Modeling the time-related fluctuations of AFP and PIVKA-II serum levels in patients with cirrhosis undergoing surveillance for hepatocellular carcinoma

Serial increase and high alpha-fetoprotein levels predict the development of hepatocellular carcinoma in 6 months

AIM

Alpha-fetoprotein (AFP) checkup with abdominal ultrasonography for hepatocellular carcinoma (HCC) surveillance remains controversial. We evaluated a serial AFP-increase and high AFP levels in the prediction of HCC.

METHODS

At-risk patients with chronic liver disease underwent HCC surveillance with trimonthly AFP measurement were included and categorized into HCC and non-HCC groups. Their AFP levels at 12, 9, and 6 months (-6M) before the outcome date were evaluated. Group-based trajectory analysis and multivariable regression analysis were performed to identify AFP trajectories as risk predictors for HCC.

RESULTS

Overall, 2776 patients were included in the HCC (n = 326) and non-HCC (n = 2450) groups. Serial AFP levels were significantly higher in the HCC than the non-HCC groups. Trajectory analysis identified AFP-increase group (11%) increased 24-fold risks of HCC compared with the AFP-stable (89%) group. Compared with patients without the AFP-increase, a serial 3-month AFP-increase ≥10% elevated HCC risk by 12.1-fold (95% CI: 6.5-22.4) in 6 months, and the HCC risks increased 13-60 fold in patients with cirrhosis, hepatitis B, or C receiving antiviral therapy, or AFP levels <20 ng/ml. Combining serial AFP-increase ≥10% and AFP ≥20 ng/ml at -6M significantly increased 41.7-fold (95% CI: 13.8-126.2) HCC risks. In patients who underwent biannual AFP checkups, those with both 6-month AFP-increase ≥10% and AFP ≥20 ng/ml increased 22.1-fold (95% CI: 12.52-39.16) HCC risks in 6 months. Most HCCs were detected at an early stage.

CONCLUSIONS

Serial 3-6-month AFP-increase of ≥10% previously and AFP level of ≥20 ng/ml significantly increased HCC risks in 6 months.

Identification of the Best Cut-Off Value of PIVKA-II for the Surveillance of Patients at Risk of Hepatocellular Carcinoma Development

Patients with cirrhosis are at risk of hepatocellular carcinoma (HCC) development and, according to current guidelines, should undergo surveillance by ultrasound at six month intervals. Due to the known limitations of surveillance strategies based on ultrasonography, the use of tumor biomarkers, although debated, is common practice in many centers. The aim of the study was to identify the best cut-off value for one of such biomarkers, protein induced by vitamin K absence, or antagonist-II (PIVKA-II). We retrospectively enrolled 1187 patients with liver cirrhosis: 205 with a diagnosis of HCC (median age 67 years, 81.0% males) and 982 without tumor (median age 64 years, 56.2% males). During a median follow-up (FU) of 34.6 (11.4−43.7) months, 118 out of 982 (12.0%) patients developed HCC. Serum PIVKA-II was assessed by chemiluminescence immunoassay on the Lumipulse® G600 II platform (Fujirebio, Tokyo, Japan). In the overall cohort (n = 1187), PIVKA-II showed an area under the curve (AUC) of 0.802 for HCC detection. The best cut-off value that maximized sensitivity was 50 mAU/mL (sensitivity = 80%, specificity = 64%). In the 982 patients without HCC at baseline, PIVKA-II > 50 mAU/mL was associated with an increased risk of HCC development during the FU (HR = 1.74, 95% CI 1.21−2.51; p = 0.003)). In conclusion, the evaluation of serum PIVKA-II showed a good performance for HCC detection; a cut-off value > 50 mAU/mL could be suitable for the surveillance of patients who are at risk of developing HCC.

Liver Cancer-Specific Isoform of Serine Protease Inhibitor Kazal for the Detection of Hepatocellular Carcinoma: Results from a Pilot Study in Patients with Dysmetabolic Liver Disease

Reliable non-invasive biomarkers for the surveillance of patients at risk of hepatocellular carcinoma (HCC) development represent an unmet medical need. Recently, the liver-cancer-specific isoform of serine protease inhibitor Kazal (LC-SPIK) has been proposed as a valuable biomarker for the detection of HCC in patients with chronic liver disease of viral etiology. In the present study, we assessed the diagnostic accuracy of LC-SPIK, alone or in combination with standard serologic biomarkers (i.e., alpha-fetoprotein and protein induced by vitamin K absence or antagonist-II, PIVKA-II), for the detection of HCC among patients with dysmetabolic liver disease. A total of 120 patients with non-alcoholic fatty liver disease (NAFLD), including 62 patients with a diagnosis of HCC and 58 with cirrhosis but without tumor, were retrospectively analyzed. The serum levels of LC-SPIK were measured by enzyme-linked immunosorbent assay (ImCare Biotech, Doylestown, PA). The serum LC-SPIK values were significantly different between patients with HCC (24.3, 17.6−39.8 ng/mL) and those with cirrhosis but without tumor (11.7, 8.7−18.2 ng/mL) (p < 0.001). By receiver operating characteristic curve analysis, we observed an area under the curve (AUC) of 0.841 for the detection of HCC; the combination with PIVKA-II further increased the accuracy to AUC = 0.926 (cross-validation). The promising results observed in the present pilot study foster additional research to investigate the usefulness of LC-SPIK for the stratification of the risk of HCC development in patients with NAFLD and advanced liver disease.

Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy

Extracellular vesicles (EVs) are abundantly released into the systemic circulation, where they show remarkable stability and harbor molecular constituents that provide biochemical information about their cells of origin. Due to this characteristic, EVs are attracting increasing attention as a source of circulating biomarkers for cancer liquid biopsy and personalized medicine. Despite this potential, none of the discovered biomarkers has entered the clinical practice so far, and novel approaches for the label-free characterization of EVs are highly demanded. In this regard, Fourier Transform Infrared Spectroscopy (FTIR) has great potential as it provides a quick, reproducible, and informative biomolecular fingerprint of EVs. In this pilot study, we investigated, for the first time in the literature, the capability of FTIR spectroscopy to distinguish between EVs extracted from sera of cancer patients and controls based on their mid-IR spectral response. For this purpose, EV-enriched suspensions were obtained from the serum of patients diagnosed with Hepatocellular Carcinoma (HCC) of nonviral origin and noncancer subjects. Our data point out the presence of statistically significant differences in the integrated intensities of major mid-IR absorption bands, including the carbohydrate and nucleic acids band, the protein amide I and II bands, and the lipid CH stretching band. Additionally, we used Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) for the automated classification of spectral data according to the shape of specific mid-IR spectral signatures. The diagnostic performances of the proposed spectral biomarkers, alone and combined, were evaluated using multivariate logistic regression followed by a Receiving Operator Curve analysis, obtaining large Areas Under the Curve (AUC = 0.91, 95% CI 0.81–1.0). Very interestingly, our analyses suggest that the discussed spectral biomarkers can outperform the classification ability of two widely used circulating HCC markers measured on the same groups of subjects, namely alpha-fetoprotein (AFP), and protein induced by the absence of vitamin K or antagonist-II (PIVKA-II).

Surveillance for hepatocellular carcinoma: current status and future perspectives for improvement

INTRODUCTION

Hepatocellular carcinoma (HCC) is a globally relevant medical problem. Fortunately, risk factors for this tumor have been identified, and surveillance protocols developed. Patients with liver cirrhosis have the highest risk of developing HCC and have historically been included in surveillance programs. Special categories have also emerged in recent years, especially patients with eradicated HCV infection or nonalcoholic fatty liver disease. Novel serum biomarkers and magnetic resonance imaging protocols are currently being proposed to refine existing surveillance protocols.

AREAS COVERED

We discuss the rationale of surveillance programs for HCC and report the most recent recommendations from international guidelines about this topic. Gray areas, such as nonalcoholic fatty liver disease and the role of intrahepatic cholangiocellular carcinoma, are also discussed.

EXPERT OPINION

Surveillance is recognized as a tool to favor early diagnosis of HCC, access to curative treatment, and increase survival, even if the supporting evidence is mainly based on observational studies. As new randomized clinical trials are difficult to propose, future challenges will include optimizing implementation in the primary care setting and a more personalized approach, balancing the opportunities and risks of overdiagnosis of novel techniques and biomarkers.

Prothrombin induced by vitamin K absence or antagonist-II and alpha foetoprotein to predict development of hepatocellular carcinoma in Caucasian patients with hepatitis C-related cirrhosis treated with direct-acting antiviral agents

BACKGROUND

Prothrombin induced by vitamin K absence or antagonist-II (PIVKA-II) and alpha fetoprotein (AFP) are biomarkers for hepatocellular carcinoma (HCC). However, their performance in patients with cirrhosis related to hepatitis C virus (HCV) treated with direct-acting antiviral agents (DAA) is unknown.

AIM

To evaluate PIVKA-II and AFP as HCC predictors in DAA-treated patients with HCV-related cirrhosis METHODS: In this single centre study, patients with cirrhosis from chronic HCV infection and with a sustained virological response (SVR) to DAA were tested for PIVKA-II and AFP (Fujirebio, Japan) at the start of DAA treatment (baseline), end of treatment (EOT) and at HCC diagnosis.

RESULTS

We included 400 patients with mean age 65 (24-92); 56% were men. From baseline to EOT, PIVKA-II did not change (35 vs 35 mAU/mL, P = 0.43) while AFP significantly decreased (12 vs 6 ng/mL, P < 0.0001). After 52 (3-66) months from baseline, 34 (8.5%) patients developed de novo HCC; median AFP 9 (2-12 868) ng/mL and PIVKA-II 80 (22-1813) mAU/mL. EOT-PIVKA-II (HR 3.05, P < 0.0001) and AFP (HR 2.77, P = 0.001) independently predicted HCC together with diabetes (HR 6.12, P < 0.001) and GGT (HR 1.01, P = 0.03). The 4-year cumulative probability of HCC was 24% vs 2% in patients with EOT-PIVKA-II > or ≤41 mAU/mL (P < 0.0001), and 26% vs 9% for EOT-AFP > or ≤15 ng/mL (P = 0.02). By combining EOT-PIVKA-II and AFP, the 4-year probabilities of HCC were 3% in patients testing negative for both markers, 18% in patients positive for both, and 38% in patients positive for at least one (P < 0.0001).

CONCLUSIONS

In patients with HCV-related cirrhosis treated with DAA, PIVKA-II and AFP independently predicted HCC, while their combination improved risk stratification.

Progression of Prothrombin Induced by Vitamin K Absence-II in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer and the third leading cause of cancer-related death worldwide. Due to the lack of efficient tools for early detection, asymptomatic HCC patients are diagnosed at an advanced stage, leading to a poor prognosis. To improve survival, serum biomarker prothrombin induced by vitamin K absence-II (PIVKA-II) was under investigation. PIVKA-II is an abnormal protein produced in HCC. The coagulation function was insufficient due to the lack of Gla residues. Elevated PIVKA-II was associated with bad tumor behavior in terms of proliferation, metastasis, and invasion. Three major signaling pathways were proposed to clarify the mechanism. With the advantages including affordability, minimal invasiveness, convenience, and efficiency, PIVKA-II could improve HCC management consisting of four aspects. First, PIVKA-II was an effective and dynamic tool for improving HCC surveillance in high-risk population. Changes in the serum levels of PIVKA-II provided valuable molecular alteration information before imaging discovery. Second, PIVKA-II offered a complementary approach for HCC early detection. Compared to traditional diagnostic approaches, the combination of PIVKA-II and other biomarkers had better performance. Third, PIVKA-II was an indicator for the assessment of response to treatment in HCC. Preoperative assessment was for selecting personalized therapy, and postoperative measurement was for assessing treatment efficacy. Fourth, PIVKA-II was considered as a prognostic predictor for HCC. Patients with elevated PIVKA-II were more likely to develop microvascular invasion, metastasis, and recurrence.

Validation and update of a multivariable prediction model for the identification and management of patients at risk for hepatocellular carcinoma

Background

A hepatocellular carcinoma (HCC) prediction model (ASAP), including age, sex, and the biomarkers alpha-fetoprotein and prothrombin induced by vitamin K absence-II, showed potential clinical value in the early detection of HCC. We validated and updated the model in a real-world cohort and promoted its transferability to daily clinical practice.

Methods

This retrospective cohort analysis included 1012 of the 2479 eligible patients aged 35 years or older undergoing surveillance for HCC. The data were extracted from the electronic medical records. Biomarker values within the test-to-diagnosis interval were used to validate the ASAP model. Due to its unsatisfactory calibration, three logistic regression models were constructed to recalibrate and update the model. Their discrimination, calibration, and clinical utility were compared. The performance statistics of the final updated model at several risk thresholds are presented. The outcomes of 855 non-HCC patients were further assessed during a median of 10.2 months of follow-up. Statistical analyses were performed using packages in R software.

Results

The ASAP model had superior discriminative performance in the validation cohort [C-statistic = 0.982, (95% confidence interval 0.972–0.992)] but significantly overestimated the risk of HCC (intercept − 3.243 and slope 1.192 in the calibration plot), reducing its clinical usefulness. Recalibration-in-the-large, which exhibited performance comparable to that of the refitted model revision, led to the retention of the excellent discrimination and substantial improvements in the calibration and clinical utility, achieving a sensitivity of 100% at the median prediction probability of the absence of HCC (1.3%). The probability threshold of 1.3% and the incidence of HCC in the cohort (15.5%) were used to stratify the patients into low-, medium-, and high-risk groups. The cumulative HCC incidences in the non-HCC patients significantly differed among the risk groups (log-rank test, p-value < 0.001). The 3-month, 6-month and 18-month cumulative incidences in the low-risk group were 0.6%, 0.9% and 0.9%, respectively.

Conclusions

The ASAP model is an accurate tool for HCC risk estimation that requires recalibration before use in a new region because calibration varies with clinical environments. Additionally, rational risk stratification and risk-based management decision-making, e.g., 3-month follow-up recommendations for targeted individuals, helped improve HCC surveillance, which warrants assessment in larger cohorts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-021-09326-w.

Biomarkers of Oncogenesis, Adipose Tissue Dysfunction and Systemic Inflammation for the Detection of Hepatocellular Carcinoma in Patients with Nonalcoholic Fatty Liver Disease

Simple Summary

Circulating biomarkers for the detection of hepatocellular carcinoma in patients with dysmetabolic liver disease are an unmet need. In the present study, we observed that serum values of five biomarkers (namely, AFP, PIVKA-II, GPC-3, adiponectin and IL-6) were significantly different between patients with and without hepatocellular carcinoma; the best accuracy for the detection of tumor was achieved by PIVKA-II. Furthermore, we developed a model combining age, gender, PIVKA-II, GPC-3 and adiponectin that showed an excellent performance for the identification of patients with hepatocellular carcinoma. This model may be useful for the surveillance of patients with dysmetabolic liver disease at risk of hepatocellular carcinoma development.

Abstract

Current surveillance strategy for patients with nonalcoholic fatty liver disease (NAFLD) at risk of hepatocellular carcinoma (HCC) development is unsatisfactory. We aimed to investigate the diagnostic accuracy of alpha-fetoprotein (AFP), protein induced by vitamin K absence or antagonist-II (PIVKA-II), glypican-3 (GPC-3), adiponectin, leptin and interleukin-6 (IL-6), alone or in combination, for the discrimination between NAFLD patients with or without HCC. The biomarkers were investigated in a cohort of 191 NAFLD patients (median age 62, 54–68 years; 121 males and 70 females) with advanced fibrosis/cirrhosis, 72 of whom had a diagnosis of HCC. PIVKA-II showed the best performance for the detection of HCC with an area under the curve (AUC) of 0.853, followed by adiponectin (AUC = 0.770), AFP (AUC = 0.763), GPC-3 (AUC = 0.759) and by IL-6 (AUC = 0.731), while the leptin values were not different between patients with and without HCC. The accuracy of the biomarkers’ combination was assessed by a stratified cross-validation approach. The combination of age, gender, PIVKA-II, GPC-3 and adiponectin further improved the diagnostic accuracy (AUC = 0.948); the model correctly identified the 87% of the patients. In conclusion, we developed a model with excellent accuracy for the detection of HCC that may be useful to improve the surveillance of NAFLD patients at risk of tumor development.

Modeling Hepatocellular Carcinoma Cells Dynamics by Serological and Imaging Biomarkers to Explain the Different Responses to Sorafenib and Regorafenib

Simple Summary

Systemic therapy in advanced hepatocellular-carcinomas (HCC) has limited benefits, but some patients show partial responses (PR) and a few even a complete response (CR). Understanding the biological mechanisms could help clinicians in decision-making. Aim of this study was to develop a physic-mathematical model to investigate tumor dynamics using α-fetoprotein (AFP) and protein induced by vitamin K absence-II (PIVKA-II) measures combined with digital imaging. The model was set-up in three prototype patients with CR/PR to sorafenib and PR to regorafenib, and then applied in seven patients with different types of response. Overall, the rate constant of cancer cells production ranged between 0.250–0.372 C × day⁻¹. During therapy, neo-angiogenesis reduction was higher in four CR than in four PR or stable disease (SD) and in two non-responders (median: 83.2% vs. 29.4% vs. 2.0%). Tumor vasculature decay appeared accelerated in CR. We conclude that modeling serological and imaging biomarkers could help personalization of systemic therapy.

Abstract

In advanced HCC, tyrosine-kinase inhibitors obtain partial responses (PR) in some patients and complete responses (CR) in a few. Better understanding of the mechanism of response could be achieved by the radiomic approach combining digital imaging and serological biomarkers (α-fetoprotein, AFP and protein induced by vitamin K absence-II, PIVKA-II) kinetics. A physic-mathematical model was developed to investigate cancer cells and vasculature dynamics in three prototype patients receiving sorafenib and/or regorafenib and applied in seven others for validation. Overall four patients showed CR, two PR, two stable-disease (SD) and two progressive-disease (PD). The rate constant of cancer cells production was higher in PD than in PR-SD and CR (median: 0.398 vs. 0.325 vs. 0.316 C × day⁻¹). Therapy induced reduction of neo-angiogenesis was greater in CR than in PR-SD and PD (median: 83.2% vs. 29.4% and 2.0%), as the reduction of cell-proliferation (55.2% vs. 7.6% and 0.7%). An additional dose-dependent acceleration of tumor vasculature decay was also observed in CR. AFP and cancer cells followed the same kinetics, whereas PIVKA-II time/dose dependent fluctuations were influenced also by tissue ischemia. In conclusion, pending confirmation in a larger HCC cohort, modeling serological and imaging biomarkers could be a new tool for systemic therapy personalization.

Alpha-Fetoprotein, Protein Induced by Vitamin K Absence or Antagonist II and Glypican-3 for the Detection and Prediction of Hepatocellular Carcinoma in Patients with Cirrhosis of Viral Etiology

International guidelines recommend the use of ultrasound as a surveillance tool for hepatocellular carcinoma (HCC) in patients with cirrhosis, while the role of serum biomarkers is still debated. We investigated serum alpha-fetoprotein (AFP), protein induced by vitamin K absence or antagonist II (PIVKA-II) and glypican-3 (GPC-3) diagnostic accuracy for HCC detection and prediction in patients with liver cirrhosis of viral etiology under surveillance. A total of 349 patients (200 cirrhosis and 149 HCC) were enrolled. The 200 patients with cirrhosis consisted of 114 patients still HCC-free after 36 months of follow-up and 86 patients that developed HCC after 13.8 (11.0-19.8) months. AFP, PIVKA-II and GPC-3 were measured in serum samples collected at tumor diagnosis in the 149 patients with HCC, and at the beginning of follow-up in the 200 patients with cirrhosis. The higher performance for HCC detection was observed for PIVKA-II (area under the curve (AUC) = 0.790), followed by AFP (AUC = 0.737) and GPC-3 (AUC = 0.637); the combination of AFP + PIVKA-II improved the diagnostic accuracy to AUC = 0.822. Serum PIVKA-II values, but not AFP and GPC-3, were significantly higher in the 86 cirrhotics that developed HCC compared with the 114 cirrhotics still HCC-free after 36 months of follow-up (p = 0.020). PIVKA-II ≥ 55 mAU/mL allowed to identify patients with cirrhosis at higher risk of HCC development (Log-rank test, p < 0.001; adjusted Hazard Ratio = 1.99, p = 0.001). In conclusion, the measurement of PIVKA-II in patients with cirrhosis may be useful to tailor personalized surveillance strategies.