DOCK10 Regulates Insulin Hypersecretion in Insulinoma and Serves as a Diagnostic and Therapeutic Target

Abstract

Background & aims: Insulinomas are rare pancreatic neuroendocrine neoplasms (pan-NENs) characterized by inappropriate insulin secretion. Despite advances in imaging techniques, the reliable identification of insulin-secreting lesions remains challenging. In addition, medical treatment options are limited and have seen little development in recent years, highlighting the unmet need for improved diagnostic tools and therapeutic strategies. This study aimed to identify the molecular mechanisms underlying insulin hypersecretion in insulinomas.

Methods: We established a biobank of human insulinoma surgical specimens and matched organoids. Comprehensive transcriptomic analyses-including bulk RNA sequencing, single-cell RNA sequencing, quantitative polymerase chain reaction, and immunohistochemistry-were conducted to identify genes enriched in insulin-secreting components. Functional validation was performed using MIN6 cells, a xenograft mouse model, and long-term cultured human insulinoma organoids.

Results: We identified dedicator of cytokinesis 10 (DOCK10) as a gene selectively overexpressed in insulin-secreting components of insulinomas. DOCK10 knockdown impaired glucose-stimulated insulin secretion in both mouse insulinoma cells and patient-derived organoids. Inhibition of the downstream effector Cdc42 with ML141 reduced insulin hypersecretion and improved survival in a MIN6 xenograft mouse model. These findings uncover a previously unrecognized role of the DOCK10-Cdc42 axis in regulating insulin secretion in insulinoma.

Conclusions: This study suggests that DOCK10 may serve as a diagnostic marker for insulin-secreting lesions and a potential therapeutic target in insulinoma. It provides mechanistic insights that may inform future strategies for precision diagnostics and treatment of functional pancreatic neuroendocrine tumors.

Keywords: DOCK10; Insulin Secretion; Insulinoma; Pancreatic Neuroendocrine Tumor.

Graphical abstract

Figure 1

Chronological overview of the case cohort used in this study. This diagram provides an overview of the case cohort and sample usage in this study. The dashed box on the upper right indicates the subset of patients with primary pan-NETs resected between January 2020 and January 2025, which were included in clinical feature analyses (n = 74). The pan-NEN biobank includes all surgically resected pan-NEN cases from May 2014 to January 2025. It comprises both tissue samples and organoids that could be established from the respective resected specimens. Bulk RNA-seq was performed on 97 surgical specimens and 22 organoid samples, all derived from 68 cases between May 2014 and September 2022, from which sufficient RNA could be obtained. A subset of cases was also subjected to qPCR (n = 11), immunostaining analysis (n = 12), and multiplex immunostaining in morphologically heterogeneous insulinomas (n = 2). Additionally, scRNA-seq (n = 1) and 2D organoid culture (n = 3) were performed using samples from the biobank.

Figure 2

A biobank of pan-NEN organoids derived from tumor and adjacent normal tissues. (A) Schematic overview of organoid establishment using surgical specimens derived from tumor and adjacent normal tissue. (B) Immunofluorescent staining for insulin in organoid cultures from insulinoma: primary insulinoma (left), liver metastasis (right). (C) Immunofluorescent staining for synaptophysin (left) and CD56 (right) in organoids from insulinoma. Scale bar: 500 μm in (A); 100 μm in (B and C). (D) H&E staining (top row, first column). Immunofluorescence for insulin (top row, second column), KRT19 (top row, third column), MUC1 (top row, fourth column), PDX1 (bottom row, first column), and SOX9 (bottom row, second column), with DAPI. Scale bars: 500 μm in top row, first columns; 100 μm in all other columns.

Figure 3

Transcriptomic profiling of surgical specimens. (A) Summary of surgical samples for RNA-seq. PCA plot of all surgical samples. Tumor includes both primary tumor and liver metastasis. (B) PCA plot of tumor samples only, including primary and liver metastases from both insulinoma and NF-NET. (C) Heatmap of DEGs across insulinoma, NF-NETs, and normal pancreas, showing row-wise z-scores of normalized counts. (D) Volcano plot of DEGs between insulinoma samples and normal pancreatic tissue obtained from surgical specimens. (E) Functional enrichment analysis of DEGs between insulinoma and normal pancreatic tissue from surgical specimens. Dot size represents gene ratio; color indicates q-value.

Figure 4

RNA-seq–based gene expression of the insulin pathway in surgical samples of insulinoma variance-stabilized expression of key insulin signaling genes in insulinoma vs normal pancreas. Adjusted P-values from DGE analysis: ns, not significant; ∗P < .05; ∗∗P < .01; ∗∗∗P < .0001.

Figure 5

RNA-seq–based transcriptomic profiling of organoid samples. (A) Summary of organoid samples used for RNA-seq. PCA plot of organoid cultures derived from surgical specimens of insulinoma, NF-NET, and normal pancreatic tissue. (B) Volcano plot of DEGs between insulinoma-derived and normal pancreas in organoids.

Figure 6

Identification of candidate genes regulating aberrant insulin secretion in insulinoma by integrative analysis of surgical samples and organoids. (A) Venn diagram comparing DEGs in insulinoma between surgical samples and organoid cultures, relative to normal pancreas by RNA-seq. (B) Expression patterns of 441 genes significantly differentially expressed in both surgical and organoid samples. (C) Top 10 genes most positively associated with INS expression among commonly upregulated genes. (D) Association between top 10 genes and INS expression (β, LMM effect size).

Figure 7

Validation and comparison of candidate gene expression. (A) qPCR validation of DOCK10, CACNA2D1, UCHL1, NTM, and EFNA5 expression in surgical samples (insulinoma, n = 5; NF-NET, n = 6; normal, n = 5); mean ± SD; unpaired Student’s t-test; ns, not significant; ∗P < .05; ∗∗P < .01; ∗∗∗∗P < .001. (B) RNA-seq–based expression levels of DOCK10, CACNA2D1, and UCHL1 in surgical and organoid samples; adjusted P-values from DGE analysis; ns, not significant; ∗∗P < .01; ∗∗∗P < .0001.

Figure 8

Immunofluorescence images of CACNA2D1 in insulinoma and NF-NET surgical samples. Representative images from 3 cases are shown. For each case, the upper left panel shows the H&E image, the upper right panel shows the low-magnification image, and the lower panel shows a high-magnification view of the region indicated by the yellow square. Green represents the protein signal, and blue (DAPI) marks the nuclei. Black dashed lines indicate the boundary between normal and tumor regions. Scale bars: 500 μm (low magnification) and 100 μm (high magnification).

Figure 9

Immunofluorescence images of DOCK10 in insulinoma and NF-NET surgical samples. Representative images from 3 cases are shown. For each case, the upper left panel shows the H&E image, the upper right panel shows the low-magnification image, and the lower panel shows a high-magnification view of the region indicated by the yellow square. Green represents the protein signal, and blue (DAPI) marks the nuclei. Black dashed lines indicate the boundary between normal and tumor regions. Scale bars: 500 μm (low magnification) and 100 μm (high magnification).

Figure 10

Immunofluorescence images of UCHL1 in insulinoma and NF-NET surgical samples. Representative images from 3 cases are shown. For each case, the upper left panel shows the H&E image, the upper right panel shows the low-magnification image, and the lower panel shows a high-magnification view of the region indicated by the yellow square. Green represents the protein signal, and blue (DAPI) marks the nuclei. Black dashed lines indicate the boundary between normal and tumor regions. Scale bars: 500 μm (low magnification) and 100 μm (high magnification).

Figure 11

Expression of DOCK10 in multiple metastatic lesions containing a mixture of insulin-secreting and non-secreting tumors. Immunofluorescence staining of DOCK10 (green), insulin (red), and DAPI (blue) in multiple metastatic insulinoma lesions. Blue circle: insulin-secreting tumor; gray circle: non-secreting tumor. Scale bar: 200 μm.

Figure 12

Expression of UCHL1 in multiple metastatic lesions containing a mixture of insulin-secreting and non-secreting tumors. Immunofluorescence staining of UCHL1 (green), insulin (red), and DAPI (blue) in multiple metastatic insulinoma lesions. Blue circle: insulin-secreting tumor; gray circle: non-secreting tumor. Scale bar: 200 μm.

Figure 13

DOCK10 marks the high insulin-secreting tumor population at the single-cell level. (A) scRNA-seq of 2984 cells from primary insulinoma, visualized by t-SNE and k-means clustering into 8 clusters. (B) Expression of selected marker genes overlaid on t-SNE map. (C) t-SNE of 370 tumor cells classified into Clusters 1 and 2 by graph-based clustering. (D) Heatmap of 808 genes differentially expressed between Clusters 1 and 2. (E) Violin plot of DOCK10, UCHL1, and ZNF385D expression in Clusters 1 and 2. (F) Violin plots of insulin synthesis pathway genes between Clusters 1 and 2. (G) Violin plots of insulin secretion pathway genes between Clusters 1 and 2. Statistical significance was corrected by Benjamini–Hochberg; ns, not significant; ∗∗P < .01; ∗∗∗∗P < .001.

Figure 14

Expression of DOCK10 in pancreatic islets. H&E staining of pancreatic islets (left), DOCK10 immunofluorescence (second from left), insulin immunofluorescence (third from left), and the merged image of DOCK10, insulin, and DAPI (right). Green: DOCK10; red: insulin; blue (DAPI): nuclei. Scale bar: 50 μm. Analysis was performed on normal regions from the same specimens as in Figure 9.

Figure 15

DOCK10 regulates insulin secretion via CDC42 in MIN6 cells. (A) Dock10 mRNA levels by qPCR in control and DOCK10-knockdown (KD) MIN6 cells. (B) ELISA measurement of insulin secretion after stimulation with 3 mM glucose, 25 mM glucose, or 3 mM glucose + 30 mM KCl. (C) ELISA measurement of intracellular insulin levels in control and knockdown MIN6 cells (n = 3/group). (D) Schematic of Dock10–Cdc42 pathway regulating GSIS; ML141, a Cdc42 inhibitor. (E) Protein levels of phosphorylated PAK1 (p-PAK1), total PAK1, and β-actin after glucose stimulation (2-hour fasting) in control and knockdown cells by Simple Western; table shows p-PAK1/PAK1 ratio normalized to β-actin. (F) Protein levels after 1-hour fasting and ML141 or vehicle (DMSO) pretreatment, assessed by Simple Western; table shows normalized p-PAK1/PAK1 ratios. (G) ELISA measurement of insulin secretion after ML141 or vehicle pretreatment under the same stimulations (n = 3/group). Data were pooled from 3 independent experiments for panels in (A–C) and (G). Values are presented as mean ± SD. Statistical analysis was performed using unpaired Student’s t-test. ns, not significant; ∗∗P < .01; ∗∗∗P < .005.

Figure 16

ML141, an inhibitor of CDC42, improves outcomes in an insulinoma mouse model. (A) Experimental timeline of OGTT and ML141 treatment following MIN6 or vehicle (Matrigel) transplantation. (B) Random blood glucose in unsuccessfully engrafted MIN6 mice (n = 9) and controls (n = 8). (C) Blood glucose time course during OGTT in unsuccessfully engrafted MIN6 mice (n = 9) and controls (n = 8) at 2 weeks post-transplantation. (D) Random blood glucose levels in MIN6-transplanted (n = 14) vs control mice (n = 8). (E) Blood glucose time course during OGTT at 2 weeks post-transplantation. (F) OGTT time course after ML141 (1 mg/body) (n = 7) or vehicle (n = 6) administration. (G) Survival curves of transplanted mice treated with ML141 or vehicle (n = 7/group); significance by log-rank test. (H) ELISA measurement of serum insulin levels after 4-hour fasting in MIN6-transplanted (n = 9) vs control mice (n = 8). (I) Relative post/pre changes in 4-hour fasting serum insulin levels (ELISA) in MIN6-transplanted mice administered ML141 (n = 4) or vehicle (n = 3). Data in (B–F, H–I) are mean ± SD; significance by unpaired Student’s t-test. ns, not significant; ∗P < .05; ∗∗P < .01; ∗∗∗P < .005; ∗∗∗∗P < .001.

Figure 17

Comparison between 3D and 2D cultures of insulinoma organoids. (A) Images of human insulinoma organoids in 3D culture: Day 1 (passage 0) and Day 27 (passage 2). (B) ELISA measurement of C-peptide levels in 3D organoids from insulinoma and normal tissue at day 13, 20, and 27. (C) Images of human insulinoma organoids in 2D culture: Day 1 and Day 27. (D) ELISA measurement of C-peptide levels in 2D organoids from insulinoma and normal tissue at day 13, 20, and 27.

Figure 18

Pathological diagnosis of insulinoma cases used for 2D culture. Staining for H&E, CHGA, synaptophysin, and insulin, top to bottom. Scale bar: 100 μm.

Figure 19

ML141 suppresses insulin secretion in human insulinomas. (A) Schematic timeline of 2D organoid establishment and medium collection before and after ML141 treatment. (B) Relative C-peptide changes in 2D insulinoma organoids treated with ML141 or vehicle, measured by ELISA. Post-treatment levels were compared with pre-treatment. Data are mean ± SD (n = 3/group); significance by unpaired Student’s t-test. ∗P < .05; ∗∗∗∗P < .001.