Download Transforming growth factor β 2: A predictive marker for breast cancer

Indian Journal of Experimental Biology
Vol. 49, November 2011, pp. 879-887
Transforming growth factor β 2: A predictive marker for breast cancer
Heena Dave1, Sunil Trivedi2*, Manoj Shah3 & Shilin Shukla4
1,2
Receptor & Growth Factor Laboratory, 3Pathology Department, 4Medical Oncology Department,
The Gujarat Cancer & Research Institute, Asarwa, Ahmedabad 380 016, India
Received 18 August 2011; revised 1 September 2011
Dual role of TGF-β signaling in breast tumorigenesis as an inhibitor in early stages and promoter in advanced stages
has been well established and known as TGF-β switch. However, the biological mechanisms needs to be explored. Aim of
the present study was to look for the usefulness of TGF-β2 as a predictive marker for breast cancer and to offer a better
predictability to identify patients likely to benefit from antiTGF-β strategies. Circulatory as well as transcript levels of TGFβ2 were estimated from 118 pretherapeutic breast cancer patients using ELISA and q-PCR with ddCt method. Multifactorial
analysis was performed to correlate the results to clinico-pathological prognosticators and Kaplan-Meier survival analysis
with a median follow-up of 49 months was also evaluated. Circulating TGF-β2 was similar in control and breast cancer
patients. TGF-β2 was significantly upregulated in advanced tumors compared to early tumors. An inverse correlation was
observed between TGF-β2 protein and mRNA; nevertheless both exhibited significant correlations with clinico-pathological
prognosticators. Higher expression of TGF-β2 mRNA was connected to an early relapse in advanced stage than early stage
patients. It is the first report to evaluate circulatory and transcript levels exhibiting TGF-β switch and confirming the utility
of TGF-β2 as an important predictive marker for breast cancer.
Keywords: Breast cancer, mRNA, Prognosis, Serum, Survival, TGF-β2
Growth and differentiation in a multicellular organism
is regulated by a number of physiological networks
including growth factors. Numerous growth factors
and their receptors play an imperative function in
normal mammary gland development, differentiation
and are well implicated in the genesis as well as
progression of breast cancer1. Presence of hormone
receptors like estrogen receptors (ER) – the gold
standard- and progesterone receptors (PR) are
accepted markers of anti-hormonal responsiveness of
breast cancers. Majority of breast tumors are detected
at later stages with aggressive features and a low ER
content2. Such hormone independent tumors are
thought to be growth factor dependent; many
molecules that halt the growth factor mediated signal
transduction are currently under clinical trials.
Transforming growth factor β (TGF-β) signalling is
one of the potential markers amongst them3.
TGF-β was originally reported to induce
anchorage-independent growth of mouse fibroblasts4.
Each of the three hTGF-β isoforms (TGF-β1, TGF-β2
———————
*
Correspondent author
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and TGF-β3) is encoded by a different gene and is
expressed in a tissue-specific manner5. TGF-β
heterodimerizes with receptors (TβRs; having
serine/threonine kinase activity) and lead to the
phosphorylation of SMAD proteins. The complex
then translocates to the nucleus and form functional
transcription complexes in association with DNA
binding partners, coactivators, or corepressors and the
signal proceeds in a cell specific manner6.
Studies reporting the dual role of Transforming
Growth Factor β and related molecules in breast cancer
are known from 1990s (Ref. 7). At early stages of
breast tumorigenesis, transformed epithelial cells are
believed to be sensitive to TGF-β mediated growth
arrest where it may act as anti-tumor promoter.
At advanced stages, resistance to such an action
develops and is proposed to result into loss of growth
inhibitory response that contributes to breast tumor
progression8. Until now, many studies are performed on
TGF-β1 especially at circulatory levels and is shown to
be an independent prognostic marker 9-14.
Very limited studies are conducted to evaluate
circulating TGF-β2 as prognostic and predictive
marker in breast cancer. Increase in circulatory
TGF-β2 was reported with anti-estrogen treatment
880
INDIAN J EXP BIOL, NOVEMBER 2011
and can be used as an early marker for predicting
response15. All three TGF-β isoforms were
detectable by immunohistochemical staining in
breast cancer; however, the role of TGF-β2 remains
unexplored16. A higher tumoral TGF-β2 expression
was seen than the normal tissues17 and in ER
positive tumors. Extracellular TGF-β2 expression
was reported in 91% patients and was associated
with smaller size, low grade and ER18. Secretion
of TGF-β2 was not influenced by tamoxifen
treatment in glioblastoma19. Tumoral TGF-β2 was
undetectable in the gastric tumor tissues also20.
TGF-β2 mRNA was found to be increased with
tamoxifen treatment and can be used as marker of
treatment response in breast cancer21. Preoperative
upregulation of TGF-β2 transcripts was verified in
breast cancer patients that may predict clinical
response independent of ERα and PR status and
TGF-β2 mRNA was demonstrated as a useful
biomarker that discriminates responders from nonresponders in postmenopausal patients22.
There are no reports on the combined expression of
TGF-β2 at mRNA and circulating levels in relation to
their prognostic potential and therefore, the objective
of the present study was to find out the clinical
significance of TGF-β2 as predictive- or surrogatemarker in human breast cancer. Further, the potential
usefulness of TGF-β2 as disease marker or as an
intermediate biomarker of therapeutic efficacy has
been evaluated.
Materials and Methods
Patients and controls—Newly diagnosed 118
breast cancer patients [mean age: 47 years (Range:
25–80 yrs)] were randomly enrolled for this
prospective study. The study was approved by the
Institutional Ethics Committee and informed consent
was obtained from each patient. Subjects with
positive HBsAg and/or HIV and with distant
metastasis were excluded from the study. AJCC
TNM Classification was used for staging23. Forty
two patients (35.6%) had early-and seventy six
(64.4%) patients had advanced- stage disease. The
control group consisted of 87 normal healthy
subjects matched for age, weight and menopausal
status. Predominance of aggressive tumor phenotype
with high metastatic potential was noted since
majority of patients were from middle age group and
postmenopausal; majority of tumors were node
positive, ductal origin, moderate and poor
differentiation, absence of lymphatic and vascular
permeation and presence of lymphocytic infiltration
(Table 1). Disease progress charts were maintained
at the hospital and updated every 3 months. The
median follow-up of the patients was 49 months
(Range 6–92 months). Cut-off levels for both
circulating and transcript were obtained with ROC
analysis; deciphered into positivity or negativity and
employed both for Relapse free survival (RFS) and
Overall survival (OS) analysis. A total of 43.2%
(51/118) patients relapsed during the study
from which 23.5% (12/51) were of early stage and
76.5% (29/51) were of advanced stage. Moreover,
16.9% (20/118) patients died of which 25.0%
(5/20) had early stage and 75.0% (15/20) had
advanced disease.
Samples and collection—Circulating (N=117) as
well as transcript levels (N=118) of TGF-β2 were
measured from the same set of patients. Pretherapeutic
blood samples were collected prior to surgery
[Modified radical mastectomy (MRM)] from all
patients. Samples were collected in gel clot activated
Table 1—Patient and tumor characteristics
Parameter
Age (Years)
Total
patients
≤ 40
41 – 60
>60
Early
Advanced
N (%)
N (%)
N (%)
28(23.73) 11(26.19) 17(22.37)
80(67.80) 28(66.67) 52(68.42)
10(8.47) 03(7.14) 07(9.21)
Menopausal
status
Premenopausal 47(39.83) 16(38.09) 31(40.79)
Perimenopausal 19(16.10) 03(7.14) 16(21.05)
Postmenopausal 52(44.07) 23(54.76) 29(38.16)
Nodal status
Node Negative
Node positive
53(44.92) 38(90.48) 15(19.74)
65(55.08) 04(9.52) 61(80.26)
Ductal
Carcinoma
Lobular
Carcinoma
Others
101(85.59) 35(83.33) 66(86.84)
Histologic
type
Histologic
grade
04(3.39)
02(4.76)
02(2.63)
13(11.02) 05(11.90) 08(10.52)
Well
18(15.25) 11(26.19) 07(9.21)
Differentiation
Moderate+Poor 100(84.75) 31(73.81) 69(90.79)
Differentiation
Lymphatic
permeation
Present
Absent
56(47.46) 09(21.43) 47(61.84)
62(52.54) 33(78.57) 29(38.16)
Vascular
permeation
Present
Absent
04(3.39) 01(2.38) 03(3.95)
114(96.61) 41(97.62) 73(96.05)
Lymphocytic
infiltration
Present
Absent
104(88.14) 35(83.33) 69(90.79)
14(11.86) 07(16.67) 07(9.21)
N=Number of patients
DAVE et al.: TGF-β2 IN BREAST CANCER PATIENTS
vacutainer tubes and allowed to clot for 30 min at room
temperature. Serum was separated by centrifugation at
3000 rpm for 15 min, aliquoted and stored at -70°C
until analysis. Breast tissues were collected from the
patients during surgery. Synchronous tissues (tumor
and adjacent normal tissues) were selected by the
pathologist and the specimens with more than 90%
tumor cells were considered as malignant. The tissues
were immediately snap-frozen, pulverized and
maintained in liquid nitrogen till assayed. Histology
was reviewed by the same pathologist to avoid
individual bias.
Quantitation of TGF-β2—Circulating TGF-β2 was
estimated using sandwich ELISA (Quantikine, R & D
systems, USA) kits with manufacturer’s protocol.
Active TGF-β2 was measured after in vitro acid
activation by 1N HCl incubated for 10 min at room
temperature. Neutralization was done by 1.2N
NaOH/0.5M HEPES and assayed after recommended
dilution. Absorbance was measured at 450 nm with
pathlength and wavelength correction using Multiskan
spectrum (ThermoLabsystems, Finland). Each
measurement was performed in duplicate.
Relative quantitation by Real time reverse
transcriptase polymerase chain reaction (Real time
RT-PCR) of TGF-β2—Total RNA was extracted
using RNease Tissue Mini Kit (Qiagen) according to
manufacturer’s instructions. Briefly, 50 mg of tumor
tissues and 100 mg of adjacent normal tissues were
taken for the RNA isolation for each sample. DNAse
digestion was performed with RNAse free-DNAse set
(Qiagen) to obtain a pure yield. RNA was dissolved in
PCR grade water and stored at -70°C. RNA was
quantified with A260 nm/A280 nm ratios in the range
of 1.7 – 2.1. The purity of RNA was checked on 1%
FA gels and visualized on Gel Doc XR+ system
(BioRad, USA). cDNA was synthesized using high
capacity cDNA archive kit (Applied Biosystems,
USA) for reverse transcription. Total 5 µg RNA in a
reaction volume of 50 µl for each sample was reverse
transcribed according to the manufacturer’s
instructions. Real time florescence detection was used
with FAM dye labelled TaqMan Probes (Applied
Biosystems, USA) for the expression of the target
gene. Universal 40 cycles run protocol was used as
per manufacturer’s advice using ABI 7000 sequence
detection system. Probe for TGF-β2 transcript
(Hs00234244_m1; ABI, USA) was used which
detected in exon 7. Values obtained for the
target gene was normalized to the expression of
881
housekeeping gene GAPDH (glyceraldehyde 3phosphate dehydrogenase) (Hs99999905_m1; ABI,
USA) using ddCt method and respective adjacent
non-neoplastic tissue for each tumor was used as
calibrator. The relative gene expression was evaluated
as mean fold change.
Statistical analysis—SPSS 13.0 software was used
for statistical analysis. Receiver operative curve
(ROC) was used to establish the cut off between
controls and patients. Both parametric (Mean ± SE,
ANOVA including the post-hoc test) and nonparametric [positive {+ve; >cut-off}, negative {-ve;
<cut-off}, chi-square test, Fischer’s exact test]
statistics was used to establish the correlation of
TGF-β2 with clinicopathologic prognosticators and to
evaluate it as a biomarker. Survival analysis was done
using Kaplan Meier survival method. P value < 0.05
was considered to be statistically significant.
Results
Circulatory TGF-β2 protein by ELISA was
detected in all the sera. TGF-β2 mRNA was also
quantitated by reverse transcription and real time PCR
in tumors as well as adjacent normal breast tissues
from all patients.
Circulatory TGF-B2 and its correlation with
clinico-pathological prognosticators—TGF-β2 (pg/ml)
was detectable in all patients with a range from 0 to
870.42 pg/ml [Median; 239.52 pg/ml]. Controls and
patients did not differ significantly. In controls (N=87),
the mean value of TGF-β2 was 260.2±15.4 pg/ml.
Higher TGF-β2 levels were seen in advanced stage
patients [N=75; (Mean±SE: 254.4±13.3pg/ml)] than
early stage [N=42; (Mean±SE: 244.5±24.5 pg/ml)].
Receiver operative curve analysis showed Area under
curve (AUC ) of 0.529 and the cut-off was
250.91pg/ml that showed a similar distribution between
two populations. The sensitivity and specificity was
88.89% and 20.51% respectively. Moreover, Positive
predictive value (PPV) was 52.80% and Negative
predictive value (NPV) was 64.90% (Fig. 1). ROC
analysis also revealed that circulatory serum TGF-β2
was no different in controls and patients.
In early stage young patients (<40years), TGF-β2
was lower as compared to advanced stage patients. In
advanced stage patients, TGF-β2 was higher in
perimenopausal-than premenopausal-patients. TGFβ2 exhibited an inverse correlation with menopausal
status in advanced stage patients. The distribution of
node positivity was significantly non-uniform in the
INDIAN J EXP BIOL, NOVEMBER 2011
882
study [Chi-square=51.60; p=0.0001]. It was observed
that 90.5% (38/42) early stage patients were node
negative whereas in advanced stage patients, 80.0%
(60/75) were node positive. The Odds ratio was
38.00 (10.64 – 149.68) and relative risk was 4.52
(2.85 – 7.19). Thus, nodal status evidently emerged as
an independent prognosticator (Data not shown).
Fig.1—Receiver operative curve (ROC) of circulating TGF-β2
between controls (N=87) and breast cancer patients (N=118).
TGF-β2 positivity and TGF-β2 negativity both
exhibited significantly dissimilar distribution amongst
the nodal subgroups and between early and advanced
stage tumors.
A lowest level of TGF-β2 was seen in lobular
carcinomas than ductal and others histologic types
that could not reach statistical significance. TGF-β2
was lower in tumors with moderate + poor
differentiation and was dissimilarly distributed in
different histologic grades. A significant difference in
distribution was observed amongst different histologic
grades [Chi-square:4.653; p=0.031] (Data not shown).
However, in the advanced stage group, TGF-β2
showed an inverse correlation [r=-0.240; p=0.038]. In
advanced stage patients, TGF-β2 negativity was
higher in patients with lymphatic permeation. The
same was true for negativity in which dissimilar
distribution was observed between early and
advanced stages. TGF-β2 was higher in tumors with
vascular permeation than without. Incidence of TGFβ2 was different in both these groups. TGF-β2
showed significantly inverse correlation with vascular
permeation amongst which advanced stage patients
[r=-0.269; p=0.020]. TGF-β2 levels were higher in the
tumors with lymphocytic infiltration of tumors than
the tumors without that could not reach statistical
significance (Table 2).
Table 2—Circulating TGF-β2 and its correlation with the clinicopathologic prognosticators
[Values are mean ± SE of TGF-β2 in pg/ml]
Parameter
Age (yrs)
Menopausal status
Nodal status
Histologic type
Histologic grade
Lymphatic permeation
Vascular permeation
Lymphocytic
infiltration
Parametric statistics
0-40
41-60
>60
Premenopausal
Perimenopausal
Postmenopausal
Node negative
Node positive
Ductal Carcinoma
Lobular Carcinoma
Others
Well Differentiation
Moderate+Poor
Differentiation
Present
Absent
Present
Absent
Present
Absent
Non-parametric statistics
Early
mean±SE
202.9±17.2 a
261.4±35.4
238.7±70.3
231.9±021.0
327.4±271.5
242.9±031.3
231.8±020.9
364.4±173.1
246.4±28.1
165.1±101.9
262.4±56.5
265.4±68.2
237.0±23.7
Advanced
mean±SE
266.7±17.4a
249.7±17.7
261.8±43.7
285.2±18.5b
219.5±22.6b
240.3±25.6
262.0±31.4
252.6±14.8
252.1±14.8
187.9±18.0
295.6±27.0
309.6±20.5
248.8±14.4
Early†
+ve
02
14
02
06
01
11
16d
02d
15
01
02
05
13
-ve
09
14
01
11
02
11
22e
02e
20
01
03
06
18
Advanced†
+ve
-ve
10
06
10
32
05
02
19
12
05
11
11
17
08d
07e
27d
33e
30
36
00
02
05
02
06f
01f
29f
39f
268.5±71.0
236.9±24.1
205.9±0.04
246.4±25.8
234.6±26.4
293.6±67.0
251.2±16.5
259.9±22.9
389.9±64.4c
246.8±13.2c
247.7±13.7
311.2±48.4
03g
15g
00
18
14
04
07h
17h
02
22
21
03
22g
13g
04i
31i
29
06
† =Number of patients; aP=0.019; bP=0.0366; cP=0.015; dP=0.000005; eP=0.00001; fP=0.045; gP=0.0036; hP=0.049; iP=0.043
25h
15h
00i
40i
38
02
DAVE et al.: TGF-β2 IN BREAST CANCER PATIENTS
Circulatory TGF-B2 and relapse free survival and
overall survival—Breast cancer patients with
circulating TGF-β2 above cut-off [>250.91pg/ml]
relapsed later (45.3%) as compared to the patients
with levels below cut-off (40.6%). TGF-β2 showed no
significant association between the patients who died
and who did not. No differences were noted between
early and advanced stage patients. A similar trend was
observed for RFS in the total cohort and also in the
early and advanced stage patients.
Tumoral expression of TGF-B2 and its correlation
with clinicopathological prognosticators—TGF-β2
transcript levels were expressed as mean fold change
and were evaluated as up- and or down-regulation
(obtained with ddCt method). In the total cohort, 1.59
fold upregulation of TGF-β2 was seen using GAPDH
as housekeeping gene and adjacent normal tissues
from the same patient as calibrator. Subsequently, the
data was grouped according to disease stage to
evaluate the changes during disease progression from
early to advanced stage disease. Elevation in the
upregulation was seen in advanced stage (1.74 fold)
than early stage (1.30 fold); hence showing increase
with disease progression.
Early and advanced stage patients were further
divided according to the upregulation and
downregulation with an aim to correlate the up and/or
downregulation with the disease aggressiveness and
to find out their relation with the clinicopathologic
prognosticators. Upregulation of TGF-β2 was noted
in 47.6% early stage patients (2.33 fold) as compared
to 39.5% advanced stage patients (3.79 fold); thus, a
1.46 fold increase in upregulation was seen in
advanced stage breast cancer patients as compared
to early stage. As opposed to that, TGF-β2
downregulation was evident in 52.4% early stage
patients (2.65 fold) and 60.5% advanced stage
patients (2.42 fold). Thus, a similar downregulation
was seen between early- and advanced-stage disease.
Taken together, these findings provide an evidence of
a ‘switch’ for this TGFβ isoform also.
TGF-β2 showed a higher upregulation in all three
age groups in advanced stage patients than early
stage. A statistically significant linear correlation was
observed in the early stage patients with upregulation
of TGF-β2 in all age groups [r=+0.464; p=0.040].
TGF-β2 transcript levels were significantly increased
in the advanced stage postmenopausal patients than
early stage. A significant nonuniform distribution
of TGF-β2 was observed between early-versus
883
advanced-stage tumors in both up- and downregulation. TGF-β2 transcript was also significantly
upregulated in node negative patients as compared to
node positive patients in early stage tumors. In node
positive patients, a significant elevation in
upregulation of TGF-β2 transcript was observed in
advanced stage tumors as compared to early stage
tumors. The upregulation of TGF-β2 demonstrated a
significant inverse correlation in different histologic
types in the early stage patients [r=+0.480; p=0.028].
Amongst the histologic grades, transcript levels also
exhibited a nonuniform distribution in early and
advanced stage patients. A significant non-uniform
distribution of TGF-β2 transcript was seen between
early and advanced stage tumors in all subgroups of
lymphatic permeation. An increased upregulation of
TGFβ2 in the tumors without lymphatic permeation
within advanced tumors was seen as compared to
early tumors. No differences in TGF-β2 expression
were seen amongst the tumors with or without
vascular permeation. A higher expression of TGF-β2
was also seen amongst the tumors with lymphocytic
infiltration than without lymphocytic infiltration.
Lower expression of TGF-β2 transcript was seen in
early stage patients than advanced stage (Table 3).
Transcript levels of TGF-B2 and relapse free
survival and overall survival—Patients with higher
TGFβ2expression had a significantly higher
recurrence rate in advanced stage patients [18/23
(78.3%)] as compared to early stage [5/23 (21.7%)]
(Fig. 2). Such differences were not evident with the
downregulation of the transcript even though the
incidence of relapse was higher in advanced tumors.
Similarly, the overall survival of advanced stage
patients (80%) was found to be reduced than early
stage. The finding however, was not statistically
significant probably due to the smaller number of
patients (Fig. 3).
Thus, circulatory TGF-β2 protein as well as
TGF-β2 mRNA levels correlated with almost all the
clinicopathological parameters and unveiled its utility
as prognostic marker. Moreover, both the circulatory
levels of TGFB2 protein and tumoral TGFB2
transcript expression were evaluated from the same
set of patients. A trend of inverse correlation was also
observed between the circulatory and transcript levels
[r=-0.067; p=0.633]. TGF-β2 also demonstrated a
correlation with survival obviating its utility as a
predictive marker.
884
INDIAN J EXP BIOL, NOVEMBER 2011
Table 3—TGF-β2 mRNA and its correlation with clinicopathologic prognosticators
Early
Advanced
UP
Down
UP
Down
N
MFC
N
MFC
N
MFC
N
MFC
Age (yrs)
0-40
07
1.74
04
2.55
06
3.66
11
2.71
41-60
13
2.64
15
2.83
23
3.90
29
2.36
>60
00
03
2.08
01
2.03
06
2.30
Menopausal status
Premenopausal
09
2.56
07
2.91
10
4.17
21
2.80
Perimenopausal
01
2.21
02
5.20
08
2.77
08
2.65
Postmenopausal
10
2.12a
13
2.35
12
4.14a
17
2.01
Nodal status
Node negative
18b
2.38b
20g
2.59
08d
3.67
07g
1.96
d
~c
c
d
c
Node positive
02
1.81
02
9.51
22
3.83
39g
2.53
Histologic type
Ductal carcinoma
15
2.58
20
2.45
26
3.64
40
2.42
Lobular carcinoma
01
1.10
01
8.47
01
1.35
01
1.75
Others
04
1.69
01
34.48
03
5.90
05
2.71
Histologic grade
Well differentiation
07e
1.98
04
2.08
02e
1.91
05
2.65
e
Moderate + poor differentiation
13
2.51
18
2.82
28e
3.92
41
2.40
Lymphatic permeation
Present
04f
3.19
05h
2.34
21f
3.56
26h
2.41
Absent
16f
2.11i
17h
2.75
09f
4.33i
20h
2.44
Vascular
Present
00
01
6.66
00
03
2.21
permeation
Absent
20
2.33
21
2.57
30
3.79
43
2.44
Lymphocytic infiltration Present
16
2.49
19
2.99k
29
3.83
40
2.44
Absent
04
1.65
03
1.53jk
01
2.43
06
2.30j
Parameter
a
P=0.0027; bP=0.023; cP=0.050; dP=0.0001; eP=0.020; fP=0.0015; gP=0.016; hP=0.018; iP=0.016; jP=0.05; kP=0.026;
N=Number of patients; MFC= Mean fold change
Fig.2—TGF-β2 mRNA upregulation and relapse free survival
between early and advanced breast cancer patients.
Fig.3—TGF-β2 mRNA upregulation and overall survival of early
and advanced breast cancer patients.
Discussion
The current study evaluated usefulness of TGF-β2
as a predictive and prognostic marker in breast cancer
at circulatory as well as transcript levels from the
same set of patients. TGF-β2 was measured by ELISA
from serum and mRNA was estimated with Real Time
PCR. The levels were also correlated to the known
clinicopathological parameters and survival. ROC
analysis yielded a high sensitivity (88.89%) and a high
negative predictive value (64.90%) announcing its likely
utility as a reliable biomarker discriminating the
potential ‘benefactors’. Higher circulating was
connected to TGFβ2 positivity, non-premenopausal
status, infiltrating ductal carcinoma, higher histologic
grade, presence of vascular permeation, presence of
lymphocytic infiltration of the tumors and its connection
to a longer RFS and announce its likely use as a maker
of favourable prognosis. A higher upregulation of
TGFβ2 expression in advanced stage tumors, a similar
down regulation between early- and advanced-tumors,
an upregulated transcript in early stage node negative
tumors, an inverse correlation of transcript with
histologic type, and a non-uniform distribution between
early and advanced tumors and association of higher
transcript levels to RFS in advanced tumors announces it
to be a marker of worse prognosis.
These contradictory inferences are well explained
by an inverse correlation between TGFβ2 protein and
DAVE et al.: TGF-β2 IN BREAST CANCER PATIENTS
transcript levels. Thus, it may be inferred that TGFβ2
actin a cell-and tissue-specific manner and is
detectable both at protein and transcript levels.
Further, higher circulatory levels are connected to a
favourable predictive marker and higher tissue
transcript levels may be inferred as a marker of
unfavourable prognosis. This is the first report on a
large cohort that correlated TGF-β2 with relapse free
and overall survival.
Since TGF-β1 is believed to be a representative of
the signaling axis molecules, it has been evaluated in
many studies and the levels have been compared to
clinical parameters, survival and treatment response9-13.
Earlier, the prognostic utility of TGF-β1 in breast
cancer patients has been reported and the levels were
compared with clinical parameters and survival and
found that TGF-β1 may be useful marker for
prognosis of breast cancer14. It was hypothesized that
TGF-β2 may also have a challenging role as
predictive and prognostic biomarker. The present
study was conducted to demonstrate the usefulness of
TGF-β2 at genotypic and phenotypic levels to know
on the differential expression pattern between early
and advanced stage disease.
TGF-β2 overexpression was seen in MVLN/CL6.7
cells and VP229/VP267 cells. These original cell lines
serve as valuable models of cross-resistance to
tamoxifen (partial agonist) and fulvestrant (pure
antiestrogen)24. Results also showed a significant
overexpression of TGF-β2 in samples from ERpositive breast cancer patients who had relapse after
tamoxifen treatment as compared to samples from
patients who did not. Further, TGF-β2 overexpression
was also correlated with a shorter relapse free
survival. Similarly, it was evaluated that the
upregulation of TGF-β2 performed with QRT-PCR
correlated with a shorter disease free survival.
Usefulness of TGF-β2 and its receptors was first
established in early breast carcinogenesis with studies
performed on Human mammary epithelial cells
(HMECs)25. It was found that these molecules were
suppressed through histone modifications and TGFbeta signalling pathway emerged to be a novel target
for gene activation by epigenetic therapy. Likewise,
we have also found TGF-β2 to be a promising
predictive marker both in early as well as advanced
breast cancer since it had a correlation with almost all
clinical parameters and survival.
Buck et al.26 revealed a significant antiproliferative
activity of two tamoxifen metabolites (4hydroxytamoxifen and N-desmethyl-4-hydroxytamoxifen)
885
in human breast cancer cells (MCF-7 and T47D).
Induction of TGF-β2 and TβRII was evaluated with
quantitative RT-PCR in these cells exposed to these
metabolites. The authors advocated use of these two
molecules as specific and sensitive biomarkers for the
antiestrogenic activity of tamoxifen metabolites in
breast cancer. The same group demonstrated an
enhanced TGF-β2 protein expression27,28; due to a
polymorphism in TGF-β2 promoter that was
associated to lymph node metastasis in breast cancer
patients. Thus, they pointed towards a pro-invasive
and pro-metastatic role of TGF-β2 similar to our
study. However, the present study was performed on
breast cancer patients that estimated TGF-β2
expression in vivo pointing towards its utility as
biomarker similar to in vitro studies.
Figueroa et al.18 found expression of extracellularTGF-β2 in 91% tumors using immunohistochemistry
and tissues microarray. They found it to be
associated with favorable pathological prognostic
variables like small size and low grade. In addition,
they found a similar association in both ER positiveand negative tumors. In the present study the
circulatory levels of TGF-β2 protein has been
determined which showed an association with
majority of pathological variables. Moreover, TGFβ2 up-regulation was also evident that was related
to clinical prognosticators and survival. TGF-β2
and other ligands were evaluated in breast
tumorigenesis17 The study determined the tumoral
mRNA expression as well as the protein levels from
25 breast cancer tissue samples and adjacent normal
tissues, and correlated them to clinicopathological
features. Results showed a higher TGF-β2 at both
the levels in tumors as compared to their normal
counterparts and a strong hormonal influence of ER
and PR. However, the study did not find any
correlation with patients’ age and menopausal
status. A similar tumoral up-regulation of TGF-β2
mRNA and a significant correlation in postmenopausal breast cancer patients and stage was
seen in this study. Earlier study however, did not
mention on TGF-β2 protein levels. The present
study has successfully assessed the circulating
TGF-β2 levels and shown its relationship with
clinicopathological parameters.
Plasma TGF-β2 levels were measured in a study15
on only 20 breast cancer patients and 7 controls. A
significant elevation of TGF-β2 was seen in 10/13
patients and no change in samples collected during
886
INDIAN J EXP BIOL, NOVEMBER 2011
tamoxifen treatment. In addition, in another study
performed on 10 breast cancer patients, the same
group22 reported the presence of TGF-β2 mRNA in all
specimens. In addition, they observed an increase in
its expression in 7/10 cases during tamoxifen
treatment and suggested the potential utility of TGFβ2 in prediction of clinical response independent of
ERα/PR status in some cases. Similarly, the current
study provides evidence of the utility of TGF-β2 as a
predictive marker in a large cohort of 118 patients
with its correlation to clinical, pathologic criteria
and survival. TGF-β2 plasma levels have also
been explored in the prediction of tamoxifen
responsiveness in glioblastoma patients on a daily
dose of 200 mg. It was concluded that the clinical
response to tamoxifen is not reflected by changes
of plasma TGF-β2 despite its elevated production
in vitro by glioblastoma cells19. Correlation of
circulating TGF-β2 with resistance to antihormonal
treatment has not been reported in a large cohort of
breast cancer patients and therefore, needs to be
analysed in future.
Recent studies have successfully established the
importance of TGF-β2 for the administration of
antiTGF-β2 strategies. However, implication of
such therapy is currently indicated in glioblastoma
and pancreatic cancers. Antisense phosphorothioate
oligodeoxynucleotide trabedersen (AP 12009), a
compound designed for the specific inhibition of
TGF-β2 biosynthesis is currently under a phase III
trial in glioblastoma29 (antisense pharma). Increased
TGF-β2 levels in serum or tumor tissue of patients
with pancreatic cancer have been reported to be
associated with the poor prognosis and hence
inhibition of TGF-β2 synthesis via the antisense
oligonucleotide trabedersen (AP 12009) is
suggested to be a promising approach30,31. Due to
the benefits of antiTGF-β2 strategy, its use in breast
cancer has been envisaged and attempts are made
to find out the best subset that may benefit from
such therapies.
In conclusion, the current study performed on a
large cohort of patients provide the first evidence of
the predictive potential of circulating as well as
mRNA levels of TGF-β2 in human breast cancer.
The differences in TGF-β2 expression pattern
between early-and advanced-stage tumors revealed
existence of TGF-β switch. Moreover, results of the
present study provides a way to stamp a subset of
patients likely to benefit from antiTGF-β strategies.
Acknowledgement
The study was supported by the funding from
Indian Council of Medical Research, India (IndoGerman project) and Gujarat Cancer Society, India.
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