vegf-a expression correlates with tp53 mutations in non-small
TRANSCRIPT
Cancer Research – Priority Report
VEGF-A Expression Correlates with TP53 Mutations
in Non-Small Cell Lung Cancer: Implications for Anti-Angiogenesis
Therapy
Schwaederlé M1*
, Lazar V2*
, Validire P3, Hansson J
4, Lacroix L
2, Soria JC
2, Pawitan Y
4, and
Kurzrock R1.
*These authors contributed equally to this work and are corresponding authors.
1Center for Personalized Cancer Therapy, UCSD Moores Cancer Center, La Jolla, USA
2Gustave Roussy Institute, Villejuif, France
3Institut Clinique Montsouris, Paris, France
4Karolinska Institutet, Stockholm, Sweden
Running Title: VEGF-A Expression Correlates with TP53 Mutations in NSCLC
Keywords: Cancer, TP53, VEGF, bevacizumab, NSCLC
Financial Support: Chemores (www.chemores.org), an EU FP6 funded program.
Funded in part by the Joan and Irwin Jacobs Fund and My Answer To Cancer philanthropic
fund.
Information for Corresponding Authors:
Maria Schwaederlé, Pharm.D.
Center for Personalized Cancer Therapy
UC San Diego - Moores Cancer Center 3855
Health Sciences Drive, MC #0658
La Jolla, California 92093-0658
(858) 822 2171 Direct
(858) 822 2300 Fax
Vladimir Lazar, M.D., Ph.D
Director of the genomic platform
Gustave Roussy Institute
114, rue Édouard-Vaillant
94805 Villejuif Cedex –France
Phone : 0033 (0) 142 1140 20
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Conflict of interest: Dr. Johan Hansson is a member of the steering committee for the STEVIE
trial of vismodegib in basal cell carcinoma, sponsored by Roche. Dr. Jean-Charles Soria receives
consultancy fees for advisory boards from Roche. The other authors declare no competing
financial interests.
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ABSTRACT
Bevacizumab is one of the most widely used anti-angiogenic drugs in oncology, but the
overall beneficial effects of this VEGF-A targeting agent are relatively modest, in part due to the
lack of a biomarker to select patients most likely to respond favorably. Several molecular
aberrations in cancer influence angiogenesis, including mutations in the tumor suppressor gene
TP53 which occur frequently in many human malignancies. In this study, we present a multiple
regression analysis of transcriptomic data in 123 patients with non-small-cell lung cancer
(NSCLC) showing that TP53 mutations are associated with higher VEGF-A expression
(p=0.006). This association was interesting given a recent retrospective study showing longer
progression-free survival in patients with diverse tumors who receive bevacizumab, if tumors
harbor mutant TP53 instead of wild-type TP53. Thus, our current findings linking TP53 mutation
with VEGF-A upregulation offered a mechanistic explanation for why patients exhibit improved
outcomes after bevacizumab treatment when their tumors harbor mutant TP53 versus wild-type
TP53. Overall, this work warrants further evaluation of TP53 as a ready biomarker to predict
bevacizumab response in NSCLC and possibly other tumor types.
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Introduction
Non-small cell lung cancer (NSCLC) is a leading cause of cancer deaths(1), and
represents a heterogeneous group of neoplasms, mostly squamous cell and adenocarcinoma. A
diagnosis of NSCLC carries a grim prognosis; five-year survival is less than 15%(2).
Bevacizumab is an antibody that targets vascular endothelial growth factor-A (VEGF-A).
Bevacizumab combined with carboplatin and paclitaxel has been approved for the initial
treatment of unresectable NSCLC, based on a two-month increase in survival (12.3 versus 10.3
months) when compared to the chemotherapy alone(3). Bevacizumab is also used in the
treatment of renal and colon cancer and glioblastoma multiforme, with similar modest benefits;
its approval for breast cancer was recently revoked by the US FDA. The relatively small impact
of bevacizumab on outcome may be due to the fact that a subset of patients responds, while
others derive no salutary effects or, conceivably, might even be harmed by bevacizumab. Yet, no
biomarker for patient selection has been identified. This is especially important because
bevacizumab can have serious toxicity, including hypertension and bowel perforation; it is also
extremely expensive, costing about 40,000 to 100,000 dollars per year(4).
Of interest in this regard, we recently reported, in a retrospective study of patients with
diverse cancers, that use of bevacizumab-containing regimens predicted for longer progression-
free survival (PFS) in TP53-mutant tumors (multivariate analysis (p<0.001) (PFS = 11 versus 5.0
months; mut versus wt TP53))(5). The mechanism by which this correlation might occur remains
unclear. However, several studies suggest a role for TP53 in angiogenesis (6,7). Importantly in
this regard, though early data failed to find a clear association between VEGF expression and
outcome after bevacizumab administration, recent data using improved technology suggest that
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circulating levels of the short isoform of VEGF-A is a strong biomarker candidate for predicting
benefit(8).
Herein, we report that, in a transcriptomic evaluation of NSCLC(2), multiple regression
analysis showed that VEGF-A expression correlated independently with TP53 mutational status.
These data link TP53 mutations directly with VEGF-A, the primary target of bevacizumab, and
suggest that TP53 status merits further exploration as a biomarker for bevacizumab response in
NSCLC as well as in additional neoplasms.
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Materiel and Methods
Patients and tissue samples
Snap-frozen tumor and adjacent normal lung tissue samples from a cohort of 123 patients
who underwent complete surgical resection at the Institut Mutualiste Montsouris (Paris, France)
were used. All tissues were banked after written informed patient consent, and the study was
approved by the Ethics Committee of Institut Gustave Roussy (IGR).
Gene expression assay and analysis
RNA was extracted with TRIzol®, quantified and qualified with a Nanodrop. Gene
expression was performed with 244K Human exon array from Agilent (custom design with the
content of the 44K Human genome plus 195,000 probes, one for each exon as defined in refGene
list of UCSC build hg18 (http://genome.ucsc.edu/)). The differential gene expression in tumor
versus matched normal lung tissues was calculated in each patient and used in our analysis.
Gene mutations analysis
DNA was extracted with QIAamp DNA Mini Kit (Qiagen, Hilden, Germany). This was
follow by PCR amplification of target exons. Sequence analysis and alignment was performed
with SeqScape® software (Applied Biosystems). All detected mutations were confirmed in at
least one independent PCR reaction. In all 123 samples, full coding sequences of exons including
oncogenic mutational hotspots were analyzed corresponding to: TP53 (NM_000546.4) exons 5–
8; KRAS (NM_004448.2) exons 2 and 3; EGFR (NM_005228.3) exons 18–21; PIK3CA
(NM_006218.2) exons 10 and 21; BRAF (NM_004333.4) exon 15; ERBB2 (NM_004448.2)
exons 18, 20–24.
Statistical analysis
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Associations between TP53 mutational status and RNA expression levels were assessed
with a Mann-Whitney test in a univariable analysis. Multiple regression models were fit to assess
the best predictors for VEGF-A expression and the association between TP53 status and other
variables. Assumptions of multiple regression have been checked graphically. A subanalysis was
performed, segregating by histology. P-values less than 0.05 were considered statistically
significant. All statistical analysis were conducted using SPSS software (v.22.0).
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Results and Discussion
Our study population (N=123) was comprised of 57 patients with adenocarcinoma of the
lung (46%); 50, squamous cell (41%); 13, large cell (11%); and 3, unclassified cases (3%).
Testing for aberrations in the TP53, KRAS, EGFR, BRAF, PIK3CA and ERBB2 genes revealed
the following rates of abnormalities: TP53 (N=31 (25%) (24.6% of adenocarcinoma versus
28.6% of squamous cell; p=0.665)) (Supplemental Results); KRAS (N=20 (18%)); EGFR (N=13
(12%)); PIK3CA (N=2); BRAF and ERBB2 (N=1 each) (Supplemental Table 1).
In univariable analysis, transcriptomic data (84 gene products; Supplemental Table 2)
showed differential expression as follows: median fold changes of tumor versus normal tissues
of VEGF-A (3.9 vs. 3.0, p=0.015), mTOR (1.8 vs 1.4, p=0.013), BAX (1.8 vs 1.6, p=0.033),
APAF1 (0.7 vs 0.6, p=0.028), and AREG (0.1 vs. 0.2, p=0.015) (mut versus wt TP53). In
multiple regression analysis, TP53 mutations correlated independently with higher VEGF-A
(p=0.006) and BAX (p=0.032) expression (Table 1).
Using VEGF-A as the dependent variable, in a multiple linear regression analysis
including TP53, KRAS, and EGFR (all mut versus wt); histology (adenocarcinoma versus
squamous); and the other genes found differentially expressed (BAX, mTOR APAF1, and
AREG) as variables, the only statistically significant independent predictor for VEGF-A
expression was TP53 mutational status (p=0.006) (Table 2). When forward and backward
regression analyses were performed, both tests confirmed that TP53 mutation was the best
independent predictor for higher VEGF-A levels (p=0.008). Segregating by histology, a multiple
regression analysis demonstrated that TP53 mutational status was the only independent factor
predicting increased VEGF-A expression in adenocarcinoma (p=0.007) but not in squamous cell
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carcinoma (p=0.599), consistent with the observation that expression levels of VEGF-A were
significantly higher in TP53-mutated specimens in adenocarcinoma (median 5.95 versus 3.0; p =
0.012), but not in squamous cell carcinoma (median 3.9 versus 3.1; p = 0.636, Supplemental
Table 3). This difference between adenocarcinoma and squamous cell carcinoma suggest the
complexity of the mechanisms involving TP53 and angiogenesis regulation, and illustrates
possible mechanistic differences between tissues.
Angiogenesis plays a critical role in the growth and spread of cancer, as the resulting new
blood vessels supply the tumor with needed nutrients and oxygen; VEGF is probably the most
commonly involved pro-angiogenic factor(9). Our data complement previous preclinical data in
NSCLC correlating either aberrant TP53 expression with higher VEGF level(10) (measured by
quantitative reverse transcription polymerase chain reaction), or TP53 gene mutations with a
strongly positive VEGF immunoreactivity(11). Further, wt TP53 indirectly represses VEGF
promoter activity by inhibiting transcription factors, e.g., SP1 and E2F; there is also a TP53-
binding site adjacent to the hypoxia inducible factor-1alpha (HIF-1alpha) binding site that
resides within the VEGF promoter, and is essential for VEGF induction during hypoxia(12). In
addition, Narendran A et al. (8) showed that transfection of stromal cells with mutant p53
increased synthesis of VEGF. These mechanistic data are consistent with our observation of
high VEGF-A transcripts in the presence of mutant TP53. BAX transcript levels were also
higher in tumors harboring mutant TP53 (Table 1). The BAX product, also known as Bcl-2-like
protein 4, promotes apoptosis by binding to and antagonizing the Bcl-2 protein. Association
between BAX overexpression and specific TP53 mutations of the loop-sheet-helix in NSCLC
has previously been reported, though other types of TP53 mutations correlated with lower levels
of BAX expression(13).
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Using gene expression profiling techniques, prior studies also demonstrated that
adenocarcinoma and squamous cell NSCLC have different expression portfolios(2,14), which is
in line with our observation that the association between TP53 mutations and increased VEGF-A
transcripts appears specific for adenocarcinoma of the lung. It is conceivable that the improved
outcome that was previously reported by our group(5) in bevacizumab-treated patients who
harbored TP53 mutations versus wild type TP53 is due to the association between TP53
mutations and higher VEGF-A, the target for bevacizumab. But this association may not hold
true for all tumor types. For instance, benefit from bevacizumab could not be correlated with
TP53 status in metastatic colorectal cancer(15,16). On the other hand, these prior studies in
colorectal cancer had significant differences in methodology that might have influenced
outcome. Kara, O. et al.(15) examined only 34 patients and analyzed p53 expression, not
mutational status; Ince, W. L. et al.(16) examined survival, not progression-free survival. In
contrast, the multivariate analysis demonstrating that a bevacizumab-containing regimen was an
independent factor associated with better outcomes in TP53-mutated patients included a variety
of tumors and analyzed progression-free survival(5).
The salutary effects of anti-angiogenic therapy can differ dramatically, depending on the
cancer type. For the majority of tumors, bevacizumab must be combined with other drugs to
show benefit. Few responses are observed with monotherapy(9). One exception is ovarian
cancer, where monotherapy with bevacizumab can achieve response rates in the 16-21% range
even in advanced disease(17). One of the most responsive subsets of ovarian cancer is the high-
grade serous histology. Of interest in this regard, TP53 mutations are a hallmark of these tumors,
with a frequency exceeding 90%(18). In sharp contrast, prostate carcinomas, with a rather low
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TP53 mutation frequency (approximately 11%)(19), failed to demonstrate benefit from
bevacizumab(20).
Our study demonstrates an independent correlation between TP53 mutations and VEGF-
A expression in a comprehensive transcriptomic analysis of 123 patients with NSCLC. One of
the distinctive features of this dataset is the investigation of differential gene expression in tumor
versus matched normal lung tissues, in each patient. This methodology enabled us to discard the
noise from the background variability between patients, and pinpoint expression anomalies most
likely related to oncogenesis. This unique study feature enabled the demonstration, for the first
time, of an independent association between TP53 mutational status and overexpression of
VEGF-A. Further interrogation of the data indicates that this correlation pertains to
adenocarcinomas, consistent with bevacizumab’s approval for adenocarcinomas of the lung.
Bevacizumab has previously been hailed as the best-selling drug in oncology. However,
for most cancers in which it is used, including NSCLC, renal, and colon cancer as well as
glioblastoma multiforme, bevacizumab increases survival by only a couple of months.
Furthermore, the FDA recently acted to rescind its approval in breast cancer because of lack of
proof a survival advantage, despite previous evidence of some activity in this disease(8). Most
likely, in relevant malignancies, a subgroup of patients is responsive to bevacizumab, but a
biomarker defining this subset has remained elusive. TP53 mutations are found in diverse
cancers, and 25% of our NSCLC patients had a TP53 alteration. Indeed, TP53 is one of the most
commonly aberrant genes across tumors, yet there is no approved therapy that targets it. Our data
have previously suggested a clinical association between TP53 mutations and better PFS after
bevacizumab treatment(5). Our current observations show that TP53 mutations are an
independent predictor of high expression of VEGF-A, the primary target of bevacizumab. These
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observations suggest that upregulation of transcription of the VEGF-A gene(12) may link TP53
status to anti-angiogenic therapy outcome. Prospective investigation of TP53 as a biomarker for
response to bevacizumab, and possibly other anti-angiogenic agents, in NSCLC, as well as other
malignancies, is therefore warranted.
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Acknowledgements
We thank Drs. Sarah Murray and Lisa Madlensky for their help on TP53 alterations
classification. We are grateful for the support from Joan and Irwin Jacobs Fund,
MyAnswerToCancer philanthropic fund, and Chemores (www.chemores.org), an EU FP6
funded program.
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TABLES
Table 1. TP53 association with biologic parameters (multiple regression model)
Parameters Mut TP53 (N=31) Median (CI 95%)
Wt TP53 (N=91) Median (CI 95%) Coefficient CI 95% P-value
VEGF-A 3.9 (3.3-5.6) 3.0 (2.2-3.4) 0.032 0.01−0.05 0.006 BAX 1.8 (1.7-2.0) 1.6 (1.5-1.7) 0.167 0.02−0.32 0.032 mTOR 1.8 (0.6-2.0) 1.4 (0.8-1.5) 0.074 -0.09−0.24 0.381 APAF1 0.7 (0.6-1.1) 0.6 (0.5-0.7) 0.177 -0.05−0.40 0.124 AREG 0.1 (0.0-0.2) 0.2 (0.1-0.4) 0.000 -0.002−0.001 0.608 Mut TP53 (N=31)
N (%) Wt TP53 (N=91)
N (%) Coefficient CI 95% P-value
Histology Adenocarcinoma Squamous cell
14 (24.6) 14 (28.6)
43 (75.4) 35 (71.4)
0.143 -0.04−0.32 0.115
KRAS Mut KRAS Wt KRAS
7 (35) 21 (23)
13 (65) 70 (77)
0.183 -0.04−0.41 0.108
EGFR Mut EGFR Wt EGFR
3 (23) 26 (26)
10 (77) 73 (74)
-0.063 -0.31−0.18 0.613
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Table 2. VEGF-A association with biologic parameters (multiple regression model)
Parameters Coefficient CI 95% P-value TP53 2.039 0.61-3.47 0.006 Mut TP53 Wt TP53 KRAS Mut KRAS Wt KRAS
-0.693 -2.5-1.11 0.448
EGFR Mut KRAS Wt KRAS
0.594 -1.4-2.6 0.552
Histology Adenocarcinoma Squamous cell
-1.091 -2.5-0.33 0.131
Gene expression BAX -0.218 -1.5-1.0 0.729 mTOR 0.322 -1.01-1.67 0.635 APAF1 -0.765 -2.6-1.1 0.408 AREG -0.001 -0.01-0.01 0.815
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Published OnlineFirst February 11, 2015.Cancer Res Maria Schwaederle, Lazar Vladimir, Pierre Validire, et al. Therapy
Anti-AngiogenesisNon-Small Cell Lung Cancer: Implications for VEGF-A Expression Correlates with TP53 Mutations in
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