Genetic amplification of the vascular endothelial growth factor (VEGF) pathway genes, including VEGFA, in human osteosarcoma

Abstract

BACKGROUND:

Osteosarcoma is the most common primary tumor of bone. It is a highly vascular and extremely destructive malignancy that mainly affects children and young adults. The authors conducted microarray-based comparative genomic hybridization (aCGH) and pathway analyses to gain a systemic view of pathway alterations in the genetically altered genes.

METHODS:

Recurrent amplified and deleted genes that were detected by aCGH were subjected to an analysis based on the Kyoto Encyclopedia of Genes and Genomes to identify the altered pathways. Among the enriched pathways, vascular endothelial growth factor (VEGF) pathway genes collectively were amplified, and alterations of this pathway were validated by fluorescence in situ hybridization (FISH) and immunohistochemistry analyses in 58 formalin-fixed, paraffin-embedded osteosarcoma archival tissues that had clinical follow-up information.

RESULTS:

The pathway enrichment analyses of the aCGH data revealed that VEGF pathway genes, including the VEGFA gene itself, were amplified significantly in osteosarcoma. Genetic amplification of the VEGFA gene, both focally and in larger fragment, was validated by FISH analysis. It is noteworthy that amplification of the VEGFA gene and elevated expression of the VEGFA protein were associated significantly with microvascular density and adverse tumor-free survival in patients with osteosarcoma.

CONCLUSIONS:

The authors report for the first time that VEGF pathway genes, including the VEGFA gene, are amplified in osteosarcoma. Amplification of the VEGFA gene is not only an important mechanism for elevated VEGFA protein expression but also is a poor prognostic factor for tumor-free survival. Combined classification of VEGFA gene amplification and positive VEGFA protein expression may provide a more accurate stratification method of selecting anti-VEGF therapy for patients with osteosarcoma. Cancer 2011;. © 2011 American Cancer Society.

Osteosarcoma is the most common primary tumor of bone and affects approximately 1500 individuals per year in the United States (Surveillance, Epidemiology, and End Results database, National Cancer Institute). According to the latest statistics of Tianjin Cancer Registry Center in 2006, in Tianjin, the third largest city of China, there were 56 patients with osteosarcoma among the population of 9488,900. Osteosarcoma affects primarily those in the second decade of life, and the incidence has a steady, gradual decrease thereafter.1 Because survival rates in patients with metastatic osteosarcoma have not improved significantly in recent years, identifying the key genetic and molecular events in the development of osteosarcoma is critical to the development of effective therapeutics.2 Increased vascular endothelial growth factor A (VEGFA) expression has been associated with osteosarcoma development and metastasis. Furthermore, inhibition of VEGF signaling has resulted in the suppression of both tumor-induced angiogenesis and tumor growth.3, 4 Several preclinical and clinical studies have provided evidence that antiangiogenic therapies, such as antibodies and small-molecule inhibitors against the VEGF-VEGF receptor (VEGFR) axis, are promising strategies in the treatment of osteosarcoma.3-5 Several transcriptional factors, including hypoxia-inducible factor 1, alpha subunit (HIF-1A) and retinoblastoma 1 (RB1), have reportedly activate VEGF expression and angiogenesis in cancer cells.6 However, although numerous studies have reported chromosomal and gene aberrations in human osteosarcoma, to our knowledge, no genetic aberrations of the VEGF pathway have been reported in this tumor type.7-10 In the current study, we interrogated genome-wide, microarray-based comparative genomic hybridization (aCGH) profiling data on osteosarcoma by using pathway analysis and observed that VEGF pathway genes, including VEGFA, were amplified. We also investigated the clinical significance of VEGFA gene amplification in osteosarcoma.

MATERIALS AND METHODS

Osteosarcoma Tissues and Clinical Information

We collected clinicopathologic data and formalin-fixed, paraffin-embedded (FFPE) tissue sections from 58 patients with primary, conventional, central osteosarcoma from the Tianjin Medical University Cancer Institute and Hospital in Tianjin, China. The clinical and pathologic characteristics of the patients included age, sex, tumor location, Enneking stage, and follow-up (Table 1). All neoadjuvant and adjuvant chemotherapy was administered according to the Rosen T10 regimen.11, 12 Disease-free and overall survival rates ranged from 0 to 94 months, with medians of 9 months and 13 months, respectively. In addition, we obtained 10 frozen biopsy samples (from 9 patients) from the Tissue Bank of the Tianjin Medical University Cancer Institute and Hospital to perform the aCGH microarray analysis (Gene Expression Omnibus [GEO] database identification number 19180 [GSE19180]).2 All tissue and information collection took place at Tianjin Medical University Cancer Institute and Hospital with institutional review board-approved protocols, and all patients provided consent.

Table 1. Clinical and Pathologic Features in 58 Patients With Conventional Osteosarcomas

		Disease-Free Survival			Overall Survival
Characteristic	No. of Patients	P	HR	95% CI	P	HR	95% CI
Abbreviations: CI, confidence interval; HR, hazard ratio. a Significantly different.
Sex
Male	29	.86			.07a
Female	29	.86	1.11	0.36-3.44	.08	3.49	0.86-14.28
Age, y
≤15	14	.76			.79
15-20	23	.94	1.10E+04	0-1.40E+116	.5	1.82	0.32-10.42
21-30	11	.94	3.70E+04	0-4.40E+116	.72	0.73	0.13-4.05
31-40	1	.93	5.30E+04	0-6.40E+116	.97	0	0-1.90E+282
>40	9	1.00	1.02	0-3.90E+225	.99	0	0
Tumor location
Limbs	51	.28			.97
Others	7	.48	23.34	0.004-1.60E+05	.97	0.97	0.12-7.72
Enneking stage
I	4	.96			.43
IIA	19	.78	0.71	0.06-7.88	.17	0.1	0.004-2.74
IIB	2	.631	0.59	0.07-5.01	.10	0.09	0.01-1.61
III	1	.897	0.83	0.05-13.39	.99	0	0
Neoadjuvant chemotherapy
No	10	0.51			1.5E-4a
Yes	30	0.51	1.51	0.44-5.15	.003	11.85	2.36-59.45
Adjuvant chemotherapy
No	3	.21			.41
Yes	19	.43	0.04	0-129.34	.61	0.04	0-1.20E+04
Recurrence
No	50				.49
Yes	8				0.49	2.05	0.26-16.26
Metastasis
No	38				.045a
Yes	11				.436	0.01	0-2.40E+03

aCGH and Kyoto Encyclopedia of Genes and Genomes Pathway Analysis

The aCGH analysis of osteosarcoma genomic DNA was performed on an Agilent Human Genome CGH Microarrays (4 × 44 k; Agilent Technologies, Palo Alto, Calif). All aCGH analyses were performed with R statistical software (version 2.10.0; R Foundation for Statistical Computing, Vienna, Austria), as described previously.2 Briefly, first, the median-normalized log-2 ratio data were subjected to a circular binary segmentation (CBS) algorithm13 to reduce the effect of noise. Then, the CGHcall algorithm14 was used to call segments of DNA sequences as amplified or deleted in each sample. A permutation analysis also was applied to call recurrent copy number aberrations in osteosarcoma.2 In addition, we obtained raw aCGH data (GEO database identification number GSE9654) from another 10 biopsy samples.10 Both datasets were measured on Agilent Human Genome CGH Microarrays. Another set of bacterial artificial chromosome (BAC), clone-based, aCGH data from 36 patients with osteosarcoma also were analyzed to confirm the overall recurrent gene copy alteration patterns.15

Pathway enrichment analyses were performed separately on the recurrent amplified and deleted gene lists from gene sets GSE19180 and GSE9654. For those analyses, we used gene annotation data from the Kyoto Encyclopedia of Genes and Genomes (KEGG). Pathways that had more annotations in our gene list than expected (Fisher exact test; P < .05) were considered to be significantly enriched with amplified or deleted genes.

Fluorescent In Situ Hybridization Detection and Analysis

A 5-tetramethylrhodamine, deoxyuridine triphosphate-labeled BAC clone (RP1-261G23; conjugated to produce an orange signal) that covered chromosome 6 (from 43,709,997 to 43,882,030) was used for the VEGFA probe (Empire Genomics, Buffalo, NY). A chromosome enumeration probe 6 (CEP 6) Spectrum Green Probe (D6Z1; Abbott Molecular, Abbott Park, Ill) was used for the reference probe. The CEP 6 probe with a green signal indicates the chromosome 6 centromere, and the VEGFA probe with an orange signal indicates the VEGFA gene copy number. Fluorescent in situ hybridization (FISH) was performed to analyze 58 FFPE tissues, as described previously,16, 17 with some modifications. Briefly, after pretreatment of the slides using the Paraffin Pretreatment Kit II (Abbott Molecular) and denaturation of specimen DNA in denaturing solution (70% formamide/2 × standard saline citrate, pH 7.0), 10 to 20 μL of mixed, denatured VEGFA probe and CEP 6 probe were applied to the slides in an approximately 1-cm² area that was selected for a pure tumor cell population (>90% tumor cells), and hybridization was performed at 37°C overnight in a moist chamber. Excess probe was washed away, and the nuclei were counterstained with 4′,6-diamidino-2-phenylindole dihydrochloride. Slides were analyzed using a multifiltered fluorescence microscope (Olympus BX5; Applied Imaging, San Jose, Calif) and Cytovision Genus 4.0 software (Applied Imaging) with a ×10 ocular lens and a ×63 oil-immersion lens according to standard procedures. Staining of experimental slides was accompanied concurrently with positive and negative control slides to monitor assay performance and to assess the accuracy of signal enumeration.

Copy number alterations of the VEGFA gene were evaluated according to established methods by 2 pathologists in a blinded fashion.18, 19 Briefly, copy number alterations in which >90% of nuclei had hybridization signals were considered informative. In the informative cases, if the ratio of orange signals to green signals was >1 and there were >2 orange and green signals in each single tumor cell, then the VEGFA amplification was considered focal. If the ratio was 1 and there were >2 green and orange signals in each single tumor cell, then it was considered large fragment VEGFA amplification. If the ratio was <1 or there were only 2 green and orange signals in each single tumor cells, then it was considered no VEGFA amplification.

Immunohistochemical Analysis and Determination of Microvascular Density

The 58 FFPE tissues were sectioned for immunohistochemical staining as described previously.2 Antibodies of VEGFA and cluster of differentiation 34 (CD34) (both from Abcam, Cambridge, United Kingdom), were used at dilutions of 1:100 and 1:150, respectively. Known VEGFA-positive and CD34-positive control slides also were stained for quality control. Assessment of VEGFA expression was made based on the overall intensity of membranous and cytoplasmic staining within the tumor cells and the percentage of cells stained.20 The intensity of cytoplasmic immunostaining was assessed and graded as follows: 0 indicated no staining; 1, weak staining; 2, moderate staining; and 3, strong staining. The percentage of cells stained for VEGFA was calculated by comparing the number of positively stained cells relative to the number of nuclei (0 indicated no cells stained; 1, 1%-25% of cells stained; 2, 26%-50% of cells stained; and 3, >50% of cells stained). By combining both scores, the degree of VEGFA protein expression was determined; a combined score <2 represented negative expression (−), a combined score of 2 indicated weak positive expression (+), a combined score of 3 or 4 indicated moderate/multifocal positive expression (++), and a combined score of 5 or 6 indicated strong/diffuse positive expression (+++). It should be noted that, although some tumors were designated as negative for VEGFA expression based on these criteria, there were no cases in which VEGFA staining was completely absent. Because of the subjectivity and semiquantitative nature of immunohistochemistry, this kind of grading system is used commonly to indicate the relative levels of marker staining. Anti-CD34 antibody was used for immunohistochemical staining of endothelial cells in tumor sections to determine the microvascular density (MVD), as previously described.20

Statistical Analysis

Comparisons of mean values were performed by using the Student t test or an analysis of variance. Comparisons of frequencies were performed by using the chi-square test or the Fisher exact test, as necessary. Kaplan-Meier and Cox regression analyses were used to examine the relations between survival rates and the following variables: age, sex, tumor site, metastasis, recurrence, treatments, protein expression, and gene amplification. All P value < .05 were considered statistically significant in multivariate analysis. All analyses were performed using SPSS software (version 16.0; SPSS, Inc., Chicago, Ill). All aCGH analyses were performed in R (version 2.10.0; R Foundation for Statistical Computing).

RESULTS

Osteosarcomas in Diverse Populations Share Common Genetic Defects

To gain insight into the most common genetic changes at the chromosomal level in osteosarcoma, we carried out a whole-genome aCGH analysis of fresh osteosarcoma samples from Chinese patients and identified major regions of genetic alterations (GSE19180).2 Our analysis indicated that the pattern of overall copy number alterations from our aCGH dataset was strikingly similar to that from an independent aCGH dataset (GSE9654) of osteosarcoma samples obtained from Canadian patients.10 It is noteworthy that 1 recently published BAC aCGH dataset obtained from 36 Norwegian patients exhibited a pattern at the chromosomal level with very similar to that of the 2 Agilent aCGH datasets from Chinese and Canadian patients.15 This suggests that, surprisingly, osteosarcomas from diverse populations share common and distinct genetic alterations. This unexpected similarity is highly significant, because, unlike other cancer sample types, osteosarcoma samples are difficult to acquire technically; thus, the issue of small sample size commonly associated with most cancer types may not be so serious for osteosarcoma. In the current study, we combined the 2 high-resolution Agilent aCGH datasets for subsequent analysis to identify the most commonly altered genes at the gene copy level (Fig. 1A,B). The BAC aCGH dataset was not used because of its low resolution at the gene copy level.15

Figure 1. Chromosomal and gene aberrations in 20 human osteosarcomas (OS) are illustrated. (A) The recurrence pattern of copy number alterations (CNAs) are illustrated in 2 microarray-based comparative genomic hybridization (aCGH) datasets (GSE19180 and GSE9654). The x-axis indicates chromosome numbers, and the y-axis indicates the aberration frequency of gains (positive) and losses (negative) for each measured aCGH probe arranged based on their genomic coordinates along the x-axis. Dashed lines indicate the thresholds for significant recurrent aberrations. Measured sequences with aberration frequency that exceeded the thresholds are color coded to emphasize the locations of significantly recurrent aberrations (red indicates significantly recurrent amplification; green, significantly recurrent deletion; gray, nonsignificant recurrence of aberrations). (B) This is a heat map of genetic aberrations corresponding to the CNAs illustrated in A. Columns denote the measured aCGH probes, which are arranged based on their genomic coordinates in chromosome order; and rows indicate the patient identification of the 20 OS samples. Red areas indicate that the probe was amplified in the corresponding sample, green indicates deletion, and black indicates no CNAs.

Genetic Alterations of the VEGF Pathway, Including the VEGFA Gene, in Osteosarcoma

Our analysis of the pooled GSE19180 and GSE9654 datasets led to the identification of amplifications of 1p, 6p, 18q, and 21q and deletions of 2q, 4q, 6q,10p, 10q, and 13q (Fig. 1A,B). These alterations included 3795 genes (2519 significantly amplified genes and 1276 significantly deleted genes) with statistically significant aberrations in the 20 osteosarcoma samples. To gain systemic insight into the genetic preferences that allow the emergence of osteosarcoma, we performed a KEGG pathway enrichment analysis of these amplified and deleted genes. That analysis identified 33 key pathways that had multiple component genes altered at the chromosome level. These pathways included the VEGF signaling, mammalian target of rapamycin (mTOR), cellular adhesion molecule (CAM), adherens junction, wingless-type mouse mammary tumor virus integration site family (Wnt), and hedgehog signaling pathways (Table 2). Among them, the VEGF pathway was ranked first with 13 amplified genes, including VEGFA itself (Fig. 2A,B). The genes with copy number aberrations in the VEGF pathway are indicated on the pathway graph in Figure 2B. The top ranking VEGF pathway genes for genetic alteration in osteosarcoma were novel but not entirely surprising, because osteosarcoma is a highly vascular tumor type. The only other known related report was of a VEGFA-containing 6p21 chromosomal over representation in 27% to 51% of uveal melanoma,21 and it is not clear whether other genes in the VEGF pathway also were amplified in those uveal melanomas.

Figure 2. Genes with copy number aberrations (CNAs) in the vascular endothelial growth factor (VEGF) pathway are illustrated. (A) The status of CNAs is indicated for genes involved in the VEGF pathway in 20 osteosarcoma (OS) samples. Red denotes amplification, green denotes deletion, and black represents no CNAs. Significantly altered genes in the VEGF pathway are indicated on the right, and samples are indicated on the bottom. PIK3R1 indicates phosphoinositide-3-kinase, regulatory subunit 1 (alpha); MAPK1, mitogen-activated protein kinase 1; AKT1, v-akt murine thymoma viral oncogene homolog 1; NFATC4, nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 4; SPHK1, sphingosine kinase 1; RAC1, ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1); PIK3R3, phosphoinositide-3-kinase, regulatory subunit 3 (gamma); MAPK13, mitogen-activated protein kinase 13; MAPK14, mitogen-activated protein kinase 14; PTK2, protein tyrosine kinase 2; SH2D2A, SH2 domain containing 2A; CDC42, cell division cycle 42 (GTP binding protein, 25 kDa); PLA2G2F, phospholipase A2, group IIF; PLA2G2D, phospholipase A2, group IID, PLA2G5, phospholipase A2, group V; PLA2G2A, phospholipase A2, group IIA (platelets, synovial fluid); PLA2G2E, phospholipase A2, group IIE; CASP9, caspase 9, apoptosis-related cysteine peptidase; PIK3CD, phosphoinositide-3-kinase, catalytic, delta polypeptide; RAC3, ras-related C3 botulinum toxin substrate 3 (rho family, small GTP binding protein Rac3). (B) This chart provides a visualization of the location of altered genes in the VEGF pathway. Pink indicates genes with significantly recurrent amplification, and green denotes genes with significantly recurrent deletion. SPK, serine/threonine-protein kinase; Raf-1, v-raf-1 murine leukemia viral oncogene homolog 1; +p, phosphorylation; PKC, protein kinase C; MAPK, mitogen-activated protein kinase; MEK, MAP kinase kinase; ERK, extracellular signal-regulated kinase; VRAP, VEGF receptor-associated protein; DAG, dystroglycan; cPLA2, cytosolic phospholipase A2; PLCγ, phospholipase C gamma; IP3, inositol (1.4.5)-trisphosphate; CALN, calcineurin; −p, dephosphorylation; NFAT, nuclear factor of activated T-cells; COX2, cytochrome C oxidase subunit II; PGI₂, prostacyclin; VEGFR2, VEGF receptor 2; Sck, Shc-like protein; FAK, focal adhesion kinase; Src, v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene (avian); Cdc42, cell division cycle 42 (GTP binding protein, 25 kDa); p38, p38 kinase; MAPKAPK3, MAP kinase-activated protein kinase 3; HSP27, heat-shock protein 27; PI3K, phosphatidylinositol 3-kinase; PIP3, phosphatidylinositol (3,4,5)-trisphosphate; Rac, ras-related C3 botulinum toxin; Akt/PKB, serine/threonine protein kinase; eNOS, endothelial nitric oxide synthase; NO, nitric oxide; Casp9, caspase-9; Bad, Bcl-2-associated agonist of cell death.

Table 2. Kyoto Encyclopedia of Genes and Genomes Pathway Analysis of Genetic Aberrations in Osteosarcoma

	P
KEEG Pathways	Gain	Deletion
Abbreviations: C21-steroid, 21-carbon steroid; ECM, extracellular matrix; Fc-epsilon RI, high-affinity receptor for the fragment crystallizable region of immunoglobulin E receptor; GnRH, gonadotropin-releasing hormone; KEEG, Kyoto Encyclopedia of Genes and Genomes; mTOR, mammalian target of rapamycin; PPAR, peroxisome proliferator-activator receptor; VEGF, vascular endothelial growth factor.
1. VEGF signaling pathway	.000612	.994021
2. Tight junction	.044333	.719851
3. mTOR signaling pathway	.024894	.676616
4. Hedgehog signaling pathway	.609822	.012811
5. Cell adhesion molecules	.630	.05
6. Adherens junction	.119062	.014329
7. Wnt signaling pathway	.81461	.01039
8. Alpha-linolenic acid metabolism	.003363	1.00
9. Asthma	.003038	1.00
10. Ether lipid metabolism	.006548	1.00
11. Nitrogen metabolism	.007842	.48671
12. Peptidoglycan biosynthesis	.017208	1.00
13. Synthesis and degradation of ketone bodies	.019871	1.00
14. Alzheimer disease	.020851	.290129
15. Biosynthesis of unsaturated fatty acids	.021314	.198297
16. Arachidonic acid metabolism	.022277	.323251
17. Systemic lupus erythematosus	2.49E-06	.997392
18. Glycan structures-biosynthesis 2	.025972	.806243
19. Antigen processing and presentation	.028228	.984565
20. C21-steroid hormone metabolism	.042216	.166058
21. Fc-epsilon RI signaling pathway	.000481	.899467
22. Allograft rejection	.046891	.250208
23. Insulin signaling pathway	.047775	.331333
24. GnRH signaling pathway	.048738	.812648
25. PPAR signaling pathway	.052305	.039963
26. ECM-receptor interaction	.457871	.032505
27. T-cell receptor signaling pathway	.539028	.020903
28. Nonhomologous end-joining	.552678	.001607
29. Phosphatidylinositol signaling system	.714791	.040426
30. Melanogenesis	.960398	.007761
31. Basal cell carcinoma	.978857	.00088
32. Metabolism of xenobiotics by cytochrome P450	.999938	.006437
33. Monoterpenoid biosynthesis	1.00	.004507

Validation of VEGFA Amplification by FISH

Because VEGFA is the best characterized prototype gene in the VEGF pathway, next, we focused our investigation on VEGFA. The aCGH data analysis (GSE19180 and GSE9654) revealed VEGFA gene amplification in 12 of 20 samples from the 2 aCGH datasets (Fig. 3A). To validate this finding, we carried out FISH analysis on 58 FFPE samples (including 10 samples that were used in a previous aCGH analysis) with the VEGFA and CEP 6 probes (Fig. 3B).

Figure 3. Validation of vascular endothelial growth factor A (VEGFA) gene amplification by fluorescent in situ hybridization (FISH) is illustrated. (A) VEGF gene copy number aberrations in osteosarcomas (OS) are indicated. Identification numbers of the 20 OS samples in microarray-based comparative genomic hybridization (aCGH) datasets GSE9654 and GSE19180 are indicated on the bottom. OS1 through OS19 represent samples from the GSE9654 dataset, and S6272 through S6285 represent samples from the GSE19180 dataset. Scatters denote copy number changes of the VEGFA gene. Black and gray lines denote the regional copy number value estimated by the circular binary segmentation (CBS) algorithm. Black lines denote significant amplification or deletion, whereas gray lines denote nonsignificant amplification or deletion. Twelve samples had amplification of the VEGF gene. (B) Location of chromosome enumeration probe 6 (CEP 6) and the VEGFA gene FISH probe. The green arrow indicates the FISH CEP 6 probe located to the Chromosome 6 centromere. The red line on the right indicates the location of the VEGFA gene FISH probe. NM indicates nucleotide sequence record identification number. (C-E) Validation of the different patterns of VEGFA gene status in aCGH and FISH assay is illustrated. The aCGH probes for chromosome 6 are ordered on the basis of their genomic position (x-axis). Scatters denote the copy number change (y-axis) of probes. Dotted lines indicate the thresholds for significant aberrations. Blue lines denote regional copy number values estimated by CBS, and blue lines above and below the break line indicate amplification or deletion in the corresponding region, respectively. The dashed red line and the green arrows in the images on the left denote the location of centromere 6; the red dots and arrows denote 4 probes corresponding to the VEGFA gene and its location on chromosome 6 in aCGH analysis. For the CEP 6 FISH probe, a green signal indicates the chromosome 6 centromere in FISH detection and is indicated by green arrows on the photomicrographs to the right. For the VEGFA gene FISH probe, an orange signal represents the VEGFA gene copy number, which is indicated by red arrows on the photomicrographs. (C) Pattern 1 is shown (VEGFA gene amplifications with polysomy 6). Sample S6275 harbors polysomy 6 with amplifications of the VEGFA gene. (D) Pattern 2 is shown (focal amplification of the VEGFA gene). Genetic amplifications of the VEGFA gene are detected in local fragments in from Sample S6284. FISH detection indicates that Sample S6284 harbors disomy 6 with amplification of the VEGFA gene. (E) No VEGFA gene amplification pattern is evident. Two green signals with 2 orange signals suggest that there is no VEGFA gene amplification in Sample S6272.

We detected VEGFA gene amplification in 32 of 50 evaluable samples (results were not available for 8 samples because of loss of tissues during the pretreatment process) (Tables 3, 4; Fig. 3C,D). In our 6 samples that had VEGFA amplification verified based on aCGH data analysis, VEGFA gene amplification was detected in 5 samples with a FISH assay. The detectable ratios of VEGFA amplification using both methods were significantly consistent (chi-square statistic, 6.667; P = .048; correlation coefficient [r] = 0.816). Only 1 sample was inconsistent, perhaps because of the different locations of samples that were used for aCGH and FISH assays and because various parts of the same tumor can be heterogeneous.

Table 3. Vascular Endothelial Growth Factor A (VEGFA) Gene Amplification, VEGFA Protein Expression, and Microvessel Density in Osteosarcoma

		Disease-Free Survival			Overall Survival
Variable	No. of Patients	P	HR	95% CI	P	HR	95% CI
Abbreviations: CI, confidence interval; HR, hazard ratio; MVD, microvessel density. a Significantly different.
VEGFA amplification
No amplification	18	.04a			.24
Amplification	32	.04	0.25	0.06-1.03	.25	0.43	1-1.83
Focal	15
Large fragment	17
VEGFA protein expression
Negative	15	.04a			.76
Positive
Weak	23	.17	0.2	0.02-2.02	.35	2.37	0.39-14.3
Moderate	7	0.23	0.38	0.078-1.82	.85	1.18	0.21-6.56
Strong	13	0.08	4.67	0.811-26.91	.87	1.22	0.11-13.54
VEGFA status
Low	20	.037a			.23
High	30	.05	0.25	0.06-1.00	.24	0.42	1.00-1.79
MVD	58	.92	1.00	0.97-1.04	.32	0.98	0.93-1.02

Table 4. Vascular Endothelial Growth Factor A (VEGFA) Gene Amplification Correlated With VEGFA Protein Expression and Microvessel Density in Patients With Osteosarcoma

		VEGFA Amplification, No. of Patients
Variable	Value	No	Yes
Abbreviations: MVD, microvessel density; SD, standard deviation; VEGFA, vascular endothelial growth factor A. a Significantly different. b Mean±standard deviation.
VEGFA protein expression
Negative		9	2
Positive
Weak		5	16
Moderate		1	5
Strong		3	9a
VEGFA protein expression
Negative		9	2
Positive		9	30a
MVD, per 0.26 mm^2
Mean	22	15.8±3.3b	22.3±2.6a,b
Median	19
Range	2-60

In the 32 samples that harbored VEGFA amplifications, 15 samples had focal amplifications, and the other 17 samples had large fragment amplifications (Tables 3, 4). A detailed analysis of the aCGH and FISH results from the same 10 samples further validated the 2 different patterns of VEGFA amplification in osteosarcoma (Fig. 3C,D). In aCGH data analysis, 3 samples (S6273, S6275, and S6277) had amplification of a large chromosomal fragment that contained the VEGFA gene as well as the centromere of chromosome 6 (Fig. 3C, left). FISH hybridization revealed that in, these 3 samples, multiple tumor cells exhibited polysomy of chromosome 6 and multiple VEGFA gene amplifications (Fig. 3C, right). In contrast, we observed focal genetic amplification of the VEGFA gene in aCGH analysis of Samples S6284 and S6282 (Fig. 3D, left). FISH analysis in the same samples detected primarily disomy with multiple VEGFA gene copy amplifications (Fig. 3D, right). We also observed heterogeneity in VEGFA gene amplification in different cells from the same samples. The other 5 samples (for example, S6272) did not have VEGFA gene amplification identified with either aCGH or FISH analysis (Fig. 3E).

VEGFA Gene Amplification, Elevated VEGFA Protein Expression, Angiogenesis, and Tumor-Free Survival in Osteosarcoma

We compared VEGFA gene amplification, VEGFA expression, and angiogenesis by determining CD34-positive MVD in the 58 FFPE osteosarcoma tissue samples. Abundant expression of VEGFA was observed in 43 of 58 patients (74.1%) with osteosarcoma, as indicated in the top portion of Figure 4A (Tables 3, 4). The MVD of osteosarcoma ranged from 2 to 60 microvessels per 0.26 mm² (mean, 22.7 microvessels per 0.26 mm²; median, 19 microvessels per 0.26 mm²) (Tables 3, 4; Fig. 4A, bottom). The samples that had positive staining for VEGFA protein (including weak, moderate, and strong staining) had significantly greater MVD than the samples with negative staining (F = 4.927; P = .04) (Fig. 4B). Kaplan-Meier survival analysis indicated that patients who had positive VEGFA expression had significantly worse tumor-free survival rates than patients who had negative VEGFA expression (Fig. 4C). These results are consistent with those from other published studies indicating that the abundant expression of VEGFA protein and high MVD are associated with reduced tumor-free and overall survival rates in patients with osteosarcoma.3, 20, 22

Figure 4. Correlations of vascular endothelial growth factor A (VEGFA) gene amplification, VEGFA protein expression, microvascular density (MVD), and disease-free survival are illustrated in patients with osteosarcoma. (A) Strong positive expression of (Top) VEGFA protein was detected by immunohistochemical staining, and (Bottom) MVD was measured by scoring cluster of differentiation 34 (CD34)-positive cells (original magnification, ×40). (B) MVD in VEGFA protein-positive patients was significantly greater than MVD in VEGFA protein-negative patients. (C) Kaplan-Meier analysis of cumulative (Cum) survival indicates that positive VEGF expression was associated significantly with adverse tumor-free survival. (D) Concordance of VEGFA gene amplification with VEGFA protein expression is illustrated. (E) Kaplan-Meier survival analysis indicates that VEGFA gene amplification was associated significantly with adverse tumor-free survival. (F) Kaplan-Meier survival analysis indicates that high VEGFA levels were associated significantly with adverse tumor-free survival.

To assess the correlation between VEGFA gene amplification and VEGFA protein expression and angiogenesis, we divided all 58 samples into a positive VEGFA protein expression group (including those with weak, moderate, and strong positive expression) and a negative VEGFA protein expression group according to the immunohistochemical staining results for VEGFA protein; then, we examined the correlations between each group and VEGFA gene amplification. The analyses indicated that VEGFA gene amplification had a significantly positive correlation with abundant VEGFA protein expression (Fig. 4D). Furthermore, the MVD in VEGFA-amplified samples (22.3 ± 2.6 microvessels per 0.26 mm²) was much greater than the MVD in VEGFA-unamplified samples (15.8 ± 3.3 microvessels per 0.26 mm²) (Table 3). These results suggested that VEGFA gene amplification contributes significantly to the elevated expression of VEGFA and vascular features in osteosarcoma. To explore whether VEGFA FISH results could be used to identify patients with poor outcomes who need novel treatment approaches, we performed a Kaplan-Meier survival analysis and observed that patients with VEGFA amplification had significantly worse disease-free survival rates (Fig. 4E).

Joint Consideration of VEGFA Gene Amplification and Positive VEGFA Protein Expression for Patient Stratification

In targeted therapy, the target status must be ascertained to determine which patients will receive therapy. Our studies indicate that there are 2 independent assays, FISH and immunohistochemical analysis, for measuring VEGFA status in patients with osteosarcoma. This is similar to targeting the v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (HER2, ERBB2) in breast cancer, in which both gene amplification and protein overexpression are evaluated for targeted therapy.23 To explore whether joint consideration of VEGFA gene amplifications and positive VEGFA protein expression may provide an additional benefit to patients with osteosarcoma in their selection for possible future anti-VEGFA treatment, we stratified patients into the high-VEGFA group if both VEGFA gene amplification and positive VEGFA protein expression (including weak, moderate, and strong positive expression) were detected (Table 3). All other patients were stratified into the low-VEGFA group. Kaplan-Meier survival analysis indicated that patients in the high-VEGFA group had significantly worse tumor-free survival rates than patients in the low-VEGFA group (Fig. 4F). All data on VEGFA gene amplification, VEGFA protein expression, and MVD are summarized and listed for individual patients in Table 5. Furthermore, differences in survival between the 2 groups were more significant than when either VEGFA amplification alone or VEGFA protein expression alone was used, and the median (±standard deviation) tumor-free survival was 16.0 ± 4.5 months versus 11.3 ± 2.3 months and 5.0 ± 1.4 months, respectively. This result justifies consideration of a clinical trial in patients with osteosarcoma to explore the activity of an antivascular agent. If validated in future studies, then combined VEGFA amplification and VEGFA protein expression may be the most effective way to select patients with osteosarcoma for anti-VEGF therapy or other antivascular therapy.

Table 5. Vascular Endothelial Growth Factor A (VEGFA) Gene Amplification, VEGFA Protein Expression, and Microvessel Density Information in 58 Osteosarcomas

Patient	VEGFA Protein Expressiona	aCGH ID	VEGFA Gene Amplificationb	VEGFA Gene Amplification Typec	MVD, per 0.26 mm^2d	VEGFA Protein Expressione	VEGFA Status^f
Abbreviations: aCGH ID, microarray-based comparative genomic hybridization identification number as in GSE19180; MVD, microvessel density. a VEGFA protein expression was scored as 1 (positive) or 0 (negative). b VEGFA gene amplification was scored as 1 (positive) or 0 (negative). c VEGFA gene amplification type was categorized as 1 (focal) or 2 (large fragment). d VEGFA protein expression was scored as 1 (weak), 2 (moderate), or 3 (strong). e VEGFA protein status was categorized as 1 (high) or 0 (low).
1	1	S6282	1	1	20	3	1
2	1		1	1	23	1	1
3	1	S6272	1	2	60	3	1
4	1		1	2	40	3	1
5	1		1	2	13	3	1
6	1		1	1	30	3	1
7	1				42	3
8	1		1	2	17	1	1
9	1		1	1	9	1	1
10	1		0	0	31	3	0
11	1					1
12	0		1	1	7	0	0
13	1		1	2	59	3	1
14	1		1	1	24	3	1
15	1	S6273	1	2	11	2	1
16	1		1	2	32	1	1
17	1		1	1	15	1	1
18	0		0	0	3	0	0
19	1	S6275	1	2	40	2	1
20	1	S6283	1	2	20	2	1
21	1		1	2	20	2	1
22	1		1	2	16	1	1
23	1		1	2	27	1	1
24	1		0	0	36	3	0
25	0	S6276	0	0	4	0	0
26	1		1	1	15	3	1
27	1		1	1	5	2	1
28	1		1	1	10	1	1
29	1		1	1	17	1	1
30	1		0	0	48	2	0
31	1		0	0	12	1	0
32	1		1	2	27	1	1
33	1	S6284	1	1	22	1	1
34	1		1	1	10	1	1
35	1		1	1		1	1
36	1		0	0	29	3	0
37	1		0	0	30	1	0
38	1		0	0	26	1	0
39	0	S6277	1	1	46	0	0
40	0		0	0	6	0	0
41	0		0	0	5	0	0
42	0		0	0	7	0	0
43	0		0	0	8	0	0
44	0		0	0	3	0	0
45	1					1
46	0					0
47	0				8	0
48	0				49	0
49	1	S6285			34	2
50	1		1	1	8	1	1
51	0		0	0	5	0	0
52	0		0	0	9	0	0
53	1		1	2	27	3	1
54	1		0	0	4	1	0
55	0				60	0
56	1		1	2	20	1	1
57	1		0	0	18	1	0
58	1		1	1	2	1	1

DISCUSSION

Osteosarcoma is the most common primary malignant bone tumor in children and young adults and is characterized by an aggressive clinical course. Pulmonary metastases, central presentation, and local nonresectable relapse cause fatal outcomes in the majority of patients.24 Several studies have focused on the role of angiogenesis in osteosarcoma, albeit with controversial results.20, 22, 25 Angiogenesis is known as a fundamental factor in the local growth of tumors and in progression to metastases and is assessed most commonly either by measuring VEGFA expression in cancer cells or by measuring tumor CD31-positive or CD34-positive MVD. Cancer cells respond to an early hypoxic stage by activating signaling pathways that induce cell proliferation, the production of angiogenic factors like as VEGFA, and new endothelial cell formation to provide a new vascular supply.26, 27 In the current study, using integrated aCGH, FISH, and immunohistochemistry analyses, we established for the first time that VEGF pathway genes, including the VEGFA gene, are amplified in osteosarcoma.

To our knowledge, this is the first report of VEGFA gene amplification in osteosarcoma. However, VEGFA protein overexpression has been observed previously. This situation is similar to that reported for several other key signaling molecules important in cancer, such as epidermal growth factor receptor (EGFR) and ERBB2. For ERBB2, both gene amplification and immunohistochemical staining results have been used to identify patients with breast cancer who are candidates for trastuzumab treatment.23, 28 However, because of the subjectivity associated with immunohistochemistry, it has been demonstrated that gene amplification detected by FISH is a more accurate method with which to stratify patients for treatment.29, 30 An anti-VEGF antibody bevacizumab (Avastin; Genentech, South San Francisco, Calif), when used in combination with chemotherapy, significantly improved survival and response rates in patients with metastatic colorectal cancer.31 Anti-VEGF treatment has not been used commonly to treat osteosarcoma. If such a treatment were studied in osteosarcoma, then it would be critical to know the relation between VEGFA gene amplification by FISH and VEGFA protein expression by immunohistochemistry and their association with prognosis and response to antivascular therapy. Our data suggest that amplification of the VEGFA gene is a poor prognostic factor for tumor-free survival. Furthermore, the combination of VEGFA gene amplification and elevated VEGFA protein expression, if validated in future studies, may provide a valuable stratification method for the selection of patients with osteosarcoma for antivascular therapy.

Although VEGFA overexpression and the regulation of its expression have been reported in multiple cancer types, including osteosarcoma, previous reports mainly focused on its regulation by transcriptional factors like HIF-1A.32 The current results indicate that, similar to the involvement of EGFR gene amplification in a high proportion of tumors with EGFR protein overexpression,33VEGFA gene amplification is a key mechanism for VEGFA protein overexpression in osteosarcoma. Because VEGFA expression is governed by numerous environmental factors (eg, hypoxia, oxidative stress) and gene alterations (eg, K-Ras, p53),34 in the future, it would be worthwhile to determine how these known factors contribute to VEGF expression in osteosarcoma and whether both genetic and environmental factors contribute to heightened angiogenesis in osteosarcoma.

The discovery of signal-transduction pathways and their importance in a variety of cancers has led to the development of many new targeted agents. With regard to osteosarcoma, signal-transduction pathways that are activated by the binding of growth factors to their receptors are of particular interest.35 Our current KEGG analysis of aCGH data identified 33 genetically altered pathways in osteosarcomas. Genetic amplifications of VEGF and mTOR pathway genes involved VEGFA, AKT1, and other genes, suggesting that genetic amplifications of these genes and pathways are associated with tumor development and progression. Data from preclinical studies have indicated that rapamycin and its analogues inhibit cell growth in human cancer cell lines derived from osteosarcoma and tumor models in vivo.36, 37 Furthermore, it was demonstrated recently that rapamycin inhibits the expression of HIF-1A and VEGFA in vitro and inhibits metastatic tumor growth and angiogenesis in in vivo mouse models by reducing the translational production of VEGFA.36, 38, 39 Therefore, our data on genetic aberrations involved in the mTOR pathway not only provide more evidence of the utility of anti-mTOR therapy but also supply more therapeutic targets of this pathway because of significant amplifications of the VEGFA; v-akt murine thymoma viral oncogene homolog 1 (AKT1); phosphatidylinositol 3-kinase (PIK3), catalytic, delta polypeptide (PI3K3CD); mitogen-activated protein kinase 1 (MAPK1); and PIK3 regulatory subunit 3 (PIK3R3) genes in osteosarcoma. Similarly, our investigations into genetic aberrations in the Wnt, hedgehog, CAMs, tight junction, and adherens junction pathways may identify other potential targets for osteosarcoma.

FUNDING SOURCES

This work was partially supported by a grant from the Liddy Shriver Sarcoma Initiative (J. Yang and W. Zhang) and the Development of Science and Technology Funds of the Tianjin Education Bureau (20070218, J. Yang). This research is supported in part by the National Institutes of Health through The University of Texas MD Anderson's Cancer Center Support Grant CA016672. The Tissue Bank of Tianjin Medical University Cancer Institute and Hospital is partially supported by the National Foundation for Cancer Research (US). J. Yang is a recipient of the Connie and Jim Walter Fellowship in Sarcoma Research.

CONFLICT OF INTEREST DISCLOSURES

The authors made no disclosures.