Development and Validation of Epigenetic Modification-Related Signals for the Diagnosis and Prognosis of Hepatocellular Carcinoma

Nanofiber-microwell cell culture system for spatially patterned differentiation of pluripotent stem cells in 3D

The intricate interplay between biochemical and physical cues dictates pluripotent stem cell (PSC) differentiation to form various tissues. While biochemical modulation has been extensively studied, the role of biophysical microenvironments in early lineage commitment remains elusive. Here, we introduce a novel 3D cell culture system combining electrospun nanofibers with microfabricated polydimethylsiloxane (PDMS) patterns. This system enables the controlled formation of semispherical human induced pluripotent stem cell (hiPSC) colonies, facilitating the investigation of local mechanical stem cell niches on mechano-responsive signaling and lineage specification. Our system unveiled spatially organized RhoA activity coupled with actin-myosin cable formation, suggesting mechano-dependent hiPSC behaviors. Nodal network analysis of RNA-seq data revealed RhoA downstream regulation of YAP signaling, DNA histone modifications, and patterned germ layer specification. Notably, altering colony morphology through controlled PDMS microwell shaping effectively modulated the spatial distribution of mechano-sensitive mediators and subsequent differentiation. This study provides a cell culture platform to decipher the role of biophysical cues in early embryogenesis, offering valuable insights for material design in tissue engineering and regenerative medicine applications.

Analysis of clinical significance and molecular characteristics of methionine metabolism and macrophage-related patterns in hepatocellular carcinoma based on machine learning

BACKGROUND

Increasing evidence has indicated that abnormal methionine metabolic activity and tumour-associated macrophage infiltration are correlated with hepatocarcinogenesis. However, the relationship between methionine metabolic activity and tumour-associated macrophage infiltration is unclear in hepatocellular carcinoma, and it contributes to the occurrence and clinical outcome of hepatocellular carcinoma (HCC). Thus, we systematically analysed the expression patterns of methionine metabolism and macrophage infiltration in hepatocellular carcinoma using bioinformatics and machine learning methods and constructed novel diagnostic and prognostic models of HCC.

METHODS

In this study, we first mined the four largest HCC mRNA microarray datasets with patient clinical data in the GEO database, including 880 tissue mRNA expression datasets. Using GSVA analysis and the CIBERSORT and EPIC algorithms, we quantified the methionine metabolic activity and macrophage infiltration degree of each sample. WGCNA was used to identify the gene modules most related to methionine metabolism and tumour-associated macrophage infiltration in HCC. The KNN algorithm was used to cluster gene expression patterns in HCC. Random forest, logistic regression, Cox regression analysis and other algorithms were used to construct the diagnosis and prognosis model of HCC. The above bioinformatics analysis results were also verified by independent datasets (TCGA-LIHC, ICGC-JP and CPTAC datasets) and immunohistochemical fluorescence based on our external HCC panel. Furthermore, we carried out pancancer analysis to verify the specificity of the above model and screened a wide range of drug candidates.

RESULTS

We identified two methionine metabolism and macrophage infiltration expression patterns, and their prognoses were different in hepatocellular carcinoma. We constructed novel diagnostic and prognostic models of hepatocellular carcinoma with good diagnostic efficacy and differentiation ability.

CONCLUSIONS

Methionine metabolism is closely related to tumour-associated macrophage infiltration in hepatocellular carcinoma and can help in the clinical diagnosis and prognosis of HCC.

Multiple-model machine learning identifies potential functional genes in dilated cardiomyopathy

Introduction

Machine learning (ML) has gained intensive popularity in various fields, such as disease diagnosis in healthcare. However, it has limitation for single algorithm to explore the diagnosing value of dilated cardiomyopathy (DCM). We aim to develop a novel overall normalized sum weight of multiple-model MLs to assess the diagnosing value in DCM.

Methods

Gene expression data were selected from previously published databases (six sets of eligible microarrays, 386 samples) with eligible criteria. Two sets of microarrays were used as training; the others were studied in the testing sets (ratio 5:1). Totally, we identified 20 differently expressed genes (DEGs) between DCM and control individuals (7 upregulated and 13 down-regulated).

Results

We developed six classification ML methods to identify potential candidate genes based on their overall weights. Three genes, serine proteinase inhibitor A3 (SERPINA3), frizzled-related proteins (FRPs) 3 (FRZB), and ficolin 3 (FCN3) were finally identified as the receiver operating characteristic (ROC). Interestingly, we found all three genes correlated considerably with plasma cells. Importantly, not only in training sets but also testing sets, the areas under the curve (AUCs) for SERPINA3, FRZB, and FCN3 were greater than 0.88. The ROC of SERPINA3 was significantly high (0.940 in training and 0.918 in testing sets), indicating it is a potentially functional gene in DCM. Especially, the plasma levels in DCM patients of SERPINA3, FCN, and FRZB were significant compared with healthy control.

Discussion

SERPINA3, FRZB, and FCN3 might be potential diagnosis targets for DCM, Further verification work could be implemented.

Role of m6A RNA methylation in the development of hepatitis B virus-associated hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common liver malignancy that can be developed from hepatitis B and cirrhosis. Many pathophysiological alterations, including hepatitis B virus (HBV) DNA integration, oxidative stress, cytokine release, telomerase homeostasis, mitochondrial damage, epigenetic modification, and tumor microenvironment, are involved in the biological process from hepatitis B to cirrhosis and HCC. N6-methyladenosine (m6A), as an epitranscriptomic modification of RNAs, can regulate the stability, splicing, degradation, transcription, and translation of downstream target RNAs in HBV and liver cancer cells. m6A regulators (writers, erasers, and readers) play an important role in the pathogenesis of HBV-associated HCC by regulating cell proliferation, apoptosis, migration, autophagy, differentiation, inflammation, angiogenesis, and tumor microenvironment. This review summarizes the current progress of m6A methylation in the molecular mechanisms, biological functions, and potential clinical implications of HBV-associated HCC.

Does Chronic Kidney Disease Really Affect the Complications and Prognosis After Liver Resection for Hepatocellular Carcinoma? A Meta-Analysis

Purpose

The purpose of this meta-analysis was to analyze whether chronic kidney disease (CKD) affected the complications and prognosis after liver resection for hepatocellular carcinoma.

Methods

The PubMed, Embase, and Cochrane Library databases were searched from inception to 22 February 2022 to find eligible studies. Complications, overall survival (OS), and disease-free survival (DFS) were collected, and this meta-analysis was performed with RevMan 5.3.

Results

A total of nine studies including 6,541 patients were included in this meta-analysis. After pooling all baseline information, the CKD group had a higher rate of Child-Pugh grade B than the Non-CKD group (OR = 1.58, 95% CI = 1.3 to 1.93, P < 0.00001). As for surgery-related information, the CKD group had larger blood loss (MD = −404.79, 95% CI = −509.70 to −299.88, P < 0.00001), and higher rate of blood transfusion (OR = 2.47, 95% CI = 1.85 to 3.3, P < 0.00001). In terms of complications, the CKD group had a higher rate of overall complications (OR = 2.1, 95% CI = 1.57 to 2.81, P < 0.00001) and a higher rate of ≥ grade III complications (OR = 2.04, 95% CI = 1.57 to 2.81, P = 0.0002). The CKD group had poor OS compared with the non-CKD group (HR = 1.28, 95% CI = 1.1 to 1.49, P = 0.001). However, in terms of DFS, no significant difference was found (HR = 1.11, 95% CI = 0.96 to 1.28, P = 0.16).

Conclusion

Preexisting CKD was associated with higher ratio of complications and poor OS.

Advances in RNA Epigenetic Modifications in Hepatocellular Carcinoma and Potential Targeted Intervention Strategies

The current interventions for hepatocellular carcinoma (HCC) are not satisfactory, and more precise targets and promising strategies need to be explored. Recent research has demonstrated the non-negligible roles of RNA epigenetic modifications such as N6-methyladenosine (m6A) and 5-methylcytosine (m5C) in various cancers, including HCC. However, the specific targeting mechanisms are not well elucidated. In this review, we focus on the occurrence and detailed physiopathological roles of multiple RNA modifications on diverse RNAs closely related to the HCC process. In particular, we highlight fresh insights into the impact mechanisms of these posttranscriptional modifications on the whole progression of HCC. Furthermore, we analyzed the possibilities and significance of these modifications and regulators as potential therapeutic targets in HCC treatment, which provides the foundation for exploring targeted intervention strategies. This review will propel the identification of promising therapeutic targets and novel strategies that can be translated into clinical applications for HCC treatment.