In the new area of noninvasive markers of hepatocellular carcinoma

Investigation of circulating natural autoantibodies against ANXA1 and MYC as potential biomarkers in hepatocellular carcinoma

PURPOSE

In this study, we examined novel autoantibodies targeting tumor-associated antigens (TAAs) as biomarkers for clinical assessment of hepatocellular carcinoma (HCC) in a Chinese population.

METHODS AND METHODS

A total of 119 patients with HCC and 130 healthy control (HC) volunteers who were age and gender matched were enrolled. The levels of circulating IgG antibodies were detected using an enzyme-linked immunosorbent test (ELISA) developed in-house with linear peptide antigens derived from Annexin A1(ANXA1) and proto-oncogene protein (MYC). The significant level was set at P ​< ​0.025 as two tests were performed.

RESULTS

In comparison to the HC group, plasma level of ANXA1 autoantibodies was significantly elevated in HCC patients (t ​= ​-3.174, P ​= ​0.002) but the change of plasma MYC autoantibody levels failed to reach the significance level (P ​> ​0.025). There was a significant increase in these two plasma IgG autoantibodies in male HCC patients (ANXA1: t ​= ​-3.590, P ​< ​0.001; MYC: t ​= ​-2.706, P ​= ​0.007). Pearson correlation analysis demonstrated that both anti-ANXA1 and anti-MYC IgG levels had a positive correlation with BCLC staging (both P ​< ​0.025) but a negative correlation with plasma albumin (Alb) (both P ​< ​0.025). The area under the ROC curve (AUC) values were 0.613 for anti-ANXA1 IgG assay and 0.567 for anti-MYC IgG assay. The anti-ANAXA1 IgG assay showed a high sensitivity of 31.4 ​% against the specificity of 90.0 ​% for detection of BCLC stages C ​+ ​D.

CONCLUSIONS

Plasma anti-ANXA1 and anti-MYC autoantibodies are likely to serve as a potential biomarker for clinical assessment of HCC prognosis, particularly in male patients.

Establishment of a Novel Mouse Hepatocellular Carcinoma Model for Dynamic Monitoring of Tumor Development by Bioluminescence Imaging

In this study, a novel mouse model of hepatocellular carcinoma (HCC) was established by simultaneously knocking out Pten and p53 suppressor genes and overexpressing c-Met and △90-β-catenin proto-oncogenes in the livers of mice via hydrodynamic injection (HDI). The mutations were introduced using the CRISPR/Cas9 and Sleeping Beauty transposon systems. In this way, a primary liver cancer model was established within six weeks. In addition, macrophages expressing arginase-1(Arg1) promoter coupled with firefly luciferase were engineered for bioluminescence imaging (BLI) of the tumor microenvironment. This novel, rapidly-generated model of primary hepatocellular carcinoma can be monitored noninvasively, which can facilitate not only applications of the model, but also the development of new drugs and treatment strategies of HCC.

A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody-antigen system

Hepatocellular carcinoma (HCC) is a malignancy with a dismal survival rate. The novel autoantibodies panel may provide new insights for the diagnosis of HCC. Biomarkers screened by two methods (bioinformatics and the antigen‐antibody system) were taken as candidate tumor‐associated antigens (TAAs). Enzyme‐linked immunosorbent assay was used to detect the corresponding autoantibodies in 888 samples of verification and validation cohorts. The verification cohort was used to verify the autoantibodies. Samples in the validation cohort were randomly divided into a train set and a test set with the ratio of 6:4. A diagnostic model was established by support vector machines within the train set. The test set further verified the model. Eleven TAAs were selected (AAGAB, C17orf75, CDC37L1, DUSP6, EID3, PDIA2, RGS20, PCNA, TAF7L, TBC1D13, and ZIC2). The titer of six autoantibodies (PCNA, AAGAB, CDC37L1, TAF7L, DUSP6, and ZIC2) had a significant difference in any of the pairwise comparisons among the HCC, liver cirrhosis, and normal control groups. The titer of these autoantibodies had an increasing tendency. Finally, an optimum diagnostic model was constructed with the six autoantibodies. The AUCs were 0.826 in the train set and 0.773 in the test set. The area under the curve (AUC) of this panel for diagnosing early HCC was 0.889. The diagnostic ability of the panel reduced with the progress of HCC. The positive rate of the panel in diagnosing alpha‐fetoprotein (AFP)‐negative patients was 75.6%. For early HCC, the sensitivity of the combination of AFP with the panel was 90.9% and superior to 53.2% of AFP alone. The novel immunodiagnosis panel combining AFP may be a new approach for the diagnosis of HCC, especially for early‐HCC cases.

Serological Biomarkers for Early Detection of Hepatocellular Carcinoma: A Focus on Autoantibodies against Tumor-Associated Antigens Encoded by Cancer Driver Genes

Substantial evidence manifests the occurrence of autoantibodies to tumor-associated antigens (TAAs) in the early stage of hepatocellular carcinoma (HCC), and previous studies have mainly focused on known TAAs. In the present study, protein microarrays based on cancer driver genes were customized to screen TAAs. Subsequently, autoantibodies against selected TAAs in sera were tested by enzyme-linked immunosorbent assays (ELISA) in 1175 subjects of three independent datasets (verification dataset, training dataset, and validation dataset). The verification dataset was used to verify the results from the microarrays. A logistic regression model was constructed within the training dataset; seven TAAs were included in the model and yielded an area under the receiver operating characteristic curve (AUC) of 0.831. The validation dataset further evaluated the model, exhibiting an AUC of 0.789. Remarkably, as the aggravation of HCC increased, the prediction probability (PP) of the model tended to decrease, the trend of which was contrary to alpha-fetoprotein (AFP). For AFP-negative HCC patients, the positive rate of this model reached 67.3% in the training dataset and 50.9% in the validation dataset. Screening TAAs with protein microarrays based on cancer driver genes is the latest, fast, and effective method for finding indicators of HCC. The identified anti-TAA autoantibodies can be potential biomarkers in the early detection of HCC.

Relationship between platelet-based models and the prognosis of patients with malignant hepatic tumors

Platelets (PLTs) are involved in tumor growth, metabolism and vascular activation. PLT-based models have been reported to have significant value on the recurrence of malignant hepatic tumors. The present study aimed to investigate the effect of PLT count and 18 PLT-based models on the prognosis of patients with malignant hepatic tumors. The clinical data from 189 patients with malignant hepatic tumors were retrospectively analyzed and used to calculate the scores of the 18 PLT-based models. Receiver operating characteristic curve was used to determine the suitable cut-off values of mortality and recurrence in patients with malignant hepatic tumors. The overall survival and cumulative recurrence rates of patients were calculated using Kaplan-Meier survival curves and the difference was analyzed using log-rank test. Multivariate analysis was performed to determine the independent risk factors of recurrence-free survival and overall survival. In the present study, 11 models were considered as predictors of mortality (P<0.05) and six models were considered as predictors of recurrence (P<0.05). The results from multivariate analysis demonstrated that vascular cancer embolus, uric acid >231 µmol/l, hemoglobin >144 g/l and the Lok index model >0.695 were considered as independent risk factors of mortality (P<0.05). Furthermore, vascular cancer embolus, PLT to lymphocyte ratio (PLR) >175 and fibrosis-4 (FIB-4) >4.82 were independent factors of recurrence (P<0.05). In addition, the results from this study indicated that the Lok-index could be considered as a predictor of the overall survival rate. In conclusion, the FIB-4 and PLR model may be valuable for predicting the recurrence-free rate of patients with malignant hepatic tumors.

Tumor associated antigens or anti-TAA autoantibodies as biomarkers in the diagnosis of ovarian cancer: a systematic review with meta-analysis

OBJECTIVE

This systematic review aims to outline and summarize known tumor-associated antigens (TAAs) or anti-TAA autoantibodies and their diagnostic values in ovarian cancer (OC).

METHODS

A systematic literature search was conducted in two databases. Data were independently extracted and reviewed by two junior investigators and the disagreement was further resolved by consulting one of the senior investigators.

RESULTS

Sixty publications reporting 113 different TAAs or anti-TAA autoantibodies were included. The majority of the studies were conducted in western countries. CA125, p53 and HE4 were the most frequently tested TAAs in OC. Meta-analysis showed that there was a significant association between serum anti-p53 autoantibody and increased risk of OC.

CONCLUSION

Serum TAAs or anti-TAA autoantibodies are promising diagnostic biomarkers in the detection of OC. A customized mini-array of multiple TAAs may enhance the detection of anti-TAA autoantibodies in OC. Additional studies with sufficient number of OC patients and carefully selected controls are needed to further verify the results.

Using immunomic approach to enhance tumor-associated autoantibody detection in diagnosis of hepatocellular carcinoma

To explore the possibility of using a mini-array of multiple tumor-associated antigens (TAAs) as an approach to the diagnosis of hepatocellular carcinoma (HCC), 14 TAAs were selected to examine autoantibodies in sera from patients with chronic hepatitis, liver cirrhosis and HCC by immunoassays. Antibody frequency to any individual TAA in HCC varied from 6.6% to 21.1%. With the successive addition of TAAs to the panel of TAAs, there was a stepwise increase of positive antibody reactions. The sensitivity and specificity of 14 TAAs for immunodiagnosis of HCC was 69.7% and 83.0%, respectively. This TAA mini-array also identified 43.8% of HCC patients who had normal alpha-fetoprotein (AFP) levels in serum. In summary, this study further supports the hypothesis that a customized TAA array used for detecting anti-TAA autoantibodies can constitute a promising and powerful tool for immunodiagnosis of HCC and may be especially useful in patients with normal AFP levels.

Autoantibodies to tumor-associated antigens combined with abnormal alpha-fetoprotein enhance immunodiagnosis of hepatocellular carcinoma

The identification and characterization of tumor-associated antigens (TAAs) and their use in antigen mini-arrays for cancer immunodiagnosis has been of interest recently as an approach to cancer detection. In this study, autoantibodies in sera from a patient with HCC were used as probes to immunoscreen a HepG2 cDNA expression library for the identification of TAAs involved in malignant liver transformation. Recombinant proteins from two genes identified in this manner, Sui1 and RalA were expressed, purified and used as antigens in immunoassays to detect the presence of antibodies in sera from 77 patients with HCC, 30 with chronic hepatitis (CH), 30 with liver cirrhosis (LC) and 82 normal human sera (NHS). The prevalence of antibody to Sui1 and RalA in HCC were 11.7% (9/77) and 19.5% (15/77), respectively, which were significantly higher than prevalence in liver cirrhosis (3.3% and 3.3%), chronic hepatitis (0% and 0%) and normal human sera (0% and 0%). When Sui1 and RalA were added to a panel of eight other TAAs used in a previous study, the final cumulative prevalence of anti-TAA antibodies in HCC to the 10 TAA array was raised to 66.2% (51/77). The specificity for HCC compared with LC, CH and NHS, was 66.7%, 80.0%, and 87.8%, respectively. When anti-TAA was added to abnormal serum AFP as combined diagnostic markers, it raised the diagnostic sensitivity from 66.2% to 88.7%. AFP and anti-TAA were independent markers and the simultaneous use of these two markers significantly resulted in the increased sensitivity of HCC detection.

Identification of liver cancer-specific aptamers using whole live cells

Liver cancer is the third most deadly cancers in the world. Unfortunately, there is no effective treatment. One of the major problems is that most cancers are diagnosed in the later stage, when surgical resection is not feasible. Thus, accurate early diagnosis would significantly improve the clinical outcome of liver cancer. Currently, there are no effective molecular probes to recognize biomarkers that are specific for liver cancer. The objective of our current study is to identify liver cancer cell-specific molecular probes that could be used for liver cancer recognition and diagnosis. We applied a newly developed cell-SELEX (Systematic Evolution of Ligands by EXponential enrichment) method for the generation of molecular probes for specific recognition of liver cancer cells. The cell-SELEX uses whole live cells as targets to select aptamers (designed DNA/RNA) for cell recognition. In generating aptamers for liver cancer recognition, two liver cell lines were used: a liver cancer cell line BNL 1ME A.7R.1 (MEAR) and a noncancer cell line, BNL CL.2 (BNL). Both cell lines were originally derived from Balb/cJ mice. Through multiple rounds of selection using BNL as a control, we have identified a panel of aptamers that specifically recognize the cancer cell line MEAR with Kd in the nanomolar range. We have also demonstrated that some of the selective aptamers could specifically bind liver cancer cells in a mouse model. There are two major new results (compared with our reported cell-SELEX methodology) in addition to the generation of aptamers specifically for liver cancer. The first one is that our current study demonstrates that cell-based aptamer selection can select specific aptamers for multiple cell lines, even for two cell lines with minor differences (MEAR cell is derived from BNL by chemical inducement); and the second result is that cell-SELEX can be used for adhesive cells and thus open the door for solid tumor selection and investigation. The newly generated cancer-specific aptamers hold great promise as molecular probes for cancer early diagnosis and basic mechanism studies.