Abstract 1150: Biomarkers discovery and racial disparity in hepatitis C-associated hepatocellular carcinoma.

Abstract

Abstract Cancer health disparities represent a major public health concern in the US. Even when factors such as socioeconomic status, carcinogen exposure, and access to care are accounted for, disparities persist in the form of higher overall incidence rates and worse clinical outcomes for minority populations than for overall population. A case of point is the racial disparities in liver cancer-related mortality. Hepatitis C virus (HCV) is the most significant contributing factor in the development of hepatocellular carcinoma (HCC). In the US, African Americans (AAs) have twice the prevalence of HCV/genotype 1 infection, and develop HCC at more than twice the rate as Caucasian (CA) counterparts. African Americans are, however, less likely to respond to interferon-based therapy than CAs, and have considerably lower likelihood of receiving liver transplantation. While it is evident that viral infection with HCV is associated with the development of HCC, there are critical gaps in our understanding of the biological basis for this racial disparity. The aim of the current study was to define the molecular signatures of HCV disease progression in liver & tumor tissue samples obtained from AA & CA patients using 8-plex iTRAQ-based proteomics coupled with bioinformatics data analyses. The raw data were analyzed by the ProteinPilot v3.0 using the paragon algorithm. Searches were performed against a comprehensive database generated from SwissPort, Refseq, and Tremble protein sequences. The data were normalized for loading error & background correction. The proteins with confidence score > 90% and with at least 1 peptide of 95% identification confidence were used for further quality control & differential expression analysis. The quality control analysis was performed using pairwise correlation plots, boxplots, principal component analysis (PCA), and unsupervised hierarchical clustering. Supervised analysis was performed to identify differentially expressed proteins (DEP), where the relative protein expression values were compared between groups (Normal vs. Cirrhosis (CIR), Normal vs. HCC, CIR vs. HCC). Based on our experimental design, 787 unique proteins were identified. Of those, 32 were differentially expressed between normal, cirrhosis & HCC groups. Targets validation using real-time PCR (RT-PCR) or western blotting (WB) shows racially distinct alteration in the expression of certain targets. For example, the mRNA expression levels of TF were 2 and18-fold higher in CIR & HCC, respectively in AAs compared to CAs. Similarly, the expression of APOA1 mRNA levels was 7-fold higher in HCC of AAs compared to CAs. This trend was similar to their protein expression levels using WB. However, the level of HNF4α protein was down regulated in AAs compared to CAs. This indicates that HNF4α does not regulate TF & APOA1 expression in HCC of AA samples. Citation Format: Simon T. Dillon, Manoj K. Bhasin, Xiaoxing (Stella) Feng, David Koh, Sayed Salih Daoud. Biomarkers discovery and racial disparity in hepatitis C-associated hepatocellular carcinoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1150. doi:10.1158/1538-7445.AM2013-1150