Integrative analysis of cancer dependency data and comprehensive phosphoproteomics data revealed the EPHA2-PARD3 axis as a cancer vulnerability in KRAS-mutant colorectal cancer.

Colorectal cancer (CRC), a common malignant tumour of the gastrointestinal tract, is a life-threatening cancer worldwide. Mutations in KRAS and BRAF, the major driver mutation subtypes in CRC, activate the RAS pathway, contribute to tumorigenesis in CRC and are being investigated as potential therapeutic targets. Despite recent advances in clinical trials targeting KRASG12C or RAS downstream signalling molecules for KRAS-mutant CRC, there is a lack of effective therapeutic interventions. Therefore, understanding the unique molecular characteristics of KRAS-mutant CRC is essential for identifying molecular targets and developing novel therapeutic interventions. We obtained in-depth proteomics and phosphoproteomics quantitative data for over 7900 proteins and 38 700 phosphorylation sites in cells from 35 CRC cell lines and performed informatic analyses, including proteomics-based coexpression analysis and correlation analysis between phosphoproteomics data and cancer dependency scores of the corresponding phosphoproteins. Our results revealed novel dysregulated protein-protein associations enriched specifically in KRAS-mutant cells. Our phosphoproteomics analysis revealed activation of EPHA2 kinase and downstream tight junction signalling in KRAS-mutant cells. Furthermore, the results implicate the phosphorylation site Y378 in the tight junction protein PARD3 as a cancer vulnerability in KRAS-mutant cells. Together, our large-scale phosphoproteomics and proteomics data across 35 steady-state CRC cell lines represent a valuable resource for understanding the molecular characteristics of oncogenic mutations. Our approach to predicting cancer dependency from phosphoproteomics data identified the EPHA2-PARD3 axis as a cancer vulnerability in KRAS-mutant CRC.

Automated Proteomics Sample Preparation of Phosphatidylserine-Positive Extracellular Vesicles from Human Body Fluids.

Extracellular vesicles (EVs) are ubiquitously secreted by almost every cell type and are present in all body fluids. Blood-derived EVs can be used as a promising source for biomarker monitoring in disease. EV proteomics is currently being analyzed in clinical specimens. However, their EV proteomics preparation methods are limited in throughput for human subjects. Here, we introduced a novel automated EV isolation and sample preparation method using a magnetic particle processing robot for automated 96-well processing of magnetic particles for EV proteomics analysis that can be started with a low volume of multiple clinical samples. The automation of EV purification reduced the coefficient of variation of protein quantification from 3.5 to 2.2% compared with manual purification, enabling the quantification of 1120 proteins in 1 h of MS analysis. This automated proteomics EV sample preparation is attractive for processing large cohort samples for biomarker development, validation, and routine testing.

Identification of CD14 and lipopolysaccharide-binding protein as novel biomarkers for sarcoidosis using proteomics of serum extracellular vesicles.

Sarcoidosis is a complex, polygenic, inflammatory granulomatous multi-organ disease of unknown cause. The granulomatous inflammation in sarcoidosis is driven by the interplay between T cells and macrophages. Extracellular vesicles (EVs) play important roles in intercellular communication. We subjected serum EVs, isolated by size exclusion chromatography, from seven patients with sarcoidosis and five control subjects to non-targeted proteomics analysis. Non-targeted, label-free proteomics analysis detected 2292 proteins in serum EVs; 42 proteins were up-regulated in patients with sarcoidosis relative to control subjects; and 324 proteins were down-regulated. The protein signature of EVs from patients with sarcoidosis reflected disease characteristics such as antigen presentation and immunological disease. Candidate biomarkers were further verified by targeted proteomics analysis (selected reaction monitoring) in 46 patients and 10 control subjects. Notably, CD14 and lipopolysaccharide-binding protein (LBP) were validated by targeted proteomics analysis. Up-regulation of these proteins was further confirmed by immunoblotting, and their expression was strongly increased in macrophages of lung granulomatous lesions. Consistent with these findings, CD14 levels were increased in lipopolysaccharide-stimulated macrophages during multinucleation, concomitant with increased levels of CD14 and LBP in EVs. The area under the curve values of CD14 and LBP were 0.81 and 0.84, respectively, and further increased to 0.98 in combination with angiotensin-converting enzyme and soluble interleukin-2 receptor. These findings suggest that CD14 and LBP in serum EVs, which are associated with granulomatous pathogenesis, can improve the diagnostic accuracy in patients with sarcoidosis.

Quantitation of putative colorectal cancer biomarker candidates in serum extracellular vesicles by targeted proteomics.

At the moment, there is no sensitive clinical test for detecting early-stage colorectal cancer (CRC). Target proteomics has enabled high-throughput verification of hundreds of biomarker candidate proteins. Using this technology, we verified 725 previously reported CRC biomarker candidate proteins that are functionally correlated with CRC in extracellular vesicles (EVs) from patients. Of these, 356 proteins were quantified, and 34 peptides (22 proteins) showed significant differences in the serum EVs between healthy controls and CRC patients of two independent cohorts (n = 77 and 84). These peptides were evaluated as single or multiple markers, and four single peptides in annexin family proteins and eight combinations of peptides showed area under the curve > 0.9 for discriminating between healthy controls and CRC patients. The sensitivities of annexins A3, A4, and A11 peptides for detecting early-stage CRC greatly exceed those of carcinoembryonic antigen. These peptides are promising biomarkers for early detection of CRC.