VEGF-A Expression Correlates with TP53 Mutations in Non-Small

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

[email protected]

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

[email protected]

on March 17, 2018. © 2015 American Association for Cancer Research.cancerres.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on February 11, 2015; DOI: 10.1158/0008-5472.CAN-14-2305

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mailto:[email protected]

http://cancerres.aacrjournals.org/

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.




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.




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




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.




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



http://genome.ucsc.edu/)


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).




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




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).




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




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




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.




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.



http://www.chemores.org/


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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

on March 17, 2018. ©

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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




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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VEGF-A Expression Correlates with TP53 Mutations in Non-Small