Contribution of biomarkers and imaging in the management of hepatocellular carcinoma

Predicting Overall Survival with Deep Learning from 18F-FDG PET-CT Images in Patients with Hepatocellular Carcinoma before Liver Transplantation

Positron emission tomography and computed tomography with 18F-fluorodeoxyglucose (18F-FDG PET-CT) were used to predict outcomes after liver transplantation in patients with hepatocellular carcinoma (HCC). However, few approaches for prediction based on 18F-FDG PET-CT images that leverage automatic liver segmentation and deep learning were proposed. This study evaluated the performance of deep learning from 18F-FDG PET-CT images to predict overall survival in HCC patients before liver transplantation (LT). We retrospectively included 304 patients with HCC who underwent 18F-FDG PET/CT before LT between January 2010 and December 2016. The hepatic areas of 273 of the patients were segmented by software, while the other 31 were delineated manually. We analyzed the predictive value of the deep learning model from both FDG PET/CT images and CT images alone. The results of the developed prognostic model were obtained by combining FDG PET-CT images and combining FDG CT images (0.807 AUC vs. 0.743 AUC). The model based on FDG PET-CT images achieved somewhat better sensitivity than the model based on CT images alone (0.571 SEN vs. 0.432 SEN). Automatic liver segmentation from 18F-FDG PET-CT images is feasible and can be utilized to train deep-learning models. The proposed predictive tool can effectively determine prognosis (i.e., overall survival) and, thereby, select an optimal candidate of LT for patients with HCC.

The prominence of potential biomarkers in the diagnosis and management of hepatocellular carcinoma: Current scenario and future anticipation

Hepatocellular carcinoma (HCC) is one of the most aggressive and truculent types of cancer. Early detection of HCC is a massive concern that can boost the overall survival rates of HCC patients. As a result, there is a continual quest for advancements in screening, diagnosis, and treatment strategies to enhance the prognosis at its early stages. However, the confluence of inflammation and cirrhosis hampers the early detection of HCC. The analysis of different types of biomarkers such as tissue biomarkers, serum biomarkers, protein biomarkers, autoantibody markers, and improved imaging techniques has played a vital role in ameliorating HCC monitoring responses. Therefore biomarkers that can identify HCC early with a high degree of sensitivity and specificity might be prodigiously serviceable in the diagnosis and treatment of this notorious disorder. This study offers an overview of the contemporary understanding of several types of biomarkers implicated in hepatocarcinogenesis and their applications in monitoring, diagnosis, and prognosis presage. In additament, we address the role of image techniques associated with HCC diagnosis.

Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), one of the leading causes of cancer deaths in the world, is offering a challenge to human beings, with the current modes of treatment being a palliative approach. Lack of proper curative or preventive treatment methods encouraged extensive research around the world with an aim to detect a vaccine or therapeutic target biomolecule that could lead to development of a drug or vaccine against HCC. Biomarkers or biological disease markers have emerged as a potential tool as drug/vaccine targets, as they can accurately diagnose, predict, and even prevent the diseases. Biomarker expression in tissue, serum, plasma, or urine can detect tumor in very early stages of its development and monitor the cancer progression and also the effect of therapeutic interventions. Biomarker discoveries are driven by advanced techniques, such as proteomics, transcriptomics, whole genome sequencing, micro- and micro-RNA arrays, and translational clinics. In this review, an overview of the potential of tissue- and serum-associated HCC biomarkers as diagnostic, prognostic, and therapeutic targets for drug development is presented. In addition, we highlight recently developed micro-RNA, long noncoding RNA biomarkers, and single-nucleotide changes, which may be used independently or as complementary biomarkers. These active investigations going on around the world aimed at conquering HCC might show a bright light in the near future.

Using aptamers to elucidate esophageal cancer clinical samples

The epithelial cell adhesion molecule (EpCAM) is closely correlated with the occurrence and development of various cancers of epithelial origin. This study tested, for the first time, the ability of EpCAM aptamer SYL3C to detect EpCAM expression in 170 cases of esophageal cancer (EC) and precancerous lesions, as well as 20 cases of EC series samples, using immunofluorescence imaging analysis. Corresponding antibodies were used as control. EpCAM overexpression was 98% in both esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EACA) and 100% in metastasis, but no EpCAM overexpression was detected in undifferentiated EC (UEC). Significant differences were noted among various stages of differentiation (p < 0.05) with the degree of differentiation inversely correlated with the expression of EpCAM. Overexpressed EpCAM was detected in severe dysplasia, but negative in mild to moderate dysplasia and benign esophageal lesions. In a competitive binding experiment, EpCAM aptamer generated a staining pattern similar to that of antibody, but the binding sites with EpCAM were different. Based on these results, it can be concluded that EpCAM is suitable for use as an EC biomarker, therapeutic target, and effective parameter for tumor transfer and prognosis evaluation by aptamer SYL3C staining.

Evaluation of antiangiogenic efficacy in advanced hepatocellular carcinoma: Biomarkers and functional imaging

Many years after therapeutic wilderness, sorafenib finally showed a clinical benefit in patients with advanced hepatocellular carcinoma. After the primary general enthusiasm worldwide, some disappointments emerged particularly since no new treatment could exceed or at least match sorafenib in this setting. Without these new drugs, research focused on optimizing care of patients treated with sorafenib. One challenging research approach deals with identifying prognostic and predictive biomarkers of sorafenib in this population. The task still seems difficult; however appropriate investigations could resolve this dilemma, as observed for some malignancies where other drugs were used.

Using DNA aptamer probe for immunostaining of cancer frozen tissues

Tissue immunostaining is critically important in clinical applications, and antibodies have been used extensively as the molecular probes. Recently, aptamer, as a new class of probes, have attracted much attention for their potential clinical and research value. Epithelial cell adhesion molecule (EpCAM) is a specific biomarker which is overexpressed in many cancers of epithelial origin. Here, a DNA-based EpCAM aptamer SYL3C is reported as a probe for the immunostaining of frozen and paraffin-embedded sections of colorectal cancer tissues. Commercialized EpCAM antibodies were also used as a standard control. EpCAM aptamer SYL3C specifically recognized and immunostained cancer nests of colorectal tumor sections, but it neither reacted with background cells within tumor sites nor exhibited cross-reaction to the benign lesions or inflammation of colorectal tissues. No cross-linking to EpCAM-negative malignant tumor sections occurred. Compared with standard antibody staining, our EpCAM aptamer SYL3C protocol is simpler to implement with a shorter reaction time. Moreover, SYL3C can specifically bind with either frozen or paraffin-embedded tissue sections. Since the histopathology of frozen tissue is closer to that of fresh tissue and since frozen sections can be produced more quickly than paraffin-embedded sections, SYL3C immunostaining of frozen sections is a quick protocol that is easy to implement.

Metastatic hepatocellular carcinoma: when surgery and successive palliative treatments lead to remission

Hepatocellular carcinoma (HCC) is the third leading cause of death by cancer worldwide. The prognosis of patients with metastatic HCC remains limited, with an expected median survival lower than 50% at 1 year. Here, we report the case of a 63-year-old man who suffered from a small HCC in the liver and a large unique metastasis in the right adrenal gland. A surgical resection of both lesions was performed. Seven months later, HCC recurred with an isolated right renal metastatic lymphadenopathy and a high alpha-fetoprotein level. HCC was brought under control by sorafenib; the alpha-fetoprotein level was greatly reduced but remained moderately elevated and stable over 2 years after the onset of chemotherapy. Additional external radiotherapy on the metastatic lymphadenopathy led to a normalization of the alpha-fetoprotein level and discontinuation of sorafenib treatment. One year after the end of radiotherapy, a second isolated metastasis occurred in the right lung. This tumor was surgically removed. Twenty-one months after this second surgical procedure, i.e., more than 5.5 years after the initial diagnosis of metastatic HCC, the patient was asymptomatic and tumor free.

Monoclonal antibody preparation and expression profile analysis of a novel hepatoma associated gene

Hepatoma associated gene (HTA), a gene screened and cloned by our previous research, was specifically expressed in certain kinds of tumors and had a cancer-promoting role in hepatocellular carcinoma (HCC). To further elucidate the mechanism of HTA in hepatoma carcinogenesis and its potential role as a cancer biomarker, refolded HTA protein (HTA) was obtained by prokaryotic recombinant expression system and immobilized metal affinity chromatography. Then anti-HTA monoclonal antibody (mAb) was produced by hybridoma technique. Using the high titer anti-HTA mAb with high specificity obtained, the expression profile of HTA was analysed by immunohistochemistry staining. It showed that HTA expressed specifically in some kinds of tumors, and didn't express in almost any of the normal tissues. The positive expression rate and expression quantity of HTA was significantly higher in HCC tissues than in hepatic cirrhosis tissues, hepatic fibrosis tissues and normal hepatic tissues. The expression of HTA was positively correlated with hepatoma carcinogenic process.

Selection of DNA aptamers against epithelial cell adhesion molecule for cancer cell imaging and circulating tumor cell capture

Epithelial cell adhesion molecule (EpCAM) is overexpressed in most solid cancers and is an ideal antigen for clinical applications in cancer diagnosis, prognosis, imaging, and therapy. Currently, most of the EpCAM-based diagnostic, prognostic, and therapeutic strategies rely on the anti-EpCAM antibody. However, the use of EpCAM antibody is restricted due to its large size and instability. In this study, we have successfully identified DNA aptamers that selectively bind human recombinant EpCAM protein. The aptamers can specifically recognize a number of live human cancer cells derived from breast, colorectal, and gastric cancers that express EpCAM but not bind to EpCAM-negative cells. Among the aptamer sequences identified, a hairpin-structured sequence SYL3 was optimized in length, resulting in aptamer sequence SYL3C. The Kd values of the SYL3C aptamer against breast cancer cell line MDA-MB-231 and gastric cancer cell line Kato III were found to be 38 ± 9 and 67 ± 8 nM, respectively, which are better than that of the full-length SYL3 aptamer. Flow cytometry analysis results indicated that the SYL3C aptamer was able to recognize target cancer cells from mixed cells in cell media. When used to capture cancer cells, up to 63% cancer cell capture efficiency was achieved with about 80% purity. With the advantages of small size, easy synthesis, good stability, high binding affinity, and selectivity, the DNA aptamers reported here against cancer biomarker EpCAM will facilitate the development of novel targeted cancer therapy, cancer cell imaging, and circulating tumor cell detection.

Molecular profiles of HCV cirrhotic tissues derived in a panel of markers with clinical utility for hepatocellular carcinoma surveillance

BACKGROUND

Early hepatocellular carcinoma (HCC) detection is difficult because low accuracy of surveillance tests. Genome-wide analyses were performed using HCV-cirrhosis with HCC to identify predictive signatures.

METHODOLOGY/PRINCIPAL FINDINGS

Cirrhotic liver tissue was collected from 107 HCV-infected patients with diagnosis of HCC at pre-transplantation and confirmed in explanted livers. Study groups included: 1) microarray hybridization set (n = 80) including patients without (woHCC = 45) and with (wHCC = 24) HCC, and with incidental HCC (iHCC = 11); 2) independent validation set (n = 27; woHCC = 16, wHCC = 11). Pairwise comparisons were performed using moderated t-test. FDR<1% was considered significant. L(1)-penalized logistic regression model was fit for woHCC and wHCC microarrays, and tested against iHCC. Prediction model genes were validated in independent set by qPCR. The genomic profile was associated with genetic disorders and cancer focused on gene expression, cell cycle and cell death. Molecular profile analysis revealed cell cycle progression and arrest at G2/M, but progressing to mitosis; unregulated DNA damage check-points, and apoptosis. The prediction model included 17 molecules demonstrated 98.6% of accuracy and correctly classified 6 out of 11 undiagnosed iHCC cases. The best model performed even better in the additional independent set.

CONCLUSIONS/SIGNIFICANCES

The molecular analysis of HCV-cirrhotic tissue conducted to a prediction model with good performance and high potential for HCC surveillance.

Biomarkers for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) ranks high among the most common and fatal cancers in the world. HCC develops from chronic liver diseases, especially from hepatitis C virus-related and hepatitis B virus (HBV)-related liver diseases. In this sense, useful biomarkers for HCC detection for the patients at risk of HCC are quite important. Recently, new therapies for HCC have been developed, and the prognosis of the patients has improved. However, considering the recurrence rate of HCC after treatment is very high, biomarkers that detect recurrence at an early stage are also required. In addition, since new drugs such as multikinase inhibitors have been introduced to the clinical scene, surrogate biomarkers to predict the effectiveness of treatment will be required in the near future. So far, many biomarkers for HCC have been developed, and their clinical usefulness has been assessed. As a result, several biomarkers for HCC are widely used. However, investigations to discover more useful biomarkers that fit in clinical settings are under way. In this review article, biomarkers for HCC are overviewed to examine their clinical usefulness.

Biomarkers for hepatocellular carcinoma

The hepatocellular carcinoma (HCC) is one of the most common malignant tumors and carries a poor survival rate. The management of patients at risk for developing HCC remains challenging. Increased understanding of cancer biology and technological advances have enabled identification of a multitude of pathological, genetic, and molecular events that drive hepatocarcinogenesis leading to discovery of numerous potential biomarkers in this disease. They are currently being aggressively evaluated to establish their value in early diagnosis, optimization of therapy, reducing the emergence of new tumors, and preventing the recurrence after surgical resection or liver transplantation. These markers not only help in prediction of prognosis or recurrence but may also assist in deciding appropriate modality of therapy and may represent novel potential targets for therapeutic interventions. In this paper, a summary of most relevant available data from published papers reporting various tissue and serum biomarkers involved in hepatocellular carcinoma was presented.