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MET as a biomarker for target therapies
Gabriele Minuti
Medical Oncology Division
Civil Hospital of Livorno
MET as a biomarker for target therapies
 MET and its ligand HGF regulate multiple cellular processes that stimulate cell
proliferation, invasion/metastasis and angiogenesis.
 MET/HGF signaling pathway represents a relevant target for personalized cancer
treatment based on high frequency of MET and/or HGF overexpression, activation
and amplification.
 Aberrant MET activation occurs in different kind of tumor such as non small cell lung
cancer, gastro-esophageal cancer, ovarian cancer, breast cancer, kidney cancer,
thyroid cancer, liver cancer and gliomas.
 The key role that MET plays in malignant transformation suggests that inhibition of
MET signaling may abrogate growth and progression of cancers in which its activity is
increased.
MET and HGF INHIBITORS
 INHIBITORS of HGF ACTIVATORS and HGF
 MET ANTAGONISTS
 MET KINASE INHIBITORS
MET/HGF INHIBITORS ONGOING TRIALS
MET and HGF in BREAST CANCER
 MET and HGF overexpression correlates with short relapse-free and overall
survival.
 Raghav et al. reported that high levels of MET protein expression was associated
with poor prognosis in early breast cancer.
 Functional crosstalk of MET with EGFR, ERBB2 or insulin-like growth factor 1
receptor (IGF1R) has been reported in several systems and has emerged as a major
mechanism for cancer progression and resistance to therapy.
 Lindemann et al. reported MET overexpression in 25% of HER2-positive breast
tumors, supporting the hypothesis that both HER2 and MET receptors could synergize
in promoting tumor growth.
 Shattuck et al. showed that MET contributes to trastuzumab resistance, and a
subset of HER2-positive breast cancer patients may benefit from combined inhibition
of both HER2 and MET.
MET and HGF in BREAST CANCER
 Aim of the study: to investigate
whether copy number gain of MET
or its ligand HGF affect
trastuzumab sensitivity in HER2+
MBC patients.
 130 HER2+ MBC treated with
trastuzumab as single agent or in
combination with chemotherapy.
 MET and HGF gene copy
numbers (GCN) were assessed by
FISH in primary breast cancer
samples.
 MET FISH analysis was
successfully performed in all 130
cases. HGF FISH analysis was
performed in 84 cases (64.6%).
ROC analysis was applied to find the best cut-off point for both MET
and HGF GCN discriminating between sensitive (CR+PR+SD) and
refractory (PD at the first imaging assessment) patients.
MET CUT-OFF : 3.72 mean GCN
HGF CUT-OFF : 3.01 mean GCN
1,0
1,0
MET ROC analysis
HGF ROC analysis
,8
,8
,5
AUC=0.679
Sensitivity
Sensitivity
MET and HGF in BREAST CANCER
,5
AUC=0.663
,3
0,0
0,0
,3
,3
,5
Specificity
,8
1,0
0,0
0,0
,3
,5
Specificity
,8
1,0
MET FISH positive Vs negative
1,0
1,0
P=0.006;HR 1.74 (95% CI 1.16-2.62)
P=0.681;HR 1.12 (95% CI 0.65-1.93)
,8
Cumulative survival function
,8
,6
,4
,6
,4
MET FISH N=83
,2
MET FISH +
N=17
,2
MET FISH N=55
MET FISH +
N=34
0,0
0,0
0
10
20
30
40
50
60
70
0
20
Time To Progression (months)
40
60
80
100
Survival time (months)
Failure Rate (%)
TTP (months)
OS (months)
MET FISH +
(N=36, mean≥3.72)
44.4%
5.7
26.4
MET FISH (N=94, mean<3.72)
16.0%
9.9
29.1
0.001
0.006
0.681
P-value
120
140
HGF FISH positive Vs negative
1,0
1,0
1,0
P=0.567;
HR 0.83
P=0.681;HR
1.12(95%
(95%CI
CI0.44-1.56)
0.65-1.93)
P=0.665
; HR 1.10
P=0.006;HR
1.74(95%
(95%CICI0.70-1.74)
1.16-2.62)
,8
,8
Cumulativesurvival
survivalfunction
function
Cumulative
,8
,6
,4
,6,6
HGF FISH +
N=14
,4,4
MET FISH N=83HGF FISH N=48
,2
0
10
20
30
40
HGF FISH MET FISH N=31
N=55
,2,2
HGF FISH
FISH ++
MET
N=31
N=34
0,0
MET FISH +
N=17
50
60
0,0
0,0
00
2020
Time To Progression (months)
4040
6060
8080
100
100
Survival
time
(months)
Survival
time
(months)
Failure Rate (%)
TTP (months)
OS (months)
HGF FISH +
(N=33, mean ≥3.01)
30.3%
9.9
35.2
HGF FISH (N=51, mean<3.01)
7.8%
10.5
26.1
0.007
0.665
0.567
P-value
120
120
140140
MET/HGF FISH combination
Results confirmed that failure rate was significantly lower in the population negative
for both MET and HGF (P=0.007), with a percentage of progressing patients not
significantly different than that detected with a single biomarker assay .
Outcome according to MET and HGF GCN in 84 patients evaluable for both biomarkers
MET and HGF in BREAST CANCER
 Response to trastuzumab therapy as well as TTP were significantly better in patients
with no MET GCN gain, supporting the potential therapeutic impact of anti-MET agents
in MBC, particularly in combination with anti-HER2 agents.
 A combination of anti-MET and anti-HER-targeted agents should be tested as a
treatment option in HER2-positive patients with MET-overexpressing tumors.
 We find a strong association of MET and HGF GCN. The presence of increased GCN of
both MET and HGF in the same tumors could explain why a single test was equally
predictive than the combination of both assays.
 Ligand-dependent MET activation could represent the predominant mechanism in
HER2-positive breast cancer, indicating a potential role for anti-MET monoclonal
antibodies in breast cancer.
G. MINUTI et al. SUBMITTED
CONCLUSIONS
 The role of HGF/MET aberrant signalling in cancer is clear, and effective therapeutics
are now available.
 Methods for assessing the level of HGF/MET expression and activity have not been
extensively validated and deployed.
 Patient stratification according to HGF/MET expression or MET phosphorylation
needs further development and is not currently an important component of study
design in the numerous clinical trials that are in progress.
 Patient stratification is an essential component for therapeutic success and suggest
that analysis of HGF/MET expression levels and/or receptor phosphorylation may
constitute valid strategies.
I would like to thank…
F. Cappuzzo, R. Duchnowska, J. Jassem, A. Fabi, T. O’Brien, A. D. Mendoza, L. Landi, W.
Biernat, B. Czartoryska-Arłukowicz, T. Jankowski, D. Zuziak, J. Zok, B. Szostakiewicz, M.
Foszczyńska-Kłoda, A. Tempińska-Szałach, E. Rossi, A. Destro, M. Roncalli , M. VarellaGarcia
Department of Medical Oncology, Civil Hospital of Livorno/Istituto Toscano Tumori, Livorno, Italy
Military Institute of Medicine, Warsaw, Poland
Medical University of Gdańsk, Gdańsk, Poland
National Cancer Institute Regina Elena, Rome, Italy
Laboratory of Molecular Pathology, University of Colorado Cancer Center, Aurora, Colorado, USA
Białystock Oncology Center, Białystock, Poland
Lublin Oncology Center, Lublin, Poland
Beskidy Oncology Center, Bielsko-Biała, Poland
Warmia and Masuria Oncology Center, Olsztyn, Poland
West Pomeranian Oncology Center, Szczecin, Poland
District Hospital of Elbląg, Elbląg, Poland
Milan University, Istituto Clinico Humanitas, Milan, Italy