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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 1 | J. Karkera et al.
Title: Oncogenic Characterization and Pharmacologic Sensitivity of Activating Fibroblast Growth Factor Receptor (FGFR) Genetic Alterations to the Selective FGFR Inhibitor Erdafitinib Jayaprakash D. Karkera1*, Gabriela Martinez Cardona1, Katherine Bell1, Dana Gaffney1, Joseph C. Portale1, Ademi Santiago-Walker1, Christopher H. Moy1, Peter King1, Michael Sharp1, Rastislav Bahleda2, Feng R. Luo3, John D. Alvarez1, Matthew V. Lorenzi1, and Suso J. Platero1§ 1Janssen Research and Development, LLC, Spring House, Pennsylvania 2Drug Development Department (DITEP), Gustave Roussy Cancer Campus and University Paris-Sud, Villejuif, France 3Janssen Research and Development, LLC, Raritan, New Jersey §Current Address: Suso Platero, PhD Head Precision Medicine Oncology Clinical Development Services Covance Inc. 206 Carnegie Center Princeton, NJ 08540-9375 Phone: 609-452-4893 E-mail: [email protected] Running title: Predictive and Pharmacodynamic Biomarkers for Erdafitinib Keywords: Erdafitinib, Fibroblast growth factor receptor (FGFR), FGFR inhibitor, biomarker, gene translocation Abbreviation list: EGFR epidermal growth factor receptor FFPE formalin-fixed paraffin-embedded FGF fibroblast growth factor FGFR fibroblast growth factor receptor FISH fluorescence in situ hybridization MAPK mitogen-activated protein kinase NSCLC non-small cell lung cancer pErk phospho-Erk pMAPK phosphorylated MAPK pS6 phosphorylated S6 SCC squamous cell carcinoma TBST tris-buffered saline plus 0.1% Tween 20 TMA the tissue microarray
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 2 | J. Karkera et al.
Study fund: Janssen Research and Development, LLC. *Corresponding Author: Jayaprakash Karkera, PhD Janssen Research and Development, LLC 1400 McKean Road Spring House PA 19477 Tel: 215-628-5219 Fax: 215-540-4763 E-mail: [email protected]
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 3 | J. Karkera et al.
Abstract
Fibroblast growth factor receptor (FGFR) genetic alterations are frequently observed
in cancer, suggesting that FGFR inhibition may be a promising therapy in patients harboring
these lesions. Identification of predictive and pharmacodynamic biomarkers to select and
monitor patients most likely to respond to FGFR inhibition will be the key to clinical
development of this class of agents. Sensitivity to FGFR inhibition and correlation with
FGFR pathway activation status were determined in molecularly annotated panels of cancer
cell lines and xenograft models. Pathway inhibition in response to FGFR inhibitor treatment
was assessed in cell lines (both in-vitro and in-vivo) and in samples from patients treated with
the FGFR inhibitor JNJ-42756493 (erdafitinib). Frequency of FGFR aberrations was
assessed in a panel of NSCLC, breast, prostate, ovarian, colorectal, and melanoma human
tumor tissue samples. FGFR translocations and gene amplifications present in clinical
specimens were shown to display potent transforming activity associated with constitutive
pathway activation. Tumor cells expressing these FGFR activating mutants displayed
sensitivity to the selective FGFR inhibitor erdafitinib and resulted in suppression of FGFR
phosphorylation and downstream signal transduction. Clinically, patients receiving
erdafitinib showed decreased Erk phosphorylation in tumor biopsies and elevation of serum
phosphate. In a phase I study, a heavily pre-treated bladder cancer patient with an FGFR3-
TACC3 translocation experienced a partial response when treated with erdafitinib. This
preclinical study confirmed pharmacodynamics and identified new predictive biomarkers to
FGFR inhibition with erdafitinib and supports further clinical evaluation of this compound in
patients with FGFR genetic alterations.
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 4 | J. Karkera et al.
Introduction
The successful development of new oncology therapies most unequivocally requires
identifying the patients most likely to respond to a particular targeted intervention. Thus, the
discovery and characterization of biomarkers that accurately distinguish those more likely to
respond patients from a broader population is critical for successful clinical development.
Examples of such biomarkers that have already been identified and approved as predictors of
response to therapy include human epidermal growth factor receptor (EGFR)-2 amplification,
which predicts positive response to trastuzumab in women with breast cancer (1), and KRAS
mutation, which predicts resistance to the EGFR inhibitors panitumumab and cetuximab in
individuals with colorectal tumors (2, 3). In lung cancer, EGFR activating point mutations
predict activity to EGFR tyrosine kinase inhibitors erlotinib and gefitinib (4), and ALK
translocation has been shown to be a predictor of response to crizotinib, a compound
targeting the ALK tyrosine kinase (5). More recently, fibroblast growth factor receptor
(FGFR) mediated signaling has been shown to play a role in tumor progression, and recent
evidence suggests that FGFRs are oncogenic drivers in various types of cancer (6),
highlighting the need to find predictive biomarkers of FGFR to support clinical development.
Fibroblast growth factors (FGFs) are a family of secreted factors involved in signaling
pathways responsible for embryonic development, cell proliferation, survival, and migration
(7). Twenty-two unique FGF family members have been identified, and are differentially
expressed in many, if not all, tissues and organ systems, albeit with different patterns and
timings (7). FGF activity is mediated by four transmembrane receptor tyrosine kinases
(FGFRs 1−4) (8). FGF binding induces FGFR dimerization, leading to phosphorylation of
the intracellular tyrosine kinase domain (9, 10). The dimerization-mediated phosphorylation
leads to the activation of downstream signaling transduction pathways, including FRS2, RAS,
RAF, mitogen-activated protein kinase (MAPK), PI3K/AKT, signal transducer and activator
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 5 | J. Karkera et al.
of transcription and Phospholipase-C-γ (9, 11), which culminate in transcriptional regulation
that mediates the functional outcomes of FGFR activation.
The normal regulation of FGFR signaling is often genetically subverted to
constitutively activate the pathway in a variety of malignancies. FGFR activation is
attributed to gene amplification, chromosomal translocation, alternative splicing, or point
mutations. Dramatic gene amplification of FGFR2 was originally observed in gastric tumor
cell lines, highlighting the oncogenic potential of the receptor family (12). Subsequently,
FGFR family alterations have been observed in several other malignancies including breast
cancer (FGFR1 amplification) (13), bladder (FGFR3 mutations) (14-16), colorectal (FGFR1
amplification, FGFR2 and FGFR3 mutations) (17), and hematologic cancers (FGFR3
overexpression) (18, 19). More recently, FGFR1 gene amplification has also been observed
in 10% of squamous cell carcinoma (SCC) lung cancer patient samples, but not in lung
adenocarcinoma (20). Notably, this aberration has been observed only in tumor samples
from patients with a history of smoking. Approximately 24% of all lung cancers are of the
SCC subtype, which is most common in patients with smoking histories (20-22). Unlike
other forms of non-small cell lung cancer (NSCLC), for which there are molecularly targeted
therapies available, SCC treatment options are generally limited to conventional
chemotherapy (23). FGFR1 is one of the first actionable genetic targets to be identified as
having therapeutic potential in SCC lung cancer, as evidenced in preclinical studies of
FGFR1 inhibition showing regression of FGFR1 amplified tumors in a xenograft model (20,
22). FGFR1 may also be a potential therapeutic target in other smoking-related malignancies
(22, 24).
FGFR translocations have also been recently observed in a broad range of malignant
cell lines, including glioblastoma, NSCLC, breast cancer, bladder cancer, and
cholangiocarcinoma (6, 25, 26), however, they largely remain functionally uncharacterized.
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 6 | J. Karkera et al.
FGFR2 was the first family member found to be activated by chromosomal rearrangement
(FGFR2-FRAG1) in a functional screen to identify oncogenes in osteosarcoma (27).
Recently, an FGFR3-TACC3 translocation has been reported in lung cancer (28, 29). In
general, FGFR translocations result in constitutive activation of FGFR, due to fusion of the
FGFR kinase domain with the N-terminal portion of an unrelated gene harboring domains
which promote constitutive receptor dimerization. This dimerization results in receptor
phosphorylation and downstream signaling leading to oncogenic transformation (6, 25, 27).
The identification of genetic alterations in multiple FGFR family members in human
cancers highlights pan-FGFR inhibition as a promising therapeutic approach in a variety of
malignancies. Several small molecule FGFR inhibitors with differing selectivity and potency
profiles, such as brivanib, dovitinib, AZD-4547, NVP-BGJ398, and erdafitinib, are in various
stages of clinical development. Here we determined the sensitivity of molecularly annotated
panels of cancer cell lines to FGFR pathway inhibition; assessed the frequency of select
FGFR alterations in tumor tissue samples from multiple cancers; and confirmed pathway
inhibition in clinical specimens from patients treated with erdafitinib. These analyses
revealed a high frequency of FGFR gene amplification in a variety of malignancies and tumor
cell lines. Cell lines harboring FGFR alterations were dependent on the active pathway for
survival and therefore sensitive to treatment with erdafitinib. We also extended this
characterization to FGFR2 and FGFR3 chromosomal rearrangements recently identified in
human tumors (26), highlighting the oncogenic potency of these fusions and their sensitivity
to FGFR inhibition. Collectively, these data further inform the oncogenic potency and
frequency of FGFR genetic alterations in human cancers and point to the use of specific
FGFR inhibitors as a rational approach to treating patients harboring these genetic
aberrations.
Materials and Methods
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 7 | J. Karkera et al.
Experimental gastric tumor models
All animal experiments were performed under approved protocols of the Institutional
Animal Use and Care Committee of Janssen Pharmaceuticals, Inc. Human gastric cancer
xenografts were established by injection of 106 SNU-16 cells (American Type Culture
Collection) from culture into male nude Nu/Nu rats (nude rate – Crl : NIH-Foxn1(mu) from
Charles River Laboratories). Tumors were grown for 18 days, followed by 10 days of dosing
with JNJ-42883919 (precursor of the clinical candidate erdafitinib) or vehicle. The rats were
subsequently sacrificed, and tumors were harvested and prepared into formalin-fixed
paraffin-embedded (FFPE) blocks. SNU-16 human gastric carcinoma cells (106 cells) were
fixed in 10% neutral buffered formalin and also processed for FFPE blocks. Tumor sections
and cell blocks were cut at a thickness of 4 μm and placed on silanized glass slides. Antigen
retrieval was carried out in AR10 citrate buffer (Biogenex) for 20 minutes at 120°C in a
Model 2100 Retriever (Prestige Medical). Tumor sections were incubated with rabbit
monoclonal anti-human pMAPK antibody or rabbit monoclonal anti-human p-S6 antibody
(Cell Signaling Technology) at room temperature for 45 minutes. Cell block sections were
incubated with rabbit polyclonal anti-human pFGFR3 (Santa Cruz Biotechnology, Inc.) at
room temperature for 45 minutes. The Dako EnVisionTM + DAB rabbit detection system
(Dako North America, Inc.) was used as described by the manufacturer, and sections were
counterstained in hematoxylin. All staining was carried out on a Biogenex i6000TM
Automated Staining System. Slides were scanned with an Aperio ScanScope (Leica
Biosystems), and images were analyzed for antigen content by positive pixel quantitation
using ImageScope software.
Fluorescence in situ hybridization (FISH)
The tissue microarrays (TMAs) for human NSCLC, prostate, colorectal, and breast
(ER/PR-positive) cancer were constructed and manufactured at ORDIS Biomed using tissues
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 8 | J. Karkera et al.
from the Biobank of the Medical University of Graz, the Lung Biobank of the Institute of
Pathology, and the Medical University of Innsbruck. Tissue blocks and the TMAs for
malignant melanoma, ovarian, and breast cancer were obtained from Asterand Bioscience.
The TMAs were constructed with triplicate 0.6 mm diameter cores extracted from FFPE
patient tumor samples, and tissue cores derived from canis lupus kidney were used as
orientation markers. Collection of tumor specimens was approved by local Institutional
Review Boards of Innsbruck and Graz, Austria.
Dual-color FISH probes for estimation of FGFR gene locus amplification were
designed, produced, and obtained from Kreatech Diagnostics (acquired by Leica Biosystem).
The FGFR1 probe was specific for locus 8p12 and SE8; the FGFR2 probe was specific for
locus 10q26 and SE10; and the FGFR3 probe was specific for locus 4p16 and the
chromosome-4 centromere (SE4). For estimation of FGFR4 gene locus amplification, a
probe specific for NSD1 (5q35) was used as a surrogate for the FGFR4 gene locus (5q33) and
an hTERT (5p153) probe was used as a hybridization control.
Probe hybridization was executed per standard procedures with optimized
pretreatment conditions for the individual tissue types. In brief, 1.5-5 µm sections of TMAs
were deparaffinized at 65°C for 30 minutes and washed with Hemo-De solvent. Tissue
pretreatment was executed with 0.2 N hydrochloric acid (20-45 minutes, room temperature),
followed by microwave heating (600 W, 20 minutes) and a final protease (Abbott) treatment
(15-75 minutes, 37°C). For co-denaturation, mixed probes (i.e., FGFR1/SE8 and
FGFR2/SE10) were applied on each section and incubated at 80°C for 5 minutes.
Subsequent hybridization was performed at 38-42°C overnight (16-18 hours). Post-
hybridization washings were performed with 2X saline-sodium citrate/0.3% NP-40 detergent
(72°C, 5 minutes). Finally, slides were dehydrated, stained with 4', 6-diamidino-2-
phenylindole, and covered with Vectashield® (Vector Laboratories).
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 9 | J. Karkera et al.
FISH signals in tumor tissue were enumerated in non-overlapping nuclei with
complete and intact contours. Target signals (red; i.e., FGFR1 and FGFR2) and control
signals (green; i.e., SE8 and SE10) were recorded for each individual core. Digital FISH
images were captured using a Zeiss Axiophot microscope with an Axiocam MRm camera
(Zeiss) at a magnification of 1000X. Images were processed using Adobe PhotoshopTM 7.0
and exported at a resolution of 150 pixels/inch.
Gene amplification was estimated by the gene ratio (number of target signals vs.
control). A gene ratio ≥ 2 was defined as amplification. When gene locus amplification was
restricted to < 20% - 50% of the tumor, an average gene ratio of < 2 was computed (i.e.,
down to 1.4). These cases were classified as amplified but presenting with substantial intra-
tumor heterogeneity. The gene dose of either target or control was computed by the ratio of
number of target signals vs. nuclei evaluated. A gene dose ≥ 3 was defined as gene dose
elevation (i.e., FGFR1, FGFR2, FGFR3, or FGFR4) or polysomy of the probed chromosome
(i.e., SE4, SE8, or SE10). Student’s t-test was used to determine statistical differences
between FGFR genetic profiles in different types of prostate cancer and between SCC and
adenocarcinoma in NSCLC.
FGFR fusion overexpressing cell lines
RK3E cells (American Type Culture Collection), from rat kidney epithelial cells,
were cultured in DMEM supplemented with 10% FBS and 1% antibiotics (Invitrogen).
FGFR fusion gene constructs were designed and cloned into the pReceiver expression vector
(Genecopoeia). Clones were transfected into RK3E cells using the Amaxa Cell Line
Nucleofector (Lonza) following the manufacturer’s protocol. The stably transfected cells
were selected in complete medium with 800 μg/mL of G418 (Invitrogen). Overexpression of
the fusions in the stably transfected cells was confirmed by real-time PCR and
immunoblotting.
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 10 | J. Karkera et al.
Colony formation assay
Anchorage independent growth of the fusion gene overexpressing cells was tested.
One mL culture medium with 0.8% low melting point agarose was first plated into each of
three wells of a six-well plate. After the agar solidified, each well received another 1 mL of
0.4% agar in culture medium containing 100 cells. After 14 days, colonies were fixed and
stained with 0.1% cresyl crystal violet (Sigma-Aldrich). The number of colonies was
determined microscopically by manual counting from triplicate wells for each cell line.
Immunoblotting analysis
Fusion overexpressing RK3E cells were plated in complete growth medium, serum
starved overnight, then re-fed with 0.5% FBS growth media. Cells were treated with 1μM of
erdafitinib and comparator compounds in the presence of ligands for 1 hour. For
immunoblotting, whole cell lysates were collected in RIPA buffer (Thermo Fisher Scientific)
and sample protein concentration was assayed using BCA Protein Assay (Thermo Fisher
Scientific). Equal amounts of protein (30 μg per lane) were loaded onto 4-12% Bis-Tris gels
(Invitrogen) followed by SDS-page. Proteins were transferred to nitrocellulose membranes
and probed with antibodies against p-FGFR (#3476), total-FGFR2 (#11835), p-MAPK
(#4370), total-MAPK (#4695), p-S6 (#4858), total S6 (#2317), B-actin (#3700 or #8457)
(Cell Signaling Technology), and total-FGFR3 (Santa Cruz Biotechnology). The membranes
were blocked with Odyssey blocking buffer (Li-Cor Biosciences) for 1 hour at room
temperature, and then incubated overnight at 4°C in a primary antibody solution (1:1000)
diluted in Odyssey blocking buffer. After three washes in tris-buffered saline plus 0.1%
Tween 20 (TBST) the membranes were probed with goat anti-mouse or donkey anti-rabbit
IRDye® 680RD or 800CW (Li-Cor Biosciences) labelled secondary antisera (1: 10,000) in
Odyssey blocking buffer for 1 hour at room temperature. Washes were repeated after
secondary labelling and the membranes were imaged using an Odyssey scanner and the
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 11 | J. Karkera et al.
Odyssey 3.0 analytical software (Li-Cor Biosciences). Effects of erdafitinib were compared
with AZD4547 and NVP-BGJ398.
Drug response testing for FGFR fusion overexpressing cell lines
Fusion overexpressing RK3E cells were seeded into CulturPlate-96 (Perkin Elmer)
well plates (1000 cells/well) in triplicate in complete growth medium plus the ligands FGF-1
and FGF-2 (R&D Systems Inc.). After 24 hours, cells were serum starved overnight then re-
fed with 0.5% FBS growth media plus FGF-1 and FGF-2. Seventy-two hours after plating,
cells were treated with an 18 point 1:3 dilution series, starting at 10 μM of erdafitinib,
AZD4547, and NVP-BGJ398. The Microtiter plates were then incubated for 72 hours and
assayed for adenosine triphosphate content using the Cell Titer-Glo® Luminescent Cell
Viability assay (Promega Corp.) following the manufacturer’s instructions with
modifications. Briefly, the cells were allowed to equilibrate to room temperature, at which
time a 1:1 mixture of Cell Titer-Glo® reagent was added. The cells were then placed on an
orbital shaker for 2 minutes and incubated for 10 minutes at room temperature to stabilize the
luminescent signal. The luminescence was quantified and the measurements were then
conducted using an Envision Multilabel plate reader (Perkin Elmer). IC50 values were
calculated using GraphPad Prism 5.0 (GraphPad Software Inc.).
Test and authentication of cell lines
The RK3E and SNU-16 cells lines were purchased directly from American Type Culture
Collection on September 4, 2014. The cell lines were tested for Mycoplasma using the
MycoAlert kit (Lonza) before they were used in any experiments. After four passages the
cell lines were aliquoted and frozen in vials as stocks. The transformed stable cell lines were
last tested in July 2015. No independent cell line authentication was performed on these cell
lines.
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 12 | J. Karkera et al.
Phase I clinical trial
Erdafitinib, or JNJ-42756493 (Supplement Figure S1), discovered in collaboration
with Astex Pharmaceuticals, is an investigational agent currently in clinical development.
The dose escalation and expansion phase I study has been previously described (30).
Immunohistochemical analysis of tumor pharmacodynamic biomarkers
Tumor biopsies for pharmacodynamic analyses were optional in the dose escalation
phase but mandatory in the dose confirmation phase. Tumor biopsy samples were collected
at pretreatment (within 28 days prior to the first dose of study drug) and posttreatment (Day 1
of Cycle 2 ± 7 days). Immunohistochemical analysis was performed on the Ventana
Benchmark platform using a standard protocol. The phospho-p44/42 MAPK (Erk1/2)
(Thr202/Tyr204) (D13.14.4E) rabbit mAb #4370 (R647) from Cell Signaling Technology
was used as the detecting antibody.
Results
Predictive and pharmacodynamic biomarkers
SNU-16 cells, which carry a high-level FGFR2 amplification, were sensitive to the
FGFR inhibitor JNJ-42883919, and FGFR phosphoprotein levels decreased upon treatment
with the study drug, as measured by immunohistochemical staining of FFPE tumor cells (Fig.
1A and B). Quantification of the pan-FGFR signal in SNU-16 cells treated with the vehicle
versus with the FGFR inhibitor showed a shift from strong labelling to more moderate
labelling (Fig. 1B). In athymic rats carrying SNU-16 gastric tumor xenografts,
phosphorylated S6 and MAPK (pS6 and pMAPK) levels markedly decreased upon treatment
with JNJ-42883919 (Fig. 1C-F), thus confirming downstream signal transduction endpoint
modulation that could be explored as pharmacodynamics marker of response in a clinical
trial.
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 13 | J. Karkera et al.
To determine the frequency of FGFR amplifications in human cancers, tumor
microarrays were analyzed by FISH for the presence and abundance of the four FGFR genes
(Fig. 2). In breast tumor samples FGFR1, FGFR2, FGFR3, and FGFR4 were amplified at a
frequency of 11.7% (29/248), 6.6% (13/198), 3% (1/29), and 8.6% (15/175), respectively. In
NSCLC tumor samples FGFR1, FGFR2, FGFR3, and FGFR4 were amplified at a frequency
of 21.6% (45/208), 5.6% (11/195), 5.3% (1/19), and 5.1% (5/99), respectively (Supplement
Table S1). In prostate tumor samples only FGFR1 and FGFR2 amplifications were measured
and the frequencies were 14.6% (14/96) and 1.1% (1/94), respectively. While in ovarian
cancer FGFR1 and FGFR2 were amplified at a frequency of 2.9% (1/35) and 5.6% (2/36),
respectively. No FGFR family gene amplifications were detected in either colon cancer or
malignant melanoma tumor samples (Supplement Table S1).
Characterization of FGFR fusion genes
One tumor cell line, RT-4, in the selected tumor cell line panel analyzed carries an
FGFR3 C-terminal translocation and was sensitive to both JNJ-42541707 (IC50 = 27 nM) and
erdafitinib (IC50 = 0.19 nM, Supplement Table S2). Based on this finding we assessed the
capability of other clinically relevant FGFR translocations to transform normal RK3E cells
and confer sensitivity to erdafitinib (26). FGFR3:TACC3v1, FGFR3:TACC3v3,
FGFR3:BAIP2L1, FGFR2:BICC1, FGFR2:AFF3, FGFR2:CASP7, FGFR2:CCDC6, and
FGFR2:OFD1 translocations were cloned into vectors and transfected into untransformed
RK3E recipient cells to determine the oncogenic potential of the FGFR alterations in an
anchorage independent growth assay. All FGFR activating translocations tested conferred
the ability to promote soft agar growth compared to wild type FGFRs (Fig. 3A). The
transformation activity of these translocations was associated with constitutive activation of
FGFR and downstream signaling. The effects of three pan-FGFR inhibitors, erdafitinib,
AZD4547, and NVP-BGJ398 on the MAPK signaling pathway in RK3E cells expressing
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 14 | J. Karkera et al.
these FGFR fusion genes was assessed by immunoblotting. All FGFR inhibitors tested
reduced the levels of MAPK and S6 phosphorylation induced by the transfection of RK3E
cells with FGFR3 and FGFR2 fusion proteins (Fig. 3B). In contrast, the effect of AZD4547
and NVP-BGJ398 on proliferation of these FGFR fusion gene-expressing cells was weaker
than the growth inhibition by erdafitinib (Supplement Table S2). The detection of total
FGFR2 by the FGFR2 antibody was not successful in any of the FGFR2 fusion harboring
RK3E cells, but we could detect the HA tag expression in each of the FGFR2 overexpressing
cell lines thus suggesting that the FGFR2 protein was expressed (Supplement Figure S2).
The failure to detect FGFR2 by FGFR2 antibody could potentially be due to the masking of
the specific epitope the FGFR2 antibody targets caused by the tertiary conformation of the
fusion protein. Overall, these results demonstrate that the FGFR2 and FGFR3 translocations
tested are oncogenic and confer sensitivity to FGFR inhibitors.
Assessment of response markers in patients treated with erdafitinib
To confirm the utility of pharmacodynamic markers identified in this study,
immunohistochemical analysis for phospho-Erk (pErk), a downstream mediator of the FGFR
pathway, was carried out on pretreatment and posttreatment biopsies from patients treated
with erdafitinib (30). Samples were obtained from two patients enrolled in the phase I
clinical trial of erdafitinib. One breast cancer patient with archival tumor harboring a FGFR1
amplification was treated with erdafitinib at 12 mg daily for 2 weeks and biopsied after 7
days of drug interruption (Fig. 4A). An approximate 40% reduction in pErk posttreatment
was observed. In another patient with pleural mesothelioma of unknown FGFR status (Fig.
4B), a 45% reduction in pErk was observed after 3 weeks of treatment with erdafitinib at 6
mg daily. Other pharmacodynamic makers such as calcium, phosphate, soluble FGF23,
soluble VEGFR, soluble FGFR2, 3 and 4, and vitamin D, were also measured from sera of
patients undergoing the trial. Of those, only phosphate levels showed significant dose
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 15 | J. Karkera et al.
proportional changes upon treatment (30). The increase of serum phosphate concentrations
in response to erdafitinib, due to renal tubular FGFR inhibition (31), extends similar findings
on serum phosphate levels observed for other FGFR inhibitors (32).
In the phase I study (30), a 52-year old bladder cancer patient, enrolled in the dose
escalation cohort, with metastases to the lung who had failed three prior therapies was treated
with erdafitinib. This patient had tumor shrinkage of 38% (Fig. 5) with a confirmed partial
response by RECIST criteria (33), and stayed on treatment (at 9 mg daily) for about 10
months. The tumor shrinkage was calculated based on target lesion measurements at baseline
and posttreatment efficacy assessment time point. The FGFR3-TACC3 translocation was
detected in this patient’s tumor sample, extending the observation that these alterations are a
predictor of sensitivity to erdafitinib clinically.
Discussion
A detailed analysis of sensitive and resistant cell lines identified FGFR gene
amplification and translocations as potential markers of response to FGFR inhibitors.
FGFR2 and FGFR3 translocations were shown to be potent oncogenes and resulted in
constitutive FGFR phosphorylation and downstream signaling. Transformed cells expressing
these FGFR alterations were sensitive to FGFR small molecule inhibition with several
inhibitors in clinical development, but erdafitinib showed the highest potency in a
comparative analysis. Interestingly, a patient whose tumor harbored an FGFR translocation,
FGFR3-TACC3, showed a durable partial response to erdafitinib by RECIST criteria,
demonstrating that the effects observed in cell lines were also applicable to cancer patients in
the clinic.
FGFR amplifications were shown to be frequent genetic events in a variety of
malignancies. Preclinically, sensitivity was also seen with FGFR amplifications in tumor cell
lines and xenografts models, where a decrease in signaling downstream of FGFR was
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 16 | J. Karkera et al.
demonstrated upon administration of FGFR inhibitors. Recent report of positive clinical
activity of FGFR inhibitor AZD4547 in gastric and breast cancer patients with high-level
amplification of FGFR2 is very encouraging (34). Interestingly, in the current study the
high-level amplification of FGFR2 was observed in breast, NSCLC, and ovarian cancers at a
frequency of 6.6%, 5.6%, and 6.0%, respectively. But, in a recent report (35) using next-
generation sequencing method, researchers reported the amplification of FGFR2 in breast,
NSCLC, and ovarian cancers at a frequency of 0.8%, 1.7%, and 0.3%, respectively.
Similarly, a high-level amplification of FGFR1 was reported in breast, ovarian, and NSCLC
at a frequency of 14%, 5%, and 9% (NSCLC squamous) or 4% (NSCLC adenocarcinoma)
(35), respectively, whereas, our data using the FISH method showed a frequency of 11.7%,
2.9%, and 21.6%, respectively. The discrepancy of the findings may be due to the different
methodologies used in the assessment of the FGFR high-level amplifications. The SNU-16
gastric cell line with high-level of FGFR2 amplification has been shown to be sensitive to
erdafitinib, which is in concordance with the data reported for AZD4547 (34). However,
overexpression of FGFRs in transformation assays is not sufficient to confer a potent
oncogenic effect without ligand expression (27), suggesting that FGFR gene amplifications
may be less dominant driver pathway events compared to translocations.
A key aspect of drug development is generating clinical data to support what dose
levels are taken forward into late clinical development. To this end, we examined FGFR-
mediated signal transduction and functional endpoints to determine maximal target
engagement as a component of dose selection. In preclinical models, down regulation of the
pharmacodynamic biomarkers (pErk and pS6) was demonstrated in the SNU-16 model after
treatment with an FGFR inhibitor. These endpoints were subsequently shown to be
modulated in two patients receiving erdafitinib, confirming the activity of the inhibitor on
suppressing FGFR-mediated signal transduction (36). Serum phosphate homeostasis has
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 17 | J. Karkera et al.
been reported to be controlled by FGFR activity in the renal tubules through the FGF23-
klotho signaling axis and that genetic deletion of FGF23 results in upregulation of serum
phosphate (32). We showed that erdafitinib regulating serum phosphate levels in a dose
dependent manner in patients was managed clinically through chelation therapy and was not
associated with significant adverse events (30), an observation consistent with this being an
on-mechanism class effect (26). Interestingly, FGFR-mediated phosphate increases provide
an interesting on-mechanism endpoint for monitoring clinical target engagement to support
subsequent dose selection.
In conclusion, the data from this study credential FGFR amplifications and C-terminal
translocations as dominant oncogenic events that confer sensitivity to small molecule FGFR
inhibitors. These FGFR activating alterations resulted in constitutive pathway activation that
was observed preclinically and clinically. On-target FGFR-mediated changes in phosphate
regulation were observed clinically and a patient expressing a FGFR3-TACC3 translocation
received clinical benefit from treatment with JN-J42756493. Collectively, these observations
highlight erdafitinib as a selective FGFR family inhibitor and support its ongoing clinical
development in patients with activating FGFR genetic alterations.
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 18 | J. Karkera et al.
Acknowledgments
This study was funded and supported by Janssen Research & Development, LLC.
The authors would like to thank Harry Ma for writing and editorial assistance; Clifford O.
Motley, Dan Rhodes, Timothy Perera, Chris Takimoto, Vijay Peddareddigari, and Marcus
Otte for their support and guidance.
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 19 | J. Karkera et al.
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 22 | J. Karkera et al.
Figure Legends
Figure 1. Pharmacodynamic markers of FGFR inhibition. SNU-16 cells stained with anti-
pan-FGFR. A. Vehicle; B. After treatment with JNJ-42883919. Tumors harvested from rats
carrying SNU-16 xenografts were stained with anti-pS6 (panels C and D) and anti-pMAPK
(panels E and F). Tumors of vehicle control treated animals are shown in panels C and E;
Xenograft tumor of animals treated with JNJ-42883919 is shown in D and F.
Figure 2. Fluorescence in situ hybridization analysis of FGFR gene amplifications. A.
FGFR1; B. FGFR2 gene locus amplification in NSCLC; C. High-grade FGFR1 gene locus
amplification in ER/PR-positive breast cancer; D. High-grade FGFR2 gene locus
amplification in triple-negative breast cancer; E. FGFR1; and F. FGFR2 low- to moderate-
grade amplification in prostate cancer; G. FGFR4 low-grade level gene amplification in
breast cancer.
Figure 3. Characterization of FGFR2 and FGFR3 fusion gene transformation activity and
sensitivity to FGFR inhibitors. A. Effect of expression of FGFR2 and FGFR3 fusion
constructs in RK3E cells in an anchorage independent colony assay; B. Effect of FGFR
inhibitors on MAPK signalling pathway in RK3E cells expressing stable FGFR2 and FGFR3
fusion constructs and empty vector.
Figure 4. Pharmacodynamic biomarkers modulation in patients receiving erdafitinib.
Phospho-Erk staining in: A. a patient with breast cancer receiving erdafitinib 12 mg daily; B.
a patient with pleural mesothelioma receiving erdafitinib 6 mg daily. Left and right panels
represent pre-dose and post-dose conditions, respectively.
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Predictive and Pharmacodynamic Biomarkers for Erdafitinib 23 | J. Karkera et al.
Figure 5. CT scan images of a patient with FGFR3-TACC3-translocated bladder cancer with
a confirmed partial response in lung metastases (marked with white arrows on baseline scans)
responding to erdafitinib. A and C are baseline lung images, and B and D are posttreatment
lung images at week 6 for the same patient.
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Figure 1
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Figure 2
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Figure 3
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B
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Figure 4
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B
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Figure 5
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Published OnlineFirst April 17, 2017.Mol Cancer Ther Jayaprakash D. Karkera, Gabriela Martinez Cardona, Katherine Bell, et al. Alterations to the Selective FGFR Inhibitor ErdafitinibActivating Fibroblast Growth Factor Receptor (FGFR) Genetic Oncogenic Characterization and Pharmacologic Sensitivity of
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