~15-200 nucleotides) molecules that implicate cell differentiation, development, and signaling signatures. Finally, our integrated proteo-transcriptomic analyses reveal that EVs are enriched of RNAs (RNY3, vtRNA, and MIRLET-7) and their complementary proteins (YBX1, IGF2BP2, SRSF1/2), implicating an interrelated mechanism that may protect and regulate transcripts until a biological function is achieved. Based on these results, we envision that the next-generation clinical assays will take an integrative multi-omic (proteomic and transcriptomic) approach for liquid biopsy in numerous diseases.
Cancer systems biology, Microenvironment, Science, Q, Transcriptomics, Article
Cancer systems biology, Microenvironment, Science, Q, Transcriptomics, Article
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 41 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
