Functional proteomic analysis of advanced serous ovarian cancer using reverse phase protein array: TGF-beta pathway signaling indicates response to primary chemotherapy.
OBJECTIVE
Using reverse phase protein array, we measured protein expression associated with response to primary chemotherapy in patients with advanced-stage, high-grade serous ovarian cancer.


METHODS
Tumor samples were obtained from 45 patients with advanced high-grade serous cancers from the Gynecology Tumor Bank at the British Columbia Cancer Agency. Treatment consisted of platinum-based chemotherapy following debulking surgery. Protein lysates were prepared from fresh frozen tumor samples, and 80 validated proteins from signaling pathways implicated in ovarian carcinogenesis were measured by reverse phase protein array. Normalization of Ca-125 by the 3rd cycle of chemotherapy was chosen as the primary outcome measure of chemotherapy response. Logistic regression was used for multivariate analysis to identify protein predictors of Ca-125 normalization and Cox regression to test for the association between protein expression and progression-free survival. A significance level of P<or=0.05 was used.


RESULTS
The mean age at diagnosis was 56.8 years. epidermal growth factor receptor, YKL-40, and several transforming growth factor beta (TGF-beta) pathway proteins [c-jun-NH2-kinase (JNK), JNK phosphorylated at residues 183 and 185, plasminogen activator inhibitor 1, Smad3, TAZ] showed significant associations with Ca-125 normalization on univariate testing. On multivariate analysis, epidermal growth factor receptor (P<0.02), JNK (P<0.01), and Smad3 (P<0.04) were significantly associated with normalization of Ca-125. Contingency table analysis of pathway-classified proteins revealed that the selection of TGF-beta pathway proteins was unlikely because of false discovery (P<0.007; Bonferroni adjusted).


CONCLUSIONS
TGF-beta pathway signaling likely plays an important role as a marker or mediator of chemoresistance in advanced serous ovarian cancer. On this basis, future studies to develop and validate a useful predictor of treatment failure are warranted.
Carey
Mark S
MS
Department of Systems Biology, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA. mark.carey@vch.ca
Agarwal
Roshan
R
Gilks
Blake
B
Swenerton
Kenneth
K
Kalloger
Steve
S
Santos
Jennifer
J
Ju
Zhenlin
Z
Lu
Yiling
Y
Zhang
Fan
F
Coombes
Kevin R
KR
Miller
Dianne
D
Huntsman
David
D
Mills
Gordon B
GB
Hennessy
Bryan T
BT
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000970:Antineoplastic Agents / Q000627:therapeutic use; D014408:Biomarkers, Tumor / Q000378:metabolism*; D018284:Cystadenocarcinoma, Serous / Q000188:drug therapy / Q000235:genetics / Q000378:metabolism*; D018572:Disease-Free Survival; D019008:Drug Resistance, Neoplasm / Q000235:genetics; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008875:Middle Aged; D010051:Ovarian Neoplasms / Q000188:drug therapy / Q000235:genetics / Q000378:metabolism*; D016016:Proportional Hazards Models; D040081:Protein Array Analysis; D040901:Proteomics; D012680:Sensitivity and Specificity; D015398:Signal Transduction / Q000502:physiology*; D016212:Transforming Growth Factor beta / Q000378:metabolism*; D016896:Treatment Outcome
D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor; D016212:Transforming Growth Factor beta
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