SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

Vasohibin-1 is a recently identified negative feedback regulator of angiogenesis induced by VEGF-A and bFGF. In this study, we first evaluated mRNA expression of vasohibin-1 and CD31 in 39 Japanese female breast carcinoma specimens including 22 invasive ductal carcinoma (IDC) and 17 ductal carcinoma in situ (DCIS) using a real-time quantitative RT-PCR (QRT-PCR) with LightCycler system. In addition, we also immunolocalized vasohibin-1 and CD31 and compared their immunoreactivity to nuclear grades and histological grades of 100 carcinoma cases (50 IDC and 50 DCIS). There were no statistically significant differences of CD31 mRNA expression and the number of CD31 positive vessels between DCIS and IDC (= 0.250 and = 0.191, respectively), whereas there was a statistically significant difference in vasohibin-1 mRNA expression and the number of vasohibin-1 positive vessels in DCIS and IDC (= 0.022 and P ≤ 0.001, respectively). There was a significant positive correlation between vasohibin-1 mRNA level and Ki-67 labeling index in DCIS (r2 = 0.293, P ≤ 0.001). In addition, vasohibin-1 mRNA expression was correlated with high nuclear and histological grades in DCIS cases and a significant positive correlation was detected between the number of vasohibin-1 positive vessels and Ki-67 labeling index or nuclear grade or Van Nuys classification of carcinoma cells (P ≤ 0.001, respectively). These results all indicate the possible correlation between aggressive biological features in DCIS including increased tumor cell proliferation and the status of neovascularization determined by vasohibin-1 immunoreactivity.

(Cancer Sci 2010; 101: 1051–1058)

Breast cancer is one of the most common malignancies in woman worldwide and its morbidity has recently increased.(1) Numerous factors have been reported to be associated with development of breast cancer including angiogenesis. Angiogenesis or the formation of new blood vessel networks not only plays a pivotal role in human normal development, but also in pathological conditions such as inflammatory diseases and neoplasms.(2) A switch to the actively angiogenic phenotype is in general considered to be dependent upon an in situ balance between stimulatory and inhibitory factors of angiogenesis.(2,3) Therefore, numerous studies have been reported on the mechanisms of control or regulation of angiogenesis since the discovery of endothelium-specific proangiogenic factors, namely vascular endothelial growth factor (VEGF) and angiopoietin family proteins.(2) In addition, other molecules involved in this process of angiogenesis, including pigment epithelium derived factor (PEDF), platelet factor 4, angiostantin and endostatin, have been proposed as angiogenesis inhibitors.(2,4)

Vasohibin-1 has been very recently identified as one of the first established negative feedback regulators of angiogenesis, from an extensive microarray analysis originally designed to identify genes up-regulated by VEGF in cultured vascular endothelial cells.(2,5–8) Vasohibin-1 was subsequently demonstrated to be specifically expressed in ECs and its expression increased in response to angiogenic stimulators such as VEGF and basic fibroblastic growth factor (bFGF).(5,8) Vasohibin-1 is also abundantly present in human placenta and fetus,(4,5,7) in which angiogenic events markedly occur in vivo, but controversies exist as to whether this is the cases in all these tissues. Vasohibin-1 inhibits growth, migration, and network formation of endothelial cells and works in an autocrine manner as negative feedback regulators for angiogenesis.(8) Signals mediated by VEGF-A, one of the known VEGF family members, are transduced via VEGF receptor 2 (Flk-1),(9) and protein kinase C δ (PKCδ), one of the factors located in important downstream of intrasignaling pathway of Flk-1. These intracellular signals also markedly induced vasohibin-1 expression(6) but the status of vasohibin-1 in human malignancies has not necessarily been examined in detail with an exception of a few studies.(10,11)

We previously reported immunolocalization of vasohibin-1 in human breast disorders including carcinoma in order to examine whether this factor is expressed in endothelial cells or not in human breast tissues.(11) Vasohibin-1 immunodensity obtained by employing histomorphometry was significantly higher in invasive ductal carcinoma (IDC) than in ductal carcinoma in situ (DCIS)(11) and results of double immunostaining analysis further demonstrated that the Ki-67 labeling index among vasohibin-1 positive endothelial cells was significantly higher than that in all CD31 positive endothelial cells.(11) These results all indicated that vasohibin-1 is considered a more appropriate biomarker for intratumoral neovascularization compared to frequently employed CD31, and also demonstrated that the anti-angiogenic compensatory mechanisms may also work in invasive breast carcinoma, possibly in response to an induction of angiogenesis by various factors associated with the process of carcinoma invasion into the surrounding stromal tissue.(11) In addition, an evaluation of the number of vasohibin-1 positive vessels in human breast carcinoma turned out one of the prognostic markers for metastasis and prognosis of the patients with IDC.(11)

mRNA expression of this important regulator of angiogenesis, vasohibin-1, has, however, not been evaluated in any of the human malignancies. In addition, the status of vasohibin-1 has not been well-characterized in non-invasive human tumors. DCIS is by definition not associated with stromal invasion but its biological potentials of invasion have been always in dispute.(12,13) DCIS is also classified into several types based on its potential to recur or develop into invasive carcinoma.(12) The correlation between these phenotypes and the status of neovascularization of each cases, however, has been little examined in DCIS. Therefore, in this study, we first evaluated mRNA expression of both CD31 and vasohibin-1 in both invasive and non-invasive breast carcinomas using the LightCycler system technology(14,15) and then studied the correlation between the status of neovascularization and histological phenotypes of DCIS.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

Breast tissue specimens.  We retrieved 100 Japanese female cases of breast tissue (50 IDC and 50 DCIS) which had been operated in 2007 and 2008 at Department of Breast and Endocrine Surgery, Tohoku University Hospital and Department of Surgery, Tohoku Kosai Hospital, both located in Sendai, Japan. We received informed consents from the patients and the protocol for this study was approved by the Ethics Committee at Tohoku University Graduated School of Medicine and Tohoku Kosai Hospital (2008-472). After surgical resection of the primary tumors and gross inspection by a pathologist, all the cases had been fixed in 10% buffered formalin and embedded in paraffin, or a representative portion of the tumors of 39 cases (22 IDC and 17 DCIS) were immediately snap-frozen and stored in liquid nitrogen and stored at −80°C until use. Of the remaining 100 patients, 50 were diagnosed histopathologically as IDC and 50 as DCIS.

Real-time QRT-PCR for vasohibin-1.  Thirty-nine cases of frozen sections were stained with H&E for confirmation of the presence of carcinoma cells in the specimens examined. Total RNA was extracted from primary tumors using the TRIzol reagent (Invitrogen Corpolation, Carlsbag, CA, USA), and the Transcriptor First standard cDNA Synthesis Kit (Roche Diagnostics GmbH, Mannheim, Germany) was used in the synthesis of cDNA. Real-time quantitative RT-PCR was performed on the LightCycler System (Roche Diagnostics GmbH) and the Fast Start DNA Master SYBR Green1 (Roche Diagnostics GmbH). Characteristics of the primer sequences used in this study were summarized in Table 1.(5,6,16,17) Settings for the PCR thermal profile were as follows: initial denaturation at 95°C for 10 min, followed by 40 amplification cycles of 95°C for 10 s, annealing at 62°C (vasohibin-1), 62°C (CD31) and 62°C (ribosomal protein L 13a [RPL13A]) for 10 s, respectively, and elongation at 72°C for 12 s. The cDNA of known concentrations for target genes and the housekeeping gene, RPL13A, were used to generate standard curves for quantitative PCR in order to determine the quantity of target cDNA transcripts. Quantitative normalization of each target genes in each tissue sample was performed using the expression of RPL13A mRNA as an internal control and evaluated as a ratio compared with the average expression ratio of CD31 and vasohibin-1 in DCIS cases (the averages of CD31/RPL13A and vasohibin-1/RPL13A in DCIS cases), respectively.(18–20) PCR was set up at 2 mm Mgcl2, (Vasohibin,CD31), 3 mm (RPL13A) and 10 pmol/μL of each primer. The information of primers used in this study is summarized in Table 2.

Table 1.   Clinicopathological features of the cases examined
 AB
  1. A, 10% formalin fixed and paraffin embedded specimens. B, frozen sections.

Histologic type
 IDC5022
 DCIS5017
Nuclear grade
 IDC
  Grade 152
  Grade 22212
  Grade 3238
 DCIS
  Grade 1161
  Grade 22712
  Grade 374
Histological grade
 Nottingham histological grade
  Grade 1186
  Grade 22710
  Grade 356
Van Nuys classification
 Group 1248
 Group 2185
 Group 384
Table 2.   Primer sequences used in real-time PCR in this study
Gene (accession no.)Primer for PCRSize (bp)Reference
CD31 (NM000442)Forward: GATGTCAGAAACCATGCAA199 
Reverse: AGCCTTCCGTTCTAGAGTATC
Vasohibin-1 (KIAA1036)Forward: AGATCCCCATACCGAGTGTG167Watanabe et al.(4)
Reverse: GGGCCTCTTTGGTCATTTCC
RPL13A (NM012423)Forward: CCTGGAGGAGAAGAGGAAAAG125Vandesompele et al.(43)
Reverse: TTGAGGACCTCTGTGTATTT

Immunohistochemistry.  We performed immunohistochemical staining for vasohibin-1, CD31 and Ki-67 for all cases. The specimens had been fixed in 10% formalin, embedded in paraffin, cut into 4 μm thick sections and placed on the glue-coated glass slides. Sections were deparafinized in xylene, and hydrated with graded alcohols and distilled water. Endogenous peroxidase activity was blocked by 3% hydrogen peroxidase for 10 min at room temperature. Antigen retrieval was performed using Autoclave in 10 mmol EDTA (pH 8) for vasohibin-1 and in citrate buffer for CD31 and Ki-67, heated at 121°C for 5 min. Sections were subsequently incubated for 30 min at room temperature (RT) in a blocking solution of 10% rabbit serum (Nichirei Biosciences, Tokyo, Japan), and then immunostained for over night at 4°C with primary antibodies. The primary antibodies of vasohibin-1, CD31 and Ki-67 were mouse monoclonal antibodies, and were used as follows: anti-human vasohibin-1 monoclonal antibody(9) diluted at 1:3200, anti-CD31 (Dako, Copenhagen, Denmark) diluted at 1:400 and Ki-67 (Dako) diluted at 1:300. Anti-human vasohibin-1 monoclonal antibody (mAb) was raised against the synthetic fragment (Gly286-Arg299) of human vasohibin-1 as described by Watanabe et al.(5) The specificity and sensitivity of this mAb was confirmed by both Western blotting and immunohistochemical analysis.(5) For vasohibin-1, CD31 and Ki-67 immunohistochemistry, secondary antibody reactions were performed using biotinyted rabbit anti-mouse antibody (Nichirei Bioscience) was used according to the manufacture’s instructions. Reacted sections were visualized using 3,3′-Diaminobezidine (DAB)/30% H2O2 in 0.05 mol/L Tris buffer (pH 7.6) and couterstained with hematoxylin for nuclear stain.

Immunohistochemical analysis.  Two of the authors independently evaluated immunoreactivity. They were blinded to the clinical course of the patients and the average of numbers counted by two investigators was used for subsequent analysis. Olympus BX 50 (Olympus, Tokyo, Japan) and 20× objective were used for the analysis. The number of microvessels was counted within the tumor of IDC, whereas in DCIS, the number of vessels in the stroma among intradutal components was evaluated. Microvessels were identified based on the architecture, lumen lined by endothelial cells, complemented by positivity of the endothelial cells with anti-CD31 after scanning the immunostaining section at low magnification (×40 and ×100).(21,22) The areas with greatest number of distinctly highlighted microvessels were selected, and counted at one high power (×200).(21,22) Any immunostained endothelial cells or clusters separated from adjacent vessels were counted as a single microvessels, even in the absence of vessel lumen. Each single count is defined as the highest number of microvessels identified at the “hot spot”. Vasohibin-1 positive signals were counted in “hot spot” in which the highest number of anti-CD31 positive vessels was identified.(11) An evaluation of Ki-67 immunoreactivity was performed at high power field (×400) and used as a marker of cell proliferation. More than 500 tumor cells from each of three different representative fields were evaluated and the labeling index was subsequently obtained.

Statistical analysis.  Statistical analysis, such as the One-factor anova and Simple regression analysis, were performed using StatMate III for Windows v3.18 (ATMS Co. Ltd. Tokyo, Japan). The results were considered significant when the P-value were <0.05.

Results

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

CD31 and vasohibin-1 mRNA in breast cancers.  We first examined mRNA expression of CD31 and vasohibin-1 in both IDC and DCIS. The mRNA expression of CD31 evaluated by Light Cycler ranged from 0.03 to 2.57 (median: 0.68, average: 0.86) in all the cases examined, from 0.03 to 2.32 (median: 0.84, average: 1.00) in DCIS cases, and from 0.04 to 2.57 (median: 0.61, average: 0.74) in IDC cases. There were no statistically significant differences of CD31 mRNA between DCIS and IDC cases (= 0.250) (Fig. 1A). The mRNA expression of vasohibin-1 evaluated by Light Cycler ranged from 0.003 to 4.29 (median: 1.00, average: 1.44) in all the cases examined, from 0.003 to 3.28 (median: 0.68, average: 1.00) in DCIS cases, and from 0.44 to 4.28 (median: 1.71, average: 1.78) in IDC cases. There was a statistically significant difference of vasohibin-1 expression between IDC and DCIS (= 0.022) (Fig. 1B).

image

Figure 1.  The summary of analysis of mRNA expression of CD31 and vasohibin-1 in breast cancers and the number of CD31 and vasohibin-1 positive vessels. (A) represents CD31 mRNA expression ratio or level in all the cases, DCIS and IDC. (B) represents vasohibin-1 mRNA expression ratio or level in all the cases examined, DCIS and IDC. (C) represents CD31 positive vessels in all cases, DCIS and IDC. (D) represents vasohibin-1 positive vessels in all cases, DCIS and IDC.

Download figure to PowerPoint

CD31 and vasohibin-1 immunohistochemistry.  The representative findings for HE, CD31 and vasohibin-1 are illustrated in Figure 2. The average number of microvessels detected by CD31 was 22.9 ± 8.5 in all cases, 21.8 ± 8.8 in DCIS and 24.0 ± 8.0 in IDC, respectively. No statistically significant differences were detected between DCIS and IDC in CD31 immunoreactivity (= 0.191). Vasohibin-1 positive microvessels in “hot spot” were 15.97 ± 8.9 in all cases, 12.4 ± 9.0 in DCIS and 19.5 ± 7.3 in IDC, respectively. There was a statistically significant difference of the number of vasohibin-1 positive microvessels between DCIS and IDC (P ≤ 0.001).

image

Figure 2.  Representative illustrations of histological and immunohistochemical findings of breast carcinoma cases examined. Original magnification is x200. (A) corresponded to DCIS and (B) to IDC. These cases were stained positively for both CD31 (inline image) and vasohibin-1 (inline image).

Download figure to PowerPoint

Concordance between mRNA expression and immunoreactivity of CD31 and vasohibin-1.  A statistically significant positive correlation was detected between mRNA expression and immunohistochemical status in CD31 and vasohibin-1 in our present study (< 0.001, respectively).

Correlation between CD31 or vasohibin-1 mRNA and Ki-67 labeling in carcinoma cells.  No significant correlations were detected between the mRNA expression level of CD31 and Ki-67 labeling index of carcinoma cells in all the cases (r2 = 0.015, = 0.453) (Fig. 3A), in DCIS (r2 = 0.110, = 0.194) (Fig. 3B) and in IDC (r2 = 0.048, = 0.329) (Fig. 3C), respectively. However, a statistically significant positive correlation was detected between the mRNA expression level of vasohibin-1 and Ki-67 labeling index of carcinoma cells in all cases (r2 = 0.293, < 0.001) (Fig. 3D) and in DCIS (r2 = 0.466, = 0.002) (Fig. 3E). In addition, a positive correlation was also detected in IDC but the correlation did not reach statistical significance (r2 = 0.149, = 0.08) (Fig. 3F).

image

Figure 3.  (A), (B) and (C) represent the results of the correlation between Ki-67 labeling index and CD31 mRNA expression ratio or level. (A) represents all the cases, (B) DCIS and (C) IDC. (D), (E) and (F) represent the results of the correlation between Ki-67 labeling index and vasohibin-1 mRNA expression level or ratio. (D) all cases, (E) DCIS and (F) IDC.

Download figure to PowerPoint

Correlation between CD31 or vasohibin-1 positive vessels and Ki-67 labeling in carcinoma cell.  No significant correlations were detected between the CD31 positive vessels and Ki-67 labeling index of carcinoma cells in all the cases (r2 = 0.022, = 0.144) (Fig. 4A), in DCIS (r2 = 0.062, = 0.079) (Fig. 4B) and in IDC (r2 = 0.001, = 0.801) (Fig. 4C), respectively. However, a statistically significant positive correlation was detected between the vasohibin-1 positive vessels and Ki-67 labeling index of carcinoma cells in all cases (r2 = 0.300, P ≤ 0.001) (Fig. 4D), in DCIS (r2 = 0.521, P ≤ 0.001) (Fig. 4E) and in IDC (r2 = 0.278, P ≤ 0.001) (Fig. 4F), respectively.

image

Figure 4.  (A), (B) and (C) represent the results of the correlation between Ki-67 labeling index and CD31 positive vessels. (A) represents all the cases, (B) DCIS and (C) IDC. (D), (E) and (F) represent the correlation between Ki-67 labeling index and vasohibin-1 positive vessels. (D) all cases, (E) DCIS and (F) IDC.

Download figure to PowerPoint

Correlation between vasohibin-1 mRNA expression and nuclear grade of carcinoma cells.  The mRNA expression level of vasohibin-1 ranged from 0.47 to 0.81 (median: 0.55, average: 0.61) in NG (nuclear grade) 1 carcinoma cases, from 0.003 to 4.29 (median: 0.94, average: 1.14) in NG2 carcinoma cases and from 0.44 to 3.54 (median: 2.15, average: 2.24) in NG3 cases. There were statistically significant differences of vasohibin-1 mRNA levels between NG1 and NG3 (= 0.003), and NG2 and NG3 (= 0.01), whereas no significant differences were detected between NG1 and NG2 (= 0.374) in all cases (Fig. 5A).In DCIS, a significant difference was detected between NG2 (ranged from 0.003 to 1.27, median: 0.55, average: 0.54) and NG3 (ranged from 1.34 to 3.28, median: 2.15, average: 2.50) in DCIS (< 0.001) (Fig. 5B), whereas there were no statistically significant differences between NG2 (ranged from 0.49 to 4.29, median: 1.15, average: 1.75) and NG3 (ranged from 0.44 to 3.54, median: 2.03, average: 2.11) in IDC (= 0.444) (Fig. 5C).

image

Figure 5.  (A), (B) and (C) represent summary of results of the correlation between vasohibin-1 mRNA expression level or ratio and nuclear grade. (A) all the cases, (B) DCIS and (C) IDC. (D), (E) and (F) represent summary of results of the correlation between vasohibin-1 positive vessels and nuclear grade. (D) all cases, (E) DCIS and (F) IDC.

Download figure to PowerPoint

Correlation between the number of vasohibin-1 positive vessels and nuclear grade of carcinoma cells.  The number of vasohibin-1 positive vessels was 8.0 ± 9.6 in NG1, 16.4 ± 6.9 in NG2 and 20.9 ± 7.5 in NG3 in all DCIS cases examined, respectively (Fig. 5D). There were significant differences among the different nuclear grades of all the cases examined (P ≤ 0.001 between NG1 and the other grades, = 0.003 between NG2 and NG3, respectively). The number of vasohibin-1 positive vessels was significantly different among DCIS cases with different nuclear grades (3.7 ± 2.7 in NG1, 13.8 ± 6.1 in NG2 and 27.3 ± 4.3 in NG3 in DCIS cases, respectively, P ≤ 0.001) (Fig. 5E). In addition, the number of vasohibin positive vessels in IDC cases with different nuclear grades was 18.0 ± 7.0 in NG1, 27.1 ± 7.7 in NG2 and 21.6 ± 6.2 in NG3 in IDC cases, respectively (Fig. 5F). Statistically significant differences were not detected among these cases of IDC (= 0.559 between NG1 and NG2, = 0.746 between NG2 and NG3, = 0.469 between NG1 and NG3).

Correlation between vasohibin-1 mRNA and Van Nuys classification for DCIS, and Nottingham histological grade for IDC.  In DCIS cases, the mRNA expression levels of vasohibin-1 ranged from 0.06 to 1.13 (median: 0.48, average: 0.52) in Group 1, from 0.003 to 1.27 (median: 0.55, average: 0.57) in Group 2 and from 1.34 to 3.28 (median: 2.15, average: 2.50) in Group 3 of Van Nuys Classification. There were statistically significant differences between Group 1 and Group 3 (< 0.001), and Group 2 and Group 3 (= 0.005), respectively. No statistically significant differences were detected between Group 1 and Group 2 (= 0.832) (Fig. 6A). In IDC cases, the mRNA expression level of vasohibin-1 ranged from 0.55 to 2.52 (median: 1.00, average: 1.32) in HG (histological grade) 1, from 0.44 to 4.29 (median: 1.11, average: 1.58) in HG2 and from 1.58 to 3.54 (median: 2.40, average: 2.44) in HG3. A statistical significance was identified only between HG1 and HG3 cases of IDC (= 0.03). No significant differences were detected between HG1 and HG2 (= 0.692), and HG2 and HG3 (= 0.154) IDC cases, respectively (Fig. 6B).

image

Figure 6.  (A) and (B) represent the analysis of correlation between vasohibin-1 mRNA expression ratio and histological grade. (A) with Van Nuys classification for DCIS and (B) with Nottingham histological grades for IDC. (C) and (D) represent the analysis of correlation between vasohibin-1 positive vessels and histological grade. (C) with Van Nuys classification for DCIS cases and (D) with Nottingham histological grades for IDC cases.

Download figure to PowerPoint

Correlation between vasohibin-1 positive vessels and Van Nuys classification for DCIS, and Nottingham hisotological grade for IDC.  In DCIS cases, the number of vasohibin-1 positive vessels was 7.5 ± 5.6 in Group 1, 13.1 ± 7.8 in Group 2 and 26.0 ± 5.0 in Group 3 of Van Nuys classification, respectively (Fig. 6C). Statistically significant differences were also detected among the different groups according to Van Nuys classification, respectively (P ≤ 0.001 between Group 3 and the other groups, = 0.009 between Group 1 and Group 2). In IDC cases, the number of vasohibin-1 positive vessels was 18.0 ± 7.0 in HG1, 20.1 ± 7.7 in HG2 and 21.6 ± 6.2 in HG3. No significant differences were detected among the different grades of IDC cases, respectively (= 0.357 between HG1 and HG2, = 0.688 between HG2 and HG3, = 0.310 between HG1 and HG3) (Fig. 6D).

Discussion

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

Angiogenesis, the formation of new blood vessels from the existing vascular network, represents a complex multi-step process involving extracellular matrix remodeling, endothelial cell migration and proliferation, capillary differentiation and anastomosis. Angiogenesis is a pivotal event in various biological processes in both physiological and pathological settings. Physiological conditions include embryonic development, reproduction, and wound healing; whereas pathologic conditions include cancers, proliferative retinopathy, and rheumatoid arthritis. In situ balance between angiogenesis stimulators such as VEGF and bFGF and inhibitors such as thrombospondin-1 (TSP-1) and pigment epithelium derived factor (PEDF) is generally considered to regulate the process of angiogenesis.(3) Previous studies demonstrated that vasohibin-1 expression is induced in endothelial cells after stimulation with VEGF-A or bFGF and that these factors also stimulate proliferation and migration of endothelial cells.(2,4–6) The endothelium-derived negative feedback regulators of angiogenesis have not been elucidated until the discovery or identification of vaohibin-1. Therefore, vasohibin-1 is the first secretory anti-angiogenic factor from endothelial cells themselves.(2,4–6)

Results of our previous study(11) was the first to examine the status of vasohbin-1 in human breast diseases in which angiogenesis also plays important roles. In particular, results of double immunostaining analysis demonstrated the significant positive correlation between Ki-67 positive proliferating vascular endothelial cells, which may represent neovascular formation(23,24) and vasohibin-1 positive endothelial cells.(10) The Ki-67 labeling index among vasohibin-1 positive endothelial cells was significantly higher than that in all CD31 positive endothelial cells.(11) These results all indicated that vasohibin-1 is considered a more appropriate biomarker for neovascularization compared to CD31, which may detect all the vasculature including both resting and proliferating endothelial cells.(11) However it is known that vasohibin-1 is inhibitor for neovascularization, the high vasohibin-1 expression is related with high neovascularization and worse prognostic factors. It is all suggest that the effect of angiogenesis is higher than the anti-angiogenic effect of vasohibin-1 in high grade malignant cases.

To the best of our knowledge, this is the first reported study evaluating vasohibin-1 gene expression in human malignancies. Results of our present study demonstrated that mRNA expression of vasohibin-1 tended to be higher in IDC than DCIS, but no differences of CD31 mRNA were detected between these invasive and non-invasive lesions. These findings also indicated that the anti-angiogenic compensatory mechanism through in situ production of vasohibin-1 may play important roles in invasive breast carcinoma, possibly in response to an induction of angiogenesis by various factors related to carcinoma invasion into the surrounding stroma.

DCIS constitutes a spectrum of non-invasive proliferative epithelial lesions with a predilection for the terminal duct-lobular units of the breast.(25) DCIS is in general considered a precursor of IDC and is defined as a lesion in which carcinoma cells do not usually grow beyond the basal membrane of the mammary duct.(26) Many factors including nuclear grade, adhesion, tumor cell proliferation, and neovascularizasion have been proposed to be associated with the process of carcinoma cell invasion in breast stroma or development from DCIS to IDC.(12,27–29) For instance, Kerilkowske et al. demonstrated that nuclear grade is the best indicator of recurrence and progression to invasive carcinoma in DCIS cases.(12) Lightfoot et al. also demonstrated that the expression of focal adhesion kinase (FAK) was associated with tumor cell invasion in the progression of DCIS.(27) In addition, Shen et al. reported that tumor cells in DCIS are required not only to increase their proliferative capacity but also to escape program cell death control for development to invasive carcinoma.(28) The proliferation of small subsets of tumor cells is initially limited by the distance from basement membrane when invasion occurs in DCIS.(30) The presence of an increased vascular density suggestive of neovascularization around DCIS has been reported in a number of reported studies.(29,31,32) In addition, the possible association between higher vascularity and increased incidence of stromal invasion or recurrence has been also proposed in the cases with DCIS.(29) Results of these reported studies all indicated that a putative angiogenic switch or alteration in DCIS may contribute to the transformation from in situ to invasive carcinoma. In addition, results of previous studies demonstrated that different expression patterns of angiogenesis factors in low-grade as opposed to high-grade DCIS is consistent with the concept that characteristic pathways exist in an evolution from DCIS to invasive breast cancer.(33,34)

This is the first study to examine the vasohibin-1 expression in DCIS, in detail. Our previous study demonstrated that the cases with a higher number of vasohibin-1 positive vessels tended to be associated with better and statistically significant OS and DFS in invasive breast cancer. In addition, we also reported that vasohibin-1 immunodensity was significantly higher in IDC than in DCIS. We therefore considered vasohibin-1 as a more appropriate biomarker for intratumoral neovascularization than CD31. These results also suggested that vasohibin-1 may be induced in the spectrum of of the stromal or host reaction to carcinoma cells infiltration into stroma. Angiogenesis in invasive breast cancer has been well documented but relatively fewer studies have examined the possible roles of angiogenesis in pre-invasive ductal diseases or in what stages the angiogenic switches may occur during the process of breast carcinoma development.(35) Results of several previous studies demonstrated that the significant increment in the percentage of MVD was detected in high grade in situ breast carcinoma.(30,35–36) In addition, higher histological and nuclear grades in DCIS cases were also reported to be significantly associated with higher microvessel counts, and subsequently higher potential of invasive transformation.(37)

Results of our present study did demonstrate high vasohibin-1 expression in a number of DCIS cases. A significant positive correlation was detected between the vasohibin-1 expression and Ki-67 labeling index of carcinoma cells in DCIS. In addition, a relatively higher level of vasohibin-1 expression was detected in DCIS cases associated with high nuclear and histological grades than those with low nuclear and histological grades. Pure DCIS without any foci of stromal invasion does not generally have the potential to metastasize.(30) Therefore, the particular clinical importance of DCIS is the risk of developing into invasive carcinoma.(30) Results of our present study demonstrated that increased vasohibin-1 expression was associated with both increased cell proliferation of carcinoma cells and higher nuclear and histological grades. Therefore, these results clearly indicated that vasohibin-1 expression level in DCIS could become one of the appropriate biomarker of the potential of subsequent stromal invasion of carcinoma cells but further studies including those examining DCIS cases with known clinical outcome are required for clarification.

It has been clearly demonstrated that cancer development requires neovascularization.(30) Angiogenic pathway is also well-known to become more numerous and redundant as breast cancer progresses as in other human malignancies.(38) Therefore, an inhibition of a single factor or pathway may not necessarily result in sustained clinical therapeutic efficacy in the patients with previously treated, highly refractory diseases. Recently, newer targeted therapies toward the control of tumor neovascularization such as anti-VEGF therapy have been developed in phase II and III clinical trials of breast cancer patients.(39–42) These agents generally demonstrated the clinical effects such as reduction of neoplastic angiogenesis and inhibition of solid tumors proliferation, either alone or in combination with chemotherapy.(39–42) The most important factor in the development of these therapies is obviously a detailed investigation of angiogenic mechanism, with an emphasis on studying biological features of newly formed vessels. Results of our present study as well as of previous studies(2–8,10,11) studied angiogenic mechanism through vasohibin-1 and vasohibin-1 itself could be considered a candidate of anti-VEGF and anti-angiogenesis agent to administer adequately to control tumor angiogenesis.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

We appreciate Katsuhiko Ono, MT, for his excellent technical assistance. This work was partly supported by the grants from the Japanese Ministry of Health, Labour and Welfare for Researches on Intractable Diseases, Risk Analysis Research on Food and Pharmaceuticals, and Development of Multidisciplinary Treatment Algorithm with Biomarkers and Modeling of the Decision-making Process with Artificial Intelligence for Primary Breast Cancer. This work was also partly supported by Grant-in-Aid for Scientific Research (18390109) from the Japanese Ministry of Education, Culture, Sports, Science and Technology, and the Yasuda Medical Foundation.

References

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References