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. 2021 Apr 7;29(4):1557-1571.
doi: 10.1016/j.ymthe.2020.12.029. Epub 2020 Dec 25.

Isoforms of MUC16 activate oncogenic signaling through EGF receptors to enhance the progression of pancreatic cancer

Affiliations

Isoforms of MUC16 activate oncogenic signaling through EGF receptors to enhance the progression of pancreatic cancer

Divya Thomas et al. Mol Ther. .

Abstract

Aberrant expression of CA125/MUC16 is associated with pancreatic ductal adenocarcinoma (PDAC) progression and metastasis. However, knowledge of the contribution of MUC16 to pancreatic tumorigenesis is limited. Here, we show that MUC16 expression is associated with disease progression, basal-like and squamous tumor subtypes, increased tumor metastasis, and short-term survival of PDAC patients. MUC16 enhanced tumor malignancy through the activation of AKT and GSK3β oncogenic signaling pathways. Activation of these oncogenic signaling pathways resulted in part from increased interactions between MUC16 and epidermal growth factor (EGF)-type receptors, which were enhanced for aberrant glycoforms of MUC16. Treatment of PDAC cells with monoclonal antibody (mAb) AR9.6 significantly reduced MUC16-induced oncogenic signaling. mAb AR9.6 binds to a unique conformational epitope on MUC16, which is influenced by O-glycosylation. Additionally, treatment of PDAC tumor-bearing mice with either mAb AR9.6 alone or in combination with gemcitabine significantly reduced tumor growth and metastasis. We conclude that the aberrant expression of MUC16 enhances PDAC progression to an aggressive phenotype by modulating oncogenic signaling through ErbB receptors. Anti-MUC16 mAb AR9.6 blocks oncogenic activities and tumor growth and could be a novel immunotherapeutic agent against MUC16-mediated PDAC tumor malignancy.

Keywords: COSMC; MUC16; Sialyl-Tn; Tn; mAb AR9.6; pancreatic ductal adenocarcinoma.

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Conflict of interest statement

Declaration of interests M.A.H. and P.R. have an equity interest in OncoCare Therapeutics. R.M. is employed by Quest PharmaTech and has an equity interest in this company. All other authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
MUC16 in pancreatic cancer progression (A) LCM-RNA-seq analysis of MUC16 in frozen human pancreas tissue sections (PDAC epithelium with IPMN [n = 19], PanIN [n = 26], and primary [n = 197]; and stroma with IPMN [n = 12], PanIN [n = 23], and primary [n = 124]). MUC16 mRNA expression for different samples were quantified by Log2 TPM (transcripts per million). (B) Immunohistochemical analysis of MUC16 in pancreatic tissue microarrays containing normal pancreas (NP, n = 10), early PanIN1 (n = 6), ductal adenocarcinoma (DAC, n = 46), adenosquamous carcinoma (ASC, n = 3), and islet cell tumors (n = 11) using anti-MUC16 antibody (AR9.6). Scale bar, 40 μm. (C) Histoscore analysis of MUC16 expression by IHC. Expression of MUC16 was compared between the early PanIN and other diseased conditions. Data were presented as the median (Dunnett’s multiple comparisons test). (D) Heatmap of IHC analysis of MUC16 expression (OC125, AR9.6, 5B9, and 5E11) in normal pancreatic tissues (n = 7) and RAP primary tumors (n = 61). (E) Representative IHC images of different anti-MUC16 antibodies (OC125, AR9.6, 5B9, and 5E11) stained normal pancreatic tissues and RAP primary tumors. Scale bar, 40 μm. (F) Graphical representation of overall expression of MUC16 (OC125, AR9.6, 5B9, and 5E11) in RAP primary tumors. Data were presented as the median (n = 61) (Dunnett’s multiple comparisons test). (G) Percent expression of MUC16 using different anti-MUC16 antibodies (OC125, AR9.6, 5B9, and 5E11) in RAP tumor samples.
Figure 2
Figure 2
MUC16 in pancreatic tumor metastasis (A) Heatmap of IHC analysis of MUC16 expression (AR9.6, 5B9, and 5E11) in liver metastasis (n = 46). (B) Heatmap of comparison of MUC16 expression in matched sets of RAP primary tumors and liver mets. Higher intensity of color corresponds to high expression of MUC16 based on immunohistochemical score. (C) Representative images of IHC analysis of MUC16 expression in normal liver tissue and RAP liver mets using MUC16-specific antibodies AR 9.6, 5B9, and 5E11. Scale bar, 40 μm. (D) Percent expression of MUC16 (AR9.6) in RAP tumor tissues of primary tumor alone, liver mets alone, and primary tumor and liver mets together. (E) Survival of RAP cohort patients with high and low MUC16 (AR9.6) expression (Mantel-Cox test). (F) Histoscores of MUC16 (AR9.6) compared between short-term (n = 34) and long-term (n = 32) PDAC survivors. Data were presented as median (unpaired t test). (G) Boxplot of MUC16 expression level stratified by RNA expression dataset from Bailey class, Moffitt class, and Collisson class of PDAC. Boxplots were generated by comparing the expression of MUC16 gene among the subtypes using Mann-Whitney rank-sum test. A p value of less than 0.01 was considered statistically significant.
Figure 3
Figure 3
Genetic deletion of MUC16 in PDAC cells (A) Schematic representation of the targeted deletion of MUC16 via CRISPR-Cas9 constructs in T3M4 and Capan-2 (WT and SC) cells with three gRNA target loci are shown as red dotted lines. (B and C) Western blotting of MUC16 in T3M4 and Capan-2 (WT and SC) parental cells and MUC16KO clones respectively. Detection of α-tubulin served as a loading control. (D). Immunofluorescence analysis of MUC16 in T3M4 WT, WT-MUC16KO (2E4), T3M4 SC, SC-MUC16KO (1E10), Capan-2 WT, WT-MUC16KO (1C10), Capan-2 SC, and SC-MUC16KO (2F9) cells. Scale bar, 10 μm. (E–H) Cell proliferation assays in T3M4 WT, WT-MUC16KO (2E4) (E), T3M4 SC, SC-MUC16KO (1E10) (F), Capan-2 WT, WT-MUC16KO (1C10) (G), and Capan-2 SC, SC-MUC16KO (2F9) (H) cells. Data were presented as mean ± SD (n = 6; Tukey’s multiple comparisons test). (I) Western blotting of Cyclin D1 and Cyclin E1 in T3M4 WT, WT-MUC16KO clones, SC, and SC-MUC16KO clones. (J) Western blotting of Cyclin D1 in Capan-2 WT, WT-MUC16KO clones, SC, and SC-MUC16KO clones. β-actin was used as a loading control.
Figure 4
Figure 4
Genetic deletion of MUC16 reduces PDAC tumorigenicity (A) Schema of in vitro and in vivo experiments using WT, WT-MUC16KO, SC, and SC-MUC16KO cells. (B) Cell migration assay in T3M4 WT, WT-MUC16KO (2E4), T3M4 SC, and SC-MUC16KO (1E10) cells. Data were presented as mean ± SD (n = 3; Dunnett’s multiple comparisons test). (C) Matrigel invasion assay inT3M4 WT, WT-MUC16KO (2E4), T3M4 SC, and SC-MUC16KO (1E10) cells. Data were presented as mean ± SD (n = 3; Dunnett’s multiple comparisons test). (D and E) Tumor weight (D) and tumor volume (E) of T3M4 WT, WT-MUC16KO (2E4), T3M4 SC, and SC-MUC16KO (1E10) cells implanted orthotopic tumors. Data were presented as mean ± SEM (n = 14; Dunnett’s multiple comparisons test). (F) Analysis of tumor metastasis in T3M4 WT, WT-MUC16KO (2E4), T3M4 SC, and SC-MUC16KO (1E10) cells implanted tumor-bearing animals (Fisher’s exact test).
Figure 5
Figure 5
Interaction of MUC16 with epidermal growth factor receptors (A) Proximity ligation assay in T3M4 WT and SC cells using MUC16 and ErbB2 specific antibodies. Scale bar, 10 μm. Quantification of the number of interactions (dots/cell) quantified by blob finder 2 software. Cells incubated with a single antigen-specific antibody served as a negative control. Data were presented as mean ± SD (n = 3; unpaired t test). (B) Western blotting of T3M4 WT, WT-MUC16KO, T3M4 SC, and SC-MUC16KO cell lysates with p-ErbB3 (Y1289), ErbB3, p-ErbB2 (Y1248), ErbB2, p-ErbB1 (Y1173), and ErbB1. (C) Western blotting of Capan-2 WT, WT-MUC16KO, Capan-2 SC, and SC-MUC16KO cell lysates with p-ErbB3 (Y1289), ErbB3, p-ErbB2 (Y1248), ErbB2, p-ErbB1 (Y1173), and ErbB1. (D) Western blotting of p-AKT (S473), AKT, p-GSK3β (S9), and GSK3β in T3M4 WT, WT-MUC16KO, T3M4 SC, and SC-MUC16KO cells. (E) Western blotting of p-AKT (S473), AKT, p-GSK3β (S9), and GSK3β in Capan-2 WT, WT-MUC16KO, Capan-2 SC, and SC-MUC16KO cells. Detection of β-actin served as a loading control. (F and G) Immunohistochemical analysis of p-ErbB2 (F) and p-AKT (G) in T3M4 WT, WT-MUC16KO (2E4), T3M4 SC, and SC-MUC16KO (1E10) cells implanted mouse tumors (n = 5). Scale bar, 40 μm. (H and I) Mean histoscore of the IHC analysis of p-ErbB2 (H) and p-AKT (I) in T3M4 WT, WT-MUC16KO (2E4), T3M4 SC, and SC-MUC16KO (1E10) cells implanted mouse tumors. Data were presented as mean ± SEM (n = 5; Dunnett’s multiple comparisons test).
Figure 6
Figure 6
AR9.6 mAb inhibits MUC16 induced oncogenic signaling (A and B) Western blotting of p-AKT and AKT in T3M4 WT (A) and T3M4 SC (B) cells treated with IgG and MUC16 specific antibodies 5E11, B43.13, and AR9.6. Detection of β-actin served as a loading control. (C) Graphic representation of MUC16 tandem repeats constructs expressed in E-coli. TR1.7 includes part of TR4, the entire SEA, and the linker domain of TR5 along with half of the SEA domain of TR6 (12,660–12,923 aa). The TR1.2 (12,665–12,858 aa), 1/4 (12,665–12,785 aa), 5/2 (12,757–12,923 aa), 5/7 (12,757–12,886 aa), 5/8 (12,757–12,863 aa), 5/9 (12,757–12,839 aa), K292 (12,757–12,816 aa), and F/R (12,817–12,859 aa) constructs represent truncated forms of this construct. (D) mAb AR 9.6 epitope characterization by ELISA assay of MUC16 constructs. (E) ELISA assay of MUC16 constructs with positive control mAb 5E11. (F) Western blotting of p-ErbB3 (Y1289), ErbB3, p-ErbB1 (Y1173), ErbB1, p-GSK3β (S9), and GSK3β in MUC16KO T3M4 cells treated with TR1.2 (1 and 2 μg/mL, 14 h). (G) Western blotting of p-ErbB3 (Y1289), ErbB3, p-ErbB2 (Y1248), ErbB2, p-AKT (S473), AKT, p-GSK3β (S9), and GSK3β in MUC16KO T3M4 cells treated with TR1.2 (1 μg/mL) with or without mAb AR9.6 (5 μg/mL). Detection of β-actin and GAPDH served as the loading control. (H) Tumor weight of vehicle control (n = 11) and mAb AR9.6 (n = 13) treated T3M4 WT orthotopic tumors. Data were reported as mean ± SEM (unpaired t test). (I and J) Analysis of tumor metastasis in vehicle and mAb AR9.6 treated T3M4 WT (I) and SC (J) orthotopic tumor-bearing animals (Fisher’s exact test). (K) Representative images of live/dead cytotoxicity assay in vehicle, IgG, AR9.6, GEM, and AR9.6 + GEM treated PDAC (T3M4 and Capan-2) cells. Scale bar, 20 μm. (L and M) The percentage of cell death in vehicle, IgG, AR9.6, GEM, AR9.6 + GEM-treated T3M4 (L), and Capan-2 (M) cells. Data presented as mean ± SD (n = 3; Dunnett’s multiple comparisons test).
Figure 7
Figure 7
mAb AR9.6 plus gemcitabine treatment reduces in vivo tumor growth (A) Schematic representation of orthotopic tumor implantation and treatment schedules of tumor-bearing mice (n = 10) with PBS, IgG, GEM, mAb AR9.6, and mAb AR9.6 plus GEM. (B and C) Tumor weight (g) (B) and tumor volume (mm3) (C) of vehicle, IgG, GEM, mAb AR9.6, and GEM + mAb AR9.6-treated T3M4 orthotopic tumors. Data presented as mean ± SEM (n = 10; Dunnett’s multiple comparisons test). (D and E) IHC analysis of Ki-67 (D) and CD31 (E) in above mentioned experimental tumors. Data presented as mean ± SEM (n = 9; Dunnett’s multiple comparisons test). (F and G) IHC analysis of p-ErbB2 (F) and p-AKT (G) in above mentioned experimental tumors. (H and I) Mean histoscore of the IHC analysis of p-ErbB2 (H) and p-AKT (I) in above mentioned experimental tumors. All treatment groups were compared against vehicle control (PBS) treated groups. Scale bar, 40 μm. Data presented as mean ± SEM (n = 9; Dunnett’s multiple comparisons test).

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