The relative distribution of membranous and cytoplasmic met is a prognostic indicator in stage I and II colon cancer.
OBJECTIVE
The association hepatocyte growth factor receptor (Met) tyrosine kinase with prognosis and survival in colon cancer is unclear, due in part to the limitation of detection methods used. In particular, conventional chromagenic immunohistochemistry (IHC) has several limitations including the inability to separate compartmental measurements. Measurement of membrane, cytoplasm, and nuclear levels of Met could offer a superior approach to traditional IHC.


METHODS
Fluorescent-based IHC for Met was done in 583 colon cancer patients in a tissue microarray format. Using curvature and intensity-based image analysis, the membrane, nuclear, and cytoplasm were segmented. Probability distributions of Met within each compartment were determined, and an automated scoring algorithm was generated. An optimal score cutpoint was calculated using 500-fold crossvalidation of a training and test data set. For comparison with conventional IHC, a second array from the same tissue microarray block was 3,3'-diaminobenzidine immunostained for Met.


RESULTS
In crossvalidated and univariate Cox analysis, the membrane relative to cytoplasm Met score was a significant predictor of survival in stage I (hazard ratio, 0.16; P = 0.006) and in stage II patients (hazard ratio, 0.34; P < or = 0.0005). Similar results were found with multivariate analysis. Met in the membrane alone was not a significant predictor of outcome in all patients or within stage. In the 3,3'-diaminobenzidine-stained array, no associations were found with Met expression and survival.


CONCLUSIONS
These data indicate that the relative subcellular distribution of Met, as measured by novel automated image analysis, may be a valuable biomarker for estimating colon cancer prognosis.
Ginty
Fiona
F
GE Global Research Center, One Research Circle, Niskayuna, New York, USA.
Adak
Sudeshna
S
Can
Ali
A
Gerdes
Michael
M
Larsen
Melinda
M
Cline
Harvey
H
Filkins
Robert
R
Pang
Zhengyu
Z
Li
Qing
Q
Montalto
Michael C
MC
D000230:Adenocarcinoma / Q000175:diagnosis* / Q000378:metabolism / Q000401:mortality / Q000473:pathology*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000276:immunology / Q000378:metabolism; D002462:Cell Membrane / Q000378:metabolism*; D015331:Cohort Studies; D003110:Colonic Neoplasms / Q000175:diagnosis* / Q000378:metabolism / Q000401:mortality / Q000473:pathology*; D003593:Cytoplasm / Q000378:metabolism*; D005500:Follow-Up Studies; D006367:HeLa Cells; D006801:Humans; D008875:Middle Aged; D009367:Neoplasm Staging; D011379:Prognosis; D011518:Proto-Oncogene Proteins / Q000276:immunology / Q000378:metabolism*; D019859:Proto-Oncogene Proteins c-met; D017978:Receptors, Growth Factor / Q000276:immunology / Q000378:metabolism*; D016019:Survival Analysis; D046888:Tissue Array Analysis; D014018:Tissue Distribution
D014408:Biomarkers, Tumor; D011518:Proto-Oncogene Proteins; D017978:Receptors, Growth Factor; C491743:MET protein, human; D019859:Proto-Oncogene Proteins c-met