Prognostic significance of c-Met in breast cancer: a meta-analysis of 6010 cases
Yan et al. Diagnostic Pathology
Prognostic significance of c-Met in breast cancer: a meta-analysis of 6010 cases
Shunchao Yan 0
Xin Jiao 1
Huawei Zou 0
Kai Li 0
0 Department of Oncology, Shengjing Hospital of China Medical University , Shenyang 110022 , China
1 Department of Respiratory Medicine, Shenyang Chest Hospital , Shenyang 110044 , China
Background: The prognostic value of c-Met in breast cancer remains controversial. A meta-analysis of the impact of c-Met in breast cancer was performed by searching published data. Methods: Published studies analyzing overall survival (OS) or relapse free survival (RFS) according to c-Met expression were searched. The principal outcome measures were hazard ratios (HRs) for RFS or OS according to c-Met expression. Combined HRs were calculated using fixed- or random- effects models according to the heterogeneity. Results: Twenty-one studies involving 6,010 patients met our selection criteria. The impact of c-Met on RFS and OS was investigated in 12 and 17 studies, respectively. The meta-analysis results showed that c-Met overexpression significantly predicted poor RFS and OS in unselected breast cancer. Subgroup analysis indicated that c-Met overexpression was correlated with poor RFS and OS in Western patients, but was not associated with RFS or OS in Asian patients. C-Met was associated with poor OS in lymph node negative breast cancer and with poor RFS in hormone-receptor positive and triple negative breast cancer, but was not associated with prognosis in human epidermal growth factor receptor (HER)-2 positive breast cancer. Conclusions: C-Met overexpression is an adverse prognostic marker in breast cancer, except among Asian and HER-2 positive patients.
c-Met; Breast cancer; Meta-analysis; Prognosis
Breast cancer is the most common cancer among
women worldwide . The clinical application of
targeted therapies, such as tamoxifen and trastuzumab, has
decreased the mortality of breast cancer in recent years.
However, epidemiological studies show that more than
400,000 patients worldwide die from breast cancer each
year . Breast cancer is a heterogeneous disease that
has been classified into five molecular subtypes: luminal
A, luminal B, human epidermal growth factor receptor-2
(HER-2) overexpressing, basal-like, and normal-like .
Current therapeutic regimens for breast cancer are
designed according to clinical pathological factors and
molecular typing. However, patients with the same clinical
stage and molecular type often display markedly different
treatment responses and overall outcomes, which lead to
treatment failure [4–7]. Therefore, the identification of
new prognostic factors and potential therapeutic targets is
necessary to improve individual treatment strategies.
The tyrosine kinase c-Met, a key regulator of invasive
growth, is overexpressed in certain aggressive cancer cells
. c-Met, also called MET and hepatocyte growth factor
receptor (HGFR), is a plasma membrane protein that
transduces signals from the extracellular matrix to the
cytoplasm and is activated by binding to HGF . c-Met
is involved in uncontrolled survival, growth, angiogenesis
and metastasis of cancer cells . Crizotinib, a dual
tyrosine kinase inhibitor of ALK and c-Met kinases, has
shown promising results in the treatment of lung
adenocarcinoma . Tivantinib, a c-Met inhibitor is being
tested in patients with MET-high hepatocellular
carcinoma in an ongoing Phase III clinical trial . c-Met was
shown to be involved in the development of herceptin and
endocrine therapy resistance in breast cancer [13, 14].
However, no evidence-based clinical data are available for
c-Met inhibitors in breast cancer treatment. Despite the
fact that the prognostic role of c-Met in breast cancer has
been discussed since the 1990s [15, 16], there is no
consensus on its impact. Some studies suggest that c-Met is a
stronger prognostic indicator of poor prognosis than
traditional markers such as Her2/neu and epidermal growth
factor receptor (EGFR) [17–19], whereas others show no
statistically significant relation between c-Met and
prognosis in breast cancer [20, 21]. In recent years, c-Met was
reported to be associated with favorable prognosis in
breast cancer patients [22, 23]. Therefore, systematic
studies are necessary to obtain high level evidence-based
results of the prognostic value of c-Met for the identification
of patients who would benefit from c-Met targeted
therapy and to guide future clinical trials.
In the present study, we enrolled and combined all
eligible published studies analyzing the relationship
between c-Met expression and relapse free survival (RFS)
or overall survival (OS) in breast cancer to clarify the
relationship between c-Met expression and prognosis in
breast cancer. c-Met plays a critical role in early-stage
invasion of cancer cells , and crosstalk of c-Met
signaling pathways with estrogen receptor (ER) and HER-2
signaling pathways has been reported [13, 25]. To
validate the prognostic role of c-Met in different subtypes
breast cancer, we performed a subgroup analysis in
lymph node negative and different molecular subtypes of
We searched the electronic databases PubMed, Embase,
and the Chinese Biomedical Literature database (CBM)
(last search updated in January 1, 2015) by using the
keywords “breast cancer”, “hepatocyte growth factor
receptor”, “HGFR”, “c-Met”, and “prognosis”. The titles and
abstracts of the studies were firstly scanned to exclude all
irrelevant papers. Then, the final inclusion of studies was
determined by reading the full text of the remaining
articles. The citation lists of all retrieved articles were scanned
to identify other potentially relevant reports.
The search results were screened according to specific
inclusion and exclusion criteria as follows. Inclusion
criteria: (1) research limited to human primary breast
cancer; (2) the study was published in English or Chinese;
(3) inclusion of female patients; (4) evaluation of survival
information, such as RFS, OS, according to c-Met
expression; (5) the study provided the hazard ratios (HRs)
and 95 % confidence intervals (CIs), or data that could
be used to calculate the HRs and 95 % CIs, or Kaplan–
Meier survival curves that provided sufficient data to
extract HRs and 95 % CIs; (6) peer-reviewed and published
original articles. Exclusion criteria: (1) no data on
survival, or inability to calculate the hazard ratios of RFS
and OS based on the data provided; (2) letters to editor,
reviews and articles published in a book. If patients were
enrolled from the same institutions during the same
period, the most recently published data were included
in the study.
Two reviewers (Yan SC and Jiao X) performed the
search and assessed the studies independently, and the
inclusion of a study was decided by consensus. The
following items were recorded from each study: the first
author’s name, year of publication, language, cohort size,
assessment methods of c-Met expression, type of
patients, hazard ratio (HR) of OS and/or RFS. The studies
were assessed for quality using REMARK (reporting
recommendations for tumor MARKer prognostic studies)
, and the definitions of the 18 items for reporting
study quality provided by Chen et al. .
HRs with 95 % CIs were combined to determine the
effective value. If data on HRs and 95 % CIs were not
provided directly, the published data and Kaplan-Meier
survival curves were used to calculate the HR according
to the methods described by Parmaret et al.  and
Tierney et al. . By convention, an observed HR >1
implied a worse survival for the group with c-Met
overexpression. The χ2-square test was used to assess
heterogeneity. A P-value < 0.05 was considered significant. If
the test of heterogeneity was significant, a combined HR
was calculated using the random-effects model;
otherwise, the fixed-effects model was used. Engauge Digitizer
version 2.11 (free software downloaded from
http://sourceforge.net) was used to extract data from Kaplan–Meier
curves. Data combining was performed using RevMan
version 5.2 (free software downloaded from http://
www.cochrane.org). Begg’s tests were used to assess
publication bias. Probable significant publication bias was
considered at P < 0.05. In cases of publication bias, the
combined estimate was recalculated after imputation from
the asymmetry of the funnel plot of the number of
“missing” studies, a method known as “trim and fill”. Begg tests
and “trim and fill” were performed using StataSE12.0
(Stata Corp LP, College Station, Texas, USA).
because they were irrelevant to this study. Three studies
were performed in the same institution during the same
period; therefore, the most recent study was included
and the remaining two were excluded. Nine articles did
not provide HRs and the survival data was not sufficient
to calculate HRs (validated data unavailable for
extraction). Finally, there were 21 eligible studies published
between 1991 and 2014 that satisfied the criteria for our
meta-analysis [16–23, 30–42]. Five methods were used
for the assessment of c-Met expression in breast cancer
specimens as follows: immunohistochemistry (IHC),
real-time quantitative PCR (RT-PCR), reverse phase
protein lysate microarray (RPPA), fluorescence in situ
hybridization (FISH), and molecular inversion probes
(MIP). All of the 21 eligible studies were retrospective.
Table 1 and Table 2 summarize the characteristics of
these studies. The number of patients ranged from 33 to
1002, and the total number of patients analyzed was
6010. Most of the patients included had stage I–IIIa
disease and had undergone radical surgery, except one
study that included patients with metastatic breast
cancer (132 patients) .
Impact of c-Met on the RFS and OS of unselected
RFS was analyzed in 12 studies and in a total of 3570
cases. The results showed significant between-study
heterogeneity (P = 0.02, I2 = 50 %), and a random-effects
model was used. The combined HR was 1.60 (95 % CI
1.27–2.00; P < 0.0001) (Fig. 2a), which indicated that
cMet overexpression was associated with a 1.6-fold
increased risk of recurrence. The meta-analysis
incorporating the five imputed studies using the trim and fill
method still showed a statistically significant poor RFS
in c-Met overexpressing patients (HR, 1.28, 95 % CI,
1.01–1.63, P = 0.043). Seventeen studies including 4228
cases were evaluated for the effect of c-Met
overexpression on OS (Fig. 2b). A random-effects model was used
to combine HRs because of the heterogeneity among the
studies (P = 0.0005; I2 = 61 %). The combined HR was
1.52 (95 % CI 1.15–2.01; P = 0.004), which indicated that
c-Met overexpression was associated with a 1.52-fold
increased risk of mortality in breast cancer patients. The
trim and fill method omitted one study with a revised
estimate of HR and continued to show a statistically
significant poor OS in c-Met overexpressing patients (HR,
1.53, 95 % CI, 1.16–2.03, P = 0.003).
Impact of c-Met on the prognosis of Western and
In the subgroup analysis according to ethnicity, the
impact of c-Met expression on the RFS of Western patients
was evaluated in 8 studies including 2313 cases. No
significant heterogeneity was observed (P = 0.16, I2 = 33 %),
and the fixed-effects model was used. The results
showed that c-Met overexpression was significantly
associated with a 1.52-fold increased risk of recurrence (HR =
1.52, 95 % CI 1.27–1.83; P < 0.00001) (Fig. 3a). The
metaanalysis incorporating the four imputed studies using the
trim and fill method still showed a statistically significant
poor RFS in c-Met overexpressing patients (HR, 1.32,
95 % CI, 1.12–1.56, P = 0.001). The impact of c-Met
expression on the OS of Western patients was evaluated in
13 studies including 2969 cases. The random-effects
model was used because of the observed heterogeneity
(P = 0.003, I2 = 59 %). The results of the meta-analysis
showed a significantly poor OS in the c-Met
overexpression group (HR = 1.62, 95 % CI 1.20–2.20, P = 0.003)
(Fig. 3b). Analysis with the trim and fill method omitted
one study and continued to show a statistically significant
poor RFS in c-Met overexpressing patients (HR, 1.64,
95 % CI, 1.22–2.22, P = 0.001). Four studies including
1257 cases evaluated the impact of c-Met expression on
the RFS of Asian patients, and four studies including 1259
cases evaluated the impact of c-Met expression on the OS
of Asian patients. The random-effects model was used
Fig. 2 Forest plot of the hazard ratio (HR) for relapse free survival (RFS) (a) or overall survival (OS) (b) of unselected breast cancer
because of the observed heterogeneity (P = 0.01 and 0.009,
respectively). Although there was a trend toward increased
recurrence (HR 1.45, 95 % CI 0.80–2.62; P = 0.22) (Fig. 4a)
and mortality (HR 1.12, 95 % CI 0.39–3.20; P = 0.84)
(Fig. 4b), it was not statistically significant.
Impact of c-Met on the prognosis of lymph node negative,
hormone-receptor positive, HER-2 positive and triple
negative breast cancer
As shown in Table 1, three studies that included lymph
node negative patients (767 cases) provided the related
OS data. No significant heterogeneity was observed (P =
0.43, I2 = 0 %), and the fixed-effects model was used.
The results showed that c-Met overexpression was
associated with a 2.04-fold increased risk of mortality (HR
2.04, 95 % CI 1.48–2.80; P < 0.0001) (Fig. 5a). As shown
in Table 2, four studies included hormone-receptor
positive patients (834 cases) and provided the related RFS
data. No significant heterogeneity (P = 0.20, I2 = 36 %)
was observed among these studies. The fixed-effects
model was used, and the results of the meta-analysis
showed that c-Met overexpression was associated with
a 1.41-fold increased risk of recurrence (HR 1.41, 95 %
CI 1.11–1.79, P = 0.005) (Fig. 5b). Two studies included
HER-2 positive patients (285 cases) and provided the
related RFS data. The fixed-effects model was used
(P = 0.64, I2 = 0 %). Although there was a trend toward
increased recurrence among patients with c-Met
overexpression (HR 1.20, 95 % CI 0.91–1.59, P = 0.20)
(Fig. 5c), it was not statistically significant. The impact
of c-Met expression on RFS in patients with triple
negative breast cancer (TNBC) was evaluated in five
groups including 564 cases. No significant
heterogeneity (P = 0.63, I2 = 0 %) was observed among these
studies. The fixed-effects model was used and the result of
the meta-analysis showed that c-Met overexpression
was significantly associated with a 2.31-fold increased
risk of recurrence (HR 2.31, 95 % CI 1.53–3.48, P <
0.0001) (Fig. 5d).
Twelve studies evaluating RFS in unselected breast
cancer patients were examined by Begg’s test. Visual
inspection of the funnel plot showed asymmetry (P = 0.029)
Fig. 3 Forest plot of HR for RFS (a) and OS (b) among Western patients
(Fig. 6a), suggesting publication bias. Sensitivity analysis
was performed using the trim and fill method, which
conservatively imputes hypothetical negative
unpublished studies or omits certain studies to mirror the
positive studies that cause funnel plot asymmetry. Five
hypothetical studies were imputed and the funnel plot
symmetry was created (Fig. 6b). The meta-analysis
incorporating the imputed studies still showed a
statistically significant poor RFS in c-Met overexpressing
patients. Seventeen studies evaluating OS in unselected
breast cancer patients were analyzed by Begg’s test.
Visual inspection of the funnel plot showed
asymmetry, although the Begg’s test result was not
statistically significant (P = 0.105) (Fig. 6c). The trim and fill
method omitted one study and created a symmetrical
funnel plot (Fig. 6d). The general result was not
changed. The Western patient subgroup showed similar
results as the unselected breast cancer patients. No
publication bias was detected in the other subgroup
Fig. 4 Forest plot of HR for RFS (a) and OS (b) among Asian patients
Fig. 5 Forest plot of the HR for OS among lymph node negative (a), hormone-receptor positive (b), HER-2 positive (c) and triple negative breast
In recent years, the development of target-based
therapies has improved the prognosis of cancer patients.
However, only a subset of patients benefits from the use of
specific drugs, and the development of resistance often
results in clinical treatment failure. The identification of
novel targets is a challenging task for the medical
oncologist, and valuable prognostic markers might become
potential therapeutic targets in the future. The
trasmembrane tyrosine kinase receptor c-Met plays a vital role in
cell survival, growth and metastasis . c-Met is
overexpressed in a variety of carcinomas and is associated with
resistance to herceptin and gefitinib, and it represents an
attractive target for antitumor treatment [13, 43]. c-Met
overexpression has been reported in 14–53.6 % of
patients with breast cancer [20, 39, 40]. Evidence of the
influence of c-Met expression on survival outcomes in
breast cancer is inconclusive. In the present study, we
analyzed 21 studies published between 1998 and 2014
and comprising a total of 6010 cases. The results of the
meta-analysis showed that c-Met overexpression is a
statistically significant adverse predictor of RFS and OS in
unselected breast cancer. These results provide evidence
supporting future trials evaluating the effect of c-Met
inhibitors in breast cancer.
Originally, Iressa, a selective EGFR inhibitor, showed
promising results among Asian patients, but not in
Western populations, suggesting a possible role of ethnic
differences between Asian and Western lung cancer
patients . The differences in the characteristics of breast
cancer between Asian and Western countries have also
been discussed for several years . In the present study,
we performed a subgroup analysis according to ethnicity.
In the Western patient group, there were 8 studies
analyzing RFS and 13 studies analyzing OS according to c-Met
expression. Our results showed that c-Met is a predictor of
poor prognosis (both RFS and OS) in Western patients. In
the Asian patient group, four studies analyzing c-Met
expression according to OS/RFS were identified. The results
showed that there was a trend toward increased recurrence
and mortality in c-Met overexpressing patients, although
the difference did not reach statistical significance. Further
analysis including a larger number of patients and studies is
necessary to evaluate the prognostic role of c-Met in Asian
Fig. 6 Funnel plot without and with trim and fill for RFS (a and b) and OS (c and d) of unselected breast cancer
breast cancer patients, and to determine whether c-Met
status has a different influence on the prognosis of Asian
and Western breast cancer patients.
Lymph node status is the best indicator of prognosis
in breast cancer. Additional makers are necessary to
predict prognosis in patients with lymph node negative
breast cancer. C-Met expression is higher and more
frequently positive in metastatic lymph nodes than in the
primary tumor . In the present analysis, three studies
provided data on OS in lymph node negative patients.
The meta-analysis results showed that c-Met
overexpression was associated with a 2.04-fold increased risk of
mortality (combined HR 2.04, 95 % CI 1.48–2.80; P <
0.0001) in lymph node negative breast cancer. These
results demonstrate that c-Met might act at the early
stages of breast cancer, and its expression should be
detected on postoperative pathology to predict prognosis
and guide the postoperative treatment.
Breast cancer is divided into five molecular subtypes
based on the status of ER, PR, HER-2 and Ki67 . In
the present study, we performed subgroup analysis
according to molecular subtypes. Four studies provided
data on RFS in the hormone-receptor positive subgroup.
The meta-analysis results showed that c-Met
overexpression was associated with a 1.41-fold increased
risk of recurrence (combined HR 1.41, 95 % CI 1.11–1.79;
P = 0.005) in the hormone-receptor positive group.
Endocrine therapy is the most important systemic treatment
for hormone-receptor positive breast cancer at all stages
. C-Met and the Ron receptor tyrosine kinase, a
member of the c-Met family of receptors, are associated with
resistance to breast cancer endocrine therapy in vitro [14,
47]. Overexpression of HER-2 is associated with resistance
to endocrine therapy in breast cancer . Zagouri et al.
showed that c-Met was not a prognostic factor in ER- and
HER2-positive breast carcinomas . In addition, the
prognostic value of c-Met was shown to be independent
of HER2/neu . Consequently, c-Met might influence
the prognosis of hormone-receptor positive patients by
mediating resistance to endocrine therapy, especially in
the hormone-receptor positive/HER-2 negative subgroup
in a Her-2 independent manner. This subgroup is likely to
benefit from combined treatment with c-Met inhibitors
and estrogen inhibition therapy in the future. However,
additional studies are needed to confirm these results.
Functional crosstalk of c-Met with HER-2 has been
reported to enhance cell invasion in Madin-Darby canine
kidney (MDCK) epithelial cells in vitro . In breast
cancer cells, this crosstalk is involved in the
development of Herceptin resistance in vitro . In the present
analysis, two studies provided RFS data in HER-2
positive patients. The meta-analysis results showed that
cMet overexpression was associated with poor prognosis,
but the findings did not reach statistical significance
(combined HR 1.20, 95 % CI 0.91–1.59; P = 0.20).
Additionally, Minuti et al. found that c-Met is associated
with shorter time to progression (TTP) in HER2-positive
metastatic breast cancer . Thus, additional studies
are necessary to explore the clinical interaction of c-Met
According to currently available data, TNBC is the
most aggressive subtype of breast cancer, and no
targeted therapy is currently available . TNBC could be
further subclassified into basal-like breast cancer (BLBC)
and quintuple-negative breast cancer (QNBC), and
cMet is involved in the development of BLBC . Five
studies provided RFS data in the TNBC subgroup. The
meta-analysis results showed that c-Met overexpression
increased recurrence risk by 2.31-fold in TNBC
(combined HR 2.31, 95 % CI: 1.53–3.48, P < 0.0001), which
was the highest risk in this study. The results indicate
that c-Met could be a therapeutic target, thereby
providing new treatment options for TNBC.
Quality assessment according to REMARK guidelines
was performed for all 21 included studies. The studies
fulfilled, on average, 14 items (range, 10–18 items) of
the guidelines. Sensitivity and sub-group analyses were
performed to ensure that the results were reliable and
valid. However, our meta-analysis had several
limitations. First, the results of sub-analysis were less powerful
because the combined HR of some subgroups was
calculated on the basis of 2–5 studies with a relative small
patient sample size. Second, c-Met was detected by five
different methods, although most studies detected c-Met
by IHC (excluding the molecular subtype groups). In
addition, there were differences in the criteria for c-Met
positivity in IHC detection. Third, the funnel plot
analysis showed some asymmetry, suggesting the possibility
of publication bias in unselected patients and Western
patients. The trim and fill sensitivity analysis did not
change the general results, suggesting that the results
were not influenced by the unpublished negative studies
or the small sample size. Additional high-quality data
are necessary to draw more reliable conclusions.
Our comprehensive meta-analysis of all published
studies showed that c-Met overexpression is significantly
associated with poor survival in breast cancer patients,
especially in the TNBC subgroup. In Asian patients and
HER-2 positive breast carcinomas, c-Met might not be
associated with prognosis.
1. Ferlay J , Shin HR , Bray F , Forman D , Mathers C , Parkin DM . Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer . 2010 ; 127 : 2893 - 917 .
2. Kamangar F , Dores GM , Anderson WF . Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world . J Clin Oncol . 2006 ; 24 : 2137 - 50 .
3. Yersal O , Barutca S. Biological subtypes of breast cancer. Prognostic and therapeutic implications . World J Clin Oncol . 2014 ; 5 : 412 - 24 .
4. van 't Veer LJ , Dai H , Van de Vijver MJ , He YD , Hart AA , Mao M , et al. Gene expression profiling predicts clinical outcome of breast cancer . Nature . 2002 ; 415 : 530 - 6 .
5. Kassam F , Enright K , Dent R , Dranitsaris G , Myers J , Flynn C , et al. Survival outcomes for patients with metastatic triple-negative breast cancer: implications for clinical practice and trial design . Clin Breast Cancer . 2009 ; 9 : 29 - 33 .
6. Polyak K. Heterogeneity in breast cancer . J Clin Invest . 2011 ; 121 : 3786 - 8 .
7. Lee HJ , Seo AN , Kim EJ , Jang MH , Suh KJ , Ryu HS , et al. HER2 heterogeneity affects trastuzumab responses and survival in patients with HER2-positive metastatic breast cancer . Am J Clin Pathol . 2014 ; 142 : 755 - 66 .
8. Boccaccio C , Comoglio PM . Invasive growth: a MET-driven genetic programme for cancer and stem cells . Nat Rev Cancer . 2006 ; 6 : 637 - 45 .
9. Birchmeier C , Gherardi E. Developmental roles of HGF/SF and its receptor, the c-Met tyrosine kinase . Trends Cell Biol . 1998 ; 8 : 404 - 10 .
10. Gherardi E , Birchmeier W , Birchmeier C , Vande Woude G . Targeting MET in cancer: rationale and progress . Nat Rev Cancer . 2012 ; 12 : 89 - 103 .
11. Casaluce F , Sgambato A , Maione P , Rossi A , Ferrara C , Napolitano A , et al. ALK inhibitors: a new targeted therapy in the treatment of advanced NSCLC . Target Oncol . 2013 ; 8 : 55 - 67 .
12. Rota Caremoli E , Labianca R. Tivantinib : critical review with a focus on hepatocellular carcinoma . Expert Opin Investig Drugs . 2014 ; 23 : 1563 - 74 .
13. Shattuck DL , Miller JK , Carraway 3rd KL , Sweeney C. Met receptor contributes to trastuzumab resistance of Her 2-overexpressing breast cancer cells . Cancer Res . 2008 ; 68 : 1471 - 7 .
14. Hiscox S , Jordan NJ , Jiang W , Harper M , McClelland R , Smith C. Chronic exposure to fulvestrant promotes overexpression of the c-Met receptor in breast cancer cells: implications for tumour-stroma interactions . Endocr Relat Cancer . 2006 ; 13 : 1085 - 99 .
15. Nagy J , Curry GW , Hillan KJ , McKay IC , Mallon E , Purushotham AD , et al. Hepatocyte growth factor/scatter factor expression and c-met in primary breast cancer . Surg Oncol . 1996 ; 5 : 15 - 21 .
16. Vendrell JA , Robertson KE , Ravel P , Bray SE , Bajard A , Purdie CA , et al. A candidate molecular signature associated with tamoxifen failure in primary breast cancer . Breast Cancer Res . 2008 ; 10 :R88.
17. Ghoussoub RA , Dillon DA , D'Aquila T , Rimm EB , Fearon ER , Rimm DL . Expression of c-met is a strong independent prognostic factor in breast carcinoma . Cancer . 1998 ; 82 : 1513 - 20 .
18. Tolgay Ocal I , Dolled-Filhart M , D'Aquila TG , Camp RL , Rimm DL . Tissue microarray-based studies of patients with lymph node negative breast carcinoma show that met expression is associated with worse outcome but is not correlated with epidermal growth factor family receptors . Cancer . 2003 ; 97 : 1841 - 8 .
19. Lengyel E , Prechtel D , Resau JH , Gauger K , Welk A , Lindemann K , et al. C- Met overexpression in node-positive breast cancer identifies patients with poor clinical outcome independent of Her2/neu . Int J Cancer . 2005 ; 113 : 678 - 82 .
20. Inanc M , Ozkan M , Karaca H , Berk V , Bozkurt O , Duran AO , et al. Cytokeratin 5 /6, c-Met expressions, and PTEN loss prognostic indicators in triplenegative breast cancer . Med Oncol . 2014 ; 31 : 801 .
21. Zagouri F , Brandstetter A , Moussiolis D , Chrysikos D , Dimitrakakis C , Tsigginou A , et al. Low protein expression of MET in ER-positive and HER2- positive breast cancer . Anticancer Res . 2014 ; 34 : 1227 - 31 .
22. Gisterek I , Lata E , Halon A , Matkowski R , Szelachowska J , Biecek P , et al. Prognostic role of c-met expression in breast cancer patients . Rep Pract Oncol Radiother . 2011 ; 16 : 173 - 7 .
23. Koh YW , Lee HJ , Ahn JH , Lee JW , Gong G . MET expression is associated with disease-specific survival in breast cancer patients in the neoadjuvant setting . Pathol Res Pract . 2014 ; 210 : 494 - 500 .
24. Zhang YW , Vande Woude GF . HGF/SF-met signaling in the control of branching morphogenesis and invasion . J Cell Biochem . 2003 ; 88 : 408 - 17 .
25. Hiscox S , Jordan NJ , Jiang W , Harper M , McClelland R , Smith C , et al. Chronic exposure to fulvestrant promotes overexpression of the c-Met receptor in breast cancer cells: implications for tumour-stroma interactions . Endocr Relat Cancer . 2006 ; 13 : 1085 - 99 .
26. McShane LM , Altman DG , Sauerbrei W , Taube SE , Gion M , Clark GM . REporting recommendations for tumour MARKer prognostic studies (REMARK) . Eur J Cancer . 2005 ; 41 : 1690 - 6 .
27. Chen M , Cai E , Huang J , Yu P , Li K. Prognostic value of vascular endothelial growth factor expression in patients with esophageal cancer: a systematic review and meta-analysis . Cancer Epidemiol Biomarkers Prev . 2012 ; 21 : 1126 - 34 .
28. Parmar MK , Torri V , Stewart L. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints . Stat Med . 1998 ; 17 : 2815 - 34 .
29. Tierney JF , Stewart LA , Ghersi D , Burdett S , Sydes MR . Practical methods for incorporating summary time-to-event data into meta-analysis . Trials . 2007 ; 8 : 16 .
30. Nakopoulou L , Gakiopoulou H , Keramopoulos A , Giannopoulou I , Athanassiadou P , Mavrommatis J , et al. c-met tyrosine kinase receptor expression is associated with abnormal beta-catenin expression and favourable prognostic factors in invasive breast carcinoma . Histopathology . 2000 ; 36 : 313 - 25 .
31. Camp RL , Rimm EB , Rimm DL . Met expression is associated with poor outcome in patients with axillary lymph node negative breast carcinoma . Cancer . 1999 ; 86 : 2259 - 65 .
32. Kang JY , Dolled-Filhart M , Ocal IT , Singh B , Lin CY , Dickson RB , et al. Tissue microarray analysis of hepatocyte growth factor/Met pathway components reveals a role for Met, matriptase, and hepatocyte growth factor activator inhibitor 1 in the progression of node-negative breast cancer . Cancer Res . 2003 ; 63 : 1101 - 5 .
33. Chen HH , Su WC , Lin PW , Guo HR , Lee WY . Hypoxia-inducible factor-1alpha correlates with MET and metastasis in node-negative breast cancer . Breast Cancer Res Treat . 2007 ; 103 : 167 - 75 .
34. Ponzo MG , Lesurf R , Petkiewicz S , O'Malley FP , Pinnaduwage D , Andrulis IL , et al. Met induces mammary tumors with diverse histologies and is associated with poor outcome and human basal breast cancer . Proc Natl Acad Sci U S A . 2009 ; 106 : 12903 - 8 .
35. Liu T , FENG XH , Ren ZG , Wang JG . Expression of c-Met and its clinical significance in breast cancer . J Surg Concepts Pract . 2011 ; 16 : 42 - 4 .
36. Minuti G , Cappuzzo F , Duchnowska R , Jassem J , Fabi A , O'Brien T , et al. Increased MET and HGF gene copy numbers are associated with trastuzumab failure in HER2-positive metastatic breast cancer . Br J Cancer . 2012 ; 107 : 793 - 9 .
37. Li B , Lu YL , Liu L , Zhao P. Clinicopathological significance of expression of c-Met in invasive breast ductal carcinoma . Chin J Clinicians (Electronic Edition) . 2012 ; 6 : 99 - 102 .
38. Raghav KP , Wang W , Liu S , Chavez-MacGregor M , Meng X , Hortobagyi GN , et al. cMET and phospho-cMET protein levels in breast cancers and survival outcomes . Clin Cancer Res . 2012 ; 18 : 2269 - 77 .
39. Gonzalez-Angulo AM , Chen H , Karuturi MS , Chavez-MacGregor M , Tsavachidis S , Meric-Bernstam F , et al. Frequency of mesenchymal-epithelial transition factor gene (MET) and the catalytic subunit of phosphoinositide-3-kinase (PIK3CA) copy number elevation and correlation with outcome in patients with early stage breast cancer . Cancer . 2013 ; 119 : 7 - 15 .
40. Zagouri F , Bago-Horvath Z , Rössler F , Brandstetter A , Bartsch R , Papadimitriou CA , et al. High MET expression is an adverse prognostic factor in patients with triple-negative breast cancer . Br J Cancer . 2013 ; 108 : 1100 - 5 .
41. Ho-Yen CM , Green AR , Rakha EA , Brentnall AR , Ellis IO , Kermorgant S , et al. C- Met in invasive breast cancer: is there a relationship with the basal-like subtype? Cancer . 2014 ; 120 : 163 - 71 .
42. Kim YJ , Choi JS , Seo J , Song JY , Lee SE , Kwon MJ , et al. MET is a potential target for use in combination therapy with EGFR inhibition in triplenegative/basal-like breast cancer . Int J Cancer . 2014 ; 134 : 2424 - 36 .
43. Cappuzzo F , Jänne PA , Skokan M , Finocchiaro G , Rossi E , Ligorio C , et al. MET increased gene copy number and primary resistance to gefitinib therapy in non-small-cell lung cancer patients . Ann Oncol . 2009 ; 20 : 298 - 304 .
44. Zhou W , Christiani DC . East meets West: ethnic differences in epidemiology and clinical behaviors of lung cancer between East Asians and Caucasians . Chin J Cancer . 2011 ; 30 : 287 - 92 .
45. Leong SP , Shen ZZ , Liu TJ , Agarwal G , Tajima T , Paik NS , et al. Is breast cancer the same disease in Asian and Western countries? World J Surg . 2010 ; 34 : 2308 - 24 .
46. Sainsbury R. The development of endocrine therapy for women with breast cancer . Cancer Treat Rev . 2013 ; 39 : 507 - 17 .
47. McClaine RJ , Marshall AM , Wagh PK , Waltz SE . Ron receptor tyrosine kinase activation confers resistance to tamoxifen in breast cancer cell lines . Neoplasia . 2010 ; 12 : 650 - 8 .
48. Dowsett M. Overexpression of HER-2 as a resistance mechanism to hormonal therapy for breast cancer . Endocr Relat Cancer . 2001 ; 8 : 191 - 5 .
49. Khoury H , Naujokas MA , Zuo D , Sangwan V , Frigault MM , Petkiewicz S , et al. HGF converts ErbB2/Neu epithelial morphogenesis to cell invasion . Mol Biol Cell . 2005 ; 16 : 550 - 61 .