Download Differential role of angiogenesis and tumour cell proliferation in

Neuropathology and Applied Neurobiology (2015), 41, e41–e55
doi: 10.1111/nan.12185
Differential role of angiogenesis and tumour cell
proliferation in brain metastases according to primary
tumour type: analysis of 639 cases
A. S. Berghoff*†‡, A. Ilhan-Mutlu†‡, C. Dinhof†‡, M. Magerle†‡, M. Hackl§, G. Widhalm†¶,
J. A. Hainfellner*†, K. Dieckmann†**, J. Pichler††, M. Hutterer‡‡§§, T. Melchardt¶¶, R. Bartsch†‡,
C. C. Zielinski†‡, P. Birner†*** and M. Preusser†‡
*Institute of Neurology, Medical University of Vienna, Vienna, Austria, †Comprehensive Cancer Center CNS Tumors
Unit, Medical University of Vienna, Vienna, Austria, ‡Department of Medicine I, Medical University of Vienna, Vienna,
Austria, §Austrian National Cancer Registry, Statistics Austria, Vienna, Vienna, Austria, ¶Department of Neurosurgery,
Medical University of Vienna, Vienna, Austria, **Department of Radiotherapy, Medical University of Vienna, Vienna,
Austria, ††Department of Medicine and Neurooncology, Landes-Nervenklinik Wagner-Jauregg, Linz, Austria,
‡‡Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, Salzburg, Austria, §§Department
of Neurology and Wilhelm-Sander Neurooncology Therapy Unity, University Hospital and Medical School Regensburg,
Regensburg, Germany, ¶¶3rd Medical Department, Paracelsus Medical University Hospital Salzburg, Salzburg, Austria,
and ***Department of Pathology, Medical University of Vienna, Vienna, Austria
A. S. Berghoff, A. Ilhan-Mutlu, C. Dinhof, M. Magerle, M. Hackl, G. Widhalm, J. A. Hainfellner, K. Dieckmann,
J. Pichler, M. Hutterer, T. Melchardt, R. Bartsch, C. C. Zielinski, P. Birner and M. Preusser (2015) Neuropathology
and Applied Neurobiology 41, e41–e55
Differential role of angiogenesis and tumour cell proliferation in brain metastases according to
primary tumour type: analysis of 639 cases
Aim: We aimed to characterize angiogenesis and proliferation and their correlation with clinical characteristics in a
large brain metastasis (BM) series. Methods: Ki67 proliferation index, microvascular density (MVD) and hypoxiainducible factor 1 alpha (HIF-1 alpha) index were
determined by immunohistochemistry in BM and primary
tumour specimens. Results: Six hundred thirty-nine BM
specimens of 639 patients with lung cancer (344/639;
53.8%), breast cancer (105/639; 16.4%), melanoma (67/
639; 10.5%), renal cell carcinoma (RCC; 52/639; 8.1%) or
colorectal cancer (CRC; 71/639; 11.1%) were available.
Specimens of the corresponding primary tumour were
available in 113/639 (17.7%) cases. Median Ki67 index
was highest in CRC BM and lowest in RCC BM (P < 0.001).
MVD and HIF-1 alpha index were both highest in RCC BM
and lowest in melanoma BM (P < 0.001). Significantly
higher Ki67 indices, MVD and HIF-1 alpha indices in the
BM than in matched primary tumours were observed for
breast cancer, non-small cell lung cancer (NSCLC) and
CRC. Correlation of tissue-based parameters with overall
survival in individual tumour types showed a favourable
and independent prognostic impact of low Ki67 index
[hazard ratio (HR) 1.015; P < 0.001] in NSCLC BM and
of low Ki67 index (HR 1.027; P = 0.008) and high
angiogenic activity (HR 1.877; P = 0.002) in RCC. Conclusion: Our data argue for differential pathobiological and
clinical relevance of Ki67 index, HIF1-alpha index and
MVD between primary tumour types in BM patients. An
independent prognostic impact of tissue-based characteristics was observed in patients with BM from NSCLC and
RCC, supporting the incorporation of these tissue-based
parameters into diagnosis-specific prognostic scores.
Keywords: brain metastases, HIF-1 alpha index, ki67 proliferation index, microvascular density
Correspondence: Matthias Preusser, Department of Medicine I and Comprehensive Cancer Center, Central Nervous System Tumours Unit
(CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20,1090 Vienna, Austria. Tel: +43 1 40400 4457; Fax: +43 1 40400 6088;
E-mail: [email protected]
© 2014 British Neuropathological Society
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A. S. Berghoff et al.
Introduction
Brain metastases (BM) are a frequent and devastating
complication in cancer patients. The prognosis of BM
patients is generally poor, although long-term survivors
exist. Treatment strategies rely mainly on local
approaches such as radiotherapy and neurosurgery. So
far, progress in clinical approaches to BM patients has
been hampered by a lack of research projects aiming at
elucidating basic principles of BM formation. However,
better understanding of BM pathobiology may lead to
improvements in clinical patient care, for example, by enabling development of improved tools for prognostic evaluation or identification of targets for prevention and
treatment of BM using specific inhibitor drugs [1–5].
Proliferation and hypoxia-induced angiogenesis are
hallmarks of cancer and have repeatedly been implicated
to be relevant in BM formation and growth [6]. For
example, Ki67 proliferation index was postulated as a prognostic factor in a smaller series of BM [7]. Furthermore,
early angiogenesis, especially via vascular co-option, was
pointed out as an early mandatory mechanism in the
establishment of micrometastases [8]. However, BM originate from diverse types of primary tumours and the expression profiles of hypoxia-associated factors and angiogenic
patterns and their clinical relevance may differ between
cancer subtypes. For example, outgrowth of BM of nonsmall cell lung cancer (NSCLC) has been shown to
depend on early angiogenesis in an animal model, while
melanoma cells showed a tendency for perivascular
growth (‘vascular co-option’) without prominent
neo-angiogenesis [9]. However, systematically collected
data on human tissue samples is only available from some
smaller studies. Therefore, we investigated in the presented
study the Ki67 tumour cell proliferation index, expression
of hypoxia inducible factor 1 alpha (HIF-1 alpha), and
microvascular density (MVD) and their prognostic value in
a large and well-characterized cohort of BM patients. Our
analyses included comparative evaluation of these factors
between cases with lung cancer, breast cancer, melanoma,
renal cell carcinoma or colorectal cancer.
Methods
Patients
All patients with BM of histologically proven lung cancer,
breast cancer, melanoma, renal cell carcinoma or
© 2014 British Neuropathological Society
colorectal cancer and neurosurgical resection of BM
between January 1990 and February 2011 were identified from the Neuro-Biobank, Medical University of
Vienna. Only patients with availability of at least one
tissue block containing formalin-fixed and paraffinembedded viable BM tissue for research purposes were eligible for inclusion. Clinical data were retrieved by chart
review, and survival data were obtained from the National
Cancer Registry of Austria and the Austrian Brain Tumor
Registry [10,11].
Diagnosis-specific graded prognostic assessment (DSGPA) was calculated according to previously published
clinical characteristics. DS-GPA for lung cancer included
age (>60, 50–60, <50), Karnofsky performance score
(<70, 70–80, 90–100), status of extracranial metastatic
disease (present, absent) and number of BM (>3, 2–3, 1).
DS-GPA for melanoma and renal cell carcinoma was calculated based on Karnofsky performance score (<70,
70–80, 90–100) and number of BM (>3, 2–3, 1). DS-GPA
for breast cancer included Karnofsky performance score
(<50, 60, 70–80, 90–100), breast cancer subtype (triple
negative, luminal A, HER2, luminal B) and age (>60,
<60). For colorectal cancer, DS-GPA was calculated only
based on Karnofsky performance score (<70, 70, 80, 90,
100) [12]. Prognostic score for SCLC was calculated
according to previously published clinical characteristics
including Karnofsky performance score (<70, ≥70),
number of BM (1–3, ≥4) and status of extracranial disease
(present, absent) [13].
The ethics committee of the Medical University of
Vienna approved the study (Vote 078/2004).
Tissue-based analysis
Immunohistochemistry was performed on full slides by
using an automated horizontal slide-processing system
(AutostainerPlusLink, Dako, Glastrup, Denmark; Ki67)
and a fully automated multi-modal slide-staining system
(Benchmark ULTRA, Ventana, Tuscon, AZ, USA; HIF1alpha, CD34) according to previously published standard protocol [14,15]. Immunohistochemical staining
results were analysed using light microscopy and a counting graticule. For evaluation of Ki67 proliferation index,
area with the highest density of cells showing a specific,
strong nuclear immunohistochemical signal was identified. Within this ‘hot spot’, 500 cells were counted, giving
the percentage of positive cells (0–100%) [16]. HIF-1
alpha index was calculated according to the modified
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Differential role of angiogenesis and tumor cell proliferation in brain metastases
H-score. Here, intensity of the specific, nuclear immunohistochemical signal was defined as follows: 0 = no appreciable staining in the tumour cell nucleus; 1 = barely
detectable staining intensity in the nucleus; 2 = moderate
staining intensity distinctly in the tumour cell nucleus;
and 3 = strong staining intensity of the tumour cell
nucleus. For each intensity group, the fraction of cells
(0–100%) was recorded. By multiplying the intensity of
the nuclear staining and the fraction of cells producing
this particular intensity, the HIF-1 alpha index was calculated producing a total range of 0–300. The MVD was
evaluated by counting the number of vascular structures,
as defined by immunohistochemical staining for CD34,
using a counting graticule with an area of 0.7 mm2 at a
200-fold magnification and within the area of the highest
density (‘hot spot’) [17]. Using the immunohistochemical
staining for CD34, the angiogenic pattern was
semiquantitatively analysed. The angiogenic pattern was
scored by two independent observers to belong to the
‘angiogenic’, the ‘silent’ or the ‘balanced’ angiogenic
pattern. The ‘angiogenic type’ was defined by the predominance of sprouting vessels with multi-layered endothelium as investigated in the CD34 immunohistochemical
staining. In contrast, the ‘silent type’ was defined by the
predominance of vessels with thin, mono-layered
endothelium. Specimens with an equal distribution
between angiogenic and silent type were defined as the
‘balanced type’ [14].
Statistical analysis
Kruskal–Wallis and χ2-test were used to assess group differences as appropriate. Spearman’s rank correlation coefficient was used to evaluate monotone associations
between two continuous variables. A Spearman’s rank
correlation coefficient between 0.7 and 1 (−0.7 to −1) was
considered to indicate a strong correlation, whereas a correlation coefficient of 0.3–0.5 (−0.3 to 0.5) was considered to indicate a very low correlation, and a correlation
coefficient of 0–0.3 (0 to −0.3) was considered to basically
denote no correlation. A two-tailed significance level of
0.05 was applied. Overall survival (OS) was defined from
diagnosis of BM to death or date of last follow-up. Estimation of OS was performed using the Kaplan–Meier product
limit method. Log rank test was used to investigate group
differences. Scale variables were divided in two groups
according to the median in order to analyse the survival
impact in the univariate analysis using the log rank test.
© 2014 British Neuropathological Society
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Therefore, Ki67 proliferation index, MVD and HIF-1 alpha
index were cut at the median in order to define low (below
median) and high (above median) and entered as a
dummy variable in univariate analysis. Variables with
significant univariate results were entered into a
multivariable Cox proportional hazards model. For analysis in the multivariate analysis scale, variables were
entered as such. Due to the exploratory and hypothesisgenerating design of the present study, no adjustment for
multiple testing was applied [18]. All statistical analysis
was performed with statistical package for the social sciences (spss) 20.0 software (SPSS Inc., Chicago, IL, USA).
Results
Patients’ characteristics
Six hundred thirty-nine BM specimens of 639 patients
(336 male, 303 female) with histologically proven BM
were available for this study. Median age at first diagnosis
of BM was 57 years (range 25–82). Primary tumour was
lung cancer in 344/639 (53.8%) patients, breast cancer
in 105/639 (16.4%), melanoma in 67/639 (10.5%),
renal cell carcinoma in 52/639 (8.1%) and colorectal
cancer in 71/639 (11.1%) patients. Table 1 lists the
patients’ characteristics. Matched primary tumour
samples were available in 113/639 (17.7%) patients;
63/113 (55.8) NSCLC; 8/113 (7.1%) SCLC; 19/113
(16.8%) breast cancer; 3/113 (2.7%) melanoma; 8/113
(7.1%) renal cell carcinoma; and 12/113 (10.6%)
colorectal cancer).
Tissue-based findings in BM and corresponding
primary tumours
Examples of immunostaining results for Ki67, CD34 and
HIF-1 alpha are shown in Figure 1. The median Ki67 proliferation index in the entire BM cohort was 39.2% (range
0–97%), the median HIF-1 alpha index was 50 (range
0–300) and the median MVD was 71/0.7 mm2
(range 3–302/0.7 mm2). Predominance of microvascular
sprouting (angiogenic type) was evident in 288/619
(46.5%) evaluable specimens, while 169/619 (27.3%)
presented without signs of angiogenesis (silent type), and
in 162/619 (25.4%), specimens showed an equal distribution between microvascular sprouting and silent
angiogenesis (balanced type).
The MVD showed a significant association with the
vascular pattern, as specimens of the angiogenic type
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A. S. Berghoff et al.
Table 1. Patients’ characteristics
Entire population (n = 639)
Characteristic
Median age at first diagnosis, years (range)
Primary tumour
Lung cancer
NSCLC
SCLC
Breast cancer
Melanoma
Renal cell carcinoma
Colorectal cancer
Stage IV of primary tumour at BM diagnosis
Yes
No
Unknown
Surgery of primary tumour before diagnosis of BM
Yes
No
Unknown
Number of extracranial metastatic sites
0
1
≥2
Unknown
Visceral metastases before diagnosis of BM
Yes
No
Unknown
Lung metastases before diagnosis of BM
yes
no
Unknown
Liver metastases before diagnosis of BM
Yes
No
Unknown
BM first metastatic site/no extracranial metastases
Yes
No
Unknown
Number of chemotherapy lines before diagnosis of BM
0
1
≥2
Unknown
Time from diagnosis of primary tumour until diagnosis of BM, months (range)
Median age at first diagnosis of BM, years (range)
DS-GPA class at diagnosis of BM
I
II
III
IV
unknown
SCLC BM score according to Rades et al.
Group A
Group B
Group C
© 2014 British Neuropathological Society
n
%
55 (20–80)
344
291
53
105
67
52
71
53.8
45.5
8.2
16.4
10.5
8.1
11.1
284
350
5
42.1
57.3
0.8
366
269
4
57.3
42.4
0.6
371
151
116
1
58.2
23.6
18.1
0.2
178
443
18
27.7
69.3
2.8
121
500
18
18.9
78.2
2.8
74
547
18
11.6
85.6
2.8
371
267
1
58.1
41.8
0.2
373
183
74
9
23 (1–299)
57 (25–82)
58.4
28.6
11.5
1.4
114
266
139
32
88
17.8
41.6
21.8
5.0
13.8
4
18
31
7.5
34.0
58.5
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Differential role of angiogenesis and tumor cell proliferation in brain metastases
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Table 1. (Continued)
Entire population (n = 639)
Characteristic
Number of BM at diagnosis of BM
1
2–3
>3
Unknown
Localization of BM
Supratentorial
Infratentorial
Both
Unknown
Status of primary tumour at t diagnosis of BM
No evidence of disease
Partial response
Stable disease
Progressive disease
Synchronous 1st diagnosis of primary tumour and BM
Unknown
First-line treatment for BM
Gamma knife
Chemotherapy
Surgery
Whole brain radiation therapy
Best supportive care
Chemotherapy after diagnosis of BM
Yes
No
Unknown
Alive at last follow-up
Yes
No
Median overall survival from diagnosis of primary tumour, months (range)
Median overall survival from diagnosis of BM, months (range)
n
%
419
158
57
5
65.6
24.7
8.9
0.8
399
141
93
6
62.4
22.1
14.6
1.0
185
22
138
69
220
5
29.0
2.4
21.6
10.8
34.4
0.8
28
3
573
31
4
4.4
0.5
89.7
4.9
0.7
219
394
26
34.3
61.7
4.1
93
546
23 (0–334)
8.0 (0–207)
14.6
85.4
BM, brain metastasis; DS-GPA, diagnosis-specific graded prognostic assessment; NSCLC, non-small cell lung cancer; SCLC, small cell lung cancer.
had higher MVD values compared with specimens with
silent type (P < 0.001; Kruskal–Wallis test). No correlation was observed between Ki67 proliferation index
and MVD (P = 0.154; Spearman correlation coefficient
−0.056). Further, no correlation was observed between
MVD and HIF-1 alpha index (Spearman correlation coefficient 0.107) or between HIF-1 alpha index and Ki67
proliferation index (Spearman correlation coefficient
0.179).
We detected significant differences in MVD and expression of Ki67 and HIF-1 alpha between BM of different
origins. Ki67 proliferation index was highest in colorectal
cancer BM and lowest in renal cell carcinoma BM
(P < 0.001; Kruskal–Wallis test; Figure 2A). MVD was
© 2014 British Neuropathological Society
highest in renal cell carcinoma BM and lowest in melanoma BM (P < 0.001; Kruskal–Wallis test; Figure 2B).
Accordingly, renal cell carcinoma BM had the highest
fraction of specimens with angiogenic sprouting and
melanoma the highest fraction of specimens of the silent
angiogenic subtype (P < 0.001; χ2-test). In line with these
data, HIF-1 alpha index was highest in renal cell carcinoma BM and lowest in melanoma BM (P < 0.001;
Kruskal–Wallis test; Figure 2C).
Comparing MVD and expression of Ki67 and HIF-1
alpha between BM and matched primary tumours, we
found significant differences between tumour sites in
several tumour types (Figure 3). In brief, Ki67 index was
higher in breast cancer BM compared with the matched
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A. S. Berghoff et al.
Figure 1. Examples of immunostaining results. (A and B) Ki67 proliferation index in a primary NSCLC specimen (A) and the matched BM
specimen (B); (C and D) silent angiogenic pattern and low MVD in a primary colorectal cancer specimen (C) and the matched BM specimen
with sprouting angiogenic pattern and high MVD (D); (E and F) low HIF-1 alpha index in a primary NSCLC specimen (E) and the matched
BM specimen (F). Colour figures are available from the authors upon request.
© 2014 British Neuropathological Society
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Differential role of angiogenesis and tumor cell proliferation in brain metastases
Figure 2. Comparison of Ki67 proliferation index (A),
microvascular density (MVD, B) and HIF-1 alpha index (C) in BM of
different primary tumour types.
© 2014 British Neuropathological Society
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Figure 3. Comparison of Ki67 proliferation index (A),
microvascular density (B) and HIF-1 alpha (C) between primary
tumours and matched brain metastases for all tumour types.
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A. S. Berghoff et al.
primary tumours (46.6% vs. 38.9%; P = 0.032; paired
t-test), while MVD was higher in central nervous system
lesions than in the primary tumours in NSCLC (74/
0.7 mm2 vs. 65/0.7 mm2; P = 0.050; paired t-test). Also,
HIF-1 alpha index was higher in BM than in matched
primary tumours in NSCLC (50 vs. 30; P = 0.026; paired
t-test), breast cancer (60 vs. 30; P = 0.041; paired t-test)
and colorectal cancer (70 vs. 20; P = 0.004; paired t-test).
In NSCLC BM, higher Ki67 proliferation index (49.2%
vs. 36.4%; P = 0.002; Mann–Whitney test) and higher
HIF-1 alpha index (80 vs. 60; P = 0.021; Mann–Whitney
test) were observed in patients with squamous compared
with patients with non-squamous NSCLC histology.
However, higher MVD in NSCLC BM was observed in nonsquamous compared with squamous NSCLC histology
(71/0.7 mm2 vs. 63/0.7 mm2; P = 0.038; Mann–Whitney
test).
Survival analyses
Survival analyses in the overall cohort
Clinical parameters In the entire cohort of 639 BM
patients, median OS from diagnosis of BM was 8 months
(range 0–207). The GPA prognostic score showed a statistically significant correlation with OS. Median OS in
patients with class I was 19 months, 10 months in class II,
7 months in class III and 2 months in class IV (P < 0.001;
log rank test; Figure 4A). In SCLC BM patients, the prognostic score according to Rades et al. was applied and
showed significant impact on OS [13]. Median OS in
patients of group A was 1 month, 8 months in group B
patients and 12 months in patients belonging to group C
(P < 0.001; log rank test). Furthermore, the histology of
the primary tumour showed a significant prognostic value
with the longest survival among patients with breast
cancer and renal cell carcinoma, both with a median OS of
11 months, followed by patients with NSCLC (median OS 9
months), SCLC (median OS 10 months), melanoma
(median OS 6 months) and colorectal cancer (median OS
5 months; P = 0.001; log rank test; Figure 4B). Long-term
survival was associated with primary tumour histology as
9/52 (17.3%) patients with renal cell carcinoma compared with 38/344 (11.0%) patients with lung cancer,
12/105 (11.4%) patients with breast cancer, 1/67 (1.5%)
patient with melanoma and 0/71 (0.0%) patients with
colorectal cancer survived longer than 36 months
(P = 0.001; χ2-test).
© 2014 British Neuropathological Society
Tissue-based parameters Patients with high Ki67 proliferation index presented with significantly impaired OS
prognosis compared with patients with low Ki67 proliferation index (7 vs. 11 months; P < 0.001; log rank test;
Figure 4C). In line, long-term survival (>36 months) was
more common among patients with low Ki67 proliferation index (41/322, 12.7%) compared with patients with
high Ki67 proliferation index (19/317, 6.0%). Furthermore, patients with high MVD had an improved OS prognosis compared with patients with low MVD (11 vs. 8
months; P = 0.004; log rank test; Figure 4D). Long-term
survival (>36 months) was more common among patients
with high MVD as 40/317 (12.6%) patients with high
MVD experienced long-term survival compared with
20/322 (6.2%) patients with low MVD (P = 0.005;
χ2-test). However, no impact of angiogenic pattern on OS
was observed as patients with angiogenic, sprouting
pattern presented with a median OS of 10 months compared with 8 months in patients with silent angiogenesis
and 8 months in patient with balanced angiogenesis
(P = 0.256; log rank test). No difference in survival prognosis was observed for patients with high HIF-1 alpha
index (median OS 8 months) compared with patients with
low HIF-1 alpha index (median OS 9 months; P = 0.724;
log rank test).
Survival analyses in DS-GPA groups
Impact of tissue-based parameters was analysed in each
DS-GPA group separately. Here, high Ki67 proliferation
index correlated with unfavourable median OS in patients
with DS-GPA class II (11 vs. 7 months; P = 0.010; log rank
test) and in patients with DS-GPA class III (8 vs. 5 months;
P = 0.017; log rank test). Further, high MVD correlated
with favourable median OS in patients with DS-GPA class I
(13 vs. 22 months; P = 0.010; log rank test) and in
patients with DS-GPA class III (5 vs. 8 months; P = 0.050;
log rank test). High HIF-1 alpha index associated with
unfavourable median OS only in patients with DS-GPA
class IV (2 vs. 11 months; P = 0.005; log rank test).
In multivariate analysis, Ki67 proliferation index
[hazard ratio (HR) 1.007; P = 0.001], MVD (HR 0.997;
P = 0.004) and DS-GPA class (HR 1.530; P < 0.001)
remained significant (Cox regression model).
Survival analyses in tumour subtypes
We correlated Ki67 index, HIF-1 alpha index and MVD
with OS in the sub-cohorts of patients with NSCLC
(n = 291), SCLC (n = 53), breast cancer (n = 105),
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Differential role of angiogenesis and tumor cell proliferation in brain metastases
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Figure 4. Kaplan–Meier plots for overall survival from diagnosis of BM to death according to diagnosis-specific graded prognostic
assessment class (A), histology of the primary tumour (B), the Ki67 proliferation index (C) and microvascular density (D).
© 2014 British Neuropathological Society
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Table 2. Tissue-based findings in brain metastases
Entire cohort (n = 639)
OS in < median
OS in ≥ median
Non-small cell lung cancer (n = 291)
OS in < median
OS in ≥ median
Small cell lung cancer (n = 53)
OS in < median
OS in ≥ median
Breast cancer (n = 105)
OS in < median
OS in ≥ median
Melanoma (n = 67)
OS in < median
OS in ≥ median
Renal cell carcinoma (n = 52)
OS in < median
OS in ≥ median
Colorectal caner (n = 71)
OS in < median
OS in ≥ median
Median ki67
proliferation index
(%), (range)
Median microvascular density/
0.7 mm2 (range)
Angiogenic pattern
Angiogenic (%)
Balanced (%)
Silent (%)
39.2
11*
7*
38.3
11*
7*
55.40
11
8
39.2
12
11
28.8
8
5
17.0
19*
3*
64.0
9
4
71
8*
11*
70
8
11
72
10
11
75
9
13
50
6
7
133
6
15
65
5
6
(3–302)
288/619 (46.5)
10
162/619 (26.2)
8
169/619 (27.3)
8
(7–298)
126/281 (44.8)
9
70/281 (24.9)
9
85/281 (30.2)
8
(16–187)
26/51 (51.0)
11
13/51 (25.5)
7
12/51 (23.5)
12
(7–240)
57/104 (54.8)
11
31/104 (29.8)
16
16/104 (15.4)
11
(3–197)
16/62 (25.8)
8
17/62 (27.4)
6
29/62 (46.8)
7
(34–302)
37/51 (72.5)
15*
11/51(21.6)
3*
3/51 (5.9)
2*
(13–251)
26/70 (37.1)
5
20/70 (28.6)
4
24/70 (34.3)
6
(0–97)
(1–97)
(17–86)
(2–88)
(0–82)
(2–76)
(16–91)
Median HIF-1
alpha index;
(range)
50
9
8
60
11*
7*
60
11
7
50
11
13
10
6
6
120
8
15
50
7
5
(0–300)
(0–270)
(0–180)
(0–230)
(0–160)
(0–300)
(0–180)
*Marks significant (P < 0.05) group differences.
HIF-1 alpha, hypoxia-inducible factor 1 alpha; OS, overall survival.
melanoma (n = 67), renal cell carcinoma (n = 52) and
colorectal cancer (n = 71; Table 2). Significant correlations of these tissue-based parameters with OS from BM
diagnosis were found in NSCLC and renal cell cancer
patients.
NSCLC Patients with low median Ki67 proliferation
index (median OS 11 months) and BM from NSCLC presented with an improved prognosis compared with
patients with high median Ki67 proliferation index
(median OS 7 months; P = 0.001; log rank test;
Figure 5A). Furthermore, patients with low HIF-1 alpha
index (median OS 11 months) and BM from NSCLC survived longer than patients with high HIF-1 alpha
index (median OS 7 months; P = 0.015; log rank test;
Figure 5B).
No differences in Ki67 proliferation index (P = 0.901;
Kruskal–Wallis test), MVD (P = 0.166; Kruskal–Wallis
test) or HIF-1 alpha index (P = 0.140; Kruskal–Wallis test)
according to DS-GPA class were observed in patients with
NSCLC BM.
Further, tissue-based parameters were investigated for
their prognostic impact in each DS-GPA group. Here, low
Ki67 proliferation index correlated with favourable
median OS in patients with DS-GPA class II (12 vs. 6
© 2014 British Neuropathological Society
months: P = 0.002; log rank test) and in patients with
DS-GPA class III (7 vs. 5 months; P = 0.027; log rank test).
Further, low HIF-1 alpha index was a favourable prognostic factor in patients presenting with DS-GPA class I (22 vs.
11 months; P = 0.030; log rank test).
Thus, Ki67 proliferation index, HIF-1 alpha index and
DS-GPA were entered in multivariate analysis. Here, Ki67
proliferation index [HR 1.015; 95% confidence interval
(CI) 1.008–1.022; P < 0.001; Cox regression model] and
DS-GPA (HR 1.879; 95% CI 1.566–2.254; P < 0.001; Cox
regression model) remained as independent prognostic
factors.
Renal cell carcinoma Low median Ki67 proliferation
index correlated with favourable OS in patients with BM
from renal cell carcinoma (median OS 19 vs. 3 months;
P < 0.001; log rank test; Figure 5C). Furthermore, patients
with BM showing angiogenic pattern (median OS 15
months) survived significantly longer compared with
patients with silent angiogenic pattern (median OS 2
months) or with balanced angiogenesis (median OS 3
months: P = 0.002; log rank test; Figure 5D). Thus, Ki67
proliferation index, angiogenic pattern and DS-GPA were
entered in multivariate analysis. Here, Ki67 proliferation
index (HR 1.027; 95% CI 1.007–1.048; P = 0.008, Cox
NAN 2015; 41: e41–e55
Differential role of angiogenesis and tumor cell proliferation in brain metastases
e51
Figure 5. Kaplan–Meier plots for overall survival from diagnosis of BM to death according to Ki67 index (A) and HIF-1 alpha index (B) in
NSCLC patients. Kaplan–Meier plots for overall survival from diagnosis of BM to death according to Ki67 index (C) and angiogenic pattern
(D) in renal cell carcinoma patients.
© 2014 British Neuropathological Society
NAN 2015; 41: e41–e55
e52
A. S. Berghoff et al.
regression model), angiogenic pattern (HR 1.877; 95% CI
1.088–3.236; P = 0.024; Cox regression model) and
DS-GPA (HR 1.956; 96% CI 1.291–3.003; P = 0.002; Cox
regression model) remained as independent prognostic
parameters.
Discussion
In this project, we indicate that BM of the most relevant
solid tumour types typically show signs of prominent
neo-angiogenesis and tumour cell proliferation. However,
we document differences in the expression profiles of
angiogenesis- and hypoxia-related factors between BM of
different cancers and furthermore show that these parameters have distinct prognostic implications between
tumour types. In general, our data underscore the notion
that BM are a heterogeneous group of tumour manifestations, and more consideration should be given to this heterogeneity in the design of research protocols and
ultimately also in the clinical setting [19,20].
Comparing the microvascularization between the different tumour types, we saw the highest MVD and a predominance of angiogenic active vessels in BM of renal cell
carcinoma. Renal cell carcinoma BM were also characterized by the highest expression values of HIF-1 alpha, which
is a known driver of neo-angiogenesis in cancer [21].
Although HIF-1alpha might be only expressed for a short
time upon hypoxic stimuli, it is a widely used surrogate
marker for hypoxic conditions in various cancer types [21–
26]. In renal cell carcinoma, HIF-1 alpha expression has
been shown to be expressed not only under hypoxic but also
under normoxic conditions as a result of oncogenic activation due to the loss of the Von Hippel–Lindau gene [25].
We did not investigate in our study the mechanistic
link between HIF-1 alpha expression and hypoxia or
(epi-)genetic aberrations in BM, and this issue should be
subject to further studies. However, our findings may be of
clinical relevance for patients with BM of renal cell cancer
as they suggest that angiogenesis-targeting agents that are
routinely used for extracranial disease (e.g. VEGF pathway
inhibitors such as sunitinib, pazopanib, bevacizumab) may
also be of therapeutic value for patients with brain metastatic disease [27–29]. Moreover, we demonstrate a strong
and independent prognostic value of angiogenic patterns
and also of the Ki67 tumour cell proliferation index on
patients’ OS from BM diagnosis. In line with our data, both
Ki67 index and microvascularization were repeatedly
described as prognostic factor in extracranial manifesta© 2014 British Neuropathological Society
tions of renal cell carcinoma [30–34]. Pending validation
of our results in independent data sets, incorporation of
these tissue-based parameters into prognostic scores (e.g.
the DS-GPA) may be considered for patients with BM of
renal cell carcinoma in order to provide more accurate
approximation of survival times in the cohort of patients
treated by neurosurgical resection. Of note, current prognostic scores have been shown to predict BM patient survival with inadequate accuracy [35].
In NSCLC, we found significantly higher MVD and HIF-1
alpha indices in BM than in corresponding primary
tumours and an independent prognostic impact of the
Ki67 index on OS from BM diagnosis. These findings corroborate similar results that were elaborated by our group
in a smaller patient cohort [14,36]. Hopefully, future clinical trials on NSCLC patients undergoing resection of BM
will incorporate the Ki67 index into the study protocol to
validate its prognostic value in a prospective manner. Inhibition of neo-angiogenesis has been identified as promising
strategy for prevention and treatment of NSCLC CNS manifestations in preclinical studies [9,19,37,38]. Besides,
some other immunohistochemical markers including the
transcription factors LEF1/TCF4, netrin-1, insulin-like
growth factor 1 or integrins were postulate to correlate
with survival prognosis, further underscoring that tissuebased parameter do add valuable information to the prognostic assessment of BM patients [7,36,39,40]. Indeed,
our findings of higher MVD and HIF1 alpha expression in
BM provide further support for clinical studies on such
approaches.
We did not find prognostic value of tissue-based parameters assessed in this study in patients with BM of breast
cancer, melanoma and colorectal cancer. It must be
acknowledged that our data do not definitely exclude prognostic implications of these parameters in BM of these
tumour types due to the limitations associated with the
retrospective nature of our study and sample size issues
limiting the statistical power. However, our cohorts in these
diagnostic categories are among the largest and best characterized that are available in the literature (n = 105 for
breast cancer, n = 71 for colorectal cancer, n = 67 for melanoma), and moderate to strong prognostic effects should
have been detectable. Nevertheless, further studies, ideally
in larger and prospectively collected patient series, would
certainly be of interest. Interestingly, BM of melanoma
were characterized by the lowest MVD and HIF-1 alpha
values in comparison with the other tumour types. This
finding may be related to prior observations that brain
NAN 2015; 41: e41–e55
Differential role of angiogenesis and tumor cell proliferation in brain metastases
metastatic melanoma BM invade the brain mainly through
vascular co-option without significant induction of neoangiogenesis and again reinforce the need for differentiated
investigation of pathobiological mechanisms in BM of
various cancer types [9,41].
In conclusion, our data argue for differential
pathobiological and clinical relevance of Ki67 index, HIF1alpha index and MVD between primary tumour types in
BM patients. Specifically, we found independent prognostic
value of these tissue-based parameters in patients with BM
of NSCLC and renal cell carcinoma, thus making them
candidate biomarkers in these indications.
Acknowledgements
We thank Irene Leisser, Elisabeth Dirnberger and Bettina
Jesch for excellent technical assistance. This study was
performed within the PhD thesis project of Anna Sophie
Berghoff in the PhD program ‘Clinical Neuroscience
(CLINS)’ at the Medical University Vienna. The costs for
this project were covered by the research budget
of the Medical University of Vienna and the grant
‘Hochschuljubiläumsstiftung der Stadt Wien’ for the
project ‘Klinische Relevanz von Entzündung in
Hirnmetastasen’ (grant number: H-263727/2013).
e53
Karin Dieckmann: data collection, data interpretation,
manuscript writing, approval of final manuscript
version.
Josef Pichler: data collection, data interpretation, manuscript writing, approval of final manuscript version.
Markus Hutterer: data collection, data interpretation,
manuscript writing, approval of final manuscript
version.
Thomas Melchardt: data collection, data interpretation,
manuscript writing, approval of final manuscript
version.
Rupert Bartsch: study design, data collection, data interpretation, manuscript writing, approval of final manuscript version.
Christoph C. Zielinski: study design, data collection, data
interpretation, manuscript writing, approval of final
manuscript version.
Peter Birner: study design, data collection, data interpretation, manuscript writing, approval of final manuscript version.
Matthias Preusser: study design, data collection, data
interpretation, manuscript writing, approval of final
manuscript version.
Conflicts of interest
The authors declare no conflicts of interest.
Author contribution
Anna S. Berghoff: study design, data collection, data interpretation, manuscript writing, approval of final manuscript version.
Aysegül Ilhan-Mutlu: data collection, data interpretation,
manuscript writing, approval of final manuscript
version.
Carina Dinhof: data collection, data interpretation, manuscript writing, approval of final manuscript version.
Manuel Magerle: data collection, data interpretation,
manuscript writing, approval of final manuscript
version.
Monika Hackl: data collection, data interpretation, manuscript writing, approval of final manuscript version.
Georg Widhalm: data collection, data interpretation,
manuscript writing, approval of final manuscript
version.
Johannes A. Hainfellner: data collection, data interpretation, manuscript writing, approval of final manuscript
version.
© 2014 British Neuropathological Society
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Received 11 July 2014
Accepted after revision 22 September 2014
Published online Article Accepted on 24 September 2014
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