Use of high-throughput protein array for profiling of differentially expressed proteins in normal and malignant breast tissue.
cDNA arrays provide a powerful tool to identify gene expression pattern that are potentially associated with tumor invasion and metastasis. However, genes work at the protein level and, since the transcriptional activity of a gene does not necessarily reflect cellular protein expression, the identification and quantification of proteins is essential for the understanding of molecular events leading to malignant transformation. We have therefore employed a high-throughput protein microarray system which contains 378 well-characterized monoclonal antibodies in order to compare the gene expression pattern of malignant and adjacent normal breast tissue in a patient with primary breast cancer. Using this technique, we have identified a number of proteins that show increased expression levels in malignant breast tissues such as casein kinase Ie, p53, annexin XI, CDC25C, eIF-4E and MAP kinase 7. The expression of other proteins, such as the multifunctional regulator 14-3-3e was found to be decreased in malignant breast tissue, whereas the majority of proteins remained unchanged when compared to the corresponding non-malignant samples. The protein expression pattern was confirmed by immunohistochemistry, in which antibodies against 8 representative proteins known to be involved in carcinogenesis were employed in paraffin-embedded normal and malignant tissue sections deriving from the same patient. In each case, the results obtained by IHC matched the data obtained by antibody microarray system. Taken together, we have described for the first time a tumor cell specificity protein expression pattern by use of a novel commercially available antibody microarray system. We have thus demonstrated the feasibility of high-throughput protein arrays in the proteomic analysis of human breast tissue. We hypothesize that the use of protein arrays will not only increase our understanding of the molecular events, but could prove useful in evaluating prognosis and in determining optimal antineoplastic therapy.
Hudelist
Gernot
G
Department of Obstetrics and Gynecology, Division of Special Gynecology, University of Vienna Medical Center, Vienna, Austria.
Pacher-Zavisin
Margit
M
Singer
Christian F
CF
Holper
Tina
T
Kubista
Ernst
E
Schreiber
Martin
M
Manavi
Mahmood
M
Bilban
Martin
M
Czerwenka
Klaus
K
D000911:Antibodies, Monoclonal; D001331:Automation; D014408:Biomarkers, Tumor / Q000032:analysis*; D001943:Breast Neoplasms / Q000235:genetics / Q000473:pathology*; D002471:Cell Transformation, Neoplastic; D005260:Female; D006801:Humans; D007150:Immunohistochemistry; D008875:Middle Aged; D011379:Prognosis; D040081:Protein Array Analysis; D040901:Proteomics
D000911:Antibodies, Monoclonal; D014408:Biomarkers, Tumor