Integrated Pipeline of Rapid Isolation and Analysis of Human Plasma Exosomes for Cancer Discrimination Based on Deep Learning of MALDI-TOF MS Fingerprints

Abstract

Plasma exosomes have shown great potential for liquid biopsy in clinical cancer diagnosis. Herein, we present an integrated strategy for isolating and analyzing exosomes from human plasma rapidly and then discriminating different cancers excellently based on deep learning fingerprints of plasma exosomes. Sequential sizeexclusion chromatography (SSEC) was developed efficiently for separating exosomes from human plasma. SSEC isolated plasma exosomes, taking as less as 2 h for a single sample with high purity such that the discard rates of high-density lipoproteins and low/ very low-density lipoproteins were 93 and 85%, respectively. Benefitting from the rapid and high-purity isolation, the contents encapsulated in exosomes, covered by plasma proteins, were well profiled by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS). We further analyzed 220 clinical samples, including 79 breast cancer patients, 57 pancreatic cancer patients, and 84 healthy controls. After MS data preprocessing and feature selection, the extracted MS feature peaks were utilized as inputs for constructing a multi-classifier artificial neural network (denoted as Exo-ANN) model. The optimized model avoided overfitting and performed well in both training cohorts and test cohorts. For the samples in the independent test cohort, it realized a diagnosed accuracy of 80.0% with an area under the curve of 0.91 for the whole group. These results suggest that our integrated pipeline may become a generic tool for liquid biopsy based on the analysis of plasma exosomes in clinics.

Multiplexed analysis of a single EV (MASEV) reveals unique biomarker composition with diagnostic impact

“…S3 ). In summary, these results confirm work by others 14, 31–39 that the size exclusion column methods of isolation yield pure EV for MASEV analysis in reasonable amounts of time.…”

Advanced technologies for molecular diagnosis of cancer: State of pre-clinical tumor-derived exosome liquid biopsies

“…Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been widely used to identify specific protein fingerprints associated with pathological changes in various diseases upon analysis of body fluids or tissue samples. MALDI-TOF MS has been recently applied to analyze TDEs for rapid diagnosis of melanoma, breast cancer, pancreatic cancer, early-stage lung cancer, and osteosarcoma [ 60 , [118] , [119] , [120] ]. MALDI-TOF MS spectra and SERS data of plasma EVs were used to discriminate TDEs of osteosarcoma patients from EVs of healthy controls for more accurate diagnosis of osteosarcoma [ 119 ].…”

MALDI-TOF Mass Spectrometry in Clinical Analysis and Research

“…On the mature foundation of MALDI-TOF MS fingerprinting technology, many other samples have been used for biomarker discovery and cancer diagnosis, especially exosomes isolated from body fluids. ,− In 2019, Zhu et al used MALDI-TOF MS to analyze exosomes extracted from serum of melanoma patients and healthy donors and demonstrated that the mass fingerprinting of bloodstream-circulating exosomes can be used for cancer diagnosis and monitoring . In 2021, Han et al used MALDI-TOF MS to analyze serum exosomes from 12 healthy donors, 20 osteosarcoma patients without lung metastasis, and 20 osteosarcoma patients with lung metastasis.…”