Targeting FGFRs Using PD173074 as a Novel Therapeutic Strategy in Cholangiocarcinoma

Abstract

Cholangiocarcinoma (CCA) is an architecturally complex tumour with high heterogeneity. Discovery at later stages makes treatment challenging. However, the lack of early detection methodologies and the asymptomatic nature of CCA make early diagnosis more difficult. Recent studies revealed the fusions in Fibroblast Growth Factor Receptors (FGFRs), a sub-family of RTKs, as promising targets for targeted therapy for CCA. Particularly, FGFR2 fusions have been of particular interest, as translocations have been found in approximately 13% of CCA patients. Pursuing this, Pemigatinib, a small-molecule inhibitor of FGFR, became the first targeted therapy drug to be granted accelerated approval by the FDA for treating CCA patients harbouring FGFR2 fusions who have failed first-line chemotherapy. However, despite the availability of Pemigatinib, a very limited group of patients benefit from this treatment. Moreover, as the underlying mechanism of FGFR signalling is poorly elucidated in CCA, therapeutic inhibitors designed to inhibit this pathway are prone to primary and acquired resistance, as witnessed amongst other Tyrosine Kinase Inhibitors (TKIs). While acknowledging the limited cohort that benefits from FGFR inhibitors, and the poorly elucidated mechanism of the FGFR pathway, we sought to characterise the potential of FGFR inhibitors in CCA patients without FGFR2 fusions. Here we demonstrate aberrant FGFR expression in CCA samples using bioinformatics and further confirm phosphorylated-FGFR expression in paraffinised CCA tissues using immunohistochemistry. Our results highlight p-FGFR as a biomarker to guide FGFR-targeted therapies. Furthermore, CCA cell lines with FGFR expression were sensitive to a selective pan-FGFR inhibitor, PD173074, suggesting that this drug can be used to suppress CCA cells irrespective of the FGFR2 fusions. Finally, the correlation analysis utilising publicly available cohorts suggested the possibility of crosstalk amongst the FGFR and EGFR family of receptors as they are significantly co-expressed. Accordingly, dual inhibition of FGFRs and EGFR by PD173074 and EGFR inhibitor erlotinib was synergistic in CCA. Hence, the findings from this study provide support for further clinical investigation of PD173074, as well as other FGFR inhibitors, to benefit a larger cohort of patients. Altogether, this study shows for the first time the potential of FGFRs and the importance of dual inhibition as a novel therapeutic strategy in CCA.

Keywords: FGFR inhibitors; biliary tract cancer; cholangiocarcinoma; molecular targeted therapy; precision medicine; therapeutic biomarker.

Figure 1

Aberrant expression of FGFRs is present in CCA tissues. Boxplot histograms represent the comparative gene expression of (A) FGFR1, (B) FGFR2, (C) FGFR3, (D) FGFR4, (E) FGF1, and (F) FGF3 and (G) FGF20 between CCA (n = 704) and normal (n = 165) tissues. (H) Heatmap represents unsupervised clustering of FGFR1, FGFR2, FGFR3 and FGFR4 expression in CCA tissues. (I) Multidimensional (MDS) plot of the integrated signature of the clusters using the expression profile FGFRs (n = 4). (J) Volcano plots illustrate significantly differentially expressed genes (DEGs) in the high and low expression groups as red dots (adjusted p < 0.001, log2 fold changes) and insignificant genes as grey. (K) Significantly enriched pathways of the DEGs. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.

Figure 2

Clinical relevance of pFGFR expression in CCA. Collective mRNA expression of FGFRs (FGFR1, FGFR2, FGFR3 and FGFR4) in CCA compared to normal tissues in (a) GSE107943 and (d) TCGA cohort. The Kaplan–Meier plot shows the correlation of FGFR expression with (b) overall survival and (c) disease-free survival in the GSE107943 cohort and (e) overall survival (OS) and (f) disease-free survival (DFS) in the TCGA-CHOL cohort. (g) Immunohistochemical staining for p-FGFR in CCA tissues (20× objective). (h) The boxplot shows the signal intensity values of p-FGFR for each case in the low and high expression groups. (i) Kaplan–Meier plot showing a correlation between patient’s survival and the expressions of p-FGFR in CCA tissues compared to each other. Survival analysis was performed using the R package ‘survival’ and ‘survminer’ and GraphPad Prism 9. *** p < 0.001, **** p < 0.0001.

Figure 3

PD173074 effectively reduces cell viability and induces cytotoxicity in CCA cells. (a) Drugs enriched to target FGFRs in Enrichr. (b) Heatmap and oncoplot represent the gene expression and mutations of FGFRs in CCA cell lines from a public repository, the Cancer Dependency Map (DepMap) portal. Baseline mRNA expression of (c) FGFR1, (d) FGFR2, (e) FGFR3 and (f) FGFR4 in CCA cell lines by qPCR. CCA cells, (g) KKU-100, (h) KKU0213, (i) RBE and (j) TFK-1 were treated with varying concentrations of FGFR inhibitor, PD173074. (k) The cell viability results at 72 h were used to calculate the half-maximal inhibitory concentration (IC50) for each cell line. The dose–response curve was fitted to a non-linear model, and IC50 was calculated using GraphPad Prism. (l) The effect of PD1730374 on KKU-213 and RBE cells by colony formation assay.

Figure 4

PD173034 induces apoptosis in CCA. (a) Flow cytometry analysis of apoptotic cells stained with Annexin V and PI post-treatment with vehicle control (DMSO), 5 and 10 µM of PD173074 for 24 h. The percentage of apoptotic cells in (b) KKU-213 and (c) RBE cells post-treatment. Caspase activity was measured as optical density. Bar graph representing optical density after treatment with PD173074 or vehicle control for 48 h in (d) KKU-213 and (e) RBE cells. Bar graph representing optical density after treatment with PD173074 time-dependently in (f) KKU-213 and (g) RBE cells. Comparisons of data between groups were made with Student’s t-test in GraphPad Prism. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p <0.0001.

Figure 5

PD173074 inhibits FGF-1-activated phosphorylation of FGFRs in KKU-213 cells. (a) FGF-1 increases p-FGFR expression, which can be inhibited by PD173074 in KKU-213 cells. (b) The antibody array of phospho-kinases shows that PD173074 (5 µM) inhibits multiple kinases following 24 h treatment in KKU-213. Fold change of kinases (c) inhibited and (d) upregulated following treatment with PD173074 in KKU-213. Protein-protein interaction (PPi) network of (e) downregulated and (f) upregulated kinases. P-STAT3 expression is downregulated following p-FGFR inhibition by PD173074 in (g) KKU-213 and (h) RBE cells. (The original Western blot is in the Supplementary File S1).

Figure 6

Combination treatment with PD173074 and erlotinib is synergistic in CCA. EGFR inhibitor erlotinib increases the sensitivity of PD173074 in CCA. The cells were treated with 2-fold increasing concentrations of PD173074 and Erlotinib for 96 h. The dose–response matrix shows percentage cell survival in (a) KKU-213 and (b) RBE. The dose–response curve for PD173074 in combination with increasing concentrations of erlotinib in (c) KKU-213 and (d) RBE. Synergy scores were calculated according to (e,h) Loewe’s additivity mathematical model, (f,i) Highest Single Agent (HSA) model and (g,j) Bliss Independence model using the R package ‘SynergyFinder’.

Figure 7

Sensitivity of PD173074 in combination treatment in patient cells derived from CCA patients in 3-D Tumour growth assays (TGA). (A,B) Two primary cell lines were derived from surgically resected CCA tissue samples CCA-UK5 and CCA-UK6 (20× magnification). Sensitivity of primary lines to (C,D) Erlotinib, PD173074 and combinations of Erlotinib and PD173074. IC50s of CCA cells, in the presence of MSCs and CAFs by (E) Erlotinib, (F) PD173074, (G) Erlotinib + PD173074 and (H) Gemcitabine/Cisplatin.