Deregulation of LIMD1-VHL-HIF-1α-VEGF pathway is associated with different stages of cervical cancer.

To understand the mechanism of cellular stress in basal-parabasal layers of normal cervical epithelium and during different stages of cervical carcinoma, we analyzed the alterations (expression/methylation/copy number variation/mutation) of HIF-1α and its associated genes LIMD1, VHL and VEGF in disease-free normal cervix (n = 9), adjacent normal cervix of tumors (n = 70), cervical intraepithelial neoplasia (CIN; n = 32), cancer of uterine cervix (CACX; n = 174) samples and two CACX cell lines. In basal-parabasal layers of normal cervical epithelium, LIMD1 showed high protein expression, while low protein expression of VHL was concordant with high expression of HIF-1α and VEGF irrespective of HPV-16 (human papillomavirus 16) infection. This was in concordance with the low promoter methylation of LIMD1 and high in VHL in the basal-parabasal layers of normal cervix. LIMD1 expression was significantly reduced while VHL expression was unchanged during different stages of cervical carcinoma. This was in concordance with their frequent methylation during different stages of this tumor. In different stages of cervical carcinoma, the expression pattern of HIF-1α and VEGF was high as seen in basal-parabasal layers and inversely correlated with the expression of LIMD1 and VHL. This was validated by demethylation experiments using 5-aza-2'-deoxycytidine in CACX cell lines. Additional deletion of LIMD1 and VHL in CIN/CACX provided an additional growth advantage during cervical carcinogenesis through reduced expression of genes and associated with poor prognosis of patients. Our data showed that overexpression of HIF-1α and its target gene VEGF in the basal-parabasal layers of normal cervix was due to frequent inactivation of VHL by its promoter methylation. This profile was maintained during different stages of cervical carcinoma with additional methylation/deletion of VHL and LIMD1.This work was supported by CSIR (Council of Scientific and Industrial Research, Government of India)-JRF/NET grant [File No.09/030(0059)/2010-EMR-I] to Mr. C.Chakraborty, grant [Sr. No. 2121130723] from UGC (University Grants Commission, Government of India) to Mr. Sudip Samadder, grant [SR/SO/HS-116/2007] from DST (Department of Science and Technology, Government of India) to Dr. C. K. Panda and grant [ No. 60(0111)/14/EMR-II of dt.03/11/2014] from CSIR (Council of Scientific and Industrial Research, Government of India) to Dr. C. K. Pand

Defining a nine-biomarker panel for predicting bladder cancer outcome in combination with smoking intensity: A report from the Los Angeles Cancer Surveillance Program

4575 Background: Urothelial carcinoma of the bladder (UCB) is a disease of alterations in several cellular pathways. Routine molecular profiling studies do not account for smoking, a well established risk factor for UCB, and its influence on outcome. This study assessed the prognostic potential of a multi-pathway protein panel across all UCB stages in a population-based cohort after accounting for clinicopathologic factors and smoking history. Methods: 212 UCB patients from the LA CSP, part of the NCI/SEER cancer registry, were included. "Smoking intensity" analyzed biologic and molecular impact of smoking by combining smoking status, duration of smoking and number of cigarettes smoked daily into a composite covariate. Tumors were profiled for Bax, caspase-3, Apaf-1, Bcl-2, p53, p21, COX2, VEGF and E-cadherin alterations by IHC. Univariate analyses and multivariable modeling examined associations with outcome. Results: Median follow up was 13.2 years. Age, pathologic stage, adjuvant therapy (all p< 0.001) and surgical modality (p = 0.05) were associated with survival. Increasing smoking intensity was associated with worse outcome (P < 0.001). Apaf-1 (p = 0.005), E-cadherin (p = 0.014) and p53 (p = 0.032) were univariately prognostic; E-cadherin remained prognostic after multivariate analysis (p = 0.04). Combined alterations in all 9 biomarkers were prognostic by univariate (p < 0.001) and multivariate (p = 0.006) analysis. A multivariate model that included all 9 biomarkers and smoking intensity was more accurate in predicting prognosis than models comprising of standard clinicopathologic covariates without (p < 0.001) or with (p = 0.018) smoking intensity. Conclusions: The study confirms detrimental effects of smoking on UCB prognosis. Apaf-1, E-cadherin and p53 individually predicted UCB survival. Increasing number of biomarker alterations was significantly associated with worsening survival, although markers contained in the panel were not necessarily prognostic individually. Predictive value of the nine-biomarker panel with smoking intensity was significantly higher than that of routine clinicopathologic parameters alone