Anti-Hepatocellular Carcinoma Effect and Molecular Mechanism of the Estrogen Signaling Pathway

Nomogram built based on machine learning to predict recurrence in early-stage hepatocellular carcinoma patients treated with ablation

Introduction

To analyze the risk factors affecting recurrence in early-stage hepatocellular carcinoma (HCC) patients treated with ablation and then establish a nomogram to provide a clear and accessible representation of the patients' recurrence risk.

Methods

Collect demographic and clinical data of 898 early-stage HCC patients who underwent ablation treatment at Beijing You'an Hospital, affiliated with Capital Medical University from January 2014 to December 2022. Patients admitted from 2014 to 2018 were included in the training cohort, while 2019 to 2022 were in the validation cohort. Lasso and Cox regression was used to screen independent risk factors for HCC patients recurrence, and a nomogram was then constructed based on the screened factors.

Results

Age, gender, Barcelona Clinic Liver Cancer (BCLC) stage, tumor size, globulin (Glob) and γ-glutamyl transpeptidase (γ-GT) were finally incorporated in the nomogram for predicting the recurrence-free survival (RFS) of patients. We further confirmed that the nomogram has optimal discrimination, consistency and clinical utility by the C-index, Receiver Operating Characteristic Curve (ROC), calibration curve and Decision Curve Analysis (DCA). Moreover, we divided the patients into different risk groups and found that the nomogram can effectively identify the high recurrence risk patients by the Kaplan-Meier curves.

Conclusion

This study developed a nomogram using Lasso-Cox regression to predict RFS in early-stage HCC patients following ablation, aiding clinicians in identifying high-risk groups for personalized follow-up treatments.

Nomogram for predicting post-therapy recurrence in BCLC A/B hepatocellular carcinoma with Child-Pugh B cirrhosis

Introduction

This study conducts a retrospective analysis on patients with BCLC stage A/B hepatocellular carcinoma (HCC) accompanied by Child-Pugh B cirrhosis, who underwent transarterial chemoembolization (TACE) in combination with local ablation therapy. Our goal was to uncover risk factors contributing to post-treatment recurrence and to develop and validate an innovative 1-, 3-, and 5-year recurrence free survival (RFS) nomogram.

Methods

Data from 255 BCLC A/B HCC patients with Child-Pugh B cirrhosis treated at Beijing You'an Hospital (January 2014 - January 2020) were analyzed using random survival forest (RSF), LASSO regression, and multivariate Cox regression to identify independent risk factors for RFS. The prognostic nomogram was then constructed and validated, categorizing patients into low, intermediate, and high-risk groups, with RFS assessed using Kaplan-Meier curves.

Results

The nomogram, integrating the albumin/globulin ratio, gender, tumor number, and size, showcased robust predictive performance. Harrell's concordance index (C-index) values for the training and validation cohorts were 0.744 (95% CI: 0.703-0.785) and 0.724 (95% CI: 0.644-0.804), respectively. The area under the curve (AUC) values for 1-, 3-, and 5-year RFS in the two cohorts were also promising. Calibration curves highlighted the nomogram's reliability and decision curve analysis (DCA) confirmed its practical clinical benefits. Through meticulous patient stratification, we also revealed the nomogram's efficacy in distinguishing varying recurrence risks.

Conclusion

This study advances recurrence prediction in BCLC A/B HCC patients with Child-Pugh B cirrhosis following TACE combined with ablation. The established nomogram accurately predicts 1-, 3-, and 5-year RFS, facilitating timely identification of high-risk populations.

Bioinformatics and machine learning driven key genes screening for hepatocellular carcinoma

Liver cancer, a global menace, ranked as the sixth most prevalent and third deadliest cancer in 2020. The challenge of early diagnosis and treatment, especially for hepatocellular carcinoma (HCC), persists due to late-stage detections. Understanding HCC's complex pathogenesis is vital for advancing diagnostics and therapies. This study combines bioinformatics and machine learning, examining HCC comprehensively. Three datasets underwent meticulous scrutiny, employing various analytical tools such as Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein interaction assessment, and survival analysis. These rigorous investigations uncovered twelve pivotal genes intricately linked with HCC's pathophysiological intricacies. Among them, CYP2C8, CYP2C9, EPHX2, and ESR1 were significantly positively correlated with overall patient survival, while AKR1B10 and NQO1 displayed a negative correlation. Moreover, the Adaboost prediction model yielded an 86.8 % accuracy, showcasing machine learning's potential in deciphering complex dataset patterns for clinically relevant predictions. These findings promise to contribute valuable insights into the elusive mechanisms driving liver cancer (HCC). They hold the potential to guide the development of more precise diagnostic methods and treatment strategies in the future. In the fight against this global health challenge, unraveling HCC's intricacies is of paramount importance.

Testosterone, β-estradiol, and hepatocellular carcinoma: stimulation or inhibition? A comparative effect analysis on cell cycle, apoptosis, and Wnt signaling of HepG2 cells

Unlike breast and prostate cancers, which are specifically affected by estrogens or androgens, hepatocellular carcinoma has been reported to be influenced by both sex hormones. Given the coincidental differences of hepatocellular carcinoma in men and women, we investigated the effects of β-estradiol and testosterone on the cell cycle, apoptosis, and Wnt signaling in a model of hepatocellular carcinoma to understand the sex hormone-related etiology. To determine the effective concentration of both hormones, an MTT assay was performed. The effects of β-estradiol and testosterone on cell proliferation and death were evaluated by specific staining and flow cytometry. In addition, gene expression levels of estimated factors involved in GPC3-Wnt survival signaling were analyzed using quantitative real-time polymerase chain reaction. Both hormones inhibited hepatic cell proliferation through arresting the cell cycle at S/G2 and increased the apoptosis rate in HepG2 cells. Both hormones dose-dependently decreased GPC3, Wnt, and DVL expression levels as activators of the Wnt-signaling pathway. In the case of Wnt-signaling inhibitors, the effects of both hormones on WIF were negligible, but they increased DKK1 levels in a dose-dependent manner. In each of the effects mentioned above, β-estradiol was notably more potent than testosterone. In contrast to the primary hypothesis of the project, in which testosterone was considered a stimulating carcinogenic factor in HCC pathogenesis, testosterone inhibited the occurrence of HCC similarly to β-estradiol. However, this inhibitory effect was weaker than that of β-estradiol and requires further study.

Revealing curcumin therapeutic targets on SRC, PPARG, MAPK8 and HSP90 as liver cirrhosis therapy based on comprehensive bioinformatic study

Cirrhosis naturally progresses through three stages: compensated, decompensated, and late decompensated, which carry an elevated risk of death. Although curcumin's anti-cirrhosis effects have been studied, underlying mechanism in preventing cirrhosis progression and the correlation between curcumin's action with upregulated genes remains insufficiently explored. In this study, we employed network pharmacology approach to construct a drug-target-disease network through bioinformatics and validate the findings with molecular docking and dynamic simulation. The curcumin-targeted liver cirrhosis network encompassed 54 nodes with 282 edges in protein-protein interactions (PPI) network. By utilizing network centrality analysis, we identified eight crucial genes. KEGG enrichment pathway revealed that these crucial genes are involved in pathway of cancer, endocrine resistance, estrogen signaling, chemical carcinogenesis-receptor activation, lipid metabolism, and atherosclerosis. Notably, these eight genes predominantly participate in cancer-related pathways. Further investigation revealed upregulation of four genes and downregulation of four others in hepatocellular carcinoma patients. These upregulated genes-MAPK8, SRC, PPARG, and HSP90AA1-strongly correlated with reduced survival probability in liver hepatocellular carcinoma patients with survival times approximately under 4000 days (∼11 years). Molecular docking and molecular dynamic results exhibited curcumin's superior binding affinities and stability compared to native ligands of MAPK8, SRC, PPARG, and HSP90AA1 within 50 ns simulations. Moreover, MM-GBSA analysis showed stronger binding energy of curcumin to MAPK8, SRC, and HSP90AA1 than native ligand. In conclusion, this study provides valuable insights into curcumin's potential mechanisms in preventing liver cirrhosis progression, specifically in HCC. These findings offer a theoretical basis for further pharmacological research into anti-HCC effect of curcumin.Communicated by Ramaswamy H. Sarma.

The role of sex hormones and receptors in HBV infection and development of HBV-related HCC

Gender disparity in hepatitis B virus (HBV)-related diseases has been extensively documented. Epidemiological studies consistently reported that males have a higher prevalence of HBV infection and incidence of hepatocellular carcinoma (HCC). Further investigations have revealed that sex hormone-related signal transductions play a significant role in gender disparity. Sex hormone axes showed significantly different responses to virus entry and replication. The sex hormones axes change the HBV-specific immune responses and antitumor immunity. Additionally, Sex hormone axes showed different effects on the development of HBV-related disease. But the role of sex hormones remains controversial, and researchers have not reached a consensus on the role of sex hormones and the use of hormone therapies in HCC treatment. In this review, we aim to summarize the experimental findings on sex hormones and provide a comprehensive understanding of their roles in the development of HCC and their implications for hormone-related HCC treatment.

Development and validation of a nomogram to predict the recurrence of hepatocellular carcinoma patients with dynamic changes in AFP undergoing locoregional treatments

Background

Serum alpha-fetoprotein (AFP) is an important clinical indicator for screening, diagnosis, and prognosis of primary hepatocellular carcinoma (HCC). Our team's previous study showed that patients with negative AFP at baseline and positive AFP at relapse had a worse prognosis (N-P). Therefore, the aim of our study was to develop and validate a nomogram for this group of patients.

Methods

A total of 513 patients with HCC who received locoregional treatments at Beijing You'an Hospital, Capital Medical University, from January 2012 to December 2019 were prospectively enrolled. Patients admitted from 2012 to 2015 were assigned to the training cohort (n = 335), while 2016 to 2019 were in the validation cohort (n =183). The clinical and pathological features of patients were collected, and independent risk factors were identified using univariate and multivariate Cox regression analysis as a basis for developing a nomogram. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) curves in the training and validation cohorts.

Results

The content of the nomogram includes gender, tumor number, tumor size, lymphocyte, direct bilirubin (DBIL), gamma-glutamyl transferase (GGT), and prealbumin. The C-index (0.717 and 0.752) and 1-, 3-, and 5-year AUCs (0.721, 0.825, 0.845, and 0.740, 0.868, 0.837) of the training and validation cohorts proved the good predictive performance of the nomogram. Calibration curves and DCA curves suggested accuracy and net clinical benefit rates. The nomogram enabled to classify of patients with dynamic changes in AFP into three groups according to the risk of recurrence: low risk, intermediate risk, and high risk. There was a statistically significant difference in RFS between the three groups in the training and validation cohorts (P<0.001).

Conclusion

The nomogram developed and validated in this study had good predictive power for patients with dynamic changes in AFP.

Key Members of the CmPn as Biomarkers Distinguish Histological and Immune Subtypes of Hepatic Cancers

Liver cancer, comprising hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), is a leading cause of cancer-related deaths worldwide. The liver is a primary metabolic organ for progesterone (PRG) and PRG exerts its effects through classic nuclear PRG receptors (nPRs) and non-classic membrane PRG receptors (mPRs) or a combination of both. Previous studies have shown that the CCM signaling complex (CSC) couples both nPRs and mPRs to form the CmPn (CSC-mPR-PRG-nPR) signaling network, which is involved in multiple cellular signaling pathways, including tumorigenesis of various cancers. Despite advances in treatment, 5-year survival rates for liver cancer patients remain low, largely due to the chemoresistant nature of HCCs. The lack of sensitive and specific biomarkers for liver cancer diagnosis and prognosis emphasizes the need for identifying new potential biomarkers. We propose the potential use of CmPn members’ expression data as prognostic biomarkers or biomarker signatures for the major types of hepatic cancer, including HCCs and CCAs, as well as rare subtypes such as undifferentiated pleomorphic sarcoma (UPS) and hepatic angiosarcoma (HAS). In this study, we investigated the CmPn network through RNAseq data and immunofluorescence techniques to measure alterations to key cancer pathways during liver tumorigenesis. Our findings reveal significant differential expression of multiple CmPn members, including CCM1, PAQR7, PGRMC1, and nPRs, in both HCCs and CCAs, highlighting the crucial roles of mPRs, nPRs, and CSC signaling during liver tumorigenesis. These key members of the CmPn network may serve as potential biomarkers for the diagnosis and prognosis of liver cancer subtypes, including rare subtypes.

Network Pharmacology-Integrated Molecular Docking Reveals the Expected Anticancer Mechanism of Picrorhizae Rhizoma Extract

This study sought to explore the anticancer mechanism of Picrorhizae Rhizoma (PR) extract based on network pharmacology and molecular docking. The potential chemicals of PR were screened through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and relevant literatures. Corresponding targets of active ingredients were found with the help of the UniProtKB database, and therapeutic targets for cancer action were screened with the help of the GeneCards database. We used Cytoscape software to construct the compound-target-pathway network of PR extract. We utilized the STRING database to obtain the protein-protein interaction (PPI) network. We used DAVID database combining Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, molecular docking was employed for initial efficacy checking. We have identified 16 potential active components of PR through screening, involving 112 disease action targets. Utilizing the GeneCards database, 112 intersecting targets between PR extract and cancer were found, which mainly exerts anticancer effects by regulating tumor necrosis factor (TNF), recombinant caspase 3 (CASP3), c-Jun NH2-terminal kinase (JNK)/JUN, epidermal growth factor receptor (EGFR), and estrogen receptor-1 (ESR1) with some other target genes and pathways associated with cancer. The major anticancer species are prostate cancer, colorectal cancer, small cell lung cancer, etc. In the molecular docking study, herbactin had a strong affinity for TNF. Based on network pharmacology and molecular docking studies, PR and their compounds have demonstrated potential anticancer activities against several key targets. Our preliminary findings provide a strong foundation for further experiments with PR constituents.