Quantitative Proteomic Analysis of Serum Exosomes from Patients with Locally Advanced Pancreatic Cancer Undergoing Chemoradiotherapy.
Mingrui AnInes LohseZhijing TanJianhui ZhuJing WuHimabindu KurapatiMeredith A MorganTheodore S LawrenceKyle C CuneoDavid M LubmanPublished in: Journal of proteome research (2017)
Pancreatic cancer is the third leading cause of cancer-related death in the USA. Despite extensive research, minimal improvements in patient outcomes have been achieved. Early identification of treatment response and metastasis would be valuable to determine the appropriate therapeutic course for patients. In this work, we isolated exosomes from the serum of 10 patients with locally advanced pancreatic cancer at serial time points over a course of therapy, and quantitative analysis was performed using the iTRAQ method. We detected approximately 700-800 exosomal proteins per sample, several of which have been implicated in metastasis and treatment resistance. We compared the exosomal proteome of patients at different time points during treatment to healthy controls and identified eight proteins that show global treatment-specific changes. We then tested the effect of patient-derived exosomes on the migration of tumor cells and found that patient-derived exosomes, but not healthy controls, induce cell migration, supporting their role in metastasis. Our data show that exosomes can be reliably extracted from patient serum and analyzed for protein content. The differential loading of exosomes during a course of therapy suggests that exosomes may provide novel insights into the development of treatment resistance and metastasis.
Keyphrases
- mesenchymal stem cells
- locally advanced
- stem cells
- rectal cancer
- squamous cell carcinoma
- cell migration
- neoadjuvant chemotherapy
- end stage renal disease
- radiation therapy
- newly diagnosed
- ejection fraction
- chronic kidney disease
- big data
- case report
- lymph node
- prognostic factors
- high resolution
- artificial intelligence
- peritoneal dialysis
- phase ii study
- data analysis
- amino acid