Disease-induced immunomodulation at biomaterial scaffolds detects early pancreatic cancer in a spontaneous model

Abstract

Pancreatic cancer has the worst prognosis of all cancers due to disease aggressiveness and paucity of early detection platforms. We developed biomaterial scaffolds that recruit metastatic tumor cells and reflect the immune dysregulation of native metastatic sites. While this platform has shown promise in orthotopic breast cancer models, its potential in other models is untested. Herein, we demonstrate that scaffolds recruit disseminated pancreatic cells in the KPCY model of spontaneous pancreatic cancer prior to adenocarcinoma formation (3-fold increase in scaffold YFP + cells). Furthermore, immune cells at the scaffolds differentiate early- and late-stage disease with greater accuracy (0.83) than the natural metastatic site (liver, 0.50). Early disease was identified by an approximately 2-fold increase in monocytes. Late-stage disease was marked by a 1.5-2-fold increase in T cells and natural killer cells. The differential immune response indicated that the scaffolds could distinguish spontaneous pancreatic cancer from spontaneous breast cancer. Collectively, our findings demonstrate the utility of scaffolds to reflect immunomodulation in two spontaneous models of tumorigenesis, and their particular utility for identifying early disease stages in the aggressive KPCY pancreatic cancer model. Such scaffolds may serve as a platform for early detection of pancreatic cancer to improve treatment and prognosis.

Keywords: Biomaterials; Immunomodulation; Metastasis; Pancreatic cancer.

Figure 1:

Late stage pancreatic cancer (22-week-old mice) is identified through cell and tissue infiltration at the scaffold. (A) Timeline of pancreatic cancer formation in the KPCY model. (B) YFP+ (green) disseminated pancreatic cells are more concentrated in scaffolds from KPCY mice than scaffolds from CY mice. Cells were identified with DAPI (blue). (C) Quantification of YFP intensity in the scaffold. Grey dotted line represents YFP- mice autofluorescence control, n = 30. (D) H&E staining of scaffolds explanted from CY and KPCY mice. (E) Quantification of cell and tissue infiltration in the scaffolds. KPCY scaffolds exhibited increased tissue infiltration (Eosin positive), increased cellular infiltration, higher cell density within infiltrated area, and decreased density variability (coefficient of variation; CV), n = 17–18. Black lines denote medians, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Figure 2:

Disseminated pancreatic cells are identified in the scaffold prior to the formation of PDAC. (A) The percentage of YFP+ cells in the scaffold when mice are 12–16 weeks, as measured by flow cytometry. Black lines denote medians. Grey dotted lines represent YFP- mice autofluorescence control, n = 8–11. (B) YFP intensity at the scaffold measured by IVIS can distinguish KPCY and CY mice as early as 10 weeks of age in a longitudinal analysis. Grey dotted line represents YFP- mice autofluorescence control, n = 5. (C) Representative fluorescent images of the scaffolds under IVIS. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Figure 3:

Immune cell dynamics at the scaffold differentiate early and late stage pancreatic cancer. Heat maps were built using the fold change of immune cell populations in the KPCY mice relative to the CY mice for the (A) scaffold, (B) pancreas, and (C) liver. The scaffold can more successfully delineate disease stage then either the site of the primary tumor (pancreas) or the native metastatic site (liver). Cell types were identified as CD45+ (total immune cells), F4/80+CD11b+ (macrophages), Gr1+CD11b+ (neutrophils), Ly6C+CD11b+ (monocytes), CD11c+F4/80- (dendritic cells), CD19+ (B cells), CD4+ (CD4+ T cells), CD8+ (CD8+ T cells), and CD49b+ (NK cells).

Figure 4:

Temporal evolution of immune cells in the scaffold pre-metastatic niche prior to the formation of PDAC. The dotted lines represent the CY healthy controls. Cell types were identified as (A) CD45+ (total immune cells), (B) F4/80+CD11b+ (macrophages), (C) Gr1+CD11b+ (neutrophils), (D) Ly6C+CD11b+ (monocytes), (E) CD11c+F4/80- (dendritic cells), (F) CD19+ (B cells), (G) CD4+ (CD4+ T cells), (H) CD8+ (CD8+ T cells), and (I) CD49b+ (NK cells). * p < 0.05 relative to the CY control, # p < 0.05 over time, n = 5.

Figure 5:

Scaffolds recruit tumor cells in the MMTV-PyMT model of spontaneous breast cancer and reflect tumor-dependent immunomodulation. (A) Timeline of breast cancer formation in the PyMT model. (B) The number of RFP+ cells increase in the scaffolds, lungs, and mammary fat pads (MFP) in PyMT+ mice relative to tumor free controls. (C) Innate immune cell types were identified as CD11b+Gr1+ (neutrophils), CD11c+F4/80- (dendritic cells), CD11b+F4/80+ (macrophages), and Ly6C+F480- (monocytes). The dotted lines represent the tumor free controls. *p < 0.05 relative to the tumor free control, n ≥ 8.

Figure 6:

Principal component analysis of KPCY pancreatic cancer (early disease and end stage disease) and PyMT breast cancer mice (end stage disease). Ellipses identify 90% confidence intervals. The two types of cancers diverge in the response of the immune cells as pancreatic cancer progresses.