An efficient model for auxiliary diagnosis of hepatocellular carcinoma based on gene expression programming

High-throughput proteomics-guided biomarker discovery of hepatocellular carcinoma

Liver cancer stands as the fifth leading cause of cancer-related deaths globally. Hepatocellular carcinoma (HCC) comprises approximately 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients qualify for curative therapy, primarily due to the absence of reliable tools for early detection and prognosis of HCC. This underscores the critical need for molecular biomarkers for HCC management. Since proteins reflect disease status directly, proteomics has been utilized in biomarker developments for HCC. In particular, proteomics coupled with liquid chromatography-mass spectrometer (LC-MS) methods facilitate the process of discovering biomarker candidates for diagnosis, prognosis, and therapeutic strategies. In this work, we investigated LC-MS-based proteomics methods through recent reference reviews, with a particular focus on sample preparation and LC-MS methods appropriate for the discovery of HCC biomarkers and their clinical applications. We classified proteomics studies of HCC according to sample types, and we examined the coverage of protein biomarker candidates based on LC-MS methods in relation to study scales and goals. Comprehensively, we proposed protein biomarker candidates categorized by sample types and biomarker types for appropriate clinical use. In this review, we summarized recent LC-MS-based proteomics studies on HCC and proposed potential protein biomarkers. Our findings are expected to expand the understanding of HCC pathogenesis and enhance the efficiency of HCC diagnosis and prognosis, thereby contributing to improved patient outcomes.

2D, 3D-QSAR study and docking of vascular endothelial growth factor receptor 3 (VEGFR3) inhibitors for potential treatment of retinoblastoma

Background: Retinoblastoma is currently the most common malignant tumor seen in newborns and children's eyes worldwide, posing a life-threatening hazard. Chemotherapy is an integral part of retinoblastoma treatment. However, the chemotherapeutic agents used in clinics often lead to drug resistance. Thus there is a need to investigate new chemotherapy-targeted agents. VEGFR3 inhibitors are anti-tumour-growth and could be used to develop novel retinoblastoma-targeted agents. Objective: To predict drug activity, discover influencing factors and design new drugs by building 2D, 3D-QSAR models. Method: First, linear and non-linear QSAR models were built using heuristic methods and gene expression programming (GEP). The comparative molecular similarity indices analysis (COMISA) was then used to construct 3D-QSAR models through the SYBYL software. New drugs were designed by changing drug activity factors in both models, and molecular docking experiments were performed. Result: The best linear model created using HM had an R², S², and R²cv of 0.82, 0.02, and 0.77, respectively. For the training and test sets, the best non-linear model created using GEP had correlation coefficients of 0.83 and 0.72 with mean errors of 0.02 and 0.04. The 3D model designed using SYBYL passed external validation due to its high Q² (0.503), R² (0.805), and F-value (76.52), as well as its low standard error of SEE value (0.172). This demonstrates the model's reliability and excellent predictive ability. Based on the molecular descriptors of the 2D model and the contour plots of the 3D model, we designed 100 new compounds using the best active compound 14 as a template. We performed activity prediction and molecular docking experiments on them, in which compound 14.d performed best regarding combined drug activity and docking ability. Conclusion: The non-linear model created using GEP was more stable and had a more substantial predictive power than the linear model built using the heuristic technique (HM). The compound 14.d designed in this experiment has the potential for anti-retinoblastoma treatment, which provides new design ideas and directions for retinoblastoma-targeted drugs.

QSAR Research of Novel Tetrandrine Derivatives against Human Hepatocellular Carcinoma

BACKGROUND

The new tetrandrine derivative is an anti-human liver cancer cell inhibitor which can be used to design and develop anti-human-liver-cancer drugs.

OBJECTIVE

A quantitative structure-activity relationship (QSAR) model was established to predict the physical properties of new tetrandrine derivatives using their chemical structures.

METHODS

The best descriptors were selected through CODESSA software to build a multiple linear regression model. Then, gene expression programming (GEP) was used to establish a nonlinear quantitative QSAR model with descriptors to predict the activity of a series of novel tetrandrine chemotherapy drugs. The best active compound 31 was subjected to molecular docking experiments through SYBYL software with a small fragment of the protein receptor (PDB ID:2J6M).

RESULTS

Four descriptors were selected to build a multiple linear regression model with correlation coefficients R2, R2CV and S2 with the values of 0.8352, 0.7806 and 0.0119, respectively. The training and test sets with a correlation coefficient of 0.85 and 0.83 were obtained via an automatic problem-solving program (APS) using the four selected operators as parameters, with a mean error of 1.49 and 1.08. Compound 31 had a good docking ability with an overall score of 5.8892, a collision rate of -2.8004 and an extreme value of 0.9836.

CONCLUSION

The computer-constructed drug molecular model reveals the factors affecting the activity of human hepatocellular carcinoma cells, which provides directions and guidance for the development of highly effective anti-humanhepatocellular- carcinoma drugs in the future.

The Predictive Efficacy of Serum Exosomal microRNA-122 and microRNA-148a for Hepatocellular Carcinoma Based on Smart Healthcare

Objective

Hepatocellular carcinoma (HCC) remains a devastating tumor globally. Serum exosomes are reliable biomarkers for tumors, including HCC. Hence, this study explored the efficacy and mechanism of serum exosomes in HCC.

Methods

microRNA (miR)-122 and miR-148a expressions in serum exosomes from HCC patients and healthy subjects and their predictive efficacy for HCC were detected. Correlation between serum exosomal miR-122/148a expressions with survival rate, clinical stage, lymph node metastasis, and tumor differentiation level and levels of HCC-related serum markers (CA199, FucAFP, ALD-A, and AFu) were detected. PAX2 staining intensity and expression in HCC were measured. PAX2 predictive efficacy for HCC and its correlation with clinical stage, lymph node metastasis, tumor differentiation level, and HCC-related serum marker levels were analyzed. The targeted binding relationship between miR-122 and miR-148a and PAX2 was predicted and verified.

Results

Serum exosomal miR-122 and miR-148a expressions were downregulated in HCC, showing potent predictive efficacy for HCC, which was negatively related to clinical stage and lymph node metastasis and positively related to tumor differentiation level, patient survival rate, and HCC-related serum marker levels. PAX2 showed increased staining intensity and expression in HCC, together with high predictive efficacy for HCC. PAX2 expression showed a positive correlation with clinical stage and lymph node metastasis and a negative correlation with tumor differentiation level and HCC-related serum marker levels. miR-122 and miR-148a conjointly targeted PAX2 in HCC.

Conclusion

We demonstrated that serum exosomal miR-122 and miR-148a played a predictive role and were linked to prognosis in HCC via interactions with PAX2.

Exploring the clinical value of preoperative serum gamma-glutamyl transferase levels in the management of patients with hepatocellular carcinoma receiving postoperative adjuvant transarterial chemoembolization

BACKGROUND

Preoperative serum gamma-glutamyl transferase (γ-GT) levels is significantly related to the prognosis of hepatocellular carcinoma (HCC), but its clinical value in the management of postoperative adjuvant transarterial chemoembolization (PA-TACE) has rarely been explored. This study aimed to investigate whether γ-GT levels could be taken as a biomarker to guide the management of PA-TACE in resectable HCC.

METHODS

HCC patients receiving radical resection were identified through the primary liver cancer big data (PLCBD) from December 2012 to December 2015. Prognostic factors of overall survival (OS) and disease-free survival (DFS) were identified by univariate and multivariate cox analyses, and subgroup analysis was conducted between PA-TACE group and non-TACE stratified by γ-GT levels before and after 1:1 propensity score matching (PSM).

RESULTS

γ-GT level was found to be an independent risk factor of OS and DFS in 1847 HCC patients receiving radical resection (both P < 0.05), and patients with elevated γ-GT(> 54.0 U/L) have a shortened median OS and DFS, compared with those with normal γ-GT (both P < 0.001). In the subgroup of patients with normal γ-GT, there were no significant differences between groups of PA-TACE and non-TACE in terms of median OS and DFS before and after PSM (all P > 0.05), and PA-TACE was not a significant prognostic factor of both OS and DFS before and after PSM (all P > 0.05). In the subgroup of patients with elevated γ-GT, significant differences were found between groups of PA-TACE and non-TACE in terms of median OS and DFS before and after PSM (all P < 0.05), and PA-TACE was an independent prognostic factor of both OS and DFS (all P < 0.05).

CONCLUSION

Currently, we concluded that patients with more advanced HCC also have more elevated γ-GT, and these patients with elevated γ-GT would be benefited more from PA-TACE after radical resection.

HCC and Tumor Biomarkers: Does One Size Fits All?

Hepatocellular carcinoma (HCC) is a highly malignant disease and early diagnosis rates remain to be unsatisfactory. Owing to this limitation, advances in treatment options including liver transplantation (LT) are limited to improve survival. Recent HCC guidelines no longer recommend alpha-fetoprotein (AFP) as a surveillance and diagnostic tool for HCC. Hence, utilization of novel biomarkers has become imperative to improve disease management strategies. Noninvasive, serum-based biomarkers are potential options to aid early diagnosis as well as prompting treatment. However, further studies are required to find out the accuracy and potential of these approaches and introduce into clinical practice.

Distinctive pattern of AHNAK methylation level in peripheral blood mononuclear cells and the association with HBV-related liver diseases

The purpose of this study was to investigate the correlation between AHNAK methylation level in peripheral blood mononuclear cells (PBMC) and the progression of hepatitis B virus (HBV)‐related liver disease. Bioinformatics methods were applied to evaluate the AHNAK methylation level in PBMC and T cells at different stages of HBV related liver disease, to investigate the correlation between AHNAK methylation and clinical features, as well as to compare the methylation site of AHNAK in cancer tissues and adjacent tissues. Subsequently, the differentially expressed gene analysis technique was used to analyze the liver disease‐related genes and immune‐related pathways in hepatitis B patients with different pathological changes. Finally, promoter methylation and mRNA expression of AHNAK gene in liver cancer and adjacent tissues were determined by quantitative polymerase chain reaction (Q‐PCR), and the diagnostic value of AHNAK methylation level in hepatopathy was evaluated by receiver operating characteristic (ROC) curve. The promoter methylation level of AHNAK gene in PBMCs decreased with the progression of HBV‐related liver disease, and showed significant difference among the patients with various HBV‐related liver diseases (P = 0.0001). The AHNAK methylation level in PBMCs and T cells was negatively associated with age, white blood cell count, CREA, drinking, and positively associated with APTT and HbsAg. Higher mRNA expression of AHNAK was found in liver cancer tissues than that of adjacent tissues (P < 0.001), and the methylation level in PBMC decreased with the progression of hepatitis B‐related liver disease. The area under the ROC curve (ROC) was 0.883 (P < 0.001) in diagnosis of chronic hepatitis B (CHB), 0.885 (P < 0.001) in diagnosis of compensatory liver cirrhosis, 0.955 (P < 0.001) in diagnosis of decompensated liver cirrhosis, 0.981 (P < 0.001) in diagnosis of hepatocellular carcinoma. Our results revealed that AHNAK methylation level in peripheral blood decreases with the progression of hepatitis B‐related liver disease. This provided a potential differential diagnostic method for HBV‐related hepatopathies, and thus an early detective tool for liver cancer.