Abstract 176P
Background
Neuroendocrine tumors are tumors that originate from endocrine cells in various organs, and show very heterogeneous characteristics, and their incidence is gradually increasing. Among them, neuroendocrine tumors originating from the pancreas are divided into functional tumors and non-functional tumors according to the secretion function of hormones. Therefore, we aimed to find protein biomarkers for diagnosis and differential diagnosis of pancreatic neuroendocrine tumor (PNET) through proteomic analysis of human blood.
Methods
A total of 60 human plasma samples were collected from 17 PNETs, 23 PDACs and 20 healthy donors, and liquid chromatography-mass spectrometry (LC-MS) proteomics analysis was performed on 60 human raw data. Identification and label-free quantification were performed through the swissprot protein sequence database. To investigate the function of CD163 among these three biomarker candidates, CD163-expressing cell lines were generated and 3 kinds of experiments were conducted. Additionally, to investigate the correlation between CD163 expression and cells, CBC analysis was performed by collecting blood and tumor tissues from mice transplanted with PNET and PDAC cell lines.
Results
An average of 549 protein lists were secured through LC-MS proteomics analysis using 60 samples, proteomes increased or decreased with disease were analyzed and classified through quantitative evaluation, and ACTR3, CD163, and LECT2 increased in PNET were selected as candidates for diagnostic biomarkers. The diagnostic AUC to differentiate PNET from HD was 0.971 for CD163 and the differential AUC to distinguish between PNET and PDAC was 0.870 for CD163. Additionally, CD163 was confirmed in the blood and tumor tissues of mice transplanted with PNET and PDAC cell lines, and significant results were obtained in PNET. Among the three biomarkers, CD163 was knocked-in to the PNET cell line to confirm the effect of CD163 on PNET.
Conclusions
These three markers will be used to identify molecular biological mechanisms for the generation and progression of PNET, and to study their function as markers that can simultaneously predict diagnosis and treatment response.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
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