Date Published: March 14, 2018
Publisher: Public Library of Science
Author(s): Cristina Di Poto, Shisi He, Rency S. Varghese, Yi Zhao, Alessia Ferrarini, Shan Su, Abdullah Karabala, Mesfin Redi, Hassen Mamo, Amol S. Rangnekar, Thomas M. Fishbein, Alexander H. Kroemer, Mahlet G. Tadesse, Rabindra Roy, Zaki A. Sherif, Deepak Kumar, Habtom W. Ressom, Anand S Mehta.
Disparities in hepatocellular carcinoma (HCC) incidence and survival have been observed between ethnic groups including African-Americans (AA) and European-Americans (EA). The evaluation of the changes in the levels of metabolites in samples stratified by race could provide a snapshot of ethnically diverse disease related pathways and identify reliable biomarkers. In this study, we considered AA and EA to investigate metabolites that may be associated with HCC in a race-specific manner. The levels of 46 metabolites in plasma samples, collected from patients recruited at MedStar Georgetown University Hospital, were analyzed by Agilent GC-qMS in selected ion monitoring (SIM) mode. A least absolute shrinkage and selection operator (LASSO) regression model was applied to select metabolites with significant changes in HCC vs. cirrhosis in three groups: (1) AA and EA combined; (2) AA separately; and (3) EA separately. In addition, metabolites that distinguish HCC cases from cirrhosis in these three groups were selected by excluding those without HCV infection. The performances of the metabolites selected by LASSO in each group were evaluated through a leave-one-out cross-validation. We identified race-specific metabolites that differentiated HCC cases from cirrhotic controls, yielding better area under the receiver operating characteristics (ROC) curve (AUC) compared to alpha-fetoprotein (AFP), the serological marker widely used for the diagnosis of HCC. This study sheds light on metabolites that could potentially be used as biomarkers for HCC by monitoring their levels in high-risk population of cirrhotic patients in a race-specific manner.
Hepatocellular carcinoma (HCC) is the most common type of liver cancer. An estimated 40,710 new cases of liver cancer (including intrahepatic bile duct cancers) will be diagnosed in the US during 2017, approximately three-fourths of which will be HCC . Most of the HCC patients are diagnosed at late stage when treatment is no more effective, making HCC the most lethal type of liver cancer with an overall 5-year survival rate of approximately 15% . Worldwide, HCC is the fifth most common cancer and the third leading cause of cancer mortality .
Adult patients were recruited from the Hepatology Clinic at MedStar Georgetown University Hospital (MGUH). All participants provided informed consent to a protocol approved by the Institutional Review Board (IRB) at Georgetown University. The patients were diagnosed to have liver cirrhosis on the basis of established clinical, laboratory and/or imaging criteria. Cases were diagnosed to have HCC based on well-established diagnostic imaging criteria and/or histology. Clinical stages for HCC cases were determined based on the tumor-node-metastasis (TNM) staging system. Controls were required to be HCC free for at least 6 months from the time of study entry. Race information was collected from patients’ self-report. The characteristics of AA and EA, selected from these patients, are summarized in Table 1, whereas the characteristics of AA and EA that are HCV+ are shown in Table 2. The HCV+ participants were predominantly genotype 1a and 1b with no statistically significant difference between AA and EA.
The use of metabolomics to identify potential biomarkers of HCC is greatly advantageous to patients and healthcare providers because the dysregulation of metabolites may be an early indication of dysfunctional metabolic pathways that could offer valuable insight into the mechanism of HCC initiation, development or progression. In this study, we investigated plasma metabolites that may be associated with HCC in a race-specific manner by considering AA and EA from a cohort that we previously examined . The levels of selected plasma metabolites were measured by GC-SIM-MS. LASSO regression was conducted to select HCC-associated metabolites in a stratified analysis of AA and EA combined, adjusted or not for race, AA only, and EA only, with or without HCV infection. MSVM-RFE was used to rank the metabolites based on their ability to distinguish HCC cases from cirrhotic controls. The metabolites overlapping between the ones selected by LASSO and the top five ranked by MSVM-RFE were taken into consideration. Several metabolites including alpha tocopherol for AA and EA combined, valine for AA only, and glycine for EA only exhibited better performance than AFP.