Identification of candidate serum proteins for classifying well-differentiated small intestinal neuroendocrine tumors

Abstract

Background: Patients with well-differentiated small intestine neuroendocrine tumors (WD-SI-NETs) are most often diagnosed at a metastatic stage of disease, which reduces possibilities for a curative treatment. Thus new approaches for earlier detection and improved monitoring of the disease are required.

Materials and methods: Suspension bead arrays targeting 124 unique proteins with antibodies from the Human Protein Atlas were used to profile biotinylated serum samples. Discoveries from a cohort of 77 individuals were followed up in a cohort of 132 individuals both including healthy controls as well as patients with untreated primary WD-SI-NETs, lymph node metastases and liver metastases.

Results: A set of 20 antibodies suggested promising proteins for further verification based on technically verified statistical significance. Proceeding, we assessed the classification performance in an independent cohort of patient serum, achieving, classification accuracy of up to 85% with different subsets of antibodies in respective pairwise group comparisons. The protein profiles of nine targets, namely IGFBP2, IGF1, SHKBP1, ETS1, IL1α, STX2, MAML3, EGR3 and XIAP were verified as significant contributors to tumor classification.

Conclusions: We propose new potential protein biomarker candidates for classifying WD-SI-NETs at different stage of disease. Further evaluation of these proteins in larger sample sets and with alternative approaches is needed in order to further improve our understanding of their functional relation to WD-SI-NETs and their eventual use in diagnostics.

Figure 1. Experimental procedure of antibody suspension bead arrays.

The process starts with the distribution of samples into microtiter plates according to a defined, randomized sample positioning (A). The protein content of diluted samples is then labeled with biotin (B) and antibodies are coupled onto beads with distinct color codes to create a suspension bead array (C). Beads and samples are combined for incubation after the samples have been heat treated in assay buffer (D). Proteins that have not been captured by antibodies are removed and fluorescent streptavidin is added for detection (D). The beads are then measured and the co-occurrence of beads, which are identified via a green laser, and the emitted reporter fluorescence, excited by a red laser, allow the determination of interaction dependent intensity values in multiplex (E).

Figure 2. Correlation analysis during the discovery phase.

Correlation of two independent experiments for all 20 selected analytes (A). Each data point represents 1 of 77 patients and controls included in cohort 1. Axes represent MFI for each sample. Correlation analysis between two independent experiments of all the 124 analytes (B). X-axis represents Spearman correlation coefficients, whereas the y-axis represents frequency.

Figure 3. Multivariate classification of different individual groups.

Distribution of each individual sample belonging to the healthy control group (blue circles) and all SI-NET patients (A), patients with primary tumors (B), lymph node metastasis (C), and liver metastasis (D). Axes values correspond to the two-dimensional projection of the proximity matrices generated for each pairwise comparison using RF. For each group, the relative importance of each protein used in the multivariate classification is shown.

Figure 4. Group comparison by using the 9 selected proteins.

Boxplots and ROC curves for each of the significant analytes in each of the pairwise comparisons between Healthy individuals (green color) and all cancer patients combined (All SI-NET), Liver metastasis (LM), Primary tumors (PT) and Lymph-node metastasis (LNM). In the lower part of Figure 3, a Venn diagram for all significant analytes is presented. Common analytes for the discrimination of each cancer patient group and healthy controls are shown.

Figure 5. IGFBP2 and IGF1 sandwich immunoassays.

Commercially available sandwich immunoassays were performed to confirm the differential detection of IGFBP2 (A) and IGF1 (B). The assays were supplemented with HPA045140 for IGFBP2 and with HPA048946 for IGF1, both used during discovery. In the two assays both capture antibodies revealed concordant and previously observed differences between cases and control group (p<0.05). Data shown was normalized using a linear model.