Development of panel of urine DNA Biomarkers for Hepatocellular Carcinoma screening
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Date
2018-08
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Addis Ababa Universty
Abstract
Background: - Hepatocellular carcinoma (HCC) is one of the most common types of
cancer with an increasing incidence rate and high mortality globally. It is a malignant tumor
that arises from the hepatocytes. The principal risk factors are Hepatitis B and C viruses.
The five year survival rate of HCC is very low and can be maximized by early detection of
the disease. The current and most widely used biomarker for HCC screening is serum Alpha
Fetoprotein (AFP). However, due to the low sensitivity (40 - 60%) of this biomarker, the
need to develop better and effective assays, especially for early detection of HCC is crucial.
It must be noted that this study on urine DNA biomarkers is the first of its kind that was
conducted in Ethiopia.
Objective:- The aim of this study was to investigate the potential use of circulation derived
urine DNA biomarkers for HCC-associated mutations in the human telomerase reverse
transcriptase (hTERT), Tumor protein P53 (Tp53) and Catenin (cadherin-associated protein)
Beta-one (CTNNB1) genes and HCC associated hypermethylation in Glutathione-Stransferases
(GSTP1), Ras associated domain family one A (RASSF1A) and SEPT9 genes
detected by short amplicon quantitative polymerase chain reaction (qPCR) based assays for
HCC screenings.
Materials and Methods: - Urine samples were collected from patients with HCC, cirrhosis
and viral hepatitis attending Tikur Anbessa Specialized Hospital from May 2016 - May
2017. DNA was extracted using guanidine thiocyante and was further fractionated into high
and low molecular weight (LMW). The LMW DNA was quantified by qPCR using human
genomic DNA as standard. The mutations in the hTERT, Tp53 and CTNNB1 genes were
quantified by qPCR using fluorescent hybridization probes. The hypermethylation of
GSTP1, RASSF1A and SEPT9 genes were analyzed using methylation specific PCR (MSP).
Alpha fetoprotein (AFP) the gold standard serum biomarker for HCC, ALT (alanine
transaminase) and AST (Aspartate transaminase) were also measured. Area under receiver
operating characteristic (AUROC) curve analysis was used to assess the predictive value of
the six biomarkers for HCC detection.
Result: - The AUROC curve analysis for mutation assay of Tp53, CTNNB1 and hTERT, to
distinguish HCC from cirrhosis and hepatitis were 0.495, 0.553 and 0.561, respectively. The
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AUROC curve for the hypermethylation assay of RASSF1A, GSTP1 and Sptin9 were shown
to be 0.535, 0.544 and 0.405, respectively. hTERT, CTNNB1, RASSF1A and GSTP1 had a
better differentiating capacity since they have 50% AUROC whereas Tp53 and SEPT9 had
less AUROC. The distinguishing power of HCC from cirrhosis was 0.484, 0.575, 0.605,
0.546, 0.581, and 0.420 for Tp53, CTNNB, hTERT, RASSF1A, GSTP1 and SEPT9,
respectively implicating that hTERT, RASSF1A, CTNNB1and GSTP1 had better
differentiating capacity. The result obtained from the distinguishing capacity of HCC from
hepatitis with the AUROC curve have also showed 0.455, 0.538, 0.529, 0,518, 0.567, and
0.392, for Tp53, CTNNB1 and hTERT, RASSF1A, GSTP1 and SEPT9, respectively
indicating relatively better predictive potential of CTNNB1 and hTERT, RASSF1A, GSTP1
biomarkers. In parallel study using samples from United States RASSF1A, GSTP1 and
SEPT9 differentiated HCC from Cirrhosis and hepatitis with AUROC curve value 0.740,
0.628 and 0.559, respectively. The predictive value of HCC from cirrhosis with AUROC
curve analysis was 0.737, 0.604 and 0.587 for RASSF1A, GSTP1, and SEPT9, respectively.
The predictive values of HCC from hepatitis were also 0.746, 0.672 and 0.529 for
RASSF1A, GSTP1 and SEPT9, respectively. In all cases, Tp53 and SEPT9 shown to have
relatively low differentiating capacity as indicated by the AUROC. AFP in all the cases had
around 70% ability in distinguishing HCC from Hepatitis and Cirrhosis. This study
therefore indicated that the biomarkers from US had better predictive potential than
Ethiopian Biomarkers.
Conclusion: - Most of the biomarkers used in this study were able to differentiate HCC
from cirrhosis and hepatitis with close performance to samples from the US. The result
obtained from this study is a proof of concept for potential use of these biomarkers in the
Ethiopian population. This might require further investigation on large set of samples and
may require customized approach of the assay that would fit best to the Ethiopian
populations in order to get a better sensitivity, specificity and predictive potential. The
knowledge gained from such study could be employed in the early detection, screening,
diagnosis, treatment and counselling of hepatitis, cirrhosis and liver cancer patients.
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Keywords
Hepatocellular carcinoma