Mean MDK, OPN, DKK1 and AFP levels in HCC patients according to various clinical parameters.

<p>Mean MDK, OPN, DKK1 and AFP levels in HCC patients according to various clinical parameters.</p

Frequency of elevated serum MDK and AFP at HCC diagnosis and 6 months prior to diagnosis.

<p>Frequency of elevated serum MDK and AFP at HCC diagnosis and 6 months prior to diagnosis.</p

Midkine Increases Diagnostic Yield in AFP Negative and NASH-Related Hepatocellular Carcinoma

<div><p>Robust biomarkers for population-level hepatocellular carcinoma (HCC) surveillance are lacking. We compared serum midkine (MDK), dickkopf-1 (DKK1), osteopontin (OPN) and AFP for HCC diagnosis in 86 HCC patients matched to 86 cirrhotics, 86 with chronic liver disease (CLD) and 86 healthy controls (HC). Based on the performance of each biomarker, we assessed a separate longitudinal cohort of 28 HCC patients, at and before cancer diagnosis. Serum levels of MDK and OPN were higher in HCC patients compared to cirrhosis, CLD and HC groups. DKK1 was not different between cases and controls. More than half of HCC patients had normal AFP. In this AFP-negative HCC cohort, 59.18% (n = 29/49) had elevated MDK, applying the optimal cut-off of 0.44 ng/ml. Using AFP ≥ 20 IU/ml or MDK ≥ 0.44 ng/ml, a significantly greater number (76.7%; n = 66/86) of HCC cases were detected. The area under the receiver operating curve for MDK was superior to AFP and OPN in NASH-HCC diagnosis. In the longitudinal cohort, MDK was elevated in 15/28 (54%) of HCC patients at diagnosis, of whom 67% had elevated MDK 6 months prior. <b>Conclusion:</b> AFP and MDK have a complementary role in HCC detection. MDK increases the diagnostic yield in AFP-negative HCC and has greater diagnostic performance than AFP, OPN and DKK-1 in the diagnosis of NASH-HCC. Additionally, MDK has a promising role in the pre-clinical diagnosis of HCC.</p></div

Clinical characteristics of HCC patients and controls.

<p>Clinical characteristics of HCC patients and controls.</p

Comparison of the diagnostic performances of serum MDK, OPN and AFP.

<p><b>A) All HCC patients versus non-HCC patients (cirrhotics and chronic liver disease). B) Early HCC patients (BCLC 0-A) versus non-HCC patients (cirrhotic and chronic liver disease). C) HCV-HCC patients versus HCV-cirrhotics. D) HBV-HCC patients versus HBV-cirrhotics and chronic HBV patients. E) NASH-HCC patients versus NASH cirrhotic patients.</b> A) ROC curve for MDK, OPN and AFP for all patients with HCC (n = 86) versus patients with cirrhosis (n = 86) or chronic liver disease (n = 86). B) ROC curve for MDK, OPN and AFP for all patients with early stage (BCLC 0-A) HCC (n = 36) versus patients with cirrhosis (n = 36) or chronic liver disease (n = 36). C) ROC curve for MDK, OPN and AFP for all patients with HCV-related HCC (n = 42) versus all patients with HCV-related cirrhosis (n = 43). D) ROC curve for MDK, OPN and AFP for all patients with HBV-related HCC (n = 14) versus all patients with HBV-related cirrhosis (n = 23) or chronic hepatitis B (n = 86). E) ROC curve for MDK, OPN and AFP for all patients with NASH-related HCC (n = 16) versus all patients with NASH-related cirrhosis (n = 10). Abbreviations: ROC, receiver operating characteristics; MDK, midkine; OPN, osteopontin; DKK1, dickopff-1; AFP, alpha-fetoprotein; HCC, hepatocellular carcinoma; CLD, chronic liver disease; HBV, hepatitis B virus; HCV, hepatitis C virus; NASH, non-alcoholic steatohepatitis.</p

Summary data of publicly-available WES datasets used in this study.

<p>Summary data of publicly-available WES datasets used in this study.</p

Accumulation of Deleterious Passenger Mutations Is Associated with the Progression of Hepatocellular Carcinoma

<div><p>In hepatocellular carcinoma (HCC), somatic genome-wide DNA mutations are numerous, universal and heterogeneous. Some of these somatic mutations are drivers of the malignant process but the vast majority are passenger mutations. These passenger mutations can be deleterious to individual protein function but are tolerated by the cell or are offset by a survival advantage conferred by driver mutations. It is unknown if these somatic deleterious passenger mutations (DPMs) develop in the precancerous state of cirrhosis or if it is confined to HCC. Therefore, we studied four whole-exome sequencing datasets, including patients with non-cirrhotic liver (n = 12), cirrhosis without HCC (n = 6) and paired HCC with surrounding non-HCC liver (n = 74 paired samples), to identify DPMs. After filtering out putative germline mutations, we identified 187±22 DPMs per non-diseased tissue. DPMs number was associated with liver disease progressing to HCC, independent of the number of exonic mutations. Tumours contained significantly more DPMs compared to paired non-tumour tissue (258–293 per HCC exome). Cirrhosis- and HCC-associated DPMs do not occur predominantly in specific genes, chromosomes or biological pathways and the effect on tumour biology is presently unknown. Importantly, for the first time we have shown a significant increase in DPMs with HCC.</p></div

Bioinformatics analysis pipeline.

<p>Each resultant data file is indicated by a sloped rectangle and each process represented by a square rectangle. Our pipeline contains 3 stages: alignment and calibration; variant calling and filtering; and variants annotation and filtration of putative germline mutations.</p

Hypothetical model of HCC progression.

<p>HCC progression is presented here as multiple waves of driver sweeps within hepatocyte subclones. The equilibrium between DPM accumulation and negative selection on the hepatocyte subclones are shown in the top row. A schematic model of the liver (with each circle representing a hepatocyte and the colour gradient representing the DPM load within each hepatocyte) is shown in the centre row. The average DPM load for the tissue is depicted in the bottom row.</p

Summary statistics for normalised DPMs between datasets.

<p>Summary statistics for normalised DPMs between datasets.</p