Identification of a Therapeutic Strategy
Targeting Amplified FGF19 in Liver Cancer
by Oncogenomic Screening
Eric T. Sawey,1Maia Chanrion,1Chunlin Cai,1Guanming Wu,2Jianping Zhang,1Lars Zender,1Alice Zhao,3
Ronald W. Busuttil,4Herman Yee,5Lincoln Stein,1,2Dorothy M. French,6Richard S. Finn,3Scott W. Lowe,1,*
and Scott Powers1,*
1Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
2Ontario Institute for Cancer Research, Toronto, Ontario M5G 0A3, Canada
3Department of Medicine
4Department of Surgery
Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
5Department of Pathology, New York University School of Medicine, Bellevue Hospital Center, New York, NY 10016, USA
6Department of Pathology, Genentech Incorporated, South San Francisco, CA 94080, USA
*Correspondence: email@example.com (S.W.L.), firstname.lastname@example.org (S.P.)
We screened 124 genes that are amplified in human hepatocellular carcinoma (HCC) using a mouse hepato-
blast model and identified 18 tumor-promoting genes, including CCND1 and its neighbor on 11q13.3, FGF19.
Although it is widely assumed that CCND1 is the main driving oncogene of this common amplicon
(15% frequency in HCC), both forward-transformation assays and RNAi-mediated inhibition in human HCC
cells established that FGF19 is an equally important driver gene in HCC. Furthermore, clonal growth and
tumorigenicity of HCC cells harboring the 11q13.3 amplicon were selectively inhibited by RNAi-mediated
knockdown of CCND1 or FGF19, as well as by an anti-FGF19 antibody. These results show that 11q13.3
amplification could be an effective biomarker for patients most likely to respond to anti-FGF19 therapy.
Developing cancer therapeutic strategies is particularly impor-
tantinhuman hepatocellular carcinoma (HCC),which haslimited
treatment options and generally poor prognosis (Minguez et al.,
activated oncogene for their sustained proliferation or survival
(Weinstein and Joe, 2008). One of the best-described cases of
oncogene dependence with corresponding therapeutic efficacy
is HER2 amplification in breast cancers (Faber et al., 2010). This
argues that the wealth of genomic information that now exists
regarding gene amplification in cancer could be used to find
passenger genes are coamplified with the tumor-promoting
driver genes, which complicates driver gene identification
(Albertson et al., 2003). Currently, the only genome-wide
approaches to amplified driver gene identification are computa-
tional (Beroukhim et al., 2010; Woo et al., 2009).
The primary goal of this study was to develop a genome-wide
functional approach that could assess, in an appropriate genetic
and physiological context, the oncogenicity of candidate driver
genes from amplicons found in human HCC. Our second
goal was to determine if a specific driver gene amplification
with a corresponding oncogene dependency could pinpoint
a therapeutic strategy for HCC.
Identification and Functional Validation of Focal
Amplicons in Human HCC
To identify regions of recurrent amplification in human HCC, we
measured copy number alterations in 89 primary HCCs of
different etiologies (hepatitis B, hepatitis C, or ethyl-toxic liver
Hepatocellular carcinoma (HCC) afflicts more than 560,000 people worldwide each year and has one of the worst 1-year
survival rates of any cancer type. Currently, there are no molecular therapies that target specific mutations or other genetic
alterations in HCC. Byperforming aforward-genetic screenguided bygenomic analysis of human HCC, andthrough subse-
quent analysis with mouse models and RNAi, we found that a common genetic alteration in HCC (11q13.3 amplification)
results in activation of FGF19 and that this activation results in selective sensitivity to FGF19 inhibition. Our study under-
scores the potential for clinical translation of results obtained from genetic screens guided by cancer genome analysis.
Cancer Cell 19, 347–358, March 15, 2011 ª2011 Elsevier Inc. 347
cirrhosis) and 12 HCC cell lines using the Representational
Oligonucleotide Microarray Analysis (ROMA) array comparative
genome hybridization platform. We selected amplified genes
that were present in recurrent focal amplicons (Figure 1A) based
on our hypothesis that genes within smaller amplicons are more
likely to be tumor-promoting than those from larger chromo-
somal alterations. Early studies with amplified genes N-MYC
and ERBB2/HER2 established that gene amplification results
in overexpression and that overexpressing corresponding
cDNAs in an appropriate nonmalignant cell can be used to reca-
pitulate tumor-promoting function (Hudziak et al., 1987; Schwab
et al., 1985). Based on this premise, we constructed a focused
cDNA expression library that corresponded to genes within focal
amplicons inHCC, sothatbyforced overexpression inanappro-
priate nonmalignant cell, we could determine tumor-promoting
function. From the set of amplified genes within 29 recurrent
focal amplicons, we constructed a retroviral expression library
of 124 full-length cDNAs (see Figure S1 available online).
The selection of these 124 cDNAs was based solely on their
availability from the Mammalian Gene Collection (MGC) at
the time this project was initiated, and because many cDNAs
were not available, we could not be comprehensive in terms
of coverage for each of the 29 amplicons. To determine
whether targeting genes from this oncogenomic set was more
location in the genome, we constructed a parallel library of
35 full-length cDNAs from randomly chosen protein-coding
genes (Figure S1).
We introduced these 159 cDNAs in pools into an immortalized
line of embryonic hepatoblasts lacking p53 and overexpressing
Myc that were not tumorigenic in vivo (Zender et al., 2005) and
assessed their ability to promote tumorigenesis following trans-
plantation into recipient mice. Of note, this is a relevant genetic
context in which to assay candidate HCC tumor-promoting
genes because more than 40% of all human HCCs overexpress
MYC, and many harbor p53 mutations or deletions (Teufel et al.,
2007). Thus, these cells provide a ‘‘sensitized’’ background
where a single additional lesion can trigger tumorigenesis. After
testing the pooled cDNAs for their tumor-promoting activity, we
validated each positive hit individually. A total of 18 of the 124
amplified genes were validated as tumor-promoting genes
(Table1),whereas only one outof the35 randomly chosen genes
promoted tumor formation, a statistically significant enrichment
(p < 0.001) (Figure 1B). We also examined the relationship
between amplicon size and the ratio of tested genes that
promoted tumor formation (driver genes) versus those that did
not (passenger genes). As predicted, we found that the smaller
the amplicon size, the more likely that an individual gene within
Figure 1. Recurrent Focal Amplicons in HCC Are
Enriched for Tumor-Promoting Driver Genes
(A) Genome-wide frequency plot of focal amplicons (<10
Mb) identified by ROMA aCGH in 89 primary HCCs and
12 HCC cell lines.
(B) Comparison of the tumorigenicity induced by genes
(cDNAs) picked from focal amplicons to randomly
selected genes. p53?/?;Myc hepatoblasts transfected
with cDNA expression constructs were injected subcuta-
neously, and after 42 days the resultant tumors were
measured. Genes were scored as positive (red) if at least
half the tumors measured greater than 0.1 cm3. Confirma-
tion of tumorigenicity was performed as described in
Supplemental Experimental Procedures.
tested genes were located. Amplicon size was inversely
correlated with the proportion of driver genes (r = ?0.70;
p = 0.006).
(D) Correlation coefficients of RNA levels to DNA copy
number in two independent data sets are shown for both
are from the data set reported here, and although the
mean correlation was higher in the oncogenic set, it failed
to pass the significance level of p < 0.05. The two right-
most columns are from the data set of Chiang et al. (2008).
(E) GRAIL scores of both the driver and passenger genes.
The passenger genes have a very slightly lower mean
GRAIL score, but this difference is not significant.
(F) FIN-based ranking scores of both the driver and
passenger genes. The driver genes have a significantly
higher mean value (p < 0.018). See also Figure S2.
Targeted Anti-FGF19 Therapy in Liver Cancer
348 Cancer Cell 19, 347–358, March 15, 2011 ª2011 Elsevier Inc.
it could promote tumor formation (Figure 1C). These results
establish that focal amplicons in human HCC are enriched for
tumor-promoting genes and that they were likely caused by
genetic events that provided a selective advantage to the
evolving HCC cell.
Because our screen functionally classified the 124 amplified
genes into drivers and passengers, this provides an opportunity
to rigorously test computational filters for their ability to predict
tumor-promoting function. There are two such filters that have
been used in computationally oriented driver gene predictions:
the association of RNA expression with amplification (Woo
et al., 2009); and GRAIL (Beroukhim et al., 2010), an algorithm
that looks for related genes in the set of affected loci. Neither
of these found a significant difference between the two sets
(Figures 1D and 1E). The result from the former test indicates
that the effects of DNA copy number on the expression of driver
genes and passenger genes are relatively comparable. We also
used functional enrichment tools to find subgroups of genes
within our total list of 124candidates that were significantly over-
represented for gene ontology (GO) terms, pathways, and other
functional categories. We then tested whether the identified
subgroups were biased for either subset, but we found no signif-
Finally, we tested a newly developed functional interaction
ped to the network, and its cancer relevance was estimated by
a ranking system (http://cbio.mskcc.org/tcga-generanker/) that
took into account all of its interacting genes. There was a highly
significant difference in the FIN-based ranking scores for tumor-
promoting genes compared to inactive genes (Figure 1F), and
this corresponded with an ability to predict tumor-promoting
function with high accuracy and reasonable specificity and
sensitivity (Figure S2).
Several well-established oncogenes previously implicated in
liver cancer were discovered by our screen, including CCND1
and MET (Deane et al., 2001; Wang et al., 2001). MET encodes
a receptor tyrosine kinase that has been shown to be biochemi-
cally activated in HCC (Wang et al., 2001), but it has not
previously been shown to be genetically altered in human
HCC. Inhibitors of c-met signaling in HCCs are being clinically
tested (Gordon et al., 2010); our results would suggest that,
sponding overexpression of MET (affecting up to 23% of
patients; Table 1) may pinpoint a more responsive patient
of the previously described oncogenes CDK4 and PIM2 be
considered for targeted therapeutic development in HCC. The
serine/threonine kinase oncogene PIM2 plays a key role in
survival signaling in hematopoietic cells (Fox et al., 2003). It
has recently been shown to be overexpressed in human HCC
and to be important for survival of the HCC cell line HepG2
(Gong et al., 2009).
Table 1. Tumor-Promoting Genes Identified by the Oncogenomic cDNA Screen
3q26.313% 19% 0.14 Unknown 0.59 ± 0.16
IRF4 6p25.36% 37% 0.21Transcription factor0.14 ± 0.04
6p21.333%31%0.29 Chloride channel0.30 ± 0.11
6p21.16% 32% 0.40RNA Pol I and III subunit 0.15 ± 0.03
7q31.23% 23% 0.40 Receptor tyrosine kinase1.09 ± 0.23
9p13.2 2% 9% 0.09Unknown0.72 ± 0.13
9q34.35%10%0.46Mitochondrial ribosomal protein0.85 ± 0.19
9q34.35% 10% 0.53Mitochondrial ribosomal protein0.13 ± 0.02
9q34.35% 10% 0.50Mitochondrial peptidase 1.23 ± 0.10
11q13.1 5% 12%0.53 Rho GTPase0.76 ± 0.18
11q13.15% 12% 0.33Copper chaperone0.67 ± 0.061
CCND1 11q13.314% 20% 0.65Activates CDK4/6 and ER0.98 ± 0.33
FGF1911q13.3 14%20% 0.68Ligand for FGFR40.53 ± 0.23
12q14.1 3%13% 0.25Cell cycle serine kinase2.43 ± 0.78
12q14.13% 13% 0.05 Unknown0.71 ± 0.25
20q11.212% 34% 0.22Src-like tyrosine kinase1.70 ± 0.16
20q11.21 2%34% 0.27Glycosyltransferase0.78 ± 0.24
?0.10Serine-threonine kinase 0.96 ± 0.41
Properties of the 18 genes (out of 124) that scored positive for tumorigenicity in the oncogenomic cDNA screen. See also Figure S1.
aDetermined using the UCSC Genome Browser website.
bRepresents the percentage of HCC samples that harbored a focal amplicon (<10 Mb) containing the specified gene.
cRepresents the percentage of samples harboring either focal amplification or wider amplification.
dThe Pearson’s correlation coefficient of mRNA expression and DNA copy number was determined as described in the text.
eBiochemical functions were obtained from literature searching.
fThe mean tumor volume and standard error were determined using the subcutaneous assay (n = 8) as described in the text.
gThe gene has not previously been reported to possess tumor-promoting activity.
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Other genes that were identified in our screen include: CLIC1,
which encodes an ion channel initially identified in a screen for
genes involved in anchorage-independent growth of human
HCC cell lines (Huang et al., 2004); POFUT1, a gene that
encodes a glycosyltransferase that modifies Notch receptors
(Stahl et al., 2008); CCS, a gene encoding a copper chaperone
that is required for the activation of superoxide dismutase and
helps protect cells from oxidative stress and cell death (Leitch
et al., 2009; Matthews et al., 2000); TSPAN31, a member of
the tetraspanin family of cell surface receptors, some of which
have previously been linked to cancer (Hemler, 2008); and
RHOD, a member of the Rho GTPase family that is involved in
endosome motility and the localization of certain Src-kinase
Two have unknown biochemical functions (FNDC3B and
Figure 2. Epicenter Mapping and Expres-
sion of Genes in the 11q13.3 Amplicon in
HCC and the Difference in the Effect of
Amplification on FGF19 and CCND1Expres-
sion between Breast and Liver Tumors
(A) Individual boundaries and the region of
common overlap for the 14 11q13.3 amplicons,
along with the underlying RefSeq genes in the de-
color coded (see inserted scale) to indicate the
degree of correlation between DNA copy number
and gene expression. Correlation coefficients
between DNA copy number and expression are
for FGF3 (r = ?0.20; p = 0.36) and FGF4
(r = 0.17; p = 0.45), statistically insignificant in
(B) Scatter plots with associated correlation coef-
ficients showing the relationship in HCC samples
(both tumors and cell lines) between DNA copy
number and expression for CCND1 (left) and
(C) As in (B) but with breast cancer cell line
samples. See also Figure S3.
ZCCHC7), and three are nuclear-en-
coded mitochondrial proteins (MRPL41,
MRPS2, and PMPCA) (Table 1). It is
possible that the latter three genes play
a role in the mitochondrial apoptosis
pathway. Finally, the tumor-promoting
conserved RPA40 subunit of both RNA
Pol I and RNA Pol III. Its function can be
characterized as ‘‘housekeeping’’ and is
not associated with known signaling
pathways involved in cancer. However,
it has long been known that there is
increased Pol I and Pol III transcription
in cancer cells (White, 2008). Our results
would suggest that this increase may
actively drive cancer progression as
opposed to it being a passive secondary
event. Interestingly, RPA40 was shown
recently to be tyrosine phosphorylated
(Rush et al., 2005), and this may provide another avenue for its
activation in cancer.
FGF19 and CCND1 Are Both Overexpressed in HCCs
Harboring the 11q13.3 Amplicon
The 11q13.3 amplicon containing CCND1 is one of the most
frequent amplification events in human tumors and is well char-
acterized; thus, it was surprising to find another tumor-
promoting gene (FGF19) in the same region. FGF19 lies within
45 kb of CCND1, and the two genes are invariably coamplified
in the samples we analyzed, leading to an increase in expression
of both genes (Figure 2A). FGF4 and FGF3 are also frequently
coamplified with CCND1, though they are further away than
FGF19 (120 and 155 kb, respectively). However, CCND1 and
FGF19 are often amplified in the absence of coamplification
with these two other FGF genes (Figure 2A). Furthermore, we
Targeted Anti-FGF19 Therapy in Liver Cancer
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found that although amplification results in significant increases
in CCND1 and FGF19 expression in HCC, amplification of FGF4
and FGF3 does not correlate with increased gene expression
(Figures 2A and 2B). This lack of correlation of amplification
and overexpression for these latter two FGF genes was previ-
ously noted in breast cancer (Fantl et al., 1990).
Curiously, the only report in the literature regarding the effect
of amplification of FGF19 on its expression was a study in oral
cancer, where it was found to not be overexpressed despite
gene amplification (Huang et al., 2006). Largely because
FGF19 was discovered after analyses of the 11q13.3 amplicon
ature regarding the effect of amplification on its expression in
breast cancer. We have found that, similar to oral cancer,
FGF19 is not overexpressed when amplified in breast cancer
(Figures 2C; Figure S3), nor does FGF19 appear to be overex-
pressed when amplified in lung cancer or melanoma (Figure S3).
Thus, amplification does not invariably cause overexpression of
FGF19; rather, overexpression appears restricted to a specific
for the amplified gene TTF1, which is overexpressed when
amplified in lung adenocarcinomas, but not in lung squamous
carcinomas (Kendall et al., 2007).
ORAOV1, which is located between FGF19 and CCND1 (Fig-
ure 2A), is overexpressed in all amplified tumors that have
been tested, including in our HCC data set. However, our
screening showed that it does not promote tumorigenicity in
p53?/?;Myc hepatoblasts, nor does it show any cooperativity
with FGF19 or CCND1 (data not shown).
Effects of FGF19 and CCND1 Overexpression
on Hepatocellular Tumorigenicity
tumorigenicity using an orthotopic transplantation assay. When
planted into the liver of mice, tumors developed within 8 weeks
(Figure 3A). Microscopic examination of the resultant in situ liver
tumors classified them as aggressive solid HCCs. The tumors
were composed of a population of undifferentiated cells growing
as a sheet without any histological evidence for gland formation
or any other structure. The cells were large with a more baso-
philic-staining cytoplasm compared to normal liver and resem-
bled human HCC. We established that the tumors arose from
the transfected hepatoblasts because the carcinoma cells
were positive for the GFP marker. In addition, cellular prolifera-
tive status was examined by immunohistochemical staining for
PCNA. The tumors formed by either FGF19 or CCND1-express-
ing hepatoblasts were clearly positive for PCNA as well, indi-
cating that the tumors induced by these genes were significantly
proliferative. Similar morphological and molecular changes were
observed in orthotopic tumors induced by MET, POFUT1, or
HCK (Figure S4).
Next, we explored for possible cooperative effects when both
FGF19 and CCND1 genes were coexpressed in murine
Figure 3. FGF19 and CCND1 Cooperate to
Promote Liver Carcinoma Formation
(A) Images of mouse livers and liver sections taken
8 weeks following transplantation of p53?/?;Myc
hepatoblasts expressing empty vector, CCND1,
or FGF19. The five panel columns are, from left
to right: intact livers; fluorescent imaging of intact
liver for GFP-positive transplanted cells; hematox-
ylin and eosin staining of liver tissue sections
showing the border between normal liver and
carcinoma (arrowheads); immunohistochemical
detection of GFP; and immunohistochemical
detection of PCNA. The last three are from the
same tissue block. Scale bars, 100 mm.
(B) Kaplan-Meier plot showing the percentage of
mouse survival at various times after transplanta-
tion. The livers of mice were transplanted with
p53?/?;Myc hepatoblasts infected with control
vectors, FGF19 alone, CCND1 alone, or both
genes in combination.
(C) Subcutaneous growth of p53?/?;Myc hepato-
blasts infected with control vector pMSCVpuro,
CCND1 alone, orFGF19 withCCND1 (n= 10injec-
tions). Asterisks indicate that the indicated tumor
group is significantly different than controls. Error
bars denote ±SD. *p < 0.05, **p < 0.0005. Tumor
volumes were determined on 28 (red columns),
35 (green columns), and 42 (blue columns) days
after injection. See also Figure S4.
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Figure 4. FGF19 and CCND1 Functionally Interact through b-Catenin Signaling
(A) FGF19 and cyclin D1 protein expression in Huh-7 (11q13.3-amplified) cells following stable transfection with one shRNA targeting luciferase (control) and two
independent shRNAs targeting FGF19 (19K4 and 19K5).
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352 Cancer Cell 19, 347–358, March 15, 2011 ª2011 Elsevier Inc.
hepatoblasts. For the transplantation assays we measured the
survival of mice transplanted with p53?/?;Myc hepatoblasts
ectopically expressing the two genesalone and also in combina-
tion. None of the control mice transplanted with hepatoblasts
transfected with empty vectors died within the 100-day observa-
tion period, but 100% of the FGF19 alone, CCND1 alone, and
CCND1 plus FGF19 groups did eventually succumb to tumors
(Figure 3B). According to the log rank test for significance, the
survival of the FGF19 or CCND1 alone and CCND1 plus FGF19
groups was significantly less than control (p < 0.05). There was
an increase in morbidity when comparing the CCND1 plus
FGF19 group to the FGF19 or CCND1 alone groups (Figure 3B).
This difference was clearly significant when compared to the
FGF19 group alone (p = 0.003), but the difference compared
with the CCND1 alone group did notpass the p=0.05cutoff nor-
mally used for significance, although the p value obtained indi-
cates only a 15% chance that the null hypothesis was correct
(p = 0.15). In the subcutaneous tumorigenicity assay, which
uses tumor volume as a readout, therefore providing a greater
range of quantitative values than survival, the combination of
both CCND1 and FGF19 was very clearly significantly greater
than either gene alone (p < 0.0005; Figure 3C). Taken together,
these results suggest that the combination of overexpressing
CCND1 and FGF19 is more tumorigenic than when either single
gene is overexpressed.
FGF19 Requires b-Catenin to Mediate Cyclin
D1 Protein Levels
Because many growth factors are known to regulate cyclin D1
protein production, we wanted to determine whether FGF19
levels in turn regulated cyclin D1 levels in human HCC cells.
Toward this end, we tested and validated two shRNAs targeting
FGF19 and two shRNAs targeting CCND1 that were each effec-
tive at reducing target protein levels (Figure S5). We found that
RNAi-mediated silencing of FGF19 in the HCC cell line Huh-7,
which harbors the 11q13.3 amplicon and overexpresses both
FGF19 and CCND1 (Figure S5), caused what appeared to be
complete suppression of FGF19 protein as well as almost
complete elimination of cyclin D1 protein (Figure 4A). Further-
more, we found that silencing the expression of either FGF19
or CCND1 significantly inhibited clonogenic growth of Huh-7
cells (Figure 4B). To control for off target effects of the shRNAs,
tion of recombinant FGF19 protein to the culture medium
restored high levels of cyclin D1 protein and rescued the growth
defect caused by shRNA knockdown of FGF19 but that it could
not do either to cells with the shRNA knockdown of CCND1
(Figures 4B; Figure S5). On the other hand, overexpression of
an RNAi-insensitive CCND1 construct restored high levels of
cyclin D1 protein and completely rescued the growth defects
of both FGF19 and CCND1 shRNA knockdowns (Figures 4B;
Figure S5). These results show that the shRNA effects were
not off target, and they also establish a clear hierarchy of onco-
in human HCC cells.
We aimed to identify a potential mechanism through which
FGF19 is regulating cyclin D1 levels. Recently, one of us (D.M.F.)
showed that in colon cancer cell lines, expression of FGF19 acti-
signaling (Pai et al., 2008). b-Catenin has been proposed to acti-
2005), and it can also influence cyclin D1 levels by stabilization of
CCND1 mRNA (Briata et al., 2003). This led us to predict that
FGF19 may be signaling through b-catenin to regulate cyclin D1
protein levels. To test this we determined if the knock down of
vated b-catenin protein were analyzed by immunoblotting using
an antibody directed against NH2-terminally dephosphorylated
b-catenin. We found that both shRNAs targeting FGF19 caused
a clear reduction of b-catenin activation (Figure 4C). We wanted
to determine if this held true if we used a dual-luciferase TCF
reporter as a readout for b-catenin activity. We found that in the
11q13.3-amplified Huh-7 cell line, TCF reporter activity was
reduced by 25% when FGF19 was knocked down and that
a shRNA targeting b-catenin (CTNNB1) reduced activity by 55%
We then used shRNAs targeting CTNNB1 to determine if
reducing b-catenin would have an effect on cell growth of the
11q13.3-amplified HCC cell line Huh-7. Two shRNAs targeting
(B) Quantification of clonogenicity of Huh-7 cells infected with shRNAs against FGF19 (19K4) and CCND1 (D1K2) are shown relative to results obtained with
a shRNA against luciferase (control). Recombinant FGF19 protein was added to the medium, or a shRNA-insensitive CCND1 expression construct was trans-
fected into the cells, where indicated. Error bars denote ±SD. *p < 0.005.
(C) Active b-catenin levels in Huh-7 cells expressing the two shRNAs targeting FGF19, as revealed by immunoblotting with an antibody specific for the activated
form of b-catenin, relative to total b-catenin levels.
(D) TCF reporter activity, relative to constitutively expressing renilla luciferase activity, in Huh-7 cells infected with shRNAs against FGF19 (19K4) or b-catenin
(BcatK1), compared to a shRNA against luciferase (control). Error bars denote ±SD. *p < 0.05.
(E)Quantification of clonogenicity of Huh-7 cells infected with shRNAs againstCTNNB1(BcatK1 and BcatK4) is shown relative to anontargeting shRNA(control).
Error bars denote ±SD. *p < 0.05.
(F) Time course effects of adding FGF19 to the medium of SNU423 cells (with a single copy of 11q13.3) on active b-catenin levels, as well as the effects of added
FGF19 on cyclin D1 protein levels, as detected by immunoblotting.
(G) TCF reporter activity, relative to constitutively expressing renilla luciferase activity, in SNU423 cells treated for 24 hr with recombinant FGF19, compared to
nontreated cells. Error bars denote ±SD. *p < 0.05.
(H) Quantification of clonogenicity in SNU423 cells infected with an effective shRNA against CTNNB1 (BcatK1), compared to cells infected with a nontargeting
shRNA. Error bars denote ±SD. p = 0.169.
(I) SNU423 cells were treated with FGF19, EGF, or FGF2. b-Catenin and MAPK activity were determined by immunoblotting after 15 min, whereas cyclin D1
protein was detected after 24-hr exposure.
24 hr and then cyclin D1 protein levels were detected by immunoblotting. See also Figure S5.
Targeted Anti-FGF19 Therapy in Liver Cancer
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CTNNB1 significantly reduced the clonogenic growth potential
(Figures 4E; Figure S5). This effect was not seen in the nonampli-
fied HCC cell line SNU423 (Figure 4H). This further supports our
model thatb-catenin signalingiscriticalinFGF19-amplifiedHCC
Conversely, we added FGF19 to the culture medium of a HCC
cell line (SNU423) that has the normal copy number of both
FGF19 and CCND1 and that does not express detectable levels
of FGF19 protein by immunoblotting (Figure S6). These cells
were incubated in medium supplemented with FGF19, and
b-catenin activity was analyzed both by immunoblotting for
NH2-terminally dephosphorylated b-catenin and by measuring
TCF reporter activity. As determined by immunoblotting, the
addition of FGF19 induced activation of b-catenin within 10
min, and baseline levels returned within 24 hr (Figure 4F). Corre-
spondingly, TCF reporter activity was increased 2.1-fold in the
presence of recombinant FGF19 (Figure 4G). We found that
cyclin D1 protein levels were subsequently elevated after 24 hr
of exposure to exogenously added FGF19 (Figure 4F), support-
ing a mechanism by which FGF19 induces elevated cyclin D1
through b-catenin signaling.
Our proposed mechanism for how FGF19 induces higher
levels of cyclin D1 protein differs from how other mitogens
have been shown to increase cyclin D1 protein in fibroblasts,
a mechanism that requires MAP kinase activation (Lavoie
et al., 1996). To test if this was also true in human HCC cells,
we treated serum-starved SNU423 cells with FGF19, FGF2
(basic FGF), or EGF for 15 min and then analyzed b-catenin
and MAPK1/2 activation. We also treated the cells for 24 hr to
measure cyclin D1 protein levels. We found that all three growth
factors were able to induce elevation of cyclin D1 protein;
however, only FGF19 activated b-catenin, whereas only EGF
and FGF2 activated MAPK1/2 (Figure 4I). We also determined,
using an effective shRNA against CTNNB1, that b-catenin
function was selectively required by FGF19 to induce cyclin D1
but that this was not true for EGF or FGF2 (Figure 4J). We
conclude that there are two distinct pathways in HCC cells
through which mitogens induce elevation of cyclin D1 protein:
signaling, and the b-catenin pathway.
CCND1 and FGF19 Oncogene Dependency
in Human HCC Cell Lines
human HCC cell lines led to dependence on their continued
expression and, if so, whether such oncogene dependence
would hold true in HCC cell lines that were not amplified for
11q13.3. Toward this end we used the previously described
shRNAs targeting FGF19 and CCND1 to test oncogene depen-
dence in a panel of six HCC cell lines: three harboring amplifica-
tion of 11q13.3, and three that were single copy for this locus.
We introduced these shRNAs into each of the six cell lines and
tested their effects on growth using a clonal growth assay. Strik-
ingly, the clonogenic growth potential of each of the three
CCND1/FGF19-amplified cell lines was significantly reduced
by silencing of either FGF19 or CCND1, whereas none of the
CCND1/FGF19 single-copy cell lines was significantly affected
(Figures 5A and 5B). These results establish a clear link between
genotype (CCND1/FGF19 copy number status) and oncogene
We wanted to determine if the selective inhibition of the
11q13.3-amplified tumor cells by shRNAs targeting either
FGF19 or CCND1 was reflected in correspondingly different
levels of expression of the gene products in untreated cells.
We found that FGF19 protein could be detected in all three
11q13.3-amplified HCC cell lines, but none of the nonamplified
cell lines (Figure S6), an expected result based on the notion
that gene amplification drives increased mRNA and protein
expression. However, cyclin D1 protein levels did not vary signif-
icantly between the two groups (Figure S6), which could be
explained by the high levels of mitogens found in the cell culture
conditionskeepingcyclinD1levels high,regardless ofamplifica-
tion status. However, this result indicates that the selective
dependence of the 11q13.3-amplified cells for cyclin D1 is not
due to addiction to higher levels of cyclin D1 protein but, rather,
to selective dependence on cyclin D1 downstream effector
We then tested whether elevated expression of these two
genes in the CCND1/FGF19-amplified cell line Huh-7 played
a significant role in vivo. The shRNAs silencing either FGF19 or
CCND1 significantly slowed the growth of Huh-7 cells trans-
planted subcutaneously into nude mice (p < 0.005; Figure 5C).
Significant inhibition of tumor growth by shRNAs targeting
fied JHH-7 cells (p < 0.0001; Figure 5D). These results establish
key tumor maintenance functions for both FGF19 and CCND1
specifically in HCCs harboring the 11q13.3 amplicon, but not
in those without.
Despite the fact that most cancers contain several oncoge-
netic alterations affecting multiple genes, oncogene depen-
dence has almost always been evaluated for only a single onco-
gene, although it has been shown that in some circumstances,
inhibition of multiple altered oncogenes can be beneficial
(Podsypanina et al., 2008). This led us to test whether shRNA-
mediated silencing of both driver genes in the 11q13.3 amplicon
would be more effective than silencing of FGF19 or CCND1
alone. To test this we coexpressed effective shRNAs against
each gene in the 11q13.3-amplified JHH-7 line. By measuring
clonogenic growth we found that the dual shRNA knockdown
down of either gene alone (Figure S6). Nor did the dual shRNA
knockdown show more effective inhibition of tumor develop-
ment (Figure S6). We believe this result supports our model
that the tumor-promoting effects of FGF19 are mediated by its
ability to increase cyclin D1 protein levels and that because
single shRNAs targeting either FGF19 or CCND1 can effectively
lower cyclin D1 protein levels (Figures 4A; Figure S5), additional
lowering of cyclin D1 protein levels has no growth-inhibitory
effect. However, we do not believe that this negative result
should be extrapolated to other situations where driver genes
may operate in different pathways.
A Neutralizing Anti-FGF19 Monoclonal Antibody Blocks
Clonogenicity and Tumorigenicity of 11q13.3-Amplified
We next sought to test the potential benefit of targeting FGF19
therapeutically in 11q13.3-amplified HCCs. We assayed the
Targeted Anti-FGF19 Therapy in Liver Cancer
354 Cancer Cell 19, 347–358, March 15, 2011 ª2011 Elsevier Inc.
effect of neutralizing FGF19 on the tumor-forming ability of Huh-
7 cells using a previously characterized neutralizing antibody
specific against FGF19 (1A6) (Desnoyers et al., 2008). Mice
were injected subcutaneously with Huh-7 cells, and tumors
were allowed to reach a size of 0.2 cm3. At that point, mice
were placed into three treatment groups: one injected intraperi-
toneally with PBS, another with an isotype-matched control anti-
body, and the final group with neutralizing antibody 1A6. Most of
the animals from the PBS and isotype-matched control antibody
groups were sacrificed when the tumor burden became exces-
sive. However, the anti-FGF19 antibody had a dramatic inhibi-
tory effect on tumor growth (Figure 5E). This result highlights
the potential of using an anti-FGF19 monoclonal antibody as
a therapeutic for HCC.
To test whether the inhibitory effect of the anti-FGF19 mono-
clonal antibody was specific for CCND1/FGF19-amplified
HCCs, we examined a panel of HCC cell lines with different
11q13.3 amplification status and measured the inhibitory effect
of the anti-FGF19 monoclonal antibody using a short-term
in vitro growth assay. None of the 15 HCC cell lines that did
not harbor the 11q13.3 amplicon showed significant response
to the neutralizing antibody 1A6, whereas two out of four of the
CCND1/FGF19-amplified lines were clearly inhibited by the anti-
body (Figure 5F). The 50% response rate observed in amplified
HCC cell lines is similar to what has been shown using the
anti-Her2/neu monoclonal antibody trastuzumab in HER2-over-
exception of JHH-7, these results correspond closely with the
results obtained with RNAi: both showed that inhibition of
FGF19 attenuates the growth of 11q13.3-amplified HCCs, but
not nonamplified HCCs. The discrepancy with JHH-7 may be
due to the considerably higher level of FGF19 produced in this
cell line relative to other CCND1/FGF19-amplified cell lines,
making it potentially more difficult for the antibody to neutralize
tion of the panel of HCC cell lines shows that amplification of
CCND1/FGF19 is an accurate predictor of growth inhibition in
response to the neutralizing antibody 1A6. This would also
suggest that testing antibodies to FGF19 in the clinic should be
restricted to patients with 11q13.3-amplified HCCs.
Figure 5. CCND1 and FGF19 Oncogene
Dependency in Human HCC Cell Lines
(A) Clonogenicity assay of Huh-7 cells (11q13.3-
amplified) and SNU182 cells (single copy for
11q13.3) infected with shRNAs against luciferase
(control), FGF19 (19K4 and 19K5), and CCND1
(D1K2 and D1K4).
(B) Quantification of clonogenicity in six cell lines
(three with 11q13.3 amplification and three
without) infected with shRNAs against FGF19
(19K4 and 19K5) and CCND1 (D1K2 and D1K4)
relative to a shRNA against luciferase (control).
Results with cells infected with control shRNA
are shown in blue, anti-FGF19 results with 19K4
and 19K5 shRNAs are shown in green, and anti-
CCND1 results with D1K2 and D1K4 shRNAs are
shown in yellow. Error bars denote ±SD. *p <
(C) Subcutaneous tumor growth in nude mice of
Huh-7 cells infected with indicated shRNAs (n =
12 injections). Error bars denote ±SD. *p < 0.005.
(D)Asin (C)but withJHH-7 cells (n= 10injections).
Error bars denote ±SD. *p < 0.01, **p < 0.0001.
(E) Subcutaneous growth of established tumors
from Huh-7 cells treated with PBS, control anti-
body, or anti-FGF19 antibody (1A6). Treatment
was on the days marked with red asterisks.
Dashed lines indicate that mice were terminated
bars denote ±SEM. *p < 0.05.
(F) Growth inhibition of HCC cell lines grown
in vitro with anti-FGF19 antibody (1A6) relative to
the indicated 11q13.3 amplification status. Error
bars denote ±SEM. The bracket above the four
amplified cell lines indicates that by Student’s t
test, the average growth inhibition by the anti-
FGF19 antibody was significantly greater than
that of the nonamplified control group. See also
Targeted Anti-FGF19 Therapy in Liver Cancer
Cancer Cell 19, 347–358, March 15, 2011 ª2011 Elsevier Inc. 355
In this report we have shown that it is possible to identify the
underlying driver genes of human cancer amplicons by
screening appropriately selected pools of cDNAs for their ability
to promote tumorigenesis in a mosaic mouse model. Through
more in-depth analysis of two of these tumor-promoting ampli-
fied genes, we established that FGF19 is an oncogene that is
coamplified and co-overexpressed with CCND1 in HCC. We
also demonstrated that by inhibition of FGF19 with RNAi or
with a potentially therapeutic monoclonal antibody, one can
block the clonal growth and tumorigenicity of human HCC cells
harboring the FGF19/CCND1 amplicon. Given that there are
currently no genetically targeted therapies for HCC, we believe
these results represent an important biomedical advance.
Previously, one of us (D.M.F.) showed that transgenic mice
with FGF19 expressed in the skeletal muscle eventually devel-
oped liver tumors through a poorly understood but presumably
paracrine mechanism (Nicholes et al., 2002) and that an anti-
FGF19 monoclonal antibody prevented tumor formation in this
model in addition to inhibiting xenograft tumor formation of
some human colon cancer cell lines (Desnoyers et al., 2008).
However, these studies did not establish the basis for how
FGF19 was involved in human cancer, which clearly can involve
a cell autonomous mechanism, nor did they provide a clear
strategy for selecting a likely-to-respond subpopulation of
patients for treatment with the monoclonal antibody.
Itis notclear if there isa biological explanation for whyCCND1
and FGF19 are invariably coamplified in HCC, or if their coampli-
fication is a secondary consequence of their close proximity and
a result of amplicon formation involving DNA breaks at specific
regions (Gibcus et al., 2007). Nevertheless, our data indicate
that the two genes are functionally linked in that cyclin D1 levels
in hepatocytes are dependent upon FGF19 signaling. Addition-
ally, although the downstream effector of FGF19 in hepatocytes
and HCC cells has been clearly established as FGFR4 (Wu et al.,
2010b; Pai et al., 2008), which downstream effectors are
involved incyclin D1in HCCcellsisnotclear.CyclinD1activates
CDK4/6 kinase, which in turn inactivates RB1 (Sherr, 1996).
Genetic lesions affecting RB1 pathway members, including the
tumor suppressor p16/INK4A, can be mutually exclusive in
certain cancers (Sherr, 1996). However, in some cancers
CCND1 amplification frequently co-occurs with p16/INK4A
loss (Okami et al., 1999). Protein analysis of human HCC tumors
suggests that this could be true with HCC (Azechi et al., 2001),
ences (e.g., MYB, STAT3, PPARg) (Knudsen, 2006) are involved
in cyclin D1 oncogenic effects in HCC.
It is surprising that amplicons do not always have the same
driver genes in different tumor types; there is a fundamental
difference between the 11q13.3 amplicon in breast and liver
cancers in that FGF19 is clearly overexpressed as a result of
amplification in liver cancer but is not so in breast cancer.
Thus, driver genes can be tissue type dependent, making it
important to obtain amplification and overexpression data for
different tumor types, even in the case of well-validated
We are optimistic that forward-genetic screens can be used
generally for genome-wide identification of oncogenic driver
genes from DNA amplifications or other activating alterations
identified by human cancer genome profiling. Most importantly,
by performing follow-up experiments using RNAi in human
cancer cell lines or mouse models, it should be possible to iden-
point about amplified driver genes is that they provide an imme-
diate biomarker for identifying the patients that might benefit
Tumor Samples, Cell Lines, and Genomic Analysis
The 89 primary HCC samples were obtained with appropriate Institutional
Review Board (IRB) or corresponding committee approval, and patient
informed consent was given by the Cooperative Human Tissue Network
(n = 37), Hannover Medical School in Germany (n = 27), and the University of
Hong Kong (n = 25). All tumor samples were de-identified prior to transfer to
CSHL for analysis; hence, the study using these samples is not considered
human subject research under the U.S. Department of Human and Health
Services regulations and related guidance (45CFR, Part 46). Genomic DNA
was isolated using proteinase K and 0.5% SDS, and RNA was isolated by TRI-
ATCC or Japanese Collection of Research Bioresources (JCRB) and grown in
the culture medium recommended by the supplier. DNA copy number profiling
for all primary tumor samples and most HCC cell lines was performed by
cito et al., 2003). Gene expression profiling was performed with NimbleGen
Gene Expression arrays.
Oncogenomic Selection of Genes/cDNAs from Focal Amplicons and
Construction of the Amplicon-Focused and Randomly Selected
We selected high-level amplicons (segmented value R1.5) that were %20 Mb
in size and applied an algorithm similar to the minimal common region (MCR)
method to determine the region of common overlap (Tonon et al., 2005). This
the smallest amplicon, we obtained from Open Biosystems, a distributor of
plasmids from the MGC (Gerhard et al., 2004), all available (as of June 2007)
we had reached our target screen size of 150 cDNAs.
Generation of Liver Carcinomas and Tumorigenicity Assays
All studies utilizing murine hepatoblasts and the human xenograft experiments
involving shRNAs were approved by Cold Spring Harbor’s Institutional Animal
Care and Use Committee. The human xenograft experiments involving anti-
bodies were approved by Genentech’s Institutional Animal Care and Use
Committee. Early-passage immortalized liver progenitor cells were trans-
duced by retroviruses expressing single cDNAs. Two million cells were trans-
planted into livers of female nu/nu mice (6–8 weeks of age) by intrasplenic
injection, or one million cells were injected subcutaneously on NCR nu/nu
mice. For cDNA pools, immortalized liver progenitor cells were transduced
individually with cDNAs and, following selection, pooled in equal numbers
immediately prior to injection. Tumor progression was monitored by abdom-
inal palpation and whole-body GFP imaging. Subcutaneous tumor volume
was measured using a caliper and calculated as: 0.52 3 length 3 width2.
For tumorigenicity assessment of human HCC cell lines and their derivatives,
5million HCCcells were resuspendedinserum-free MEMand injected intothe
flanks of irradiated 4-week-old female nude mice. Tumor size was measured
weekly by caliper and calculated as above. For the xenograft studies with
the anti-FGF19 antibody, 5 million Huh-7 cells were resuspended in 50%
HBSS and 50% Matrigel (BD Biosciences) and injected subcutaneously into
nude mice. When tumors reached a mean volume of 0.2 cm3, the mice were
randomized into groups with similar mean tumor volumes. The groups of
mice were then treated intraperitoneally on the indicated days with PBS,
Targeted Anti-FGF19 Therapy in Liver Cancer
356 Cancer Cell 19, 347–358, March 15, 2011 ª2011 Elsevier Inc.
30mg/kg of an isotype-matched control antibody, or 30 mg/kg of 1A6, an anti-
FGF19 antibody previously characterized.
The ROMA microarray data in this study can be freely accessed through NCBI
Supplemental Information includes six figures and Supplemental Experi-
mental Procedures and can be found with this article online at doi:10.1016/
We thank L. Bianco, J. Marchica, T. Wang, A. Bakleh, and Q. Liu for technical
support, J. Duffy for his help preparing figures, and A. Ashkenazi for discus-
sions. This work was supported by the Hope Funds for Cancer Research
(E.T.S.), and NIH grants CA124648 (S.P.), CA105388 (S.P. and S.W.L.), and
CA076905 (R.S.F.). S.W.L. is a Howard Hughes Investigator. R.S.F. is a recip-
ient of an NIH-LRP award. E.T.S., S.P., and S.W.L. are members of the CSHL
Cancer Target Discovery and Development Center (CTD2, supported by
CA148532) and part of the NCI CTD2Network.
Received: June 23, 2010
Revised: October 26, 2010
Accepted: January 14, 2011
Published: March 14, 2011
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