Integrated proteomic profiling identifies amino acids selectively cytotoxic to pancreatic cancer cells.

Pancreatic adenocarcinoma (PDAC) is one of the most deadly cancers, characterized by extremely limited therapeutic options and a poor prognosis, as it is often diagnosed during late disease stages. Innovative and selective treatments are urgently needed, since current therapies have limited efficacy and significant side effects. Through proteomics analysis of extracellular vesicles, we discovered an imbalanced distribution of amino acids secreted by PDAC tumor cells. Our findings revealed that PDAC cells preferentially excrete proteins with certain preferential amino acids, including isoleucine and histidine, via extracellular vesicles. These amino acids are associated with disease progression and can be targeted to elicit selective toxicity to PDAC tumor cells. Both in vitro and in vivo experiments demonstrated that supplementation with these specific amino acids effectively eradicated PDAC cells. Mechanistically, we also identified XRN1 as a potential target for these amino acids. The high selectivity of this treatment method allows for specific targeting of tumor metabolism with very low toxicity to normal tissues. Furthermore, we found this treatment approach is easy-to-administer and with sustained tumor-killing effects. Together, our findings reveal that exocytosed amino acids may serve as therapeutic targets for designing treatments of intractable PDAC and potentially offer alternative treatments for other types of cancers.

EvIPqPCR, Target Circulating Tumorous Extracellular Vesicles for Detection of Pancreatic Cancer.

Pancreatic cancer patients predominantly present with advanced disease at diagnosis, contributing to its high mortality. A noninvasive, fast screening method to detect this disease is an unmet need. Tumor-derived extracellular vesicles (tdEVs) bearing information from parental cells have emerged as a promising cancer diagnostic biomarker. However, most tdEV-based assays have impractical sample volumes and time-consuming, complex, and costly techniques. To overcome these limitations, we developed a novel diagnostic method for pancreatic cancer screening. Our approach utilizes the mitochondrial DNA to nuclear DNA ratio of EVs as a collective cell-specific characteristic. We introduce EvIPqPCR, a fast method that combines immunoprecipitation (IP) and qPCR quantification to detect tumor-derived EVs directly from serum. Importantly, our method employs DNA isolation-free and duplexing probes for qPCR, saving at least 3 h. This technique has the potential to serve as a translational assay for cancer screening with a weak correlation to prognosis biomarkers and sufficient discriminatory power among healthy controls, pancreatitis, and pancreatic cancer cases.

ß-Sheet Richness of the Circulating Tumor-Derived Extracellular Vesicles for Noninvasive Pancreatic Cancer Screening.

Tumor-derived extracellular vesicles (EVs) are under intensive study for their potential as noninvasive diagnosis biomarkers. Most EV-based cancer diagnostic assays trace supernumerary of a single cancer-associated marker or marker signatures. These types of biomarker assays are either subtype-specific or vulnerable to be masked by high background signals. In this study, we introduce using the ß-sheet richness (BR) of the tumor-derived EVs as an effective way to discriminate EVs originating from malignant and nonmalignant cells, where EV contents are evaluated as a collective attribute rather than single factors. Circular dichroism, Fourier transform infrared spectroscopy, fluorescence staining assays, and a de novo workflow combining proteomics, bioinformatics, and protein folding simulations were employed to validate the collective attribute at both cellular and EV levels. Based on the BR of the tumorous EVs, we integrated immunoprecipitation and fluorescence labeling targeting the circulating tumor-derived EVs in serum and developed the process into a clinical assay, named EvIPThT. The assay can distinguish patients with and without malignant disease in a pilot cohort, with weak correlations to prognosis biomarkers, suggesting the potential for a cancer screening panel with existing prognostic biomarkers to improve overall performance.